dynamic public transportation system_group proposal

8/3/2019 Dynamic Public Transportation System_Group Proposal

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Imperial College London Electrical and Electronic Engineering

Concept Paper on Dynamic Public Transportation System

A DYNAMIC PUBLIC TRANSPORTATION SYSTEM

Intelligent Transportation System

Second Year Student Initiative

FEB 2012


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Content Page

1. Introduction2. Current Intelligent Public Transportation Systems

A. SingaporeB. ZurichC. London

3. Interview with Industry Player Cubic Corporation, Cubic Transportation System4. Proposed Model of Intelligent Public Transportation System

A. Informational Interfacei. Information Collection

1. Operating Environment2. Demand Level Assessment3. Resource Monitoring

B. Operation Interfacei. Usage of Integrated Information

1. Government2. Transport Operators3. End-Users

C. System-wide Entityi. Integration of Collected Informationii. Distributive Information Structure

5. A Vision of Future Public Transportation System6. ConclusionI. Appendix A Congestion Facts and Figures

II. Appendix B Intelligent Transportation Systems

III. Appendix C Interview with Land Transport Authority, Singapore

IV. Appendix D 2019 Implementation Framework

V. References


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Concept Paper on Dynamic Public Transportation System Page 1

1. INTRODUCTION

Many countries now face the challenge of mass transportation while having to deal with severe congestion within their

cities. Increasing affluence has resulted in the extensive usage of private vehicles and this growth is overwhelming the

transport infrastructure. Carrying capacities of roads were not planned for todays number of vehicles1

and yet, more

private vehicles are still being added to the transport network. Public transportation networks were not planned for the

rapid increase in population and were often seen as the second-class mode of transport as compared to private vehicles.

To cope with the transportation issues, conventional means such as building new transportation infrastructures were

often done however long as the number of road users increase, the same problem will resurface. In addition, new

infrastructure, such as highways, often requires long project timespan and incurs huge costs when the development

occurs within the city. A new solution is urgently needed to deal with the growing demand for transportation.

In this research, the group aims to improve public transportation systems using informational resources in three primary

aspects, operation environment, demand level assessment, and resource monitoring. The collected information can then

be processed by a system-wide entity that then proceeds to distribute the information to transport authorities, transport

operators and commuters.

2. CURRENT INTELLIGENT TRANSPORTATION SYSTEM (ITS)

There are many governments around the world that utilise information and communication technologies to increase the

efficiency of road networks. Examples of technologies that have been implemented include dynamic traffic lights, road

monitoring, demand modelling and passenger journey planners that have been implemented as a mobile application. In

particular, countries such as Singapore and Switzerland have implemented an extensive range of ITS solutions to cope with

the increasing transportation demand.

A. Singapore Land Transport Authority (LTA)

In Singapore, the LTA runs an Intelligent Transport Systems Centre that monitors and operates several ITS solutions2.

These include the Green Link Determining System (GLIDE) which monitors and optimises green signals on roads,

TrafficScan that monitors road conditions, IBMs Symphony E-payment System that manages contactless payment on

public transport and many others.

Our interviews with a transport planner at LTA revealed that information generated by such systems has been used for

modelling from as early as in the 1990s! Even though the information is only updated once a year, it has an accuracy of up

to 90%3

for various stages proving the potential of transport modelling using travel data. Furthermore, the system has

helped the government in planning infrastructure improvements and to evaluate the impacts of improvements.

B. Switzerland, Zurich - ZVV

In Zurich, transport operators have implemented a Dynamic Traffic Signal Control which takes in real time traffic

conditions from different transport networks and the location of individual transit vehicles. This is then used to establish

the most optimal phase and duration of traffic signals. Using the location of the transit vehicle, the system can predict the

arrival time of transit vehicles at road junctions up to an accuracy of 1 second4.

In addition, an interesting spill over effect of the system is that it also optimises transport networks for private vehicles as

the pipelining of vehicles in different road networks has allowed vehicles to utilise green signal time more effectively,

resulting in a smoother journey.

