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TRANSPORT AND ROAD RESEARCH LABORATORY Department of Transport
RESEARCH REPORT 341
THE 1989 TRRL LONDON TAXI SURVEY
by D J Finch
Crown Copyright 1992. The views expressed in this Report are not necessarily those of the Department of Transport. Extracts from the text may be reproduced, except for commercial purposes, provided the source is acknowledged.
Transport Demand Division Traffic Group Transport and Road Research Laboratory Crowthorne, Berkshire, RG11 6AU 1992
ISSN 0266-5247
Ownership of the Transport Research Laboratory was transferred from the Department of Transport to a subsidiary of the Transport Research Foundation on 1 st April 1996.
This report has been reproduced by permission of the Controller of HMSO. Extracts from the text may be reproduced, except for commercial purposes, provided the source is acknowledged.
- . . .
CONTENTS
Page
Abstract 1
1. Introduction 1
1.1 Background 1
1.2 The need for a survey 1
2. Survey Methodology 1
2.1 Data collection 1
2.2 Mileage estimation 2
2.3 Sample size and representivity 2
2.4 Fare estimation 2
2.5 Transport strikes 3
3. Analysis of green badge driver logs 3
3.1 Trip statistics 3
3.2 Inter-trip statistics 3
3.3 Driver work patterns 6
3.3.1 The working week 6
3.3.2 Productivity and use of the radio 8
4. Analysis of yellow badge driver logs 12
4.1 Trip statistics 12
4.2 Inter-trip statistics 13
4.3 Driver work patterns 13
4.3.1 The working week 13
4.3.2 Productivity and use of the radio 16
5. Passenger questionnaire analysis 16
5.1 Who uses taxis? 16
5.2 Whyataxi? 17
5.3 Waiting time 18
6. The geography of supply and demand 21
6.1 Taxi availability 21
6.2 Green badge drivers 21
6.3 Heathrow Airport
6.4 The "Knowledge"
6.5 Yellow badge drivers
7. Income
7.1 Fares and driver revenue
7.2 Income and taxi supply
7.3 Income and radio work
8. Discussion
9. Summary
10. Acknowledgements
11. References
Appendix A:
Appendix B:
Appendix C:
Example driver log and passenger questionnaire
Analysis of independent data sources
Figures C1 to C3
Page
22
22
24
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26
28
30
30
3O
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36
38
THE 1989 LONDON TAXI SURVEY
A B S T R A C T
A major survey of London's taxi industry was undertaken with the cooperation of 231 licensed drivers, who were asked to complete detailed records of one week's work, and to hand out self-completion questionnaires to their passengers. The resulting database of 21,769 taxi trips and 6,993 passenger responses was analysed to provide up-to-date statistics on the patterns of taxi operation and use. Comparison of these with surveys undertaken in the late sixties/early seventies suggests little has changed over the last two decades. This is a somewhat unex- pected result in view of the intervening economic and legislative changes, and leads to the belief that taxi supply has been to an extent self-regulatory.
1. I N T R O D U C T I O N
1.1 BACKGROUND
In London taxis (also known as Hackney carriages, or "cabs") and their drivers ("cabbies") are subject to strict regulation and both are licensed. This activity is carried out by the Public Carriage Office (PCO), which is a branch of the Metropolitan police.
Vehicles must conform to a specification, which currently allows three basic types: the ubiquitous FX4 (plus variants), the Fairway (variants similar in appearance to the FX4), and the recently developed Metrocab. Vehicles are required to undergo a yearly maintenance check by PCO inspectors.
There is, in theory, no limit on the number of drivers who may 'ply for hire', but in practice rigorous licensing requirements restrain growth. Prospective "cabbies" have to pass: a) a medical fitness test b) a driving test con- ducted by the PCO in addition to the national DTp test c) a criminal record check and d) a test known as the "Knowledge". There are two types of "cabbies": green and yellow. Green badge drivers form the majority (92 - 95 per cent) of all licensed drivers, and are allowed to ply for hire anywhere within the Metropolitan Police District 1. Yellow badge drivers are only allowed to ply for hire in suburban areas. This distinction is discussed in detail in section 6.2.
1.2 THE NEED FOR A SURVEY
The last survey of the trade was part of the Greater London Transportation Survey of 1981 (GLTS). Earlier surveys took place in the late sixties - mid seventies resulting in: the Maxwell Stamp Committee Report
(1970), and the Price Commission Report (1977). These previous surveys do not contain information of sufficient detail to enable thorough investigation, and there was concern that their results no longer reflected the current operation of the taxi trade.
In 1984 the responsibility for taxi legislation passed from the Home Office to the Department of Transport (DTp). As is the case with research in other transport areas the Transport and Road Research Laboratory (TRRL) was asked to provide DTp with up-to-date information on London's taxi trade as input to policy formulation.
2. S U R V E Y M E T H O D O L O G Y
2.1 DATA COLLECTION
The earlier surveys relied on a combination of volunteer taxi drivers filling out journey log sheets, and self- completion questionnaires for passengers to obtain data at the individual trip level. This method was adopted following a successful small scale trial.
Volunteer drivers were required to record deta_ils of all journeys undertaken during the course of one week's work, and to hand out self-completion questionnaires to their passengers. Example forms are reproduced in appendix A. To assist drivers log sheets demanded a minimum amount of information. They were asked to record: method of hire, number of passengers, time and place of hire and time and place of destination. Places were identified by the nearest junction. Late-night journeys have been assigned to the days during which drivers started their shifts, in accordance with the com- mon custom of regarding the early hours of, say, Sunday morning, as "Saturday night". Thus, in this report, the weekend is the 48 hour period beginning at 0600 on Saturday.
Volunteer drivers were obtained by collecting names and addresses at random from records held at the PCO. Letters were then posted inviting them to help with the survey, and to promise payment of 50 pence per legibly recorded journey 2.
Volunteers were given one of four starting dates (17th, 24th and 31st July, and 7th August 1989) to avoid concentration of the survey over just one week - in view of the possibility of freak weather, strikes, public events etc.
Returned log sheets and passenger questionnaires were coded onto computer and subjected to a suite of Fortran programs designed to check the information and create a
1 This covers all of the Greater London Area and all/part of the boroughs of Epping Forest, Epson & Ewell, Hertsmere & Spelthorne.
2 Payment was considered necessary to offset time costs incurred through form-filling, and to act as an incentive for the production of useful data.
database. Trip origin and destinations were manually coded to the nearest 100 metre map reference using a modified form of the Greater London Street Atlas (1981) reference system. Map references were then translated by computer program to standard Ordnance Survey (OS) Grid coordinates.
The administration of the survey, including coding the information onto computer was undertaken by Public Attitude Surveys Ltd.
2.2 MILEAGE ESTIMATION
In the absence of mileometer readings for individual journeys it was necessary to estimate actual road distances from calculated direct ("crow-fly") distances. This was achieved by measuring the length of the three shortest routes for a sample of 100 origins and destina- tions. 1:50,000 and 1:11,520 scale maps were used. Regression analysis was then used to model the relation- ship between the means of these measurements and their direct distances. The resulting linear modeP was built into the suite of coding and checking programs to produce trip length estimates from origin/destination coordinate pairs. For typical trips "crow-fly" distances were under-estimating road distances by 20-25 per cent, which compares favourably with the GLTS estimate (30 per cent).
Distance travelled between trips i.e. without a passenger (inter-trip length) was subsequently estimated by applying a model of taxi speeds to the length of time elapsing between trips (inter-trip duration). Analysis of variance techniques were used to identify day of week, hour of day and distance from central London (p<0.0014 for all three factors) as significant factors in determining mean taxi speed.
Mileage and time spent travelling to/from work in central London was estimated by applying these models to the direct distance between a driver's home address (also coded to Ordnance Survey Grid coordinates) and the first trip origin/last trip destination of each working day. Mileage and time spent taking a break during a shift was recorded by the driver.
These methods of estimation are of course open to error. To validate the methodology total daily mileage recorded by drivers were compared with their corresponding estimates. Mean estimated and actual daily mileage was 99.0 miles and 101.5 miles respectively. Statistical tests (Student's t-test for two sample means and linear regres- sion) confirm that there is no significant difference between estimated and actual mileage.
2.3 SAMPLE SIZE AND REPRESENTIVITY
About 3,000 letters of invitation were initially posted, which resulted in 302 replies from drivers interested in participating, total of 231 drivers eventually took part,
others dropping out for a variety of reasons (illness, cab off road, unforeseen circumstances etc). Eleven of the 231 were yellow badge drivers. The information provided by these volunteers was of a very high standard and resulted in a database containing details of 21,769 taxi trips and responses from 6,993 passengers. Simple grossing of these figures suggests that about 1.6 million taxi trips per week were being undertaken by London's taxis during the survey period. A yearly estimate is impossible without factors to account for seasonal fluctuation in passenger demand and driver behaviour - August is particularly atypical because of holidays/ tourism.
The low final response rate (about 8 per cent), together with the fact that drivers were, by necessity, self-selected led to the possibility that the information, although excellent, may have arisen from an unrepresentative sample of drivers: hard working drivers, for example, may have decided not to volunteer because of time pressures; equally, part-time drivers may have felt their contribution too little to be of use. This would in turn provide problems with scaling factors and cast doubt over the applicability of statistics generated.
To assess the extent of possible bias, and thus estimate the necessary correction factors, data on patterns of operation were collected from three independent sources to act as "yard sticks" for statistical comparison. Details of this additional exercise are given in appendix B, which provides evidence suggesting that the volunteer drivers were in fact a representative sample, in so far as any sample would be subject to random sampling error.
The survey sample of 11 yellow badge drivers (4.8 per cent of total sample) was less than expected from PCO records (8.1 per cent). Statistical tests suggest that this discrepancy cannot be allotted to sampling effects alone. However, these tests rely on the assumption that all licensed drivers are actively pursuing work as a taxi driver. This is known not to be the case: the Price Commission (1977) estimated that as many as 15 per cent of licences were held by 'drivers' in full employment elsewhere. The proportion of yellow badge drivers in this survey, therefore, may be a better estimate of the relative numbers of working yellow and green badge drivers. The sample of yellow badge drivers was considered to be too small for statistical analysis at the level of detail afforded by the green badge sample. Thus only the most robust analyses are presented for comparison with green badge data, and even these should be treated with some caution.
2.4 FARE ESTIMATION
Reluctance on the behalf of taxi drivers to give details of their daily revenue is understandable, but regrettable: this information was not gathered in order to maximise driver interest. Nevertheless it was possible to estimate a fare range for individual trips, and use this information to estimate driver revenue per day, per mile, per hour etc. A
3 Regression equation used in program: road distance = 0.043 + 1.179 x direct distance (R-squared=99.2%) 4 'p' values are the probabilities with which observed relationships may have arisen by chance.
single fare value cannot be calculated for a particular trip: the meter can operate both on a time and a distance basis, and the contributory proportions of these for each trip are unknown s . However, the theoretical boundaries can be calculated with some precision; these correspond to the minimum and maximum fares payable for a particular combination of time and distance.
These calculations were incorporated into the suite of programs used to create the database. Fare boundaries generated in this way are based on the fare tariff in operation when the survey took place. They include surcharges for evening and weekend trips as well as additional passengers. They do not include additional charges for handling heavy luggage or gratuities ("Tips") to the driver.
