Bus Fleet Management Systems

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


A bus fleet management system uses real time information on bus location and performance to ensure that buses run to schedule. Information can come from roadside equipment, but more typically employs GPS.  Such systems help improve the perception of the bus in the eyes of the travelling public and reduce the financial costs of operating services.  The former can be realised by improving journey reliability and minimising the wait and in-vehicle time when travelling by bus. The latter will result from being able to better utilise bus fleets and by reducing maintenance and operating costs.  These benefits can be accentuated by integrating bus fleet management systems with urban traffic control and real time passenger information.

There is little documented evidence from case studies of the impacts of such systems, but it appears that their main impact is in increasing the efficiency of fleet operations.  The resulting cost savings can more than cover the costs of implementation and operation.  Other benefits relate to the potential to attract modal transfer to the bus by making it more efficient and attractive.  This in turn can achieve additional benefits in terms of congestion relief, environmental enhancement and greater safety.

There are no significant barriers to implementation, and such systems are widely applicable.  More empirical evidence is needed on their contribution.  

The basic definition of a bus fleet management system is that it is a system which facilitates the efficient management and scheduling of bus routes to ensure that buses run to the schedule. Management of the bus fleet involves the timely arrival and dispatch of buses throughout their journeys and the ability to predict and react to changing circumstances which may disrupt this, e.g. vehicle breakdowns or heavy congestion. This in turn improves the operational performance of the bus which helps: 1) improve the perception of the bus in the eyes of the travelling public and; 2) reduce the financial costs of operating services. The former can be realised by improving journey reliability and minimising the wait and in-vehicle time when travelling by bus. The latter will result from being able to betterutilise bus fleets and by reducing maintenance and operating costs (less idling and better driving styles).

The key requirement of a bus fleet management system is the ability to locate a vehicle’s location throughout its journey, transmit this information back to a base office and to process this data usefully to ensure that the operator makes effective use of its fleet. Increasingly the information on vehicle location is being fed to various other systems to provide better Urban Transport Control, bus priority (including intelligent bus priority) and real time passenger information both pre-journey (at the bus stop, on the web, via SMS) and during the journey (in-vehicle). These other functions themselves can help contribute to better fleet vehicle management and whilst not considered directly by this report, are important side effects that should be borne in mind.

The majority of bus fleet management systems are somewhat limited in the amount of dynamic rerouting they can carry out during normal operations. That is because buses have pre-defined routes and bus stops which must be adhered to. This contrasts with road freight systems which possess the ability to reroute vehicles during operations to provide additional pick-ups or to avoid traffic congestion. There is however a small minority of more specialised bus services where operational rerouting is possible and we briefly outline them below.

  • One of the latest developments to arise from bus fleet management systems is the ability to provide Demand Responsive Transport (DRT). This complements fixed route buses, with DRT services dynamically adjusting themselves to the needs of the travelling public. No vehicle will run unless someone wishes to travel, and the vehicles will detour as necessary to combine a number of trip requirements onto a single vehicle. These services are managed from a central Travel Dispatch Centre, which takes the bookings and uses a sophisticated computer system to optimise the allocation of people to vehicles.
  • In the US bus fleet management systems are increasing being used to optimise routes and schedules for school bus transportation services to reflect changes in where school children live.
  • Airport shuttle buses in some large airports need to serve numerous docking bays spread over large areas, e.g. Dusseldorf has 74 docking bays. The time pressure inherent in airport set-ups makes providing a consistent and responsive service very challenging. Bus fleet management systems have been useful in optimising fleet scheduling and providing an effective two way communication between driver and base to ensure that the fleet is responsive.

Terminology & Technology

There are several technologies that allow automatic vehicle location (AVL), which are outlined below:

  1. Vehicle loop - this involves detector loops cut into the road surface that interact with a transponder (tag) on a vehicle. The loops receive information from the transponder about the vehicle and pass in to a central processing unit back at base.
  2. Roadside beacon - similar function to the detector loops;
  3. Global Positioning System (GPS) - This uses a passive device (such as a radio receiver) located on a vehicle. This reads signals from up to 12 satellites (but needs a minimum of 3) and calculates a vehicle's surface position to within 10 to 20 metres or 1 to 5 metres if differential GPS is used.