1In 2008, there were 218,000 vehicles per km of road in Singapore. Refer to reference item 1

2 Refer to reference item 113Refer to Appendix C

4Refer to reference item 3


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C. United Kingdom, London Transport for London (TFL)

In London, TFL has implemented an ITS, Automatic Vehicle Location, into an overall bus traffic priority system known as

iBus. This system uses GPS detectors to determine the position of the bus and processes this information to control traffic

signals. However, such control procedures are individual events that do not relate to other junctions along the transport

network. To facilitate the flow of information, the bus locations are shared with the public on the TFLs website5.

TFL also monitors the usage of different public transport modes through the conduction of the London Travel Demand

Survey6. Here information on the journeys travelled by 8000 households is collected to better manage transportation

demand.

3. INTERVIEW WITH INDUSTRY PLAYER Cubic Corporation, Cubic Transportation System (CTS)

On the 9th

January 2012, our project group was given a rare opportunity to interview CTS at their European Headquarters,

where the London Oyster Card Payment System was developed. CTS handles more than 1 billion passengers every year

and manages up to 50 million pounds of public transport revenue daily. The interviewees were Mr. Matthew J. Cole, Sr.

Vice President of Strategy and Business Development and Mr. Martin Howell, Director of Worldwide Marketing and

Communications.

CTS agree that information generated by public transportation will be the next edge in optimising public transportation

systems. They are currently focusing on the transaction aspect of public transportation, where they aim to create a

centralised payment system for each individual using the public transport. Such a centralised payment system could

extend to cover various modes of transportation payments, such as payment methods using mobile devices and on

account-based payment systems which provide travelling information to passengers.

Currently, Oyster card readers on buses store transaction data during the day and upload the transaction information to

the back office after the journey, which readers at Tube stations update to the database on a real-time basis.

Consolidation of data for TFL is then done overnight. However, Cubic is looking into implementing 3G readers on bus

platforms to incorporate a higher communication capacity.

As an industry player, they are unwilling to look at other forms of information collection on transport network due to not

being part of their companys strategy. However, they are interested in the information that can be collected from

different public transport subsystems.

4. PROPOSED MODEL OF INTELLIGENT PUBLIC TRANSPORTATION SYSTEM

Todays societies are becoming more instrumented, with nearly one billion transistors per human and over 30 billion radio

frequency identification tags produced globally. At the same time, the world is also becoming more interconnected, with

IP traffic expected to exceed half a zettabyte in three years, thats 1021

bytes!7

In addition, with advanced analytics and

supercomputers, organisations and research institutes have been able to process information at resounding speed,providing new insights in computational fields.

With such rapid technological developments, Mankind is now witnessing the confluence of three key technological drivers

the ability to generate significant amount of data, the means to transmit the data and the capability to process the vast

amount of data. Transportation as we know it, is about to change.

ITS solutions that were implemented worldwide were initially implemented as stand-alone systems. Opportunities to

collect information from ITS platforms were lost and there is also no exchange of information between various systems. As

a result, transport authorities and operators are not achieving the full potential of ITS platforms.

5This is available through Transport for Londons Journey Planner6Refer to reference item 16



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Proposing a Truly Information-Integrated Public Transportation System

In order to utilise information for optimising public transportation, the proposed system is separated into two interfaces,

an Informational Interface for collecting information from sensors distributed across subsystems in the transportation

network, and a Function Interface for distributing processed information to different end-users.

A. Information Interface

Under this interface, the system focuses on the role of data collection and refining the data for usage. To fully utilise the

collected data, information from different sources must be integrated to allow transport system administrators to get an

understanding of a system-wide health status of the transport infrastructure. Moreover, collected data must be

interpreted level-wise, to reduce computational demands at data processing layers which are higher up in the

informational hierarchy.

The three key layers in the proposed informational interface are the Raw Information Layer, Domain Layerand System

Layer(Information). In the Domain Layer, information is classified into three main categories; Operating Environment,

Demand Level Assessment and Resource Monitoring.

SYSTEM-WIDE INTEGRATIONOF INFORMATION

Operating Environment

Physical Road/ Track Network andConditions

Scheduled External Events

Real-Time Traffic Status

Travel Profile of Other Vehicles

Demand LevelAssessment

Passenger Travel History

Crowd Density Levels

Event Monitoring

Primitive Location of User

Resource Monitoring

Vehicle Location and Status

On-board Passenger Count

Staff Deployment

Resource Planning

Raw Information Layer Domain Layer System Layer (Information)

Figure 1 : System Schematic Showing Information Interface of the Proposed Intelligent Public Transport System


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I. System Layer (Information)

The system layer is the system-wide informational entity that collates

processed information from each domain. This information is then

analysed and integrated to provide ITS administrators with a situational

awareness of the entire public transportation system.