The accuracy of this method of estimation was tested by comparing boundary estimates with actual meter read- ings for a sample of trips booked through a radio circuit. Results of this comparison, details of which are given in appendix B, are favourable.
2.5 TRANSPORT STRIKES
Unfortunately the survey period coincided with disruption to London Transport's bus and tube network. Strike days (18th and 26th July and 2nd August) were excluded from analyses likely to suffer from distortion through changes in traffic density, increased reliance on the taxi industry and so forth. Where inclusion was deemed necessary statistics for these three daYs have been scaled using information obtained from non-strike days where this was appropriate.
3. ANALYSIS OF GREEN BADGE DRIVER LOGS
3.1 TRIP STATISTICS
The majority of taxi trips were initiated by the passenger hailing the taxi on the street (70 per cent). The next most popular method (22 per cent) was to approach one at a rank - this includes trips originating from Heathrow Airport and the various British Rail termini as well as street corner ranks. Pre-booked trips via a radio circuit com- pany (i.e. 'phoning for one) formed the remaining 8 per cent.
The distribution of estimated trip length is given in figure la. Both weekday and weekend distributions are similar, with a modal value for trips of 1 - 2 miles. The distribu- tions are skewed quite strongly toward the shorter trips, and the majority (57.1 per cent for weekdays, 53.3 per cent for weekends) were estimated to be for two miles or less. Means for the weekday and weekend distributions are 2.46 and 2.69 miles per trip respectively.
The distribution of trip duration is shown in figure lb, which is unsurprisingly similar in shape to figure 1 a. Again both weekday and weekend distributions are similar, with the exception of a greater weekend peak for trips lasting 5 - 10 minutes. Means for the distributions are 14.7 and 13.3 minutes per trip for weekdays and weekends respectively.
Both trip length and duration were found to vary from hour to hour. Figures showing this variation can be found in appendix C. Mean trip length was generally greatest between the hours 0300 and 0900, with a pronounced peak at 0600 hours. Further analysis revealed this peak to be the result of: a) an increase in trips originating in the outer suburbs, and b) a concentration of trips ending at Heathrow Airport. Apart from early morning variation (possibly resulting from the small number of observa- tions), mean trip duration and length remains relatively constant throughout the day.
The range of estimated mean trip speed was found to reflect traffic speed in central London in general, with a mean of 10.5 mph for weekdays and 12.0 mph f o r weekends. Maxwell Stamp (1970) reports an average trip speed of 10 mph for central London drivers, and in 1977 the Price Commission reported a figure of 9.6 mph. Interestingly 11.5 per cent of all weekday, and 7.5 per cent of all weekend trips were averaging five miles per hour or less - not a great deal faster than walking pace!. The distribution of trip speed is given in figure lc. De- tailed figures showing the variation in trip speed by hour are given in appendix C.
3.2 INTER-TRIP STATISTICS
Drivers' daily logs gave useful and important information about their passenger (or parcel) bearing journeys. The database however, can shed light on those moments between engaged trips. These are termed 'inter-trips' in this report but are more commonly referred to as 'dead' mileage. A comprehensive analysis of inter-trip informa- tion will potentially reveal far more about drivers' working practices, and their response to changing demand than could information on the trips alone.
The distribution of inter-trip length indicates how far, on average, drivers have to travel in order to obtain their next passenger. This is given in figure 2a, which can be compared directly with figure la. In doing so it can be seen that, in contrast, the great majority of inter-trips (68.4 per cent for weekdays and 63.0 per cent for weekends) fall within the category 0 - 1 miles. Means for weekday and weekend were 1.10 and 1.23 miles per trip respectively. An overall figure of 1.18 miles was reported in GLTS (1981).
A similar relationship is revealed in figure 2b, which shows the distribution of weekday and weekend inter-trip duration. About half (51.1 per cent weekdays, 47.1 weekends) of all inter-trips were for five minutes or less. Means for weekday and weekend were 11.7 and 12.1
5 The meter will accumulate distance units unless the speed of the vehicle drops below about 10mph, when the meter clocks time.
40 I Weekdays Weekends
30
20
10
0-1 1-2 2-3
Fig.la
3--4 4-5 5-6 6-7 7-8 8-9
Distance (miles)
Trip length distr ibution for green badge drivers
9-10 10+
40
30
E °= 20
o _
i Weekday s ~ W e e k e n d s
10
0--5 5--10 10-- 15 15--20 20--25 25-30 30--35
Duration (minutes)
Fig. l b Tr ip duration distr ibut ion for green badge drivers
35-45 45+
50
r 40
30
20
10
0--5 5--10
I1 Weekdays ~ Weekend~
10-15 15-20 20-25 25--30
Speed (mile/h)
30--35 35-45 45+
Fig. lc Tr ip speed distr ibut ion for green badge drivers
60
I1 Weekdays ~ Weekends
4O
o_
20
0-1 1-2 2-3 3-4 4--5 5--6 6--7 7-8 8--9
Distance (miles)
Fig. 2a Inter-trip length distr ibut ion for green badge drivers
9--10 1 O+
60
40
20
0--5
I1 Weekdays ~ W e e k e n d s
5-10 10-15 15-20 20-25 25-30 30-35 35-45
Duration (mins)
Fig.2b Inter-tr ip duration distribution for green badge drivers
45+
minutes per trip respectively. Drivers therefore, on average, did not have to travel very far or for long before finding another passenger. In fact eighteen per cent of all inter-trips were instantaneous: the second passenger hired the taxi as soon as the first got ouP.
The ability to find another passenger depends on many factors including demand, taxi supply, road/weather conditions, where the previous trip has left the driver and where the driver intends to work next. Inter-trip measure- ments summai'ise the net effect of these various factors, which vary from hour to hour. This variation is shown in figure 3a for mean inter-trip length and figure 3b for mean inter-trip duration. These figures reveal a complex relationship between inter-trip distance and time.
On weekdays drivers travelled furthest between trips in the early morning, with peaks for the periods 0200 - 0300 and 0500 - 0600 hours. From about 0900 to 2000 hours drivers travelled least between trips, after which the mean distance steadily rises. In contrast inter-trip duration was least during the early hours, with peaks in the periods 0500 - 0900, 1200 - 1400, 1600 - 1700 and 2000 - 2200 hours. Variation in traffic speed is the main reason for the early morning inversion between length and duration, but the peaks appear to be the result of a combination of several factors.
Overall, the weekend pattern was roughly similar, but with drivers travelling less far during the early morning/ late evening, and further during the day when compared with weekdays.
3.3 DRIVER WORK PATTERNS
3.3.1 The working week
The number of taxis available for hire at any one time is governed by a multitude of factors, but the most funda- mental perhaps is the driver's decision to work at all. Thus drivers were asked to keep a record of non-working days, along with details of breaks taken during a working shift.
The mean length of the working week, including travel to/ from home was 44 hours 48 minutes. This is considerably longer than that found by the Price Commission in 1977 (35 hours 54 minutes), but this difference may, in part, be due to an increase in commuting distance. Mean working week length excluding such travel was 37 hours 20 minutes. The mean overall daily shift length 7 was 8 hours 4 minutes: shifts being longer during the week (8 hours 24 minutes) than the weekend (6 hours 29 minutes). Analysis of shift start/end times revealed an almost uniform work pattern throughout the day, apart from a small peak for shifts starting 0900 hours, and a small peak for shifts ending 1900 - 2100 hours during week- days. Although categories overlap to some extent, drivers were classified on their preference for day, evening and night work 8. The great majority were found to be 'day workers' (86.9 per cent); all but one of the remainder tended to work evening shifts (12.7 per cent evening, 0.4 per cent night).
6 The team of observers used in a roadside survey of taxi movements found this to be a common occurrence in Oxford St.
7 Excluding commuting time, but including breaks. 8 A driver was classified on the weekly proportion of shifts started in the time bands: 0600 - 1800 (day), 1800 - 2300 (evening) and
2300 - 0600 (night).
25.0
C
E
20.0
15.0
10.0
5.0
0.0
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I t I I I I I 0 3 6 9 12 15 18 21 24
Hour ending
F i g . 3 b Mean inter-tr ip durat ion by hour for green badge drivers
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E
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Hour ending
F i g . 3 a Mean inter-tr ip length by hour fo r green badge drivers
24
The most popular period to break from the rigours of plying for hire on weekdays and weekends was 1200 - 1400 hours. About a quarter of all recorded breaks were taken in this period. Mean break duration was 58 and 52 minutes for weekdays and weekends respectively. In this time drivers would, on average travel 6.6 miles (week- days), 6.7 miles (weekends). During a shift drivers were averaging 0.91 breaks weekdays and 0.54 breaks weekends, which suggests that drivers were sometimes working complete shifts without breaks. Assuming all breaks were duly recorded, the mean length of non-break shifts was 7 hours 9 minutes weekdays and 5 hours 23 minutes weekends. Thus some drivers were working for a considerable time without rest.
The number of taxis plying for hire, whether engaged or not, when expressed as a percentage of the total number potentially available indicates what is termed the level of 'turnout'. This is displayed in figures 4a and 4b, which express turnout by day and by hour respectively. The five day working week is clearly evident in figure 4a as being Monday to Friday. Fewer drivers were willing to look for work on Saturday (46.4 per cent turnout) and Sunday (27.7 per cent turnout). This can partly be explained by the fact that a great deal of taxi work is generated by business users (section 5.1) - presumably sufficiently so for drivers not to have to work over the weekend.
By hour the turnout looks a great deal less. This is to be expected with this particular analysis: drivers only work for 7 to 8 hours in 24, implying an average turnout of about 33 per cent. Turnout reaches a peak of 46.8 per
cent around 1500 hours (weekday and weekend counts were combined), and follows a fairly predictable pattern.
3.3.2 Productivity and use of radio
Figure 5 shows a clearly defined pattern of taxi use by hour for both weekdays and weekends. The shaded area represents the most popular time for a driver to take a break (see previous section). Although this coincides with a plateau in the curve for weekday and weekend trips, it is difficult to determine whether this was caused by a lack of available taxis or passengers, who are also likely to take a lunch break at this time. Apart from a difference in scale weekday and weekend curves are remarkably similar, with the bulk of taxi work taking place during the afternoon and early evening.
Most trips were undertaken by one passenger only (60.0 per cent). The overall mean loading for weekdays and weekends was 1.55 and 1.87 passengers per taxi per trip respectively 9. A total of 32,737 passengers and 64 parcels were carried by the 220 green badge drivers during one week's work.
