Real Time Passenger Information

This measure was fully updated by INSTITUTE FOR TRANSPORT STUDIES (ITS) in 2014 under the CH4LLENGE project, financed by the European Commission.


The purpose of real time passenger information (RTPI) can be understood by considering the range of ways in which journeys are capable of varying from what is timetabled or pre-planned.  Real time passenger information systems allow passengers to access real i.e. live departure information for public transport services via a variety of different sources. Such systems have been shown to be of value to public transport passengers, to operators and to public transport regulating agencies. The primary benefit to passengers is that they reduce the psychological anxiety associated with waiting for public transport as well as uncertainty and frustration. For the operators, RTPI technology has helped in the fleet management and improvement of bus performance and schedule adherence and hence contributes to improving the image of public transport. Whether RTPI alone can increase patronage of public transport is open to debate; while some evidence suggests it can, on balance experience suggests that any ridership increase is usually achieved by a combination of measures to promote public transport services. Hence RTPI is implemented as part of a package improving the quality of public transport. Implementation costs may be high due to the associated computer technology, and strong project management will be required. Nevertheless with advances in technology, such costs may fall significantly.

Terminology

Real Time Passenger Information (RTPI) is a means of marketing public transport and providing electronic travel information to the users of public transport in “real time” via a range of sources, such as bus stops, stations, on vehicles and via the telephone or internet (Holdsworth et al, 2007). Lyons sets out three types of real time information:

“– planned deviations from schedule;
– historic information on actual journey conditions;
– observed journey conditions as they happen; and
– predicted conditions”
(2006, p.202)

An example of the RTPI for the “Countdown” system implemented in London is shown in Figure 1.

Many public transport agencies around the globe already provide real time information to the travelling public at large. Information provided via RTPI systems is usually concerned with the arrival and departure of public transport services, whether focusing on the next service at a given station or stop, or on information about service running and delays across a public transport network (see for instance, UK rail live departure boards). Further information, such as destinations, routes, fares and specific problems can be provided alongside this information.

Graphic 01
Figure 1: Example of Real Time Passenger Information System (“Countdown”) at bus stop in London, UK
Source: http://www.itsdocs.fhwa.dot.gov/JPODOCS/REPTS_TE/13845.html

Low-tech PIS
Low tech real time running information provision: Source Plural-zed

 

Technology

Information provided in real-time has to be reliable, otherwise it will hinder or confuse users rather than aid their decision making. Low-technology approaches such as Figure 2. are still used in some places and can avoid risks of glitches with information technology. However Technology has been developed over many years and can now be considered relatively stable.

For services with dedicated rights of way (e.g. metro services), the technology calculates the predicted arrival times for the next vehicles based on the location of the vehicles within a signal “block”, the speed of the vehicles and the distance to the next station. Web surveys of major metro operators of the COMET1 and NOVA2 consortia of operators suggest that RTPI is already provided at most metro stations/interchange points and at metro stops (at least for the operators within the consortia).

For road running public transport modes such as buses, a major difficulty is that they are constrained by other vehicles on the road. At the same time there have been advances in Automatic Vehicle Location (AVL) technology (Hickman, 1995) to enable tracking of bus locations (using sensors).

Early variants operated using beacon technology (Schweiger, 2003). An on-board unit receives signals from roadside beacons as the bus passes the beacon, and since each beacon has a unique identifier the location information is forwarded by radio link directly to a central system. The central system compares the scheduled arrival time with the current positioning and computes the “countdown” to arrival at the stop. This information is sent to the bus stop matrix displays (see Figure 1) which are equipped with a modem to receive the transmitted information.

However, this tag and radio technology has been improved by on board Global Positioning Systems (GPS) based on satellite technology. By calculating data based on GPS satellites, a vehicle’s location (longitude and latitude) can be calculated to within 3 to 6 metres (Sun et al 2007). This can then be similarly transmitted to the electronic matrix displays available at stops/interchange points.

