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
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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
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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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