On average drivers made 2.62 trips per hour while actually working, and 2.36 trips per hour over their working day - including breaks but excluding travel to/ from work. This latter estimate closely compares with a rate of 2.3 trips per hour reported by the Price Commis- sion in 1977, but comparison is problematic without detailed knowledge of their calculations. The hourly variation in trip rate is a useful indicator of the overall
9 GLTS (1981) reports a figure of 1.53 and 1.57 for radio and non-radio taxis respectively.
100
80
60
40
20
Mon Tue Wed Thu Fri
Fig.4a Turnout by day
Sat Sun
8
60
50
40
30
20
10
. . . . Yellow Green l
S
,. / , / _ -, / /
', / / , ' I I
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I I I I 12 15 18 21 24
Hour ending
F ig .4b T u r n o u t by hour
1400
1200
1000
A
800
600 ( .3
400
200
Weekdays - - - W e e k e n d s ~ ~ sS X
- . r ~ ' - - j "
I I I 0 3 6 9 12 15 18 21 24
Hour ending
Fig.5 Tota l tax i t r ips per hour by green badge drivers
200
160
120
E
80 ~J
40
0
level of satisfied demand and is shown in figure 6. There is close correspondence between weekday and weekend rates, particularly from 0900 hours to midnight: this is surprising - especially considering the difference in passenger volume (figure 5). To an extent therefore, the supply of taxis appears to be self-regulatory, and is capable of matching demand reasonably well. Higher rates, which are observable during the night, and particu-
larly at 0300 - 0600 hours on weekdays, are not n e c e s - sarily indicative of under-supply. Lighter traffic conditions, coupled with well defined markets (turnout from clubs and similar late-night entertainment venues), would tend to improve cab productivity. The mean total trips per week per driver was 93.7, which is higher than that found by the Price Commission (82.2 trips per week). During a working week drivers were travelling 435 miles on
9
A
._o.
4.00
3.50
3.00
2.50
2.00
I Weekdays . . . . Weekends I
-,/2 St S~ sSS~
i " t , / , \ , ,,, . . . --" ",
\ V \ / / / -
: A -.- \ . , ,~\~Iv I I I I I I I I I I
I I I I I I I 0 3 6 9 12 15 18 21 24
Hour ending
Fig.6 Mean hourly trip rate for green badge drivers
average, of which 337 were run in the course of a shift. The remainder resulted mainly from commuting: drivers were travelling about 19 miles per day to/from work. Productivity is usually expressed as the proportion of engaged time or mileage, i.e. that which is passenger bearing, but estimation of this is complicated by the significant proportion of time and mileage spent commut- ing (around a quarter of total mileage). When included in calculations 54.7 per cent of mileage and 52.3 per cent of time was spent carrying passengers. The Price Commis- sion (1977) reported a figure of 58 per cent for engaged mileage, but comparison necessarily relies on the assumption that no significant change in commuting behaviour has occurred over the last 15 years: an increase in the average commuting distance would easily account for the apparent drop in productivity. Once 'at work' 70.1 per cent of mileage and 63.6 per cent of time is gainfully employed, the difference between these figures being attributable to time spent waiting at ranks, and for passengers to emerge for their pre-booked taxi.
Just under half of the green badge drivers in the sample (48.1 per cent) were members of a radio circuit. Of these (37.8 per cent of radio circuit members) belonged to Computer Cab Ltd, London's largest radio circuit. At the time of the survey 42.0 per cent ~° of taxi cabs in service were fitted with two-way radio. The higher proportion of radio drivers in the survey is partly due to sampling effects, and partly due to drivers sharing vehicles. Public carriage Office figures quoted in the Price Commission (1977) and Maxwell Stamp (1969) surveys were 20.8 and 11.0 per cent respectively.
Radio circuit drivers, on average, were making use of the radio 0.44 times per hour weekdays and 0.25 times per hour weekends, which amounts to an overall mean of 16.2 radio initiated trips per driver per week, which accounted for about 19 per cent of all their weekly trips. Level of use was found to vary both by day and by hour. Figures 7a and 7b show this variation in terms of the percentage of all jobs undertakenlL Reliance on business users (section 5.1) was reflected in the higher rates of use for weekdays, and particularly so during the morning commuting period. The 0600 hours peak corresponded with a demand for taxis to Heathrow (section 3.1 ).
Table 1 provides a cross tabulation of mean trip length and duration by method of hire for weekdays and week- ends. An overall weekday/weekend effect can be seen, which is presumably directly due to differing traffic speeds. In addition radio initiated trips, on the whole, appeared to be longer and take more time than hailed or rank based trips. This was confirmed by an analysis of variance (weekdays and weekends: p<0.0001 for length & duration).
One possible consequence of this is that drivers under- taking radio jobs may have to travel further and/or spend more time looking for the next passenger. They may, for example, have to travel back from quiet suburbs toward areas of higher demand in central London. Conversely, it is possible that radio initiated trips are no more likely to leave areas of high demand but are longer because users have different requirements - they may require the driver to make several excursions after the initial hiring,
10 From PCO sources 11 It must be noted that these distributions were chosen to reflect reliance on radio rather than volume of radio work undertaken.
10
25.0 r
20.0
15.0
C3-
10.0
5.0
0.0 Mon Tue Wed Thu Fri
Fig.7a Radio use by day fo r green badge drivers
Sat Sun
50.0
E 8
13-
40.0
30.0
20.0
10.0
0.0
,,, / , \ /, I I !
, . ' iX t ~ ! \ \ / ; \ .J
t ! t # I I t ! I!
_ _ _ _ _ _ 1 Weekdays . . . . Weekends
Le t I 1 I ~ I ~ ./
',, . - " ' - " -" " ! Q~
I I I I I I 6 9 12 15 18 21 24
Hour ending
Fig.7b Radio use by hour for green badge drivers
11
TABLE 1
Mean trip length (miles)
Method of hire Week days Weekends
Mean trip duration (minutes)
Weekdays Weekends
Distance of origin from centre (miles)
Week days Week ends
Hail 2.17 2.20 12.77 11.58
Rank 2.75 3.46 15.88 15.69
Radio 4.15 4.82 27.67 23.72
All methods 2.46 2.69 14.67 13.33
1.77 2.07
2.12 2.48
2.20 3.02
1.88 2.23
TABLE 2
Prior method of hire
Mean Inter-trip length (miles]
Mean Inter-trip duration (minutes)
Distance of destination from centre (miles)
Weekdays Weekends Weekdays Weekends Weekdays Week ends
Hail 1.04 1.14
Rank 1.08 1.27
Radio 1.67 2.21
All methods 1.10 1.23
10.72 10.73 2.15 2.47
13.18 14.34 2.25 2.71
16.19 17.00 3.04 3.86
11.69 12.09 2.25 2.60
and/or keep the driver waiting. These opposing hypoth- eses were tested by analysing the inter-trip length and duration following a hiring. Table 2 displays the results of this exercise. Analysis of variance techniques support the hypothesis that, on average, drivers are travelling further and longer following a radio booking before they obtain their next passenger (weekdays: p<0.0001 for length & duration, weekends: p<0.0001 for length, p=0.007 for duration).
The mean "crow-fly" distances of trip origins and destina- tions from central London (Charing Cross) are also shown in tables 1 and 2 for each of the methods of hire. These means support the suggestion that radio trips are more likely to take the driver further from the centre both for origins and destinations. Analysis of variance confirms this observation (weekdays and weekends: p<0.0001 for origins and destinations).
The tendency for radio circuit drivers to average longer trips is reflected in significantly lower (p<0.0001) mean hourly trip rates for these drivers working weekdays (2.39 trips/hour) when compared with their non-radio counter- parts (2.82 trips/hour). This difference did not apply at weekends, when both driver types were likely to be concentrating on similar 'markets'. Productivity, whether measured in terms of engaged mileage or time was not
significantly different between radio and non-radio circuit drivers, apart from a suggestion (p=0.0338) of a higher engaged time ratio for radio drivers working weekends: radio drivers were engaged for 60.4 per cent, and non- radio drivers for 54.4 per cent of their shift time '2. Higher trip and inter-trip speeds attained in the suburbs would explain the overall similarity in efficiency despite the longer trip/inter-trip distances run by radio drivers. Over a working week radio circuit drivers were travelling slightly higher mileages, making fewer trips, but working similar hours. These differences are summarised in table 3.
4. A N A L Y S I S OF Y E L L O W B A D G E DRIVER LOGS
4.1 TRIP STATISTICS
The majority of trips were initiated by passengers ap- proaching taxis at a rank (72 per cent). Pre-booked trips (via a radio circuit) accounted for 17 per cent of trips, and the remaining 11 per cent of trips were hailed. This contrasts greatly with trip initiation for green badge drivers where hailing was found to be the principal method of taxi hire (70 per cent).
12 Shift time excludes 'dead time' at the beginning and end of each working day, to avoid undue influence of drivers' home locations.
12
TABLE 3
radio non-radio
trips per hour weekdays 2.39 2.82 weekends 2.69 2.65
engaged time weekdays 65.0% 63.7% weekends 60.4% 54.4%
engaged distance weekdays 70.6% 71.1% weekends 71.7% 70.2%
Total weekly mileage 346.7 329.0
Total weekly trips 84.4 101.9
Total weekly shift (hrs) 38.3 36.5
The distribution of trip length for weekdays and weekends is shown in figure 8a. Modal trip length for both weekdays and weekends is 1 - 2 miles, and the shape of the distribution from this interval onwards is quite similar to that for green badge drivers (figure la). The most striking difference between figures 8a and la is the greater proportion of very short trips undertaken by yellow badge drivers (0 - 1 miles). This is reflected in the slightly lower means of 2.21 miles and 2.13 miles for weekday and weekend trips respectively.
The distribution of trip duration is given in figure 8b, which may be compared with figure lb. The two distributions are clearly different, with a far greater proportion of yellow badge trips falling into the category 0-5 minutes - nearly half of all weekend trips fell into this category. Means for the distributions in figure 8b are 10.4 and 8.8 minutes for weekdays and weekends respectively.
As expected trip speeds attained by the suburban based yellow badge drivers were, in general, higher than those attained by their counterparts working in the heart of London. Mean trip speeds were 13.9 and 14.7 mph for weekdays and weekends respectively. The distribution of trip speeds is shown in figure 8c, which, when compared with figure lc, reveals the skew towards higher values attained by yellow badge drivers.
4.2 INTER-TRIP STATISTICS
The distribution of inter-trip length, given in figure 9a, is quite different to that produced by green badge drivers (figure 2a). Figure 9a is clearly less skewed toward lower values than figure 2a, indicating that yellow badge drivers were spending more time travelling between passengers. This could certainly be explained by their reliance on rank hirings: working from one or two main ranks would incur dead mileage directly in proportion to the length of trips undertaken. The similarity between figures 8a and 9a
provides support for this explanation. Mean inter-trip length was 1.88 and 2.11 miles for weekdays and weekends respectively.
Inter-trip duration, which is given in figure 9b, follows much the same pattern as inter-trip length, with yellow badge drivers spending longer periods between passen- gers. Means for weekdays and weekends were 16.0 and 14.9 minutes respectively.
4.3 DRIVER WORK PATTERNS
4.3.1 The working week
The mean length of the working week for the yellow badge drivers including commuting time was 50 hours 6 minutes, which is much greater than that for green badge drivers (44 hours 48 minutes). Working week length excluding commuting time, however, was 34 hours 51 minutes, which is less than the comparable figure for green badge drivers (37 hours 20 minutes). It should be noted that these figures are only based on 11 driver weeks, and should be compared with caution. The mean overall shift length was 8 hours 57 minutes. This is a more robust figure based on 37 observations, and is longer than that for green badge drivers (8 hours 4 minutes). Unlike green badges, yellow badge shifts were similar in duration for both weekdays and weekends (8 hours 54 minutes and 9 hours 6 minutes respectively).