Using advanced analytics techniques and high-speed computational

systems, ITS administrators will be able to assess thecurrent health

conditions of public transportation, predict future changes to

transportation systems, and react promptly to any system failures with

the appropriate contingent measures.

II. Domain Layer

The domain layer collates information in each of its three categories; Operating Environment, Demand Level Assessment

and Resource Monitoring. Information in these three categories is collated and partially analysed in the Domain Layer for

critical, real-time information that requires immediate attention. This is to prevent information choke at the system layer

while also providing the general ITS with a certain level of redundancy.

III. Raw Information Layer

The raw information layer consists of distributed sensors that collect information in the different traffic and transportation

subsystems. Sensors are divided into the three categories to facilitate information flow with the Domain Layer. In this

section, the report will discuss the various sensors that can be/are already deployed. In addition, technologies that are

currently under development will also be discussed.

1. Operating Environment

Operating Environment relates to information pertaining to the external conditions surrounding the operation of public

transportation systems, such as traffic conditions. The information collected will then reflect the constraints that the

public transportation systems operate under, while allowing transport authorities and operators to determine the

appropriate limits of operation for their resources.

Physical Road/Track Network and Conditions Information on road and track

networks have been actively collected and shared by transport authorities and

operators8. It is readily found online and in mobile applications. Transport authorities

often manage road and track networks through an operational centre or system,

such as the Expressway Monitoring Advisory System used in Singapore. This is to

facilitate prompt action in a contingent event.

Scheduled External Events Planned events also mean that road availability are affected at times, for instance

road closures during the New Year Countdown. The collection of this information in the system allows operators

to mitigate the effects of such events on commuters.

Real-time Traffic Status Information about the level of congestion, average vehicle speeds and traffic incidents is

collected in real-time by transport authorities or companies. Current sensing techniques include speed monitoring


Figure 2: Operations Office of the Intelligent

Transport System Centre in Singapore

Figure 3: Automatic Road Signs


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cameras, induction loops between traffic junctions measuring the average vehicle travel time and GPS-equipped

vehicles9.

Under DevelopmentTravel Behaviour of All Other Vehicles on Road/Track Vehicle tracking technologies using

image recognition, built-in GPS systems and RFID tags provide the possibility of observing the behaviours of all

vehicles on the road network.

An on-going project is the eCall10. It is a European Commission scheme to equip all new vehicles with mobile

connectivity and GPS. 14 countries have signed up for this scheme and it is likely that other countries will sign up

as well. Under this scheme, location-based information of the vehicle can be collected and be transmitted via the

on-board mobile communication devices. This allows transport authorities to observe general behaviour of the

traffic users, to react to ad-hoc variations and predict future load on transport network.

2. Demand Level Assessment

Demand Level Assessment relates to information that pertains to the requested level of service from transport operators.

Variation in demand across different timings and locations can be monitored and predicted with this information. As a

result, with a clear understanding of passenger flow, transport operators will be able to distribute resources more

efficiently by providing higher service quality while minimising resource wastage.

Passenger Travel History Using the past records of a passengers journey (i.e. Information such as

alighting/boarding time and location), simulation models could predict transportation demands in a region and so

transport operators will be able to plan the necessary transport service support levels to meet that demand. If

records are updated digitally in real-time, it is possible to get real-time predictions of passenger service demands.

Currently, transport operators are trying to collect passenger past journey information by using incentives such as

subsidised transport costs to attract commuters to record their journeys in a travel record card. However, this

method does not sample the entire commuter population, nor does it reflect the ad-hoc variation in demand

levels.

A new technology that has been gaining momentum is the usage of contactless payment methods. Through the

contactless payment systems implemented by Transport for London and Land Transport Authority of Singapore,

commuters travel records are stored real-time in digital databases. This can be used in demand monitoring for

statistical models.

By having a record of travel history, transport operators will be able to charge a flexible fare for transiting

commuters to appeal to a larger group of commuters and to reduce car ridership.