Whatever the technology deployed, all the traveller sees is the information available on the electronic displays (as shown in Figure 1). In addition, real time data can be sent to mobile phones and personal digital assistants (when users utilise a short messaging service (SMS or “text message”) to request the information), as well as displayed in the vehicle or via the Internet - see Figure 3.

figure 2
Figure 3: Example of London Underground online live departure boards. 
Source: http://www.tfl.gov.uk/tfl/livetravelnews/departureboards/

 

1 COMET is the Community of Metros, a consortium dedicated to sharing best practice and a knowledge exchange cum benchmarking forum for the world’s largest metro operators. This group comprises metro operators as follows BVG (Berlin, Germany), LUL (London, UK), MOM (Moscow, Russia), MRTC (Hong Kong, China), MSP (Sao Paulo, Brazil) NYCT(New York, USA), RATP (Paris, France), STC (Mexico City, Mexico), TRTA (Tokyo, Japan).

2 NOVA is the sister organisation to COMET and serves a similar purpose of knowledge exchange, benchmarking and knowledge forum for metro operators that have a lower number of passengers per annum and comprises 15 members at time of writing (see http://www.nova-metros.org).

Why introduce real time passenger information?

The information requirements for public transport passengers can be grouped into three categories (Huber, 1996; Caulfield and O’Mahony, 2007):

  1. information for pre-trip travel planning i.e. gathering information before embarking on the journey [this can involve both information on timetables and real time information such as live departure boards, or media sources (see Lyons 2006)];
  2. information at stops or interchange points (wayside information, which can include information supplied to personal handheld devices such as mobile phones and personal digital assistants); and
  3. information whilst inside the vehicles.

Real time information contributes to all these elements of this process. In addition, real time information can be transmitted to trip planning systems hosted on websites to enable users to check the performance (including delays) of public transport services before embarking on their journeys.

Benefits to passengers

With regard to wayside information, research has shown that waiting for the bus and not knowing when it will arrive causes passengers to feel anxious and frustrated (Dziekan and Vermulen, 2006; Dziekan and Kottenhof, 2007). The provision of RTPI is therefore useful in reducing the perceived cost of waiting (Li, 2003; Litman 2008). This is primarily because waiting/interchange time is perceived by travellers as a strong deterrent to using public transport. It has therefore been argued (e.g. Schweiger, 2003) that customer service and “goodwill” as well as the visibility of public transport’s role in the community can be improved by introducing RTPI. Furthermore, Multisystems Inc’s (2003) analysis of survey findings following RTPI introduction in Seattle, USA suggests that provision of RTPI may help public transport retain the very customers who are most likely to leave such as marginal and occasional public transport users by improving the image of public transport to such users. There is further evidence that some forms of real time information are more effective than others in prompting people to change modes, or time of travel. A study by Wang et al. 2009, suggested that provision of information online was associated with greater change than provision through other media. Nevertheless other research suggests that having made a decision to use public transport, people value information, whereas the availability of information has only limited impact of people’s decision to use public transport (Farag and Lyons, 2010).

There is evidence that customers value information provision in general (Herrala,2007) and RTPI in particular. A survey of the literature reported in Balcombe et al (2004) suggested that the value of the RTPI system in London, UK (known as “Countdown” (see Figure 1)) was valued at 10 pence per trip in 1996 prices. This suggests that provision of accurate information is of value to public transport users. In addition, Balcombe et al (2004) also found that real time information was valued more highly than conventional published information (e.g. timetables) which some users may not consult (Vance and Balcombe, 1997). As with other information, accessibility and the ability to ‘read’ and make sense of the information provided can be an important aspect in mitigating social exclusion, especially for people with conditions such as dyslexia (see Lamont, Kenyon. and Lyons 2013).

Benefits to operators

Initially, many operators were somewhat hesitant regarding the introduction of RTPI (Centaur and Warman, 2004). This was due to the possible revenue loss from passengers taking an alternative service or mode (especially in markets where operations are deregulated) once they knew that their service would be delayed. However public transport operators have come to realise that the supporting technology behind RTPI can be used for improving fleet despatch and control operations, and hence the operators’ initial scepticism with RTPI has been reduced.