The first two types of technology are dependent upon equipment fixed to roadside locations. They are therefore relatively inflexible and require relocation or new equipment to be installed if the network changes. There has therefore been a move towards GPS technology. This removes the need for roadside based equipment and provides flexible systems that are less expensive to expand geographically. The type of detection provided by GPS can be differentiated between passive and active. The former only notifies the base station of a vehicle presence in a pre-specified location, whilst the latter provides constant information about vehicle location.

Data transmission systems are generally dictated by the type of vehicle location technology used. If the system is transponder based there is a short wireless communication between the vehicle and the detector and then generally a wireline based communication to the bus depot (plus whoever else requires it, e.g. UTC). GPS systems will communicate to the depot and other offices using a wireless system such as General Pack Radio Systems (GPRS) and Private Mobile Systems (PMS).

Unlike with freight fleet management the data flow tends to be from the vehicle to the base office. In part this appears to be because there is no need for  a flow of information in the other direction since the bus route cannot be changed to avoid congestion as may be the case with a HGV. If the base office wishes to communicate with its drivers then separate radio or cell phone systems are put in place. The potential flow of data from the vehicle to the base office is outlined below:

  • Vehicle location at calibrated intervals or upon request;
  • Vehicle location when entering a pre-specified area(virtual fence placed around a destination to inform a depot of a vehicles imminent arrival);
  • Vehicle location when panic alarm triggered;
  • Vehicle and driver identification;
  • Fuel consumption - trip/totals;
  • Driving style - speed/revs/idling/braking;
  • Timed trip data - start, stops, average speed, distance;
  • Driving hours; and,
  • Engine performance, e.g. temperatures.

As outlined earlier this data might be simultaneously transferred to not only the bus fleet's central control room but also to a traffic signal controller (to provide bus priority) or to a central UTC computer if an area wide strategy such as SCOOT is being used.

Why introduce bus fleet management?

The impetus for the introduction of effective bus fleet management systems comes from the improvement in bus service performance offered by such systems.  The main benefits are better customer satisfaction and an improved perception of bus services from the public in general and,  to a lesser extent, financial benefits from better fleet utilisation and lower vehicle running costs (more effective maintenance and more economical driving styles). The key benefits are outlined below,

  • Improvement in customer satisfaction & the perception of the bus by the general public: a) ability to analyse actual running times to produce realistic time tables; b) ability to detect broken down or late running vehicles and introduce replacement vehicles; c) ability to produce real time information for passengers (pre-journey and in-vehicle); d) ability to provide the necessary information for traffic signal controllers (bus priority)  and UTC functions to help negate problems caused by congestion.
  • Data recording of the performance of the driver and vehicles.  This results in more economical and safer driving and identifies any problems with the vehicle which allows preventative maintenance as opposed to prescriptive maintenance.  Together these can lead to reductions in fuel consumption, vehicle maintenance and insurance premiums (as accident levels are reduced).
  • Fleet utilisation - better scheduling can lead to better use of the fleet of vehicles. This might lead to savings such as reduced vehicle requirements or a reduction in vehicle depreciation. 

The exact benefits will all depend upon what systems have been put in place and what the capabilities of those systems are. 

Demand impacts

The main demand impacts are likely to result from the improvement in customer satisfaction with the current service and the improvement in the perception of bus from non-users.  A more reliable bus service is more likely to retain existing customers, generate additional trips from the same group, whilst at the same time attracting additional ridership from other modes of transport.  This is in turn is likely to help reduce externalities (congestion, pollution and accidents).

Responses and situations
Response Reduction in road traffic Expected in situations
No impact on car vehicle kms. Worth noting that the improvement in bus service reliability may lead to people making bus journeys setting off later, e.g. reducing the safety margin they build into their journeys.
No impact.
No impact.
Where bus service reliability is known to have improved, some individuals may reduce their car use through increased bus patronage. However, this will free up road space which may result in induced traffic.
As non-users’ perceptions of the bus improve some scope for achieving modal shift.  Also scope for retaining existing bus customers as their experience of bus improves.
No impact.
No impact.
= Weakest possible response = Strongest possible positive response
= Weakest possible negative response = Strongest possible negative response
= No response

Short and long run demand responses

There is likely to be a slightly stronger modal shift response if the improvements in bus service can be maintained.  The improvements will also be stronger if they can be linked in with real time passenger information, bus priority measures and UTC functions.