The most popular period for drivers to take a break was 1300 - 1600 hours weekdays '3, when just under half of all recorded breaks were taken. Mean break duration was 107 minutes. In this time drivers would, on average, travel 8.0 miles. During a shift drivers were averaging 0.78 breaks weekdays and 0.77 breaks weekends.
Turnout is discussed in section 3.3.1, and may be directly compared with that for green badge drivers in figures 4a
13 Insufficient data available for weekend analysis.
13
o..
40
30
20
10
0--1 1--2
I ~ Weekdays Weekends
2--3 3--4 4-5 5--6 6-7 7-8
Distance (miles)
Fig.Sa Trip length distribution for yellow badge drivers
8--9 9--10 10+
50
40
30
20
10
0--5 5--10
I ~ Weekdays
10-- 15 15--20 20--25 25--30 30--35
Duration (mins)
Fig.8b Trip duration distr ibution for yellow badge drivers
35--45
Weekends
45+
14
u
(3_
40
30
20
10
0--5 5--10
Weekdays ~ Weekends
10--15 15--20 20--25 25--30 30--35
Speed (mile/h)
Fig.8c Trip speed distr ibut ion for ye l low badge drivers
35--45 45+
I 40 I I1 Weekdays ~ Weekends
30
20 o -
10
0-1 1-2 2-3 3--4 4-5 5-6 6-7 7--8 8--9
Distance (miles)
Fig.9a Inter-trip length distr ibution for yel low badge drivers
9--10 I0+
15
40
30
20
10
0-5
[ ~ Weekdays ~ Weekends
5--10 10--15 15 - -20 2 0 - - 2 5 25-30 30-35 35-45
Duration (mins)
Fig.9b Inter-trip duration distribution for yellow badge drivers
45+
and 4b. The most striking difference is the higher turnout of yellow badge drivers on Sundays, and during early evening. However, a larger sample of yellow badge drivers would be needed to give weight to this finding.
4.3.2 Productivity and use of radio
As with green badge drivers most trips were undertaken by one passenger only (67.0 per cent). The overall mean loading for weekdays and weekends was 1.43 and 1.61 passengers per taxi per trip respectively. A total of 1,753 passengers, and one parcel were carried by the 11 yellow badge drivers during the course of one working week.
On average drivers made 3.14 trips per hour, adjusting for breaks and commuting time, which is higher than the comparable rate for green badge drivers (2.62 trips per hour). The mean total trips per week per driver was 107.7, which is a little higher than the mean total for green badge drivers (93.7). Drivers were travelling 514 miles per week, on average, 454 of which were run in the course of a shift - the remainder arose mainly from commuting. Unadjusted engaged time and mileage was 40.1 and 49.2 per cent respectively, rising to 45.8 and 54.4 per cent when adjusted for commuting. These occupancy figures, which may be compared with those in section 3.3.2 no doubt reflect the relative inefficiency of rank based work, where 'dead' mileage has to be run returning to the only likely source of custom.
Seven of the eleven drivers were members of a radio circuit, four of which belonged to Computer Cab Ltd. These seven drivers were making use of their radio circuit 0.48 times per hour weekdays and 0.84 times per hour weekends, which amounts to an average of 29.3 radio trips per driver per week, or about 30 per cent of all their weekly trips. This is substantially more than the corresponding figure for green badge drivers (19 per cent), and indicates the importance of radio technology in suburban taxi work.
5. PASSENGER QUESTIONNAIRE ANALYSIS
5.1 WHO USES TAXIS?
Not unexpectedly, the majority of taxi users lived in Greater London (60.7 per cent). Passengers resident in the United Kingdom, but living outside Greater London (mainly from the home counties) were the next largest user group (28.5 per cent), with visitors from abroad forming the remaining 10.8 per cent of the taxi travelling public.
A cross tabulation of journey purpose by place of resi- dence is given in table 4. The majority of both London and other UK residents were using taxis for business 14, whereas visitors were mainly using them for tourism.
14 No distinction is made between commuting to/from work and use in the course of conducting business. Strike days were excluded from this analysis.
16
Business users alone accounted for just over half of London's taxi travelling public (55.7 per cent) - a similar proportion (52 per cent) was reported in GLTS (1981 ). This user group is nearly five times the size of the next largest user group - people using taxis for leisure and entertainment purposes.
Business users also dominated all three methods of hire: they accounted for 70.7 per cent of all 'phone bookings, 57.5 per cent of street hailings and 45.2 per cent of rank hirings. Ranks were also used significantly by tourists (20.2 per cent), and street hailing proved popular amongst leisure users (13.2 per cent).
5.2 WHY A TAXI?
The questionnaire was designed to distinguish journey purpose from reason for use i.e. why a taxi and not the
tube or bus?. Table 5 shows a cross tabulation of reason for use by journey purpose. For greater clarification journey purpose was condensed into three categories: "Business", "leisure" (aggregating leisure/entertainment and holidays/tourism) and "Rest" (aggregating Shopping, School/College and Medical). Reason for use was a multiple response variable i.e. passengers were able to indicate more than one reason. Cell values within a column represent the percentage of work, leisure or other users who indicated a particular reason, and as a consequence table columns will add to more than 100 per cent.
All three users types appeared to be in a hurry and/or were finding public transport difficult - the same was true in 1981 (GLTS). Business users in particular were hurrying along: 62.5 per cent gave this reason. In addition about a quarter of leisure and other users were struggling
TABLE 4
Place of residence
Journey purpose Gtr London Rest of UK Abroad All users
Work/Business 55.6% 66.5% 28.0% 55.7%
Shopping 11.0% 6.3% 14.6% 10.0%
School/College 0.4% 0.3% 0.7% 0.4%
Medical 3.6% 3.1% 1.2% 3.2%
Leisure/Entertmnt 14.0% 7.8% 9.3% 11.7%
Holidays/Tourism 4.1% 8.7% 42.0% 9.5%
Other 11.3% 7.2% 4.1% 9.3%
All purposes 60.7% 28.5% 10.8% 100.0%
TABLE 5
Reason for using a taxi Work
Main purpose of journey
Leisure Others Total cases
Bad weather
In a hurry
Heavy luggage
Driving/parking difficult
Journey by public transport is difficult
Don't know the location of destination
For personal safety
Taxi provided by employer
Total cases
5.6% 2.2% 6.5% 5.0%
62.5% 38.4% 45.6% 54.5%
11.4% 28.1% 21.3% 16.7%
14.3% 12.4% 16.5% 14.2%
35.3% 36.1% 35.9% 35.6%
5.1% 18.4% 12.0% 9.2%
7.7% 19.8% 11.7% 11.1 %
19.0% 1.5% 0.9% 12.3%
62.2% 23.0% 14.8% 100.0%
17
with heavy luggage. Further analysis revealed that heavy luggage 'sufferers' tended to be other UK residents and visitors from abroad - presumably using taxis from British Rail and Heathrow ranks. Visitors were also using taxis to find their way around. "In a hurry" at first appears to be curious response given the range of trip speeds in figure lc. If measured objectively however, alternative transport modes may indeed prove slower if, for example, time spent waiting for trains, attempting to find a parking space, queuing for tickets and transferring modes etc are all taken into account. Even more curious is the response to "Bad weather" - presumably the record temperatures during the survey were too high for some!.
It was possible to estimate the yearly total of taxi trips made by each user category. This was achieved by inversely weighting the number of responses by the frequency of use calculated from questionnaire data - otherwise estimates would have been biased toward high frequency users who are more likely to be 'sampled'. From the sample of 6,993 questionnaires 3,488 con- tained sufficient information for this purpose. The esti- mated frequency distributions for both business and non- business is user categories are shown in figure 10. It must be noted that these frequency distributions will possess a degree of 'cross-talk': a leisure user may well declare a rate of taxi use that also reflects their business use and vice versa. The extent of this is unknown, and thus statistics broken down in this way, although useful should be regarded with utmost caution.
The overall mean was estimated to be 22 taxi trips per user per year. London residents, on average, appear to
make more use of the taxi (44 trips per year) than other UK residents (13 trips per year) or visitors (10 trips per year) '°.
5.3 WAITING TIME
Perhaps the most useful statistic that can be obtained from the questionnaire is waiting time. A total of 5,125 questionnaires were completed accurately enough for waiting time to be calculated, although passengers (unlike taxi drivers) tended to round time intervals to the nearest five minutes. The overall distribution of waiting time is given in figure 1 la (mean=4.0 minutes).
Figure 1 lb shows waiting time by day of week. Mean waiting time from Thursday through to Saturday is slightly higher than earlier in the week. Because of the rounding error associated with passenger waiting time weekend means could not be sensibly compared with weekday means in statistical tests of significance. However, the Chi-squared goodness of fit statistic confirmed that there were proportionately fewer observations of less than five minutes, and more above five minutes for Sundays when compared to weekdays (p=0.002) i.e. the distribution for Sundays is skewed toward longer waiting times. Waiting time on Saturdays did not differ significantly in this manner. It should be noted that trip origins were more widely scattered at weekends - particularly Sundays, which would tend to exacerbate passenger delay.
The hourly distribution of waiting time for all methods of hire is revealed in figure 1 lc. Weekday means are fairly consistent from hour to hour, and surprisingly bear little
15 All other categories were condensed for simplicity. 16 These figures are more robust: 'cross-talk' between place of residence is unlikely, although there may be a tendency for visitors to
over-estimate taxi use.
§ c l .
80
60
40
20
0
L 1 Business ~ Non-business
0 -5 5--50 .50-500 500+ Trips per annum
Fig.10 Estimated frequency of taxi use by business and non-business travellers
18
50.
40
3O
0~ Q-
20
10
0-1 1-5
Fig.11a
5 -10 10-15 15-30
Waiting time (mins)
D is t r i bu t i on o f passenger wa i t i ng t i m e
30+
4
C
E
• ,= 3
Mon Tue Wed Thu Fri Sat Sun
Fig.11b Mean passenger wa i t i ng t ime by day o f week
19
E
1 4 -
12 -
10 -
8
6
4
2
I t I t
I t I t
I t P t
I Weekdays . . . . Weekends
- ; , , F ' - .
s ~ It / I I / ~. . /', / " .,,'\ / / " - v \ • / \ . . ," '
., / v -
" t t t l t !
I I ~1 I 1 I I I I
0 3 6 9 12 15 18 24
Hou r ending
Fig.11c Passenger waiting time by hour of day
relation to other hourly measures taken from driver logs such as trip length and duration, dead mileage, total trips undertaken and the likelihood of drivers taking breaks. The strongest correlation was with the mean hourly trip rate per cab (Pearson's correlation coefficient: R=0.544) which is probably acting as a proxy for the number of cabs actually available for hire - a high work rate means fewer empty taxis. Poor relationships and well scattered data precluded modelling of passenger waiting time with other variables. Weekend means are more erratic, but this may be partly due to fewer observations, particularly in the early morning.
Table 6 provides a breakdown of mean waiting time by method of hire, and whether the trip was made on business or not. Overall means for rank and hail were much the same, but as may be expected 'phoning for a taxi took more time. Time lags introduced by pre-booking are inevitable, but one should also bear in mind the nature of this sector of the market: the majority were using taxis for business purposes. Although just over half (52 per cent) of these users were subject to delay, despite advance notice to their radio circuit, no figures of delay imposed on the driver through meetings over- running etc are available. Such passenger - instigated delay may also apply to hail/rank methods of hire, but is unlikely to be as significant.