The supporting technology for RTPI is based on Automatic Vehicle Location (AVL). The AVL technology is of value to bus operators for several reasons (Gomez et al, 1998; BAH 2006). Firstly the main benefit of AVL is improvement of operational efficiency (Schweiger, 2003). Secondly, RTPI infrastructure allows immediate notification of delays encountered by vehicles on the network to be transmitted to users at stops and interchange points. Thirdly AVL will allow for real time frequency correction to reduce the potential of bunching (simultaneous arrival of buses at stops due to en-route delays) so that standby buses are dispatched to subsequent points to spread passenger loadings during the occurrence of incidents including breakdowns.Fourthly, incorporation of AVL technology allows for the integration of technologies for fare collection (e.g. smart card readers) in particular when the fare basis is distance or zone dependent. These applications are discussed further under bus fleet management systems.

Benefits to local authorities

Many local authorities around the world wish to improve their public transport services, increase ridership and where applicable reduce the subsidy levels for public transport funding. To enable public transport to compete more effectively with the car, the technology used to deliver RTPI and its backbone AVL infrastructure also allows for integration with traffic control systems to provide priority for late running buses (Hill et al 2001; Clarke et al, 2007).

Whatever the tangible benefits are, the following key points from Vance and Balcombe (1997) provide important considerations when delivering public transport information in general and RTPI in particular:

  1. Good passenger information is necessary as part of any strategy to stem or reverse decline in public transport use;
  2. Both regular and occasional passengers appear to have similar information needs;
  3. Expense of necessary vehicle location for RTPI may be less prohibitive if it is introduced as part of an integrated urban control system; and
  4. Investment in information systems is not a substitute for investment in other public transport improvements; good information will not sell bad services.

Demand impacts

The responses to RTPI will depend on the extent of information provided, and its perceived reliability.

Responses and situations
Response Reduction in road traffic Expected in situations
Internet information in particular may prompt people to change departure time either in response to details of delays, or due to increased reliability.
Travellers might change their route and consider taking alternative public transport routes in event of delays.
Unlikely to occur.
Unlikely to occur.
Travellers might consider taking alternative public transport routes in event of delays. Real time information might have a small impact on mode shift.
Little evidence.
Little evidence.
= Weakest possible response = Strongest possible positive response
= Weakest possible negative response = Strongest possible negative response
= No response

Short and long run demand responses

Demand responses
Response 1st year 2-4 years 5 years 10+ years
 
 
 
 
 
 
= Weakest possible response = Strongest possible positive response
= Weakest possible negative response = Strongest possible negative response
= No response

Supply impacts

Generally speaking, the supply impact is indirect and the AVL technology is intended to improve reliability of supply. The use of AVL enables operators to schedule their bus fleets more efficiently (Gomez et al 1998; BAH 2006) and also enables real time dispatching of supplementary vehicles where incidents or delays occur to maintain the scheduled service frequency and reduce “bunching”.

Financing requirements

Implementing RTPI can incur quite large sums of expenditure (A trial in the East Kent in the UK (Centaur and Warman 2004) reported capital expenditure in the region of £324,000 (2004 prices) with annual revenue expenditure per year of £100,000, this was for equipping 60 buses and providing 6 at stop displays; on the other hand London’s “Countdown” system for 6000 buses and 4000 signs cost up to US$70 m.) Therefore the cost of implementing RTPI can be substantial but generally speaking is declining as technology improves. In addition, RTPI is rarely implemented on its own but in combination with a package of measures to improve overall public transport services, which makes it difficult to attribute the cost of RTPI precisely.