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

The introduction of effective bus fleet management systems will see a more reliable supply of buses.  In addition more effective fleet utilisation may see a reduction in the number of buses required to provide an equivalent service.

Financing requirements

The costs of introduction of bus fleet management systems will differ depending upon what features the system has and the size of the bus fleet to be 'wired up'. Exact figures for bus fleet management are not available, but figures DfT (2003) suggests, for road freight GPS fleet systems, that a sophisticated application made up of several pieces of on-board hardware, networked software and integration with third party software would typically cost between £1,500 and £3,000 per vehicle. Straightforward vehicle tracking systems cost around about £1,000 per vehicle.

Expected impact on key policy objectives

The impacts on key policy objectives will differ according to the features of the fleet management system.  The assessment is made more complicated if one was to also include additional benefits that might result from linking up a bus fleet management service with real time passenger information functions, bus priority and UTC.  If this is the case we would expect the impacts on key policy objectives to be greater than those shown below.

Contribution to objectives

Objective

Scale of contribution

Comment

  Improved fleet utilisation, reduction in congestion due to modal shift; monitoring of driving style and vehicle performance also bring major benefits.
  Reduction in congestion and improvement in driving style can help make streets more liveable.
  Modal shift will help reduce vehicle km and so the level of environmental externalities.
  Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport (and others of course).
  Modal shift will help reduce vehicle km, which together with improvements in driving style will improve safety.
  Improvement in fleet efficiency unlikely to stimulate economic growth.
  Indications are that the potential gains in fleet efficiency are very likely to outweigh implementation and additional operational costs.
= 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

Modal shift should benefit other road users who will experience a reduction in traffic and congestion levels.
Community impacts Reduction in congestion and improvement in driving style can help make streets more liveable.
Environmental damage Modal shift will help reduce vehicle km and so the level of environmental externalities.
Poor accessibility Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport
Social and geographical disadvantage Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport
Accidents Modal shift will help reduce vehicle km, which together with improvements in driving style will improve safety.
Economic growth Improvement in fleet efficiency unlikely to stimulate economic growth.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Expected winners and losers

There will be three main sets of winners as a result of the implementation of bus fleet management.  The first will be existing customers who will experience an improvement in the operational performance of bus services, particularly with respect to service reliability.  The second will be the bus operators themselves who should see a reduction in fleet operational costs via improvements in scheduling, vehicle maintenance and driving style.  The final set of winners will be other road users and pedestrians/residents who will experience a reduction in car vehicle km and the associated benefits that brings, namely a reduction in congestion and externalities. 

Winners and losers

Group

Winners/Losers

Comment

Large scale freight and commercial traffic

Likely to experience a reduction in congestion levels so an improvement in operational performance.

Small businesses

Likely to experience an improvement in the reliability and delivery times of freight consignments.

High income car-users

Will tend to benefit from a reduction in congestion levels within urban areas.
People with a low income Those solely reliant on the bus as a means of transport will benefit from improved reliability.
People with poor access to public transport No impact.
All existing public transport users Will benefit from a major improvement in bus service, specifically service reliability. 
People living adjacent to the area targeted No impact.
People making high value, important journeys Will tend to benefit from a reduction in congestion levels within urban areas.
The average car user Will tend to benefit from a reduction in congestion levels within urban areas.
= 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 legal barriers to implementation.
Finance Costs for similar GPS freight systems for a sophisticated system can range from £1,500 to £3,000 per vehicle.  Cheaper, straightforward GPS vehicle tracking systems cost around £1,000 per vehicle.  However, with likely savings to fuel and labour between 5% and 10% the financial barrier will not be significant.
Governance Roadside equipment will require collaboration; otherwise no barriers.
Political acceptability There are no political barriers.
Public and stakeholder acceptability There are no acceptability barriers.
Technical feasibility The technology is generally available, but retro-fitting of vehicles may be a barrier.
= Minimal barrier = Most significant barrier

