An Overview of Real-Time

Information Technology in

Public Transportation

PLAN 548C: Urban Mass Transit Planning

& Technologies

A Paper by:

Tim Shah

June 7th, 2011

Introduction

“People don’t mind waiting for a bus if they know how long it’s going to be. Even if they have to

waste the time, at least they know it’s going to be 15 minutes. Otherwise they’re sitting there

thinking the bus will be along in about two minutes, and when it doesn’t show, then they start

getting frustrated ” (Mishalani & Wirtz, 2006, p. 90).

In public transportation, travellers are sensitive to a number of conditions. Such conditions may

include a sense of security, comfort, certainty on when a transit mode will be arriving,

affordability/cost and time savings. These are just a few selected factors that may enter the

decision-making process around taking public transportation over a private vehicle; there are a

number of others that are critical in our discussion about how to improve transit service and

quality. In more recent times, the area of public transportation has made immense strides in

utilizing technology and intelligent transportation systems (ITS) to ameliorate overall

performance (Hickman & Wilson, 1995). Among an exhaustive and innovative list of

technologies, real-time information systems have been particularly popular among travellers;

reasons for this are extensive but principally revolve around the real-time information alleviating

stress, anxiety and uncertainty when riding public transit (Dziekan & Kottenhoff, 2006).

This paper draws on the subject of real-time information in public transportation. This emerging

technology is becoming more popular and widespread around the world being adopted by a

number of transit agencies (Dziekan & Kottenhoff, 2006). Hickman & Wilson (1995) define real

time passenger information as a system in which the passenger receives up-to-the-minute

information about existing or expected travel times for the trip. The rationale for this technology

is two-fold; one, the real-time information may help to market transit to those who normally

travel by other modes; two, for existing transit passengers, real-time information can reduce

uncertainty about when the next transit service is provided and improve the passengers’

decision-making ability (Hickman & Wilson, 1995).

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With this in mind, this paper will provide a thorough overview of this emerging technology and

discuss its impact in improving transit service and quality. A major part of this analytical

discussion is centred on both the technological significance of real-time information along with

the human/psychological factors that make the technology function so well. The first section will

delve into the existing state of knowledge surrounding real-time information in public

transportation. Examples will be drawn from the literature to illustrate how the technology has

made transit more appealing and the reasoning for this. Thereafter, I provide a concrete –albeit

brief -- example of a city that has been utilizing this technology effectively, that is, the City of

Chicago with its Bus Tracker System and lessons learned. There are a few terminological

differences in defining this technology but for the purposes of this paper, it is called real-time

public transit information, known henceforth as RTPTI.

The Application of Real-Time Information Technology in Public Transportation

Caulfield and O’Mahony (2009) state “real-time public transit information is an individual-

specific travel demand management tool that is used to facilitate individuals while planning their

public transit trips; the provision of such information has been shown to encourage individuals to

examine their public transit options and choose the service that meets their requirements” (p. 2).

From a strict technological perspective, the Transit Capacity and Quality of Service Manual

(TCRP Report 100) reported that:

“In recent years, new electronic technology has been developed to provide improved traveler

information systems. For transit stations, “real-time” passenger communications can assist in

managing passenger flows and queues. This can include providing information on bus and train

departure times, bus and train berth locations, and out-of-service elevators and other facilities”

(Transit Capacity and Quality of Service Manual—2nd Edition, 2003, p.45)

Sadly, this is the only information in the manual about real-time information, but it does

demonstrate an increasing interest in this public transit technology.

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Figure 1. Next Bus technology in action (http://news.nextbus.com/how-nextbus-works-2/)

Figure 1 displays the technological process of a Next Bus system in the United States. RTPTI

systems use satellite technology and advanced computer modeling to track vehicles on their

routes. Each vehicle is fitted with a satellite tracking system. Taking into account the actual

position of the buses, their intended stops, and the typical traffic patterns, RTPTI can estimate

vehicle arrivals with a high degree of accuracy; the estimate is updated constantly. The

predictions are then made available on the World Wide Web and to wireless devices including

signs at bus stops and business, internet capable cell phones, Palm Pilots, and other Personal

Digital Assistants (PDAs).

According to Caulfield and O’Mahony (2009), RTPTI can be used and accessed through three

main networks; these include SMS (short message service) messaging, passenger information

displays (PDI) at transit stops and call centres. All three methods are diverse and are used

differently depending on the transit service, transit agency and location. However, in Caulfield &

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O’Mahony’s study, which featured Dublin as the study location, it was found that passenger

information displays yielded the greatest utility among the sample group. SMS messaging was

also popular just behind PIDs, whereas call centres were the least popular yielding the lowest

utility. The determination of utility is based on three variables; wait time saved, cost and

information. Figure 2 below displays the details of the variables used in their study along with

the different RTPIT methods.