One curious observation from table 6 is that business users suffer less delay via all three methods of hire. Certainly their requirement for cabs during the day, usually in areas of high demand, places them in a better position than others, but there may also be an element of experience serving to shorten waiting time.
TABLE 6
Method of hire Journey purpose mean (mins)
Phone business 11.4 non-business 13.3 overall mean 11.8
Rank
Hail
business 2.6 non-business 3.1 overall mean 2.9
business 3.0 non-business 3.8 overall mean 3.3
Figure 1 ld illustrates the relationship between waiting time and distance from the centre of taxi operation - nominally taken to be Charing Cross. Means for trip origins lying outside the six mile licensing boundary (see sections 1.1 and 6.1.2) were aggregated to maintain an adequate number of observations for analysis. A signifi- cant increase is evident just before the boundary, as well as a near threefold increase in mean waiting time for origins beyond. It should be noted that within the six mile boundary waiting time will be dependent on the availabil- ity of green badge drivers alone. Beyond this boundary the supply of both green and yellow badges will affect waiting times.
20
10
C
E 6
==
4
0-1 1-2
Fig.11d
2 - 3 3 - 4 4--5 5--6
Distance (miles)
Mean passenger waiting time by distance from Charing Cross
6+
6. THE GEOGRAPHY OF SUPPLY AND DEMAND
6.1 TAXI AVAILABILITY
Driver turnout was discussed in sections 3.3.1 (green badges) and 4.3 (yellow badges). This section is con- cerned with the spatial aspects of availability: where (and when) a taxi becomes available for hire is both depend- ent on the behaviour of passengers and the behaviour of the driver. Folklore has it that London's green badge drivers are nowhere to be seen South of the Thames, or for that matter, many miles from the West End - apart from Heathrow Airport. Yellow badge drivers are rela- tively few in number, and are reported to serve only a few suburban areas well (Ealing, Wimbledon, Croydon and Ilford).
6.2 GREEN BADGE DRIVERS
Sections 3.1 and 3.2 establish that taxi trips, on the whole, are short, and that drivers do not travel very far to obtain their next passenger. Taken together these findings would seem to suggest that taxis rarely wander far from their initial hiring point merely by virtue of the nature of demand, let alone driver behaviour. This effect is clearly seen in figures 12a and 12b, which display the spatial distribution of the 20,583 trips undertaken by the 220 green badge drivers. In these figures trip totals are aggregated to each kilometre square of the Ordnance Survey Grid, and then plotted to scale.
As may be expected the spread of trip origins is less than the spread of destinations, but both exhibit a high
concentration of trips in the heart of the West End. The relative lack of trips to/from areas South of the Thames is also noticeable, along with the impact of Heathrow Airport (near the Western edge of the Greater London bound- ary). In this instance folklore, it seems, is reasonably accurate: 97.5 per cent of all trip origins and 95.2 per cent of all trip destinations fell within a six mile radius of Charing Cross.
It is not easy to determine how far driver behaviour has shaped the spatial distribution of figures 12a and 12b. However, it is possible to look at their activity in suburban areas. Only 320 trips originated beyond the six mile zone (but excluding Heathrow Airport), which represents 1.8 per cent of all trip origins. About 37 per cent of these suburban trips immediately followed a previous hiring to the same locality. A further 46 per cent were coincident with the first/last jobs of working shifts - presumably when drivers were travelling between central London and home. The remaining 17 per cent were the result of drivers actively seeking work (hail/rank trips=39) or answering a radio call (16 trips) outside the central licensing zone during a work shift (0.3 per cent of all trip origins). Drivers returned directly to the central zone after 201 of the 320 suburban trips (62.8 per cent). Figure 13 shows this behaviour in the form of a vector diagram. Mean destination points were calculated for Kilometre squares, whose centres are marked with an 'o'. The vectors arising from these centres thus indicate both the mean direction and distance of trip destinations. The overall behaviour of drivers is quite clear: the majority of vectors either point toward, or reach the most central areas. There are few exceptions, the most notable being an area of local 'interest' near the six mile boundary in the South East (Lewisham). It should be noted that the
21
[ ]
[ ]
DA
Trips per Km square
- ~ 1 only
1-10
10-100
100-1000+
[ ]
[ ] [ ]
[ ] [ ] [ ]
M
[] % [ ]
% m [ ]
[ ]
Fig. 12a Green badge drivers: Spatial distribution of trip origins
'null point', just West of the licensing zone centre is caused by an equal distribution of inter-trips about this centroid, thus resulting in a vector of zero length.
6.3 HEATHROW AIRPORT
Only green badge drivers are allowed to ply for hire at Heathrow Airport. They are allowed to set-down passen- gers on the departures forecourts of each terminal, but are forbidden by airport bye-laws to pick up passengers directly. Instead they must join a queue of taxis waiting in a feeder park, which has a capacity for about 400 vehicles 17. Wardens are then able to dispatch batches of taxis to terminal forecourts as required.
Feeder park dwell times can be lengthy, with anecdotal reports typically of one to two hours, when some 500 taxis may be waiting.
Trips to/from Heathrow Airport may have been slightly under-represented in the survey, as explained in Appen- dix B. When adjusted for this such trips still only ac- counted for 2.0 per cent of the total trade (origins and
destinations). Analysis of work patterns in section 3.3.2 revealed a concentration of these around 0600 hours, when passengers were travelling to catch early flights. The impact of Heathrow is visible in figures 12a and 12b (near the Western edge of the Greater London bound- ary), but even so it does not exceed trip density else- where in the heart of the West End. Indeed independent observations (Appendix B) indicate that Waterloo Station is at least two to three times busier. Mean dwell time was 106 minutes, which compares favourably with anecdotal evidence.
Heathrow trips represent just a fraction of the total trade. Given that a proportion of the taxi supply needs to stand idle at Heathrow in order to cope with erratic demand peaks, it is considered unlikely, in view of the above findings, that the feeder park is having a significant effect on the quality of service elsewhere.
6.4 THE"KNOWLEDGE"
Prospective drivers must convince examiners at the PCO that they possess a thorough understanding of London's
17 A further 100 vehicles may queue along the feeder park road.
22
T '? - [ ]
[ ]
[ ]
@ •
Trips per Km square
1 only
1--10
10--100
I 100--1000+
[ ]
[ ]
[ ]
[ ]
[ ]
C ] I
m [ ]
[ ]
Figo12b Green badge drivers: Spatial distribution of trip destinations
geography by passing the "Knowledge of London" examination. The most demanding form of this test requires an applicant to display a detailed knowledge of:
"streets, squares, clubs, hospitals, hotels, thea- tres, Government and other buildings, British Rail and London Transport stations, police stations, coroner, crown, magistrate and county courts, diplomatic build- ings, important places of worship, cemeteries, cremato- ria, public houses of interest, museums, industrial and residential buildings, parks and open spaces, sports and leisure facilities, benevolent institutions, societies and associations, colleges and other places of learning, restaurants, historic buildings etc. and give the routes between these places."
within a six mile radius of Charing Cross, together with some degree of familiarity of the area beyond. This is a major undertaking for applicants, normally taking two or even three years, and is tested in a series of examina- tions called "Appearances". To assist the applicant the PCO provides a list of 468 routes ("Runs") which must be learned before the first "Appearance". This list is known
as the "Blue-book", despite it's red cover. Success entitles the applicant to wear a green badge, and to ply for hire anywhere within the Metropolitan Police District. A less stringent requirement of memorising a smaller area of London's suburbs beyond the six mile boundary entitles the successful applicant to a yellow badge and to ply for hire in this locality only. Requirements are thus rigorous indeed for green badge drivers, and perhaps serve as the most powerful restraint on the growth of London's taxi industry. It is of interest therefore to ascertain how well the "knowledge" prepares new drivers for the demands to be made of them.
The cumulative percentage of trip ends (origins and destinations) falling within various radial distances of Charing Cross 18 is shown in figure 14a. This curve may be compared with the cumulative percentage curve for the trip ends listed in the "Blue-book" (section 1.1 ), which were also calculated in this fashion. Up to 4 - 5 miles both curves rise steeply, and the proportion of actual trip ends exceeds the proportion of trip ends in the "Blue-book". For example, if the "Knowledge" was limited to a circle of radius 3 miles, the "Blue-book" syllabus would be 35 per
18 Charing Cross (at OS 530150,180500) lies close enough to the mean centres for trip origins and destinations (OS 529130,180650 and OS 528970,180640) to be considered the 'centre' for operational purposes.
23
"o
Fig.13 Vector diagram of green badge inter-trips
cent smaller, and yet provide newly qualified "cabbies" with an initial working knowledge sufficient to cover 82 per cent of all trip ends.
To produce data for figure 14b actual trip end counts were aggregated to kilometre squares and then plotted as a cumulative percentage distribution against the inverse probability for trips to start/end in each of the kilometre squares. There is a significant tail to this distribution: these are squares where, individually, the probability of a trip occurring is very low, but collectively they amount to a significant proportion of the total trade. The cumulative distribution for "Blue-book" trip ends is plotted for comparison. Squares with a trip probability greater than or equal to 1 in 500, for example, account for 87.5 per cent of actual trip ends and cover 76.4 per cent of the syllabus. If the "Knowledge" was limited to these squares individual drivers would expect to be baffled by passengers' requests about once every five weeks.
Although arbitrary squares were chosen for comparison, this method does suggest that the "Knowledge" could match demand more closely on an area by area basis, than by overall reduction in the central licensing zone -
the above examples are purposefully dramatic in this respect. Detailed changes to the syllabus could not, of course, be satisfactorily derived from spatial analysis alone: many factors lying outside the scope of this survey would also have to be considered before change to a key aspect of London's taxi industry. For example, two key assumptions underlying the spatial analysis are that: a) drivers remember all of what they are required to learn, and b) the "Knowledge" exam solely dictates how much a driver knows about London's geography. These are related, and will undoubtedly have complex repercus- sions on patterns of taxi operation - to what extent is figure 12b, and thus all other statistics, a function of driver memory?.
6.5 YELLOW BADGE DRIVERS
At the time of the survey London's suburbs were divided into six zones for the purpose of licensing yellow badge drivers. These are depicted in figures 15a and 15b, which show the origins and destinations of the 1,049 trips undertaken by the 11 yellow badge drivers during their week's work. Three prominent centres of activity can be discerned which correspond to the Ealing, Harrow and
24
2 8
100
80
60
40
20
0
= = = = = = =
J,
I I I I I I I I
1 2 3 4 5 6 7 8
= = . . . . . . . . .
Survey • B l u e - b o o k
I I I I I I
9 10 11 12 13 14 1
Radial d is tance (miles)
Fig. 14a Radial distribution of trip ends from Charing Cross
Q .