Expected impact on key policy objectives

Contribution to objectives

Objective

Scale of contribution

Comment

  Public transport users are able to more efficiently utilise the public transport service resulting in a reduction in the perceived cost of waiting time as well as the perceived unreliability of services and therefore representing an efficiency improvement. There may also be a benefit from congestion reduction if car use is reduced.
  To the extent that private vehicle kilometres are reduced.
  To the extent that private vehicle kilometres are reduced.
  In theory (Holdsworth et al, 2007) it helps to balance the advantages and disadvantages of using public transport with those associated by private cars.
  To the extent that private vehicle journeys and/ or distances are reduced.
  It seems unlikely that better information will have a direct effect on the economy.
  While it may be costly to introduce on its own, its cost may be reduced through partnerships with operators, technology providers and governments. In addition, RTPI is seldom provided on its own but within an integrated public transport package of improvements.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Expected impact on problems

Contribution to alleviation of key problems

Problem

Scale of contribution

Comment

Congestion

If private vehicle use is reduced. Reduced congestion of public transport may also occur if people can respond to information on disruption.
Community impacts / Display ‘boards’ could add to visual intrusion. May have small contribution to accessibility.
Environmental damage To the extent that private vehicle journeys and/ or distances are reduced.
Poor accessibility / Some benefits of information but dependent on availability of services.
Social and geographical disadvantage / Some benefits of information but dependent on availability of services.
Number, severity and risk of accidents To the extent that private vehicle journeys and/ or distances are reduced.
Economic growth It seems unlikely that better information will have a direct effect on the economy.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Expected winners and losers

Winners and losers

Group

Winners/Losers

Comment

Large scale freight and commercial traffic

If information prompts mode shift congestion might be reduced.

Small businesses

If information prompts mode shift congestion might be reduced. If travellers know how long they have to wait for the next bus, they may be able to spend their interchange/wait times browsing in shops.

High income car-users

Small benefit if increased patronage results in less congestion.

Low income car-users with poor access to public transport

Small benefit if increased patronage results in less congestion.
All existing public transport users They will have a better perception of their wait times and the service levels of public transport. They may also find alternative diversions during their wait time that better serves their purposes and not worry about missing the bus.

People living adjacent to the area targeted

No impact likely.

Cyclists including children

To the extent that private vehicle journeys and/ or distances are reduced.

People at higher risk of health problems exacerbated by poor air quality

To the extent that private vehicle journeys and/ or distances are reduced.
People making high value, important journeys May benefit from a ‘better’ service on their door step.
The average car user May find PT more attractive and hence gain some small benefit.
= Weakest possible benefit = Strongest possible positive benefit
= Weakest possible negative benefit = Strongest possible negative benefit
= Neither wins nor loses

Barriers to implementation

Scale of barriers
Barrier Scale Comment
Legal There are no obvious legal barriers to the implementation of RTPI.
Finance The cost of implementing it on its own could be expensive. However it is seldom implemented on its own but within a comprehensive package for improving public transport usage. Strong project management is critical for the successful deployment of a real-time information system.
Governance There may be issues of data ownership that need to be considered.
Political acceptability There are no obvious political barriers to the implementation of RTPI.
Public and stakeholder acceptability No major barriers unless some people consider information boards to be visually intrusive.
Technical feasibility The technology is already available and hence this would be a minimal barrier. There may be some security concerns with regard to the vulnerability of attacks knowing information about where the bus is and when it is arriving (BAH,2006) although this should be minimal. Strong project management is critical for the successful deployment of a real-time information system.
= Minimal barrier = Most significant barrier

Case study 1: Star Trak (Leicester, UK)
Case study 2: Countdown (London, UK)
Case study 3: TriMet TransitTracker  (Portland, Oregon USA)

 

RTPI, often introduced as part of modernisation packages for public transport has been shown to improve perceptions and increase usage of services (Litman, 2008). Hence it is difficult to attribute the sole effect of implementation of RTPI. Evidence on whether RTPI alone can increase patronage is inconclusive and conflicting; whilst Forsyth and Silcock (1985) suggested that patronage could be increased by 10% (London underground) and Suen and Geehan (1986) reporting on Ottawa, Canada found patronage change ranging from 2.8% in the peak to 8.2% in the off-peak, Wardman and Sheldon (1985; for London Buses) and James (1985; for Tyne and Wear Metro in Newcastle, UK) found the results to be less positive. Evidence from Brussels, Belgium (Multisystems Inc, 2003) suggested that with the introduction of RTPI known as Phoebus, ridership rose by 6%, and the system operating across San Francisco, California (USA) reported a 5% increase in patronage of rail services since the system was deployed (San Francisco Municipal Railway, 2001), yet evidence from simulation models (e.g. Hickman and Wilson, 1995) found that quantitative benefits were questionable.