Figure 2. Model Results of RTPTI in Dublin, Ireland (Caulfield & O’Mahony, 2009)

The key message from the table above is to illustrate how the wait time saved; cost and

information coefficients were estimated to be negative and significant at the 95% and 99%

confidence level for bus users for all three RTPTI methods. Indeed, bus users were shown to

have the lower cost disutility (-0.042) compared to rail users (-0.073) for SMS. Further, bus users

derive the highest benefit from real-time information provided via SMS and passengers

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information displays (Caulfield & O’Mahony, 2009). One reason why bus users might have the

highest utility for RTPTI is explained by Dziekan & Vermeulen (2006): “buses tend to have poor

schedule adherence, and thus the importance of such displays, by reducing uncertainty, may be

even higher. The same might be true for lower frequency tram or bus lines; here, the information

about the next departure is even more important than for lines with short headways” (Dziekan &

Vermeulen, 2006, p. 86).

Another significant finding from this table relevant to this paper is the wait time saved

coefficient. The wait time saved coefficients for passenger information display is the most

significant among the three methods. The bus user model produced the highest negative

coefficient (-0.088), followed by rail users (-0.042). This finding portends that bus users derive

the highest utility from the provision of information via a passenger information display (PID)

while at a stop/station. These findings show that time saving is more important to bus users

compared to rail users (Caulfield & O’Mahony, 2009). Last, public transit users (both bus and

rail), are more open to paying (willingness to pay) for the provision of transit stop/station

information provided via a passenger information display, compared to the other user groups.

Willingness to pay will be further explored in latter sections of the paper.

The findings from the Caulfield & O’Mahony study are significant because they demonstrate

how three variables (wait time saved, cost and information) impact transit users and how the

preferences for RTPTI technology differ (i.e. SMS, passenger information display, call centres).

All three methods can provide real-time information yet call centres were the least desirable in

this study. The high utility and popularity of passenger information displays are indeed critical as

many places such as Chicago (the selected case study in this project) have utilize PIDs in cafes,

liquor stores and other spots as travellers have been generally impressed with it.

Dublin is not the only city that has adopted this technology for its transit system; there are a

number of places in Europe that have experimented with it. In London, the provision of real-

time information at stops was found to reduce perceived wait time by 26 percent (Schweiger

2003). A 2007 study conducted in the Netherlands examined the introduction of passenger

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information display (PID) on a tram line in The Hague and found that the introduction of this

service reduced perceived wait time by 20 percent (Dziekan and Kottenhoff, 2007).

The study on The Hague tram line used a before and after evaluation study containing

questionnaires given to travellers. “One month before, three months after, and sixteen months

after implementation, the same sample of travelers filled out a questionnaire; the main result was

that the perceived wait time decreased significantly by 20 percent after the installation of the

displays” (Dziekan and Kottenhoff, 2007, p. 495). What’s more, the only addition to the tram

line was the RTPTI system; no changes in the frequency of the service were made. To make the

research more valid and rigorous, the authors found that after 1 year of implementation of the

RTPTI, the passengers still stated a reduction in perceived wait time. This idea of perceived

versus actual wait time will be illustrated in the next paragraph drawing on Dziekan &

Kottenhoff’s study.

Figure 3. Average perceived wait time of travellers on line 15 in The Hague (Dziekan and

Kottenhoff, 2007).

There is a whole psychology around actual and perceived wait times when it comes to public

transportation. According to Dziekan & Vermeulen (2006), wait time for public transport is

considered negative and wait time is perceived as longer than any other part of journey (Li

2003). “It is, therefore, considered unused or wasted time. Further, the traveler is exposed to an

unfulfilled goal; he or she has not arrived at the final destination. Finally, an unpredictable

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setting is expected to result in a longer perceived journey time. Li (2003) called this aspect

expectancy. These effects in combination cause discomfort and dissatisfaction that lead to the

overestimation of the traveler’s temporal judgment” (Dziekan & Vermeulen, 2006), p 83).

Reducing perceived wait time is critical for transit agencies because if done well and using the

appropriate technology, a lot of capital can be saved on operating costs. Consider Figure 3 on

page 6, before RTPTI was installed on the tram line, perceived wait time, that is, how long

people think they have been waiting for a transit service, was 6.2 minutes on average. When

considering the implementation of RTPTI at eight tram stops along one tramline, the cost was

reported to be €200,000 ($274,000 CAN) (Dziekan and Kottenhoff, 2007).