100
80
60
40
20
0 10
i i I ~ I I l t l I I ! I t I l l l I I I I I I l l l
1 O0 1000 10000
- - B l u e - b o o k
I I I
1 / p r o b a b i l i t y
Fig.14b Cumulative distribution of actual and "Blue-book" trip ends
I I i i
100000
Bromley areas. Unlike green badge driver trips (figures 12a and 12b) there is a pronounced asymmetry between origin and destination patterns which at first sight sug- gests more origins than destinations!. This arises from reliance on town centre ranks, producing a concentration of trip origins in just a few kilometre squares. Unfortu- nately there are too few yellow badge trips to allow more detailed spatial analysis.
7. I N C O M E
Although details of fares taken were not obtained from drivers, it was possible to estimate maximum and minimum values between which 'true' fares lay (see appendix C). This method of estimation was subject to statistical testing, which is discussed in appendix B, and which confirms the accuracy of the methodology. It
25
[]
- - 1
D
Trips per Km square
1 only
~ 1-10
] 10-100
100-1000
[ ]
[]
[ ]
[ ] [ ]
[ ] [ ] < - [ ]
F ig. 15a Yel low badge d rivers:
should be noted that all revenue rates given below take account of dead time and mileage, but exclude journeys to and from home and trips undertaken to, from and during lunch breaks etc. Estimation of gratuities to the driver ("Tips") was impossible: this is largely dependent on the generosity of individual passengers and is some- thing which cannot be modelled!. This extra income therefore was not included in the following analyses.
7.1 FARES AND DRIVER REVENUE
Table 7 contains three measures of revenue: income per mile, income per hour and income per trip. The last of these is, of course, a measure of the average fare paid by passengers. Columns headed 'min' and 'max' result from calculations using the minimum and maximum estimated fare boundaries. True revenue rates lie somewhere between these extremes. Drivers' gross weekly earnings varied greatly according to hours and days worked, but on average were calculated to lie between £350.08 - £477.08 for green badges and £342.82 - £446.62 for yellow badges.
Spatial distribution of trip origins
Analysis of variance techniques were used to identify statistically significant differences between cells of interest in table 7. Weekday and weekend trip rates (i.e. fares) were not significantly different for both driver types. This is surprising given the extra charges applicable to weekend hirings. It is possible that the less congested traffic conditions at weekends is serving to reduce the likelihood of taxi-meters clocking time units in addition to distance units, thus offsetting surcharges.
However, green badge trip rates were significantly higher (p<0.0001) than those for yellow badges. This is not unexpected given the lighter traffic conditions in the suburbs (see above) and the tendency for yellow badge passengers to make shorter trips (section 4.1) than those travelling in more central areas. Weekday and weekend mileage rates were not significantly different for both driver types. But again, green badge mileage rates were significantly higher (p<0.0001) than those for yellow badges. This reflects the differences in operation of the two factions of the trade: most suburban work is rank based (section 4.1 ), and thus necessarily includes a
26
-q I I___
E
Trips per Km square
I I l o n l y
1--10
U 10--100
100--1000+
i - ~ 1_.1_113 I [ ] _ _ _ [ 3 _ _ _ [ ]
[ ] [ ] [ ]
[ ]
[ ]
[ ]
EP [ ] ~ - - '__~q~- Fq ~ [ ]
[ ]
[ ]
Fig. 15b Yellow badge drivers: Spatial distribution of trip destinations
TABLE 7
£/mile min max
Estimated revenue rates
£/hour min max min
£/trip max
Green Badge Drivers
Yellow Bage Drivers
Weekday 1.05 1.44 8.41 11.52 3.87 5.32
Weekend 1.04 1.38 9.76 12.89 4.27 5.66
Weekday 0.77 1.00 6.71 8.88 3.21 4.25
Weekend 0.77 0.96 8.17 10.15 3.31 4.14
27
considerable proportion of 'dead' mileage in contrast to the greater efficiency afforded by street hailing - which forms the greater part of green badge work (section 3.1 ). Yellow badge weekday and weekend hourly rates were not significantly different, despite tariff differences. However, green badge weekday and weekend hourly rates were different (p<0.0001), and may partly be explained by a swing to rank based work at weekends by green badge drivers 19. Green badge weekday hourly rates were significantly different (p<0.0001) from yellow badge weekday rates, but the swing to rank based work at weekends results in reasonably similar hourly rates for both driver types (p=0.4503 for minimum and p=0.0069 for maximum estimates).
As discussed in section 2.4 fares cannot be calculated directly from the values of distance and time. Although desirable, it is not possible therefore to show a simple relationship between trip distance and fare paid. It is possible, however, to estimate the range of likely fares, as bound by the mean minimum and maximum esti- mates, for given intervals of distance - this fare range may be regarded as the level of 'financial uncertainty' facing a passenger. This information is presented in figure 16, where the shaded area indicates the fare range. For clarity only the upper values for the distance intervals are shown, and it should be noted that the abscissa scaling is non-linear. The level of uncertainty increases with distance in near linear fashion for trips up
to 6 miles or so. The solid thin line plots uncertainty expressed as the percentage difference between mini- mum and maximum fares over the minimum fare. Trips of six miles or less are those most likely to remain within the heaviest traffic congestion, and thus uncertainty in- creases in a fairly predictable fashion. On longer trips, the greater speeds attainable further from London's centre tend to reduce uncertainty: fares will depend mainly on distance covered 5.
7.2 INCOME AND TAXI SUPPLY
It was possible to calculate revenue rates for each hour of the day for green badge drivers (there was insufficient data from yellow badge drivers to allow a sensible comparison). In doing so journeys to/from home were necessarily excluded, thus reducing the proportion of dead time and mileage in the calculations. Revenue per mile and revenue per hour are shown in figures 17a and 17b respectively. The differential effect of tariff sur- charges is visible in figure 17b: flat rate increments 2° are added to hirings outside the time band 0600 to 2000 hours for weekdays. The same also applies on Satur- days, with a smaller increment applicable to the period 0600 to 2000 hours (a single surcharge applies to Sunday hirings). This gives rise to the shallow "U" shaped curves for weekdays, and to a lesser extent weekends, where hourly rates are higher outside the period 0600 to 2000 hours. In contrast figure 17a shows a marked
19 This was confirmed by an analysis of variance (p<0.0001).
20 At the time of the survey these were 40p or 60p per hiring, depending on the time period and day.
50.00
40.00
"~ 30.00
g E
u_ 20.00
1 0 . 0 0
0.00 I I 3 4
F i g . 1 6
I I I I I I I 5 6 7 8 9 10 12
Distance (miles)
E s t i m a t e d m e a n f a r e b o u n d a r i e s b y t r i p d i s t a n c e
14
70
60
50
§ 40
v
30 ~_ a
20
10
I I0 20 25+
28
2.50
2.00
E 1.50
1.oo
0.50
0.00
. . . . Weekday min imum
. . . . . . . . . . Weekend min imum
- - W e e k d a y max imum
. . . . Weekend max imum
\ ~ ' ~ ~ _ . , ~ ' - ' f 7 \ . I - - ~ ~ - - - - . ~ ._ " ~ ~ I \ ~ . . . . . ~ ' - - " ~ - ~ " ~ - - - - ' - " ' ~ - " . . . . . . . . .
. . . . . . ~ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . -~...,._* . . . . .
."...._ - - =>_......~_.~__..----~.-..-:-- / - . . . . . .
I I I I I I I 3 6 9 12 15 18 21
Hour ending
Fig.17a Green badge drivers: Estimated revenue per mile by hour of day
24
25.00
..c-
20.00
15.00
10.00
5.00
0.00
. . . . Weekday min imum Weekday max imum
. . . . . . . . . Weekend min imum - - - - - - Weekend max imum
//
I'-'-.'- - ~ . / \ ',, ' . r ' f '~ . ' " . -~ , . . ,~ -~ ,~ . . ' ~ . . ~ , = , " - ~ .." . . . . . I " ' / , . ~ - - " \ " v " ~ . - ~'-~-7 ~ / . - - ' _ ' . I - . . . .
I I I I I I I I 3 6 9 12 15 18 21 24
Hour ending
Fig.17b Green badge drivers: Estimated revenue per hour by hour of day
decline in revenue per mile for these "unsocial' hours. This near inverse relationship between figures 17a and 17b can be attributed to variation in traffic speed and demand, as explained in the above paragraph, and has important implications for taxi supply.
Drivers wishing to maximise overall revenue by taking account of fares taken in each hour would be expected to shift their work patterns toward higher hourly rates obtainable in the 'unsocial' hours. In attempting to maximise revenue in this way, however, drivers would certainly have to work harder at finding passengers, thus offsetting such gains by increased operating costs. Despite this disadvantage a few drivers preferred to work
during 'unsocial' hours (section 3.3.1), some simply because traffic conditions were better. The similarity between weekday and weekend hourly rates is particu- larly noteworthy: measured in this way incentives offered for weekend work (via flat-rate surcharges) are totally offset by the effects of lower demand. It is not surprising therefore that turnout on weekends is poor, even from drivers wishing to seek better traffic conditions.
Alternatively drivers may seek to maximise revenue in terms of fares taken for mileage travelled. This would certainly be the case for those drivers renting cabs on a mileage basis, or by owner drivers (known in the trade as a "Mush") wary of fuel bills and other running costs.
29
Drivers wishing to maximise revenue in this way would be expected to concentrate their working day between 0900 and 1800 hours. Flat-rate surcharges for "unsocial' hours and weekends are clearly insufficient to compensate for lower levels of demand, and drivers would therefore be expected to avoid operating during this period. Overall turnout patterns shown in figure 4b closely reflect this expectation, which suggests that most of the drivers in the survey were making operational decisions via some perception of "a good days work' akin to revenue per mile.
7.3 INCOME AND RADIO WORK
In section 3.3.2 it was discovered that use of the radio was, on average, resulting in longer trips and following dead time/mileage, and thus a lower hourly work rate. This was reflected in a higher weekly mileage for fewer trips. The disbenefit, however, was not apparent in an analysis of weekly gross fare income: radio drivers were estimated to be earning between £354.25 and £486.30, compared to £345.57 - £465.77 for non-radio drivers. Statistical tests confirm this similarity.
It should be noted that this comparison does not take account of surcharges or minimum hire charges levied by radio circuits or additional payments to member drivers, or indeed arrangements made by drivers renting their vehicle, whether equipped with a radio or not.
8. D ISCUSSION
Throughout the body of this report comparisons with various statistics from earlier surveys have been drawn. In general little seems to have changed over the last 20 years: this is evident in table 8, which summarises comparisons (1969=Maxwell Stamp, 1976=Price Com- mission, 1989=TRRL). Taking into account fare tariff increases and differences in survey methodology, the only clear changes seem to be in the slightly longer working week, the proportions of engaged time/distance and the proportions of taxis equipped with radios. Even then, working week length and engaged time/distance differences may be partly explained by changes in commuting patterns. This striking similarity with earlier surveys is in itself an interesting observation given the changing economic background: a period of relative economic "boom" in 1968, a period of high inflation and slow growth in 1976 with summer 1989 at the top of a reasonably sustained period of significant growth. Despite such change the pattern of taxi use has re- mained more or less constant - which is not altogether unsurprising: business users still need to get in and out of the City, and entertainment is still largely concentrated in the West End. What is surprising, however are the near identical hourly trip rates in view of a substantial increase in licensed drivers/vehicles 21. Patronage has clearly increased over the last two decades, but the percentage of passengers waiting more than five minutes has
changed very little. Taken together these two facts suggest that the growth in demand has been more or less evenly matched by a corresponding growth in taxi supply. This matching of supply to demand was also evident on a daily and hourly basis (section 3.3), with the result that passenger waiting time varied little by day and by hour (with the exception of Sundays/early mornings).