Currently, records are only examined periodically, instead of a real-time basis. As a result, only routine trends

such as daily commuting to and from school/work are captured in the system. However, unexpected changes indemands are not met by corresponding changes in supplied transport resources resulting in resource wastage.

Passenger travel history should be examined in real-time in order to reflect any immediate change in passenger

commuting demands.

Crowd Density Level in Hot Regions Crowds sensors could be placed in crowd-prone areas to raise alerts when

crowd levels have rose to a certain threshold and thus the area is likely to require more transportation services

and support. Automatic crowd-sensing devices have been built and are now pending patent application.11


Refer to reference item 1211

Refer to reference item 18


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In crowded areas, such as Oxford Circus, such crowd-based sensors could be integrated with existing security

cameras using image processing algorithms to track the level of crowd in separate timeframes. With such

information, transport systems are able topredict short-term changes in passenger commuting demand within 15

to 120 minutes.

Event Monitoring Information about events happening across the city should be taken into account when

predicting the demand level in a given area. For instance, the ending time of a rock concert or soccer match is a

good indicator that service demands in the region will peak rapidly. Moreover, demand variation can also be due

to long term events such as seasonal changes, resulting in changing commuter profiles (i.e. Varying percentage of

commuters who are tourists tend to peak during holiday periods).

This information about events across a country is often widely available in public. In addition, previous trends in

variation of transport demands have been recorded and investigated. This information can be used topredict

changes in demand levels over a long period of time.

Primitive Location of Users By knowing where passengers alight in real-time, transport operators can provide a

rough estimate on the level of crowd in an area. If the travel history of such commuters is available, this

information can be used topredict levels of passenger flow for return journeys. For instance, we can predict thedeparture time of any individual alighting at South Kensington by the general trend of their travel history.

In DevelopmentUser Service Demand In the near future, mobile phones, digital security and widespread use

of mobile internet are likely to provide commuters with another form of payment method for public transit, such

as the NextVision system that is being planned by Cubic Corporation. Instead of waiting at the bus stop for their

buses, commuters could instead pay for pre-booked bus trips using their mobile phone ahead of the trip. For

instance, work-related trips could be pre-booked online, with updates confirming their trip timings. In return,

transport operators will provide reliable estimated arrival timings and also estimated journey time information.

Pre-booking of trips has been implemented for long distance train journeys and flights due to high resource costs

and low passenger counts per route. This technology could be implemented for public transport, should it bedeemed convenient enough for the general user and mutually beneficial to both commuters and transport

operators.

In DevelopmentLocation of Users In the near future, location-based information of users could be accessed

via voluntary public participation programmes or through location-based information collected as a by-product of

mobile communications. Knowing where a particular commuter might be will allow the system to better

understand the commuters behaviours and allow transport operators to plan their resources in order to match

demand better.

3. Resource Monitoring

Resource Monitoring relates to information about the resources managed by transport operators. The collection of this

information allows transport operators to plan transport operations more efficiently and to react rapidly to any sudden

fluctuations in the transport networks. In addition, this information should be made available to the System Layer for

transport authorities to understand the resource capacity of the transport network in order to deal with any contingent

situations, as well as to plan future improvements in transportation.

Vehicle Location and Status Transport operators have implemented fleet management systems to monitor their

capability, in order to deploy vehicles to take different scheduled passenger loads and also to provide contingency

measures during emergencies, such as metro breakdowns.

Resource Planning Information that pertains to capacity resource planning by transport companies to deal with

future demands should be captured in the system to estimate the robustness of the transport system.


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On-board Passenger Count Information in the on-board passenger count provides transport operators an idea of

the load on their fleets, allowing them to adjust supply.

Staff Deployment Other than knowing their physical resources, transport operators must also be aware of their

human resources. Vehicle captains and fleet support personnel are very crucial to the system as they cannot be

deployed without intermittent breaks or without sufficiently early notifications.

B) Operation Interface

In this interface, the system determines the optimal reactions to be taken by different ITS subsystems, based on the

processed information from the informational interface. Decision making processes will be conducted in separate layers

such that each controller has autonomy over the subsystems that they control. In addition, this introduces a certain

degree of redundancy to the system as subsystems which are critical to the operation of transportation networks are

isolated from each other.

The three key layers in the function interface are; System Layer (Operation), Controller Layerand Function Layer. In the

User Layer, processed information and decision making processes are further divided into three categories;

Government/Transport Authorities, Transport Operators and Passengers.