As illustrated in the graph, once RTPTI was installed, perceived wait times decreased to 5.0

minutes on average after 4 months, and then to 4.8 minutes on average after 16 months. The

main message here is that the transit operator in The Hague could have also reduced perceived

wait times through increasing the frequency of the trams – at the cost of more dollars spent -- as

opposed to using RTPTI. Passengers tend to overestimate their waiting times and based on what

the authors found, the real average wait time should have been 4.0 minutes, as opposed to the

original perceived wait time of 6.2 minutes.

Had RTPTI not been used, the transit operator would have had to provide trams in greater

frequency, an average interval between two trams of 8.0 min instead of the current 10 minutes.

This would have amounted to a total of €1.1 million as opposed to the RTPTI cost of €200,000

(Dziekan and Kottenhoff, 2007). The cost savings associated with using RTPTI in The Hague are

valuable considering that transit agencies function under tight budgetary constraints with very

little financial capacity to increase the frequency of transit services, for example. When RTPTI

can help a transit agency save on capital costs, more money frees up which can be utilized in a

number of different ways including discounted transit fares or improvements and upgrades to

current transit services. The story and overall evidence from The Hague should be reviewed by

large scale transit operators around the world as the potential savings associated with RTPTI

make it worthwhile to pursue.

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Factors surrounding real-time information

Dziekan & Kottenhoff (2006) provide a comprehensive mind map model (see Figure 4) that

captures the various human/psychological factors embedded within RTPTI. For the purposes of

this paper, I will only discuss two aspects of the mind map: increased willingness to pay and

adjusted travel behaviour. Adjusted travel behaviour is particularly relevant and will transition

nicely with the case study on Chicago’s bus tracker system.

Figure 4. Mind map on possible effects of at-stop real-time information displays (Dziekan &

Kottenhoff, 2007)

Increased willingness to pay (WTP)

WTP is a common measurement used in economics and has been particularly popular in

environmental and transportation economics (e.g., see McDonald & McMillen, 2007). In

transportation, there has been interest in understanding the WTP for RTPTI. For instance, in

1989, an extensive stated preference study on Stockholm citizens’ willingness-to-pay for public

transport was done (Widlert et al., 1989). The results indicated a significant willingness-to-pay

for real-time information at bus and metro stops (Dziekan & Kottenhoff, 2007). In the Widlert et

al study, passengers were presented with different options such as shorter travel time, reduced

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ticket prices and real-time information. It was found that RTPTI was traded off as equal to about

12–16% lower fares or 6–8% shorter travel times. The systems were given a slightly higher value

for Metro (upper end of the interval) stations than for bus stops (lower end of the interval). In

sum, research has found that the value of real-time information systems at stops and stations

seems to lie in an interval between 5-20 percent of the ticket price for the trip (Dziekan &

Kottenhoff, 2007).

WTP is important in understanding RTPTI because it relates to a number of factors including

positive psychological effects, reduced perceived wait time, mode choice and adjusted travel

behaviour. While it can argued that any one of the factors in the mind map is correlated with

each other, WTP is particularly significant to this discussion because it relates to “time” and

“cost”, the two central factors in travel behaviour and personal transportation decisions

McDonald & McMillen, 2007. As the evidence suggests, WTP for RTPTI is high given the

return on utility. To demonstrate how WTP plays out, consider adjusted travel behaviour for

travelers.

Adjusted travel behaviour

As shown in Figure 4, adjusted travel behaviour is linked with increased WTP. Adjusted travel

behaviour means that people may make changes or slightly adapt their travelling decisions and

time based on new information provided. The three elements embedded within adjusted travel

behaviour are a) Utilization of wait time b) More efficient traveling and c) Other adjusting

strategies.

Utilization of wait time

According to Dziekan & Kottenhoff (2007), utilization of wait time is when the traveller knows

how much time they have (because of RTPTI), and will use this wait time to do things like last

minute shopping or carrying out other business. In a study by Nijkamp et al (1996), 20 percent

of people who left the stop after checking the passenger information displays stated that they

used the time for shopping or going to the bank (Dziekan & Kottenhoff, 2007). As the Chicago

case study will point out, with RTPTI, travellers can use their wait time to buy a coffee, lunch or

a product thereby benefiting commerce in addition to public transit.

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More efficient travelling

Dziekan & Kottenhoff (2007) found that:

“The information provided can be used by travellers to make travel decisions that lead to shorter

travel times and more efficient travelling. For instance, one researcher describes the hyperpath as

one possible effect: if a passenger is waiting for a bus, and then finds a bus on another line that

could take the passenger close to the desired destination, the passenger would probably take that

bus. But if the information system informs the passenger that the bus on the original line was

expected to arrive 1 min after the alternate bus, the passenger may decide not to board the bus

arriving soonest on the original line, therefore leading to a change in travel path” (Dziekan &

Kottenhoff, 2007, p. 493).