There remains the question of frustrated or potential demand, which cannot be measured directly, and could be inferred only from information not gathered in a survey of this kind. The spatial distribution of trips supports the folklore on availability of taxis, and no doubt potential users turn to the many private hire car companies for transport in the suburbs.
The sheer size of this market (about 37,000 vehicles: Lee 1988) provides a strong indicator that taxis are unable to meet demand, particularly in the suburbs.
In addressing frustrated suburban demand one must not forget the role of the yellow badge taxi driver. Yellow badge drivers, who are by law only allowed to work in the suburbs, rely heavily on rank and radio work for trips which, on the whole largely start and end in the same locality. This pattern of operation is probably closer in nature to that of private hire drivers, and resembles provincial taxi operation, where taxi and private hire car services share much the same market (Greening and Jackson 1982, Coe and Jackson 1983). However, these very factors combine to put them at a financial disadvan- tage with respect to their green badge counterparts (section 7.1).
Section 7.2 concluded that flat-rate surcharges for work during 'unsocial' hours were insufficient. Further, drivers appeared to be making operational decisions based on some perception akin to revenue per mile. Improvement in supply during the early hours, therefore, is only likely to take place when the fare tariff provides a financial incentive on this basis. Changing the tariff, however, will affect passenger as well as driver behaviour. Thus benefits designed to alleviate frustrated demand may not necessarily materialize. It is possible to predict likely outcomes of given fare changes using the data gathered in the survey in conjunction with economic models, but at present the critical elasticities remain unknown. These could be determined only by careful comparison of further surveys of this kind.
9. SUMMARY
A major survey of London's taxi industry was undertaken during the period 17th July to 13th August 1989. A total of 231 volunteer taxi drivers were asked to keep detailed records of a complete week's work, and to hand out self- completion questionnaires to their passengers. The main conclusions of the survey were:
21 Between 1976 and 1989 there was a 32 per cent increase in licensed vehicles and a 27 per cent increase in drivers.
30
TABLE 8
1969
Year of Survey
1976 1989
Number of volunteer drivers %age of licensed drivers Number of returned logs Number of trips in analysis
Trip length (miles) Trip duration (mins) Trip speed (mph) Mean fare per trip (£)
Trip rate (trips/hr) Idle time per trip (mins)
Hourly revenue (£/hr) Revenue per mile (£/mile)
%age engaged time
%age engaged mileage
Daily trips per driver Shift length Weekdays(hrs) Shift length Saturdays(hrs)
Weekday loading (pass/trip) Saturday loading (pass/trip)
Working week length (hrs)
Weekly mileage (miles)
Weekly trips %age drivers working >30hrs c
%age taxis with radio
%age hailed trips %age trips from ranks %age trips by radio
%age work/business trips %age passgrs waiting >5mins
347 2.7%
640 n/a
2.4 14 10
0.350
n/a n/a
n/a 0.1460
n/a
60-65
22 9 8
1.5 1.8
n/a
n/a
n/a n/a
11.0
70 25
5
54 14
106 0.6%
106 700
2.7 n/a
9.57 a 1.25 a
2.3 9.3 b
2.78 a n/a
65.6 a
58.0 c
n/a n/a n/a
n/a n/a
35.9 c
381.6 c
82.2 73.6
20.8
n/a n/a n/a
n/a n/a
231 1.1%
1,162 18,534
2.5 14.5 10.7
3.94-5.38
2.3 11.7
8.64-11.75 1.05-1.43
52.3 c 63.6 a
54.7 c 70.1 d
18.7 8.1 6.5
1.6 1.9
44.8 c 37.3 d
435 c 337 d
93.7 76.4
42.0
70 22
8
56 18
a Mid week day-time only b Their estimate c Includes dead time/mileage to/from home d Excludes dead time/mileage to/from home
31
1. Green badge driver trips were short: mean distance was 2.46 miles for weekdays and 2.69 miles for week- ends, mean duration was 14.7 minutes and 13.3 minutes for weekday and weekend trips respectively. Mean fares were estimated to lie between £3.87 and £5.32 for weekdays, and £4.27 and £5.66 for weekends. Trip speeds were found to reflect London traffic speeds in general (mean=10.5 mph weekdays, 12.0 mph week- ends). The majority of trips (70 per cent) were by street hailing.
2. Green badge inter-trips ("dead mileage") were much shorter: mean distance was 1.10 miles for weekdays and 1.23 miles for weekends, and mean duration was 11.7 minutes and 12.1 minutes for weekday and weekend inter-trips respectively. Passenger bearing trips ac- counted for 70.1 per cent of the total mileage and 63.6 per cent of total time spent plying for hire (when adjusted for driver commuting time). Unadjusted engaged mileage and time was 54.7 and 52.3 per cent respectively.
3. The average working week for green badge drivers was 37 hours 20 minutes, during which drivers were travelling a mean 337 miles (adjusted for commuting time and distance). Mean weekly revenue was estimated to lie between £350.08 and £477.08. Drivers were individually at their busiest in the early hours/late evening, although the greatest volume of trips overall was undertaken in the afternoon/early evening. Adjusted mean trip rate was 2.62 trips per hour.
4. Radio work accounted for about 19 per cent of the weekly trip total for green badge radio circuit members. Radio work was discovered to result in a statistically significant increase in "dead" mileage and time, but overall weekly revenue was no worse than that for non- radio drivers.
5. Yellow badge drivers were found to rely more heavily on rank (70 per cent) and radio work (17 per cent). Their passenger bearing trips were shorter, on average (2.21 miles and 10.4 minutes weekdays, 2.13 miles and 8.8 minutes weekends), whilst "dead" trips were longer, on average (1.88 miles and 16.0 minutes weekdays, 2.11 miles and 14.9 minutes weekends) than their green badge counterparts.
6. Yellow badge drivers were working 34 hours 54 minutes per week on average (excluding commuting time), and were more likely to work weekends and evenings than green badge drivers. Weekly earnings were calculated to lie between £342.82 and £446.62. Passenger bearing trips only accounted for 45.8 per cent of mileage and 54.4 per cent of total time spent plying for hire when adjusted for commuting (40.1 and 49.2 per cent unadjusted). Lower engaged rates were attributed to the relative inefficiency of rank based work.
7. The majority of taxi users were residents of Greater London (60.7 per cent), and were using taxis for busi- ness/work purposes (55.7 per cent). Many preferred to use a taxi because they were in a hurry, or they found public transport inadequate. Mean passenger waiting time for all methods of hire was 4.0 minutes.
8. Spatial analysis of trip origins and destinations indicated that Charing Cross could still be considered to represent the centre of taxi operations. The distribution pattern supported hitherto anecdotal evidence that the majority of green badge activity occurs within a few miles of central London: 97.5 per cent of all origins and 95.2 per cent of all destinations lay within a six mile radius of Charing Cross.
10. Further analysis suggested some scope for modifica- tion of the knowledge of London exam (the "Knowledge")in order to match the syllabus more closely to that of actual demand.
11. Historical comparisons, together with operational data suggested that on the whole, the trade is regulating itself so as to maintain the balance of supply and demand - as indicated by passenger waiting times. However, frustrated demand was deemed to occur in the suburbs in particular - as indicated by the presence of the un- licensed private hire industry. Green badge drivers appeared unwilling to work in these areas: only 0.3 per cent of all trips originated outside the six mile central licensing zone, and yellow badge drivers are relatively few in number, representing between 4.8 and 8.1 per cent of licensed drivers. No clear solution to this situation could be offered by analysis of the survey.
10. ACKNOWLEDGEMENTS
The work described in this report was carried out in the Transport Demand Division of the Traffic Group of the TRRL.
Management of the survey and preliminary analyses were carried out in the Transport Planning Division of the Safety and Transportation Group of the TRRL. Many thanks to Angle Astrop for assistance with coding and analysis, and to Dr lain York for assistance with fare modelling.
The author wishes to thank British Rail Southern Region, Computer Cab Co. Ltd., Heathrow Airport Ltd., the Licensed Taxi Drivers Association, the London Taxi Board, Public Attitude Surveys Ltd. and the Public Carriage Office for their cooperation.
Special thanks are due to the volunteer drivers for their remarkable efforts in providing clear and detailed infor- mation.
11. REFERENCES
COE G A and JACKSON R L (1983). Some new evi- dence relating to quantity control in the taxi industry. Department of Transport TRRL report SR797: Transport and Road Research Laboratory, Crowthorne.
32
GREATER LONDON COUNCIL (November 1981). GLTS '81 Taxi Survey. GLC internal note.
GREATER LONDON COUNCIL (October 1985). GLTS '81 Taxi Survey. Analysis Report No. 2, TS Note 163. Internal GLC report.
GREENING P A K and JACKSON R L (1982). The Basingstoke taxi and private hire car study. Department of Transport TRRL report LR1062. Transport and Road Research Laboratory, Crowthorne.
HOME OFFICE (October 1970). Report of the Depart- mental Committee on the London Taxicab Trade. Chair- man: The Hon. A Maxwell Stamp HMSO, Cmnd. 4483
LEE H (1988). Market study of the London mini-cab trade. Department of Transport TRRL report CR91: Transport and Road Research Laboratory, Crowthorne.
PRICE COMMISSION (1977). Prices, Costs and Margins in the Provision of Taxicab and Private Hire Car Services. Presented to parliament in pursuance of Section 11 (3) of the Price Commission Act 1977. Printed 2nd August 1978. HMSO, 655.
APPENDIX A:
Example driver log (top sheet only) and passenger questionnaire overleaf.
33
Appendix A
Example driver log (top sheet only) and passenger questionnaire
T. R. R.L. LONDON TAXI SURVEY - JOURNEY LOG IIII[III] Name of radio circuit (if applicable):
Date of shift '89
Number of this log:
Total logs used for shift: D
Mileometer readings:
At START of shift
At END of shift
Method Number PICK-UP POINT of of Road & nearest
Hire Passgs intersecting road
. . . . . . . . . . . . . .
2
!3 ...............
SET-DOWN POINT Road & n e a r e s t
Time i n t e r s e c t i n g r o a d
I
1 7 . . . . . . T . . . . . . . _ . . . . . . . . . . . . . . . . . . . . . . . . . . . . . - . . . . . . .
. . . . . . . l . . . . . . .
Time
.......
34
17.1_89 PAS 1 2 2 5 9 / R L T R R L L O N D O N T A X I S U R V E Y : P A S S E N G E R Q U E S T I O N N A I R E
( 6 - 1 0 ) (if) (:D
The Transport an~ Road Research Laboratory (TRRL), which i s part of the Department of Transport, is undertaking this survey to gather information on passenger use. Please help us by completing this form and sealing it in the envelope provided. PLEASE WRITE CLEARLY.
1 .
2 .
3 .
4 .
5 .
6 .
7 .
8 .
9 .
PLEASE WRITE IN THE DAY AND DATE OF YOUR JOURNEY : DAY .............