SYSTEM-WIDE INTEGRATIONOF INFORMATION

Government /Transport Authorities

Land-use and Transport Planning

Traffic Signal Control

Policy and Regulation Planning

Benchmarking / PerformanceIndicator

Transport Operators

Vehicle Management

Personnel Management

Seamless Transits

Flexible Fares

Dynamic Routing

Passenger

Information-Assisted JourneyPlanning

Route Condition Awareness

Function LayerUser LayerSystem Layer (Operation)

Figure 4 : System Schematic Showing Operation Interface of the Proposed Intelligent Public Transport System


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I. System Layer (Operation)

Using the generated models and processed information from the information interface, system-wide decision making can

be implemented at this stage to determine the overall condition of the public transportation system. Filtered information

and general instructions on the current state of the public transportation conditions can then be distributed to the User

Layer. For instance, the need for diversion of vehicles from a region can be set up as a general flag in this layer.

II. Controller Layer

In the User Layer, the three users Government/Transport Authorities, Transport Operators and

Passengerscan act on the information and instruction sent by the system layer. They will

generate specific instructions and conduct decision-making processes to control the various

subsystems that they are tasked with. For instance, after the system flags the need to divert

vehicles from a region, the Transport Authorities controllers can decide to set up automated road

warning signboards to divert vehicles away from a region using electronic signboard systems.

III. Function Layer

The function layer consists of all the ITS divisions and subsystems that are incorporated into the transportation network to

optimise the transport network. Subsystems are divided according to their controller under the User Layer. In this section,

the report will briefly discuss the role of each subsystem.

1. Government/Transport Authorities

Land-use and Transport Modelling Division Information report generated by the information interface can be

used by land and transport planners to create urban models that capture transport trends and predict future

population behaviour. This allows planners to make optimal decisions in urban planning.

Dynamic Traffic Signal ControlSubsystem This subsystem controls the period and phase relations between

different traffic junctions depending on the traffic controls. This is to optimise the use of green signal time for

public vehicles and to create a smoother driving experience for private car drivers.

Policy and Regulation Planning Division Information reports generated by the system interface can be used to

gauge if the current traffic regulations or policy for the traffic load is appropriate. For instance, transport decisions

such as traffic calming12

for a roadway can be taken after reviewing results from the system.

Benchmarking / Key Performance IndicatorSubsystem Information collected from the system can also be used as

a benchmark to determine the efficiency of the transport network as a whole, the effectiveness of different

improvements and implemented policies

2. Transport Operators

Fleet and Personnel ManagementSubsystem This subsystem uses the assessment of ad-hoc, short-term and

long-term demands provided by the information interface to advise and help transport operators plan vehicle and

personnel resources.

Seamless TransitSubsystem Using the information provided by the system-wide entity, this subsystem will be

able to minimise variation in transit journey times based on expected demand levels and current traffic

conditions. As a result, it is possible to plan for seamless transit between different public transportation modes

(inter-transportation and intra-transportation) and between different transport operators. Passengers requiring

12Traffic calming refers to the process for regulating vehicles such that traffic flow is slower

Figure 5 : Electronic

Signboard Systems


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transits can be shifted from one destination to another with minimal disruption and crowd levels at transit points

can be reduced.

Flexible Fares With sufficient information, transport operators will be able to implement flexible fares for

commuters who take public transport during peak hours or off-peak hours. In addition, passengers with indirect

journeys will not have to pay the full fare of another trip. This has shown to encourage public transportation

ridership levels in many cities.

Dynamic Routing Subsystem With a robust real-time information interface, buses will be able to use semi-

dynamic bus routes where certain bus stop points and congested road networks could be avoided entirely. This

information will also be made available to commuters at the various bus stops.

3. Commuters

Information-Assisted Journey Planner Such systems are very much like the applications already provided in

platforms such as the Android and IPhone. However, with the information interface processing information in

real-time, commuters will be able to get more reliable journey predictions and estimations.

User Service Request Using booking systems, commuters will be able to pre-book public transport journeys prior

to the trip. This can be forecasted weeks or months before the actual journey and allow transport operators to

better plan their resources.