Case study 1: Star Trak (Leicester, UK)

image 03
Figure 3: StarTrak Real Time Passenger Information at Bus Stop
Source: Leicester City Council

The information reported here is obtained from the following sources: 
DfT (2003b) as well as Gillam and Wright (2000)

Context

The policy of Leicester City Council and Leicestershire County Council (the local authorities of Leicester in UK) is to encourage the use of sustainable means of transport. This policy is implemented partly through a strategy of improving bus services. In doing so, they formed a quality bus partnership with the bus operators and established the Star Trak system for Leicestershire. The system was launched in November 2000 and covered 22 routes with around 250 buses though new services are continuously added to the list. In addition, a check on the website has revealed that other neighbouring authorities within the region (Derby City Council and Nottingham City Council) are also participating in this scheme.

It must be borne in mind that the system is one of a package of measures, listed below, to provide quality bus services and is designed to encourage commuters to use the bus as an alternative to driving.
In summary the system comprises the following components:

  • Bus location – using GPS technology to locate the bus at all times along its route
  • Intelligent traffic signal priority – to enable a late running bus to have priority through traffic signals
  • Passenger information – bus stop signs (see Figure 3), short messaging service (sms) and website
  • Bus fleet management – for the bus companies to keep track of their buses
  • Electronic timetable database – the main part of the system, which measures schedule adherence

Star Trak tracks the position of buses using GPS systems; this information is used to predict their time of departure at their respective bus stops and is displayed at selected stops on LED signs. On board the buses, the name of the next stop is displayed on a text screen. In addition, if a bus is running behind schedule, a traffic signal priority system is activated in favour of the bus. The various interlinked components of this system are shown in Figure 4.

image 04
Figure 4: Schematic of Star Trak System   
Source: DfT (2003b)

Impacts on demand

With the caveat that RTPI was not the only measure implemented (since new vehicles and infrastructure were acquired when Star Trak was launched), DfT (2003) reported that improved routes have seen an average 28% increase in passengers. No information is available on the previous modes used by these commuters though and hence it is unclear whether these 28% came from car users or existing public transport users or were newly generated trips. In addition, passenger attitude surveys have shown that 90% of users consider the electronic displays either useful or very useful.

Impacts on supply

All the routes that have been improved with measures including Star Trak have seen a significant increase in patronage. It was reported (DfT,2003) that as a result of the package of measures which included RTPI, an increase in ridership levels have led to the bus operator increasing the frequency of the service from every 20 minutes to every 10 minutes.

Contribution to objectives

Contribution to objectives
Objective Scale of contribution Comments
 

The main contribution through efficiency improvement is via the reduction in perceived waiting times for buses. A survey found that 68% of users felt their wait for the buses was now “more acceptable”

In addition the reductions in car use (assuming those new passengers on the bus would have made the journey by car) will have contributed to a further efficiency improvement.
  The reductions in car use (assuming those new passengers on the bus would have made the journey by car) will have contributed to a liveability improvement.
  The reductions in car use (assuming those new passengers on the bus would have made the journey by car) will have contributed to the protection of the environment.
  There was no reported impact on equity and social inclusion.
  There was no reported impact on safety.
  There was no discernable impact on economic growth.
  Capital costs for the entire package of measures cost   approximately £3,397,000 over 4 years, Recurrent expenditures are approximately £90,000 per year. However the cost of the RTPI component of star-trak itself was not separately listed.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Case study 2: Countdown (London, UK)

The information reported here is obtained from Linton (1997), Johnson (1999) and Schweiger (2003) as well as the homepage for Transport for London (http://www.tfl.gov.uk/corporate/projectsandschemes/technologyandequipment/2369.aspx)

Context

London Buses, part of Transport for London, is responsible for London’s network of over 600 routes (one of the largest urban networks in the world). Unlike other parts of the UK, services in London are planned by London Buses and then operated (via a tendering process) by bidding operators. The RTPI information implemented by London Buses is known as Countdown.