Returning to the mind map (Figure 4), you can see how more efficient travelling is related to

mode choice as real-time information can help a traveller plan a trip and effectively decide on a

transit mode that will take them to their destination in the fastest way possible. This also relates

to “reduced uncertainty” which was mentioned earlier in this paper. RTPTI provides information

that improves the decision-making and trip planning ability of a traveller; this reduces

uncertainty that may otherwise have been common when trying to work with unreliable and

inaccurate public transit schedules and trip times.

Other adjusting strategies

For Vancouverites, a good way to think of adjusting strategies is the 99 B-line. While the 99 B-

line is frequent in service, it would benefit enormously from RTPTI, especially on weekends or

during off-peak hours. There are many instances when a 99 bus is crowded as therefore has to

pass by passengers at a given stop. However, if there was RTPTI, the display could show that

another bus would be arriving shortly which could, for instance, enhance the comfort of a

journey. As there are a variety of shops and stores along with Broadway Corridor, travellers can

adjust and make use of their time efficiently while waiting for the bus. This is mostly theoretical

but demonstrates how information can lead to improved service overall.

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Case study: Chicago Bus Tracker System

To conclude this paper on RTPTI, it would be useful to provide a concrete example of a city that

has been utilizing this technology. Due to the limited information available on the Chicago

Transportation Authority’s Bus Tracker System, a majority of the information in this section has

been derived from online sources such as blogs and other social media sources. The bus tracker

program is a RTPTI system that performs many of the functions outlined in this paper and

recently won a Chicago Innovation Award because of its success and widespread popularity.

Figures 5 and 6 illustrate the bus tracker information display boards which can be found in

several locations across the city including cafes, liquor stores, restaurants etc.

Figure 5. Bus Tracker Information Display (http://blogs.skokielibrary.info/radar/files/2009/03/97_bus_status_cropped.jpg)

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Figure 6. Bus Tracker Information Display ( http://www.carlessinchicago.com/wp-content/uploads/2009/06/cta_interface.jpg)

Earlier in the paper, it was mentioned that there are typically three methods to receive real-time

information in public transit; SMS messaging from smart phones, IPhones and other cellular

devices; call centres which provide the caller with information about the next bus or train and

passenger information displays such as the ones shown in Figures 5 and 6. One of the

motivations for the Bus Tracker system was to devise a technology that could be visible in the

community so that people could make use of the real-time public transit data that did not have

smart phones or SMS applications (Press, 2011). As the next paragraph discusses, having these

large display boards is not only accessible to all people (young and old, poor and wealthy alike)

but also helps local businesses.

The Unique Commerce Connection

The Wicker Park Buckertown Chamber of Commerce in Chicago approached the CTA in 2009

with an interest in utilizing passenger information displays in various parts of the community,

particular shops, restaurants, bakeries, cafes and other stores (Press, 2011). This collaboration

was a direct benefit for the chamber in encouraging residents to use public transit and providing

RTPTI displays in the various commerce locations in the district (Press, 2011). A CTA employee

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named Joe Iacobucci, writes “Bus Tracker has been a benefit for the Chamber of Commerce

because they were able to reduce congestion while displaying community events and the things

that help the district out.  For the business it gives a more of a connection with their customers

who are stopping in for a cup of coffee or bagel on their way to work, and arming them with the

information for Bus Tracker” (Press, 2011).

This has made a stronger connection between the customers and businesses as people can access

information about the next bus and buy a coffee while waiting, for example. This goes back to

earlier discussion in this paper when I showed Dziekan & Kottenhoff’s mind map model (Figure

4) and how the utilization of wait time can result in people connecting with shops and

businesses.

According to the Chamber of Commerce, the idea of bringing PIDs to its commerce outlets was

that if residents are passing by a cafe waiting for the next bus, they could check out the real-time

information display and know they have 5 minutes to buy a coffee, or 15 minutes to read a

magazine or book (Press, 2011). Evidently, the use of RTPTI displays in shops and cafes has

helped take the mystery and stigma of riding the bus. Another CTA employee, Jamie Simon

explains:

“ The idea is that if you’re passing by a café and you know they have the sign, you might go in

and look and see you have five or ten minutes to wait and maybe you would make a purchase or,

you know, if you have fifteen minutes, maybe you would browse at some books, make it a more

seamless experience, and also it encourage people to take transit.  There is high transit ridership

in the neighbourhood, but I think anything you can do to facilitate that experience and take the

mystery out of riding the bus is really helpful for people.” (Press, 2011).