C. System-wide Entity

Through merging the information and operation interface, information flow to decision-making process is streamlined into

a collection of subsystems. Information gathered from distributed sensors will be processed into instructions. The

interplay of reactions between the public transportation network and the instructions will provide more information into

the system. This closed-loop system allows transport authorities and transport operators to continuously upgrade and

update their system. An implementation framework is available in the appendix.

Figure 6: Schematic Showing Entire Layout of Intelligent Public Transportation System


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5. A VISION OF FUTURE PUBLIC TRANSPORTATION

Autonomous vehicles, green transport and smart cities will shape the future of urban transport. However, given the

current technology, infrastructure and levels, there is a significant gap between the envisioned future technologies and

what we have now. This gap can be bridged by the proposed integrated information system and in particular, through two

revolutionary technologies in mass transport Dynamic Bus Routing Subsystem and User Service Request.

Through the simultaneous implementation of these two subsystems, transport operators will be able to gauge transport

demand ahead of schedule and plan buses with dynamic routing to meet the increased demand in certain areas. These

buses could operate with no bus numbers and offer ad-hoc routes to fulfil sudden variationsin travel demands.

These buses can operate in parallel with the current fixed-route bus systems so commuters are able to hop onto such

buses through directions given by the User Service Request subsystem. As a result, transport operators will be able to fulfil

more service requests, increase efficiency and reduce wastage while still maintaining a smaller pool of resources.

This vision will require a rethink of how public transport works and to subsequently change the publics general mind-sets.

However, we have learnt from other cities which have implemented ITS solutions that providing the public with adequate

information will result in people growing more agreeable to such changes.13

6. CONCLUSION

In conclusion, improvements in the area of public transportation are pertinent to a citys future developments. However,

given that it is resource-challenging for many cities under land constrains and high private vehicle ridership to utilise

current improvements, it is necessary for transport authorities to consider of capitalising on informational resources in

order to improve public transportation.

Currently, many of the subsystems have already been implemented in various different transportation systems

worldwide. Such subsystems have provided a significant boost to the profitability of both the transport industries and the

commuters travel experience.

We believe that the time is now ripe to harvest the vast informational resources that ITS systems are generating. The

efficient processing of such information will facilitate fast transport networks. It is therefore essential that world leading

cities incorporate such a system.


No User No User

Conventional

Routing

No User No UserDynamic Routing

Bypass

Bypass


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APPENDIX A CONGESTION FACTS AND FIGURES:

Publics Opinion to the Extent of Congestion in the United Kingdom

A majority of UK residents feel that congestion is a problem in the United Kingdom. Opinion poll shows that over 70% of

the population feel that congestion is a serious or very serious problem. In addition, many of them do not expect

congestion to improve over the next 2 years.14

IBMs Review of Congestion in Different Countries Worldwide

IBM conducted an international survey called the Commuter Pain Survey to find out more on commuters general

transportation satisfaction levels.15

It can be observed in this diagram that developing countries have a greater

transportation challenge to overcome. Already 70% of the populace in UK find that congestion is a problem, hence, one

can only imagine the severity of congestion in the other cities.



Figure 7: Table showing the Percentage of UK Residents on their

Opinion of the Severity of CongestionFigure 8: Opinion Poll about the Predict Extent of Congestion Over the

Next 2 Years

Figure 9: IBM's Consumer Poll of Congestion in Different Cities


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APPENDIX B INTELLIGENT TRANSPORTATION SYSTEMS:

Automatic Vehicle Location Subsystem

In an automatic vehicle location system, transit vehicles are equipped with GPS systems that relay the information

through a receiver station that passes the information back to a dispatch centre.

16Traffic Signal Priority Subsystem

This diagram shows a similar kind of traffic signal priority subsystem that is being used in Zurich. As the transit vehicle

draw nears to a junction, the emitter notifies a traffic signal controller. The controller then determines the most

appropriate traffic light status for the transit vehicle to pass with the least time spent.


Figure 10: Diagram on Operation of Automatic Vehicle Location

Figure 11: Diagram Showing an Implementation of Transit Priority


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APPENDIX C INTERVIEW WITH MR. DANIEL QUEK, TRANSPORT PLANNER, LAND TRANSPORT AUTHORITY, SINGAPORE

Our Ref: LTA/P&P/TPL/SPL/F20.000.000/799

Date : 14-Dec-2011

Tel : 63961843

Fax : 63961754

Dear Mr LeowEnquiries on Traffic and Public Transport Modeling

FEEDBACK NUMBER: 20111205-0100

We refer to your email of 05 December 2011.