Case Study One - Dusseldorf International Airport

Dusseldorf Airport sees millions of passengers pass through its terminals each year. Unlike most other airports Dusseldorf’s 74 docking bays are spread over a 723 square km area with 50 shuttle buses to service them. The time pressures inherent in an airport set up make providing consistent and fast services extremely challenging. An airport’s profit margin depends upon turning around planes faster and faster and so passengers need to be taken to and from their docking bays as efficiently as possible. Added in with this is the fact that the background noise makes communication between vehicle drivers and the dispatch centre very difficult with only radio telephones. As a result operational efficiency was proving difficult to maintain. What was needed was a fleet management system that could provide real time information about vehicle locations and also an efficient two-way communication with the drivers of each vehicle to allow optimal routing between docking bays. A fleet management solution was provided by Psion Teklogix and has seen an improvement in fleet effectiveness and service reliability from passengers’ viewpoint.

Case Study Two - Shanghai, China

The bus industry in Shanghai has more than 200 bus routes, thousands of buses and a large number of bus terminals. The administration of these buses used to be carried out manually in each terminal, from information collecting, inquiry sorting and statistical analysis to summary reporting and dispatch ordering. This frequently resulted in scheduling mistakes which inconvenienced both staff and passengers and which led the bus fleet to be larger than actually required. After consulting with a number of fleet management system manufacturers Shanghai decided to install a TagMaster AB fleet management system ( www.tagmaster.com ). The system has a communicator installed at the entrance to all bus terminals, connected to signal lights and communicating with the host. All buses have unique tag IDs, all of which have been stored in the communicator's database. As soon as the bus arrives at a terminal its ID is detected and a green signal  is activated by the TagMaster communicator. Simultaneously information is sent to the control centre which can then send departure information to the bus terminal’s LED display for passengers to inform them when the bus will leave. On exiting the terminal the communicator informs the control centre and this information is logged on the system. The system provides bus performance reports on a weekly, monthly and annual basis allowing bus managers to optimise routings and schedulesand to provide passengers with more precise travel information.

Case Study Three - Demand Responsive Transport in Plymouth and Cornwall

Demand responsive transport (DRT) complements fixed route buses. These services dynamically adjust themselves to the needs of the travelling public. No vehicles will run unless someone wishes to travel, and the vehicles will detour as necessary to accommodate a number of trip requirements into a single vehicle. This dynamic routing is managed from a Travel Dispatch Centre which takes bookings and uses a sophisticated computer system to optimise the allocation of people to vehicles.

The Plymouth and Cornwall DRT service utilises a bus fleet management system provided by ACIS, Mobisoft and Vodafone. The system equips the transport operator with powerful new management tools and the public with real time departure information using signs in bus shelters and potentially using the web, WAP, SMS and a phone services.

Case Study Four - Fixed Route and Demand Responsive Transport in Montachusett Regional Transit Authority

The Montachusett Regional Transit Authority (MART) serves the counties of Fitchburg , Leominster and Gardner in the State of Massachusetts , US. The authority serves a largely rural area of around 700 square miles using 150 vehicles and with daily trips of around 6,500. Besides improving the productivity via better scheduling and real time routing of their operations, MART was also concerned about the safety and security of its transit operations. As a result it implemented a fleet management system that included automatic vehicle location, GIS, electronic fare collection and real time information via the web. An additional spin-off of the system has been detailed information on bus arrival and departure times which has been used to check against customer complaints, particularly those who use the demand responsive service.

Case Study Five - Denver Regional Transportation District's Automatic Vehicle Location System

In 1993 the Regional Transit District (RTD) in Denver, Colorado installed an automatic vehicle location (AVL) system which was developed by Westinghouse Wireless Solutions. The system covered an area for 2,400 square miles and was capable of tracking the 1,335 vehicle fleet. The key objectives of the system were to: 1) develop more efficient schedules; 2) improve the ability of dispatchers to adjust on-street operations; and, 3) increase safety through better emergency management. Whilst the system has been successful in achieving objectives 2 and 3, it has not achieved the first because of conflicts in scheduling procedures and difficulties in coordinating existing and new software applications. Although ridership on RTD buses increased substantially between 1992 and 1994, the number of passengers carried per vehicle revenue mile declined due to the expansion of service and the increase in long-haul service which carries each passenger for more miles per trip. Similarly, although operating costs per vehicle hour and per passenger declined between 1992 and 1997, the decrease cannot be directly attributed to the AVL system. It does, however, coincide with its implementation.