Countdown features real-time information for all routes serving a particular bus stop. In addition to showing the order in which buses will reach a stop, it shows their destinations and the number of minutes until their expected arrival. The signs also display special messages about traffic delays or planned road works.

The initial system used tag and radio technology where sensors fitted on buses allow a central system to receive regular updates from each bus about its current location. Bus operators can then monitor exactly where a bus is and use the information to control services more effectively. This has been in development since trials began in 1992 (they were completed in 1996). The system is being continuously deployed and modified as RTPI displays are introduced at more and more bus stops across the capital.

In 2009 the system that supports Countdown (tag and radio technology) was replaced with a new system based on Global Positioning Systems employing satellite technology.

Impacts on demand

With regards to usage, about 70% of passengers referred to the display when they arrived at the stop, and about 90% looked at the sign while they waited (DfT, nd). Countdown was found to generate 1.5% new revenue (DfT, nd). In addition DfT (2003a) reported that the RTPI system in London resulted in routes showing an increase of 1% in passenger numbers. This seems very low compared to the numbers achieved elsewhere but one must consider that the public transport patronage in London is already very high.

Impacts on supply

There is no information regarding any change in supply as a result of RTPI.

Contribution to objectives

Contribution to objectives
Objective Scale of contribution Comments
  The main contribution through efficiency improvement is via the reduction in waiting times for buses.
  The reductions in car use (assuming those new passengers on the bus would have made the journey by car) will have contributed to a liveability improvement.
  Generally speaking no direct impacts would have resulted from the RTPI measures alone.
  There was no discernable impact on equity and social inclusion.
  There was no discernable impact on safety.
  There was no discernable impact on economic growth.
  US$23 million – US$28 million for AVL capital costs and approximately US$46 million for 4000 signs.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Case study 3: TriMet TransitTracker  (Portland, Oregon USA)

The information reported here is obtained from BAH (2006). 

Context

Transit Tracker is a real-time traveller information system deployed by Portland TriMet beginning in 2001. The Transit Tracker system provides TriMet riders with a real-time estimate of the expected time until the next transit vehicle arrives at a specific stop (bus) or station (rail). Transit Tracker covers all rail stops and each of TriMet’s 7,700 bus stops. 

Riders can access Transit Tracker in one of three ways:

  1. At Stops/Stations: Electronic Transit Tracker information displays have been deployed at 13 bus stops (4 of which also include voice annunciation) and at all TriMet light rail stations (deployed January 2001).
  2. By Phone: TriMet has a dedicated Transit Tracker customer service line, 503-238-RIDE (deployed September 2004).
  3. Via the Web: TriMet has a dedicated Transit Tracker web page, http://www.trimet.org/arrivals/index.htm (deployed September 2002).

image 05
Figure 5: Transit Tracker Information Display (Stop)

Transit Tracker uses global positioning system (GPS) technology to track the location of vehicles in revenue service. Every TriMet vehicle is equipped with a transmitter that allows continuous satellite tracking with an accuracy of approximately 10 metres. This real-time location information is used to calculate real-time bus and train arrival information. The information is then routed to electronic displays (Figure 5) in equipped bus shelters and rail stations as well as to the Transit Tracker Online Website and related customer service phone line. Information is provided in the form of arrival countdowns (i.e., minutes to the next arrival).

Impacts on demand

There was no information on whether RTPI generated additional ridership for TriMet. It was stated in BAH (2006) that “existing studies of Transit Tracker use do not provide a reasonable basis for assessing any potential increase in ridership resulting from implementation of the Transit Tracker system”. However at the same time, surveys have found that 78% of passengers use RTPI always or frequently.

