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Intelligent Public Transportation Systems: A Review of Architectures and Enabling Technologies


Abstract and Figures

Intelligent Public Transportation Systems (IPTS) are a subsystem of Intelligent Transportation Systems (ITS), which aim to control public transportation networks, to maintain their performance, and to provide users (passengers and decision makers) with up-to-date information about trips and network operating conditions. To reach these aims, IPTS rely on several technologies that can be embedded within different control architectures. This paper introduces IPTS components and technologies, identifies the different types of data captured from the transportation network and exchanged between IPTS components, and shows ways to integrate technological components and data within IPTS architectures. A section is dedicated to review architectural design of some developed IPTS to control public transportation networks. Finally, some challenges are discussed and further research directions are highlighted.
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Intelligent Public Transportation Systems: A Review
of Architectures and Enabling Technologies
Sabeur Elkosantini
LOGIQ Research Unit, University of Sfax
Higher Institute of Computer Science of Mahdia
Saber Darmoul
Industrial Engineering