Where the AVL system has been effective is in improving the quality of service provided to customers. Between 1992 and 1997 there was a 12% decrease in the number of vehicles that arrived at stops early. At the same time the number of vehicles that arrived at stops late decreased by 21%. This was reflected by a 26% fall in customer complaints during the same period. The AVL system has also improved the quality, timeliness and availability of customer information available at customer service centres.

The AVL system has also received wide spread acceptance from operators, dispatchers and field personnel. The operators felt that the system provided them, and customers, with more safety and security, while dispatchers felt that the knowledge they had of vehicle locations helped RTD maintenance, supervisors and emergency response teams to quickly reach incident locations. They also felt that the quality of service they could offer improved as they were able to alert drivers that they were ahead or behind schedule.

Expected contribution to objectives

The contributions reported here reflect an amalgamation of the case studies presented in the previous section. No specific evidence has been presented instead judgements have been made from anecdotal evidence and forecast benefits.

Contribution to objectives

Objective

Scale of contribution

Comment

  Improved fleet utilisation, reduction in congestion due to modal shift; monitoring of driving style and vehicle performance also bring major benefits.
  Reduction in congestion and improvement in driving style can help make streets more liveable.
  Modal shift will help reduce vehicle km and so the level of environmental externalities.
  Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport (and others of course).
  Modal shift will help reduce vehicle km, which together with improvements in driving style will improve safety.
  Improvement in fleet efficiency unlikely to stimulate economic growth.
  Indications are that the potential gains in fleet efficiency are very likely to outweigh implementation and additional operational costs.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

Contribution to problems

Again, the case studies provide little detailed information on impact.

Contribution to alleviation of key problems

Problem

Scale of contribution

Comment

Congestion

Modal shift should benefit other road users who will experience a reduction in traffic and congestion levels.
Community impacts Reduction in congestion and improvement in driving style can help make streets more liveable.
Environmental damage Modal shift will help reduce vehicle km and so the level of environmental externalities.
Poor accessibility Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport
Social and geographical disadvantage Greater service reliability will result in more reliable journeys for those solely reliant on the bus as a means of transport
Accidents Modal shift will help reduce vehicle km, which together with improvements in driving style will improve safety.
Economic growth Improvement in fleet efficiency unlikely to stimulate economic growth.
= Weakest possible positive contribution = Strongest possible positive contribution
= Weakest possible negative contribution = Strongest possible negative contribution
= No contribution

 

Appropriate contexts

Bus fleet management systems are very suitable in all areas and in different contexts of operations, e.g. demand responsive vs fixed route.  It is therefore difficult to rate the suitability of the system other than in identifying the areas where it might have more impact.

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

ACIS (2004) "Latest Newsletter" (2004). Taken from website - www.acis.uk.com

Department for Transport (2003) "Public Transport Priority". Traffic Advisory Leaflet, ITS 5/03.

Hounsell, N.B. and Cheney, C.N. (1999) "Using ITS To Improve Bus Operations: Examples and Opportunities". European Transport Conference, Proceedings of Seminar D, Cambridge .

Psion Teklogix (2004) "Dusseldorf International Airport". Web Article - www.psionteklogix.com/public .aspx?s=us&p=Solutions&CaseStudy=882&vM

Tagmaster (2001) "TagMaster Improves the Efficiency and Quality of the Bus Transport System in Shanghai , China". A web article - www.tagmaster.se/download/app_notes/shanghai%2004-067%2001.pdf

US Department of Transportation (2000) "Assessment of the Denver Regional Transportation District's Automatic Vehicle Location System".

US Department of Transportation (2002) "Transit ITS Case Studies". Report for Federal Transit Administration and Federal Highway Administration.