Impacts on supply

This was not reported.

Contribution to objectives

Contribution to objectives
Objective Scale of contribution Comments
  There was no discernable impact on efficiency.
  There was no discernable impact on liveability.
  There was no discernable impact on environment. 
  There was no discernable impact on equity and social inclusion.
  There was no discernable impact on safety.
  There was no discernable impact on economic growth.
  Transit tracker costs approximately US$1 million for capital costs and US$180,000 per year for operating costs.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Gaps and Weaknesses

The biggest gap in evidence is in isolating the impact of RTPI from the entire package of measures implemented to improve bus services. In the case of London, roll out of the scheme occurred over a period of ten years and is still continuing. It is difficult to separate the impacts of Countdown from secular growth in passenger numbers. However for the Transit Tracker, RTPI alone did not achieve any increase in demand in transport, though it could be argued that it was fitted only on 13 of the services available. There is also a lack of information on whether new users have switched from car use or other modes.

Expected contribution to objectives

Contribution to objectives

Objective

Scale of contribution

Comment

  Public transport users are able to more efficiently utilise the public transport service resulting in a reduction in the perceived cost of waiting time as well as the perceived unreliability of services and therefore representing an efficiency improvement.
  To the extent that private vehicle kilometres are reduced.
  To the extent that private vehicle kilometres are reduced.
  In theory (Holdsworth et al, 2007) it helps to balance the advantages and disadvantages of using public transport with those associated by private cars.
  To the extent that private vehicle journeys and/ or distances are reduced.
  Weak evidence.
  While it may be costly to introduce on its own, its cost may be reduced through partnerships with operators, technology providers and governments. In addition, RTPI is seldom provided on its own but within an integrated public transport package of improvements.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Contribution to problems

Contribution to alleviation of key problems

Problem

Scale of contribution

Comment

Congestion

If private vehicle use is reduced. Reduced congestion of public transport may also occur if people can respond to information on disruption.
Community impacts To the extent that private vehicle journeys and/ or distances are reduced.
Environmental damage To the extent that private vehicle journeys and/ or distances are reduced.
Poor accessibility Some benefits of information but dependent on availability of services.
Social and geographical disadvantage Some benefits of information but dependent on availability of services.
Number, severity and risk of accidents To the extent that private vehicle journeys and/ or distances are reduced.
Economic growth Weak evidence of relationship.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Appropriate contexts

Appropriate area-types
Area type Suitability
City centre
Dense inner suburb
Medium density outer suburb
Less dense outer suburb
District centre
Corridor
Small town
Tourist town
= Least suitable area type = Most suitable area type

Adverse side-effects

None reported.

BAH (Booz Allen Hamilton) (2006) “Real-time Bus Arrival Information Systems Return-on-Investment Study Final Report for the US Federal Transit Administration

Balcombe R, Mackett R, Paulley N, Preston J, Shires J, Titheridge H, Wardman M, White P (2004) “The demand for public transport: a practical guide.” Transport Research Laboratory Report 593, Crownthorne, Berkshire

Caulfield B, O’Mahony M (2007) “An examination of the public transport information requirements of users” IEEE Transactions on Intelligent Transportation Systems, 8(1), 21 – 30

Centaur and Warman(2004) “East Kent real-time bus information - before and after study” Report for the Department of Transport,UK      

Clark R, Bowen T, Head J (2007) “Mass deployment of bus priority using real-time passenger information systems in London” European Transport Conference Stream: Managing the Demand for Road Space-Bus Priority

DfT (2003a) “Public Transport Information” Traffic Advisory Leaflet ITS 7/03

DfT (2003b) “Leicester -Star Trak Real Time Information System” Traffic Advisory Leaflet ITS 13/03

DfT (nd) “Passenger Information Systems” Available at http://www.dft.gov.uk/itstoolkit/Tools/T20.php

Dziekan K, Kottenhof K (2007) “Dynamic at-stop real-time information displays for public transport: effects on customers” Transportation Research Part A 41 (6) 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

Forsyth E, Silcock D (1985) “Real Time Information for passengers on the London Underground” PTRC SAM Seminar J, 157-171

Gillam W, Wright D (2000) “An innovative approach to real-time bus information and signal priority” Proceedings of the IEEE Tenth International Conference on Road Transport Information and Control 205-208

Gomez A, Zhao F, Shen LD. (1998) “Benefits of Transit AVL and Transit AVL
Implementation in the U.S.” Paper presented at the 77th annual meeting of the Transportation Research Board, Washington, DC.