We studied your questions and provided our responses in blue below.

General Traffic Modeling:

1. How is LTA currently modeling general transport network demands and usage?

For middle to long term planning, LTA has developed a multi-modal transport model forecasting the future travel demand

based on planning parameters, population and employment distribution provided by other Landuse agencies. The model

forecasted both private transport and public transport demand. The model is calibrated using various data sources

including travel surveys, traffic counts and ticketing system (EIFS - Electronic Integrated Fare System). The EIFS system is a

database containing journey information of public transport users through the use of their contactless cards for publictransport fare payment. The information is used to understand the travelling patterns and behaviour of Singaporeans.

2. Is the model updated with real-time information?

The model is not updated in real time. However the model is updated every year.

3. Is the system integrated with other systems that optimise public transport resources such as MRTs and Taxis?

LTA has a regulatory arm that monitors the operating and service quality standards. LTA monitors the public transport

operators performances with respect to these standards to ensure compliance. These standards may be monitored daily

or monthly and reported monthly or quarterly.

Public Transport Modeling:

1. How does LTA predict public transport usages?

Please refer to response to question 1 above.

2. When did Singapore first start modeling public transportation networks and how successful was the system?

Singapore started public transport modelling in the early 90s and has sought for continual improvement in this field. We

are able to use the model to plan for infrastructural improvements required to meet the growing travel demand over the

years. The model is also used to derive information for economic and financial evaluation of new infrastructure to

facilitate decisions making.

3. What sort of information is used in the previous model and the new models?New sources of information are included in the calibration process to enhance the accuracy of the transport model

whenever it is relevant and available. Examples of this information include the EIFS data and ERP data.

4. How accurate have the current models been?

We have target to have an accuracy of about 90% for various stages of the transport modelling process.

We hope the above information is useful for you and we thank you for writing in.

Yours sincerely

DANIEL QUEK GIM SAN

TRANSPORT PLANNER


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APPENDIX D 2019 INTELLIGENT PUBLIC TRANSPORTATION SYSTEM IMPLEMENTATION FRAMEWORK

DYNAMIC PUBLIC TRANSPORTATION SYSTEM PROJECT DEVELOPMENT AND IMPLEMENTATION 2019 FRAMEW

DEVELOPMENT

STAGE

SUB-PHASE PHASE 1 PHASE II

SYSTEMS FOCUSJan

2013

May

2013

Sep

2013

Feb

2014

Jun

2014

Oct

2014

Mar

2015

Jul

2015

Nov

2015

Mar

2016

Aug

2016 2

PLANNING

AND

EVALUATION

OF OVERALL

SYSTEM

Evaluation

Trams / Train

Buses

Cabs / Taxi

Mobility-on-demand

Integration

Framework

Planning

Existing Subsystems

Proposed

Subsystems

Integratability

Policy

Planning and

Revising

Educating Public

Policy Planning

Contract Tendering

INITIAL

INTEGRATION

STAGE

Raw Information

Layer

Prototyping /

Trial

Area-wide

Implementation

Function Layer

Prototyping /

Trial

Area-wide

Implementation

Domain LayerInitial InformationIntegration with

Raw Information

Layer Subsystem

User Layer

Initial Information

Integration with

Function Layer

Subsystems


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SYSTEM-WIDE

INTEGRATION

Overall System-wide Entity Integration

Evaluation of System-wide Entity

SCALING OF

INFORMATION

SYSTEMS

Upgrading Exisiting Infrastructure

Integration with other Transport

Frameworks


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C P D i P bli T i S

REFERENCES

(1) The World Bank: Vehicle Per Km of Road. [Online] Available from:http://data.worldbank.org/indicator/IS.VEH.ROAD.K1/countries?display=default [Accessed 10 Jan 2012].

(2) Intelligent Transportation System. [Online] Available from:http://en.wikipedia.org/wiki/Intelligent_transportation_system [Accessed 12 Jan 2012].

(3) Andrew Butler Nash and Ronald Sylvia. Implementation of Zurich's Transit Priority Program. 2001.

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