Overall, Bus Tracker has been successful in Chicago as evidenced by the feedback and the

Innovation award. Time will tell if other cities study the CTA’s Bus Tracker System and whether

they adopt or bring about similar technologies.

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Conclusion and Lessons Learned

Bringing the focus of this paper to the Chicago case study helps shed light on a success story.

The Bus Tracker system has demonstrated how human beings can respond well to real-time

information. When travelling, there are a number of psychological factors at play. Among them,

safety, security, waiting time and cost can affect the way we feel while travelling and make the

journey either comfortable and uneventful or anxious and full of trepidation. RTPTI has proven

to alleviate some of the psychological factors that have been presented in this paper as

demonstrated by its application in London, The Hague, Chicago and Dublin to name a few cities.

Indeed, in cities that have utilized RTPTI, passenger uncertainty of the next bus has been greatly

alleviated. This alleviation, among other impressive technological achievements, has helped

improve the image of the various transit agencies, has led to higher customer satisfaction and an

overall improvement in level of service for transit operations.

I also discussed the economics and cost savings associated with RTPTI. As shown in the study

on The Hague tram line, the transit agency was able to save money through the provision of

RTPTI instead of taking a more conventional and costly approach in increasing the frequency of

transit. This lesson, among others, is particularly valuable for TransLink in Metro Vancouver.

With tight budgetary constraints and a new focus on bus service optimization, RTPTI can be a

valuable addition. Indeed, bus routes that play an important role in moving a diverse group of

people should be treated as experiments with RTPTI to test customer reactions and the

effectiveness of this technology. In a time when TransLink and other transit organizations are

attempting to reduce GHGs and encourage high transit usage, many tools and strategies will have

to be employed. RTPTI is perhaps one of the most promising technologies that transit agencies

can experiment with as the benefits up until now and across international cities have been

overwhelmingly positive.

References

Caufield, B, O’Mahony M. (2009). A Stated Preference Analysis of Real-Time Public Transit

Stop Information. Journal of Public Transportation, 12(3), 1-20.

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Dziekan, K., Kottenhoff, K. (2007). Dynamics at-stop real-time information displays for public

transport: effects on customers. Transportation Research Part A, (41), 489-501.

Dziekan, K, Vermeulen, A. (2006). Psychological Effects of and Design Preferences for

Real-Time Information Displays. Journal of Public Transportation, 9(1), 71-89.

Hickman, M.D, Wilson, N.H.M. (1995). Passenger Travel Time and Path Choice Implications of

Real-Time Transit Information. Transportation Research Part C, 3(4), 211-226.

Li, Yuen-Wah. (2003). Evaluating the urban commute experience: A time perception approach. Journal of Public Transportation, 6(4), 41–67.

Mishalani, R.G., Wirtz, J. (2006). Passenger Wait Time Perceptions at Bus Stops: Empirical

Results and Impact on Evaluating Real- Time Bus Arrival Information. Journal of

Public Transportation, 9(2), 89-106.

McDonald, J.F., McMillen, D.P. Urban Economics and Real Estate: Theory and Policy 2nd Edition. Hoboken: Wiley & Sons Inc.

Nijkamp, P., Pepping, G., Banister, D. (1996). Telematics and Transport Behaviour. Chapter 7: Public Transport Information Systems: An English Case Study. Springer, Heidelberg.

Press, E. (2011). Chicago’s Bus Tracker: Taking the Guesswork Out of Waiting for the Bus. Accessed online:http://www.streetfilms.org/chicagos-bus-tracker-taking-the-guesswork-out-of-waiting-for-the-bus/#more-48974

Schweiger, C.L. (2003). Customer and media reactions to real-time bus arrival information

systems (No. report 48): Transportation Research Board.

Transit Cooperative Research Program. (2003) Transit Capacity and Quality of Service Manual

(TCRP Report 100). Washington, DC: Transportation Research Board. Accessed online:

http://www.trb.org/Main/Public/Blurbs/153590.aspx

Widlert, S., Ga¨rling, T., Uhlin, S. (1989). Va¨rdering av kollektivtrafikens standard (No. 1989:2). TFB (Transportforskningsberedning), Stockholm.

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Websites:

Chicago Bus Tracker: http://www.ctabustracker.com/bustime/home.jsp

http://www.transitchicago.com/assets/1/developer_center/BusTime_Developer_API_Guide.pdf

Next Bus: http://news.nextbus.com/how-nextbus-works-2/

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