DATE / /89 Where do you normally live? TICK ONE BOX
GREATER LONDON D ! (19) - write in the borough or area
REST OF UK [---] 2 write in which county
ELSEWHERE [--7 3
What is the main purpose of this journey? TICK ONE BOX IN EACH COLUMN
WORK OR BUSINESS I I 1 ( 6 1 ) TO [ ] 1 ( 6 0 ) S } t O P P I N G I I 2
OR FROM [ ] 2 SCHOOL/COLLEGE [ ] 3 MEDICAL l i 4
ENTERTAINMENT I l 5 HOLIDAY OR TOURISM i l 6
OTHER i i 7 write in
How often do you normally use a London taxi?
PLEASE WHITE IN TIMES A DAY [ I I (14) ( 1 2 , 1 3 ) A WEEK [ I 2
A MONTH [ I 3 A YEAR I l 4
W h e r e d i d y o u s t a r t t h i s t a x i j o u r n e y ? W R I T E I N L O C A T I O N
. . . a n d a t w h a t t i m e ? a m / p m W R I T E I N AND I N D I C A T E AM o r PM
Where will you end this taxi journey? WRITE IN L O C A T I O N
How did you obtain this taxi? TICK ONE BOX BY TELEPHONE i i I (59)
AT A TAXI RANK I I 2 BY S T R E E T HAILING [ I 3
OTHER ] I 4 write in IF YOU TELEPHONED When did you arrange for the taxi to come? TICK ONE BOX AS SOON AS POSSIBLE [ J l (75)
AT A SPECIFIC TIME ~ 2 am/pm (PLEASE WRITE IN & INDICATE am or pm)
And when did you telephone? TIME am/pm (WRITE IN & INDICATE am or pm)
IF BOOKED BEFORE TODAY WRITE IN DATE BOOKED /
IF AT A RANK OR BY HAILING How long did you }]ave to wait? WRITE IN minutes
Why did you take a taxi? (YOU MAY T I C K MORE THAN ONE BOX)
BAD WEATHER [ I i ( 2 3 IN A HURRY I J i (24
HEAVY LUGGAGE I 1 1 (25 DRIVING OR PARKING DIFFICULT I I 1 (26
JOURNEY BY PUBLIC TRANSPORT DIFFICULT ~ ! (27 DON'T KNOW LOCATION OF DESTINATION f--7 1 (28
P E R S O N A L S A F E T Y I I 1 ( 2 9 PROVIDED BY EMPLOYER I ] 1 ( 3 0
O T H E R R E A S O N [ ~ 1 ( 3 1 W R I T E I N
T o t a l n u m b e r o f p a s s e n g e r s i n t a x i ? W R I T E I N I i ( 6 1 )
1 2 - 1 4 )
15 - 1 8 )
2 0 - 40)
41 - 5 0 )
6 2 - 8 0 ) ( 1 1 ) O
1 5 - 34
3 5 - 3 9
4 0 - 5 8
6 0 - 74
76 ,i17° 1 2 - 1 6
17 - 20
21 , 2 2
32 - 60
THANK YOU FOR YOUR HELP
35
APPENDIX B" ANALYSIS OF INDEPENDENT DATA SOURCES
ROADSIDE SURVEY
An independent count of taxi movements made at differing types of location was undertaken for comparison with movements made by drivers in the survey. A representative sample of volunteers would be expected to exhibit the same pattern of operation as that observed by independent means.
A team of several observers was used to count pick-ups and drops over two hour periods at different times/days at the following locations: Waterloo Rail Station, Westmin- ster Abbey, junction of Gracechurch St and Lombard St (City), junction of Oxford St and Berners St, St Martins lane (from the Duke of York's to the London Coliseum theatres) and the Hilton Hotel (forecourt). Observations were made at regular intervals throughout the duration of the main survey for a total of 33 hours.
These places were chosen a) to represent a variety of custom for 'cabbies' and b) to provide reasonably sized counts. Prior observation excluded sites where counts were likely to be low, where line of sight was restricted or where the 'boundary' of the location was likely to prove ambiguous in latter analysis.
Computer programs were employed to search for these same locations in the database of trip origins/destina- tions. A comparison of counts at these locations appears in table B1 : a Chi-squared test of association supports the hypothesis that there is no significant difference between roadside and database counts. Thus the volunteer drivers can be deemed representative in respect of work patterns across these six locations.
COMPUTER CAB OPERATING RECORDS
Computer Cab Ltd. - London's largest radio circuit kindly supplied complete details of all jobs undertaken on the 7th, 8th and 9th August 1989. This information was used as an independent measure of drivers' use of the radio, and to assess the accuracy of fare estimates (see section 2.4 of report).
Radio 'shift' length was taken to be the period of elapsed time between first and last radio jobs accepted by a driver. Mean daily radio 'shift' length for volunteer and Computer Cab drivers was 4.97 and 4.88 hours respec- tively. Analysis of variance techniques indicate that there is no significant difference between the two sources of data.
The daily number of radio jobs undertaken by volunteer and Computer Cab drivers is shown in figure BI. The close correspondence between the distributions suggests that survey drivers were using the radio at much the same rate. Mean rate of radio use for volunteer and Computer Cab drivers was 3.81 and 3.84 trips per day respectively. A Chi-squared test of association confirms the hypothesis that there is no significant difference between these distributions.
Forty two volunteer drivers were members of the Compu- ter Cab circuit. Cross referencing of journey details between the survey and Computer Cab data enabled the identification of those volunteer drivers working on the 7th, 8th and 9th of August in the Computer Cab records. Consequently, it was possible to compare their estimated fares with actual meter readings.
Figure B2 shows the estimated minimum and maximum fare boundaries for these trips along with the actual meter
TABLE B1
Location
Source of count data
Roadside survey count/hr percent count
Database percent
Oxford St junction 28 5.33 49 4.07
St Martin's lane 26 4.94 52 4.32
Westminster Abbey 32 6.14 62 5.25
Gracechurch St junc 11 2.12 33 2.74
Waterloo station 368 69.89 875 72.61
Hilton hotel 61 11.58 134 11.12
Total 527 100.00 1205 100.00
36
"E3
(3) (.3
(3_
25
20
15
10
I . . . . Computer Cab Survey
I I I I I I I l I I ' " ' ~ 1 - "t T 2 3 4 5 6 7 8 9 10 11 12 13 14
Radio jobs per day
Fig.B1 Da i ly radio use by survey and C o m p u t e r Cab drivers
40.00
5+
LL
30.00
20.00
10.00
0.00
_ - - . . . . Min boundary ........... Max boundary Meter reading Ii ( " /
/ j -
/
" ' - . / / . , . . \ . _ / . f
.. ~ . , . . . . . . . " ' ' ' , i . f ' - ' ' ~ .......... - ~ . o ...... . . - .... . ~, .. ...... • / i . . ~ f - - " " - . " ,. - . ~ " _ . ~ . " ' ~ - - _ I . . , . . _ " : . 1 " , . . . , . ' . ' . . . . . ' , i,, "
5.00 7.50 10.00 40.00
Trips in rising fare order (£s)
Fig.B2 Compar ison of fare boundar ies w i th C o m p u t e r Cab m e t e r readings
readings. Apart from one observation 22 all actual fares fall above the estimated minimum boundary. The presence of fare values above the maximum boundary does not suggest incorrect estimation: drivers are al lowed to turn the meter on before they arrive at the pick-up point. This extra cost is not accounted for when estimating the maximum boundary (see below). Correlation analysis established the maximum fare boundary as the best predictor of actual fares: the means for maximum fare estimates and meter readings being £10.96 and £11.96
respectively. Student's t-test for two sample means indicates that there is no signif icant dif ference between these values.
These f indings suggest that overall, the true fare lies close to the estimated max imum boundary for radio jobs. As ment ioned above drivers accept ing a radio job are al lowed to turn the meter on at the point of job accept- ance, thus there will often be some fare showing on the meter before their arrival at the pick-up location ~3. It is not
22 Examination of the raw Computer Cab data reveals the actual meter reading to be lower than would possibly be expected assuming the driver included all possible surcharges - it is possible he did not.
23 This is allowed under current legislation, but radio companies usually place a maximum on the excess fare that will be charged in this way.
37
possible to estimate how much this increases fares for radio trips since it is subject to driver behaviour as well as circumstance. Actual fares for non-radio trips will there- fore not lie as close to the maximum estimate.
HEATHROW AIRPORT FEEDER PARK COUNTS
Heathrow Airport Ltd kindly supplied counts of taxis called from the feeder park to the terminals for the entire survey period. This information was used as an inde- pendent measure of Heathrow based taxi operation to assess use of Heathrow by the volunteer drivers.
Volunteers made, on average, 0.81 trips each per week from Heathrow, whilst drivers overall were estimated to be using Heathrow 0.99 times each per week on aver-
age. A comparison ofrates (assuming a Poisson proc- ess) indicates that this difference is significant (p=0.007).
This difference would arise if Heathrow specialists (called 'faces' in the trade) were under represented in the volunteer sample. Calculations reveal that absence of only one such 'face' in the sample of drivers would be sufficient to cause such a discrepancy in rate of use.
Sampling error alone would account for this: although estimation may lead us to expectfive or six 'faces' in a truly representative sample of 220 green badge drivers24; the laws of probability dictate that we may only be 95 percent confident of obtaining between two and eleven 'faces'. A sample with one less than the expected number of 'faces' is therefore highly likely and no cause for concern. It does mean however, that Heathrow statistics have to be scaled up for fair comparison.
24 The number of 'faces' cannot be determined exactly: around 500 are assumed to operate on a reasonably regular basis from Heathrow (about 2.5% of total).
APPENDIX C
Figures C1 to C3
/ ~ I Weekdays . . . . Weekends 1
" ' / i ss S ~ i~ . . / i / "~ ~ ",~'s" X
. ~ S ~ % , , . , ~ , . . . m m s / ~ .
f I I I I I I I 3 6 9 12 15 18 21 24
Hour ending
Fig.C1 Mean trip length by time of day
38
25
E E
20
15
10
I W e e k d a y s . . . . Weekends
s ~
\ ; m
I I I I I ! I
3 6 9 12 15 18 21
Hour ending
24
Fig.C2 Mean trip duration by time of day
A
E
20
I Weekdays . . . . Weekends
I . . . . . , / k
I / , " \ \~
v ~" --... .___. ! j " - . . . - " \
15
10
I I I I t 1 I
3 6 9 12 15 18 21 24
Hour ending
Fig.C3 Mean trip speed by time of day
Printed in the United Kingdom for HMSO DdK50120 4/92 C4 G2516 10170
39
M O R E IN]FORMATION ]FROM TRRL
T R R L has
1. R R 2 4 0
2. R R 1 4 8
3. R R 2 0 4
4. R R 2 9 2
publ i shed the fo l lowing other reports on this area of research:
Taxi l icensing and the size o f the industry in 1989, R D Fairhead, Code B
The impact o f the 1985 Transpor t Act on the taxi industry, D J Finch, Code A
Taxi and pr ivate hire car operat ion at Ipswich Rail Station, D J Finch, Code B
Shared taxi schemes in Britain: Lessons learned in Ipswich, R J Balcombe, D J Finch, D Holl ings and H Inwood , Code B
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