Herrala M (2007) The value of transport information VTT Tiedotteita - Research Notes : 2394

Hickman M, Wilson N (1995) “Passenger travel time and path choice implications of real-time transit information” Transportation Research Part C 3(4), 211-226.

Hill R, Maxwell A, Bretherton D (2001) “Real time passenger transport information and bus priority in Cardiff - bus priority trial” European Transport Conference Stream: The Planning and Management of Public Transport Systems - Technology to Attract Patronage

Holdsworth N, Enoch M, Ison S (2007) “Examining the political and practical reality of bus-based real time passenger information” Transportation Planning and Technology 30(2/3), 183-204.

Horbury AX (1999) “Guidelines for specifying automatic vehicle location and real-time passenger information systems using current best practice” Transport Reviews 19(4), 331-351

Huber P (1996) “Advanced public transport information in Munich” IEEE International Conference on Public Transport Electronic Systems, London, May 21-22 69-71

Farag, S. and Lyons, G. (2010). Explaining public transport information use when a car is available: Attitude theory empirically investigated. Transportation, 37(6), 897-913,

James N (1986) “The provision of real time departure information at a rail-bus interchange.” Traffic Engineering and Control 27(9), 447-451

Johnson N (1999) “Countdown” Paper Presented at INFOPOLIS2 Seminar Berlin 10th June

Lamont, D., Kenyon, S. and Lyons, G. (2013) Dyslexia and mobility related social exclusion: the role of travel information. Journal of Transport Geography, 26. pp. 147-157

Lehtonen M, Kulmala R (2002) “Benefits of a Pilot Implementation of Public Transport Signal Priorities and Real-Time Passenger Information” Transportation Research Record 1799,18-5

Li Y (2003) “Evaluating the urban commute experience”       Journal of Public Transportation 6(4), 41-67.

Linton B (1997) “Vehicle positioning on London Transport Buses” Paper at the IEE Colloquium on “Where Are We Going? (And How Fast!)” , Seminar Exploring Speed And Positioning Systems For The Transport Sector 6th November

Litman T(2008) “Valuing Transit Service Quality Improvements”  Journal of Public Transportation 11(2), 43-63.

Lyons, G. (2006) The role of information in decision making with regard to travel. Intelligent Transport Systems, 153 (2). pp. 199-212.

Multisystems Inc (2003) “Strategies for Improved Traveler Information” Transportation Research Board Transit Cooperative Research Programme Report 92

San Francisco Muncipal Railway (2001) “Short Range Transit Plan 2002-2021” San Francisco, California

Schweiger C (2003) “Real Time Bus Arrival Information Systems” Transportation Research Board Transit Cooperative Research Programme Synthesis 48

Suen L, Geehan T(1986) “Information for Public Transport Users” in Bonsall P., Bell M (eds) Information Technology Applications in Transport, VNU Science Press: Dordrecht, Netherlands, 287-318.

Sun D, Luo H, Fu L, Liu W, Liao X, Zhao M (2007) “Predicting bus arrival time an the basis of global positioning system data” Transportation Research Record 2034, 62-72.

Vance C, Balcombe R(1997) “How to tell bus passengers what they need to know” CD Rom Proceedings of the European Transport Conference, Stream: Public Transport Planning and Operations - Improving Public Transport For The User

Wardman M, Sheldon D (1985) “Real time information for bus travellers in London”
PTRC SAM Seminar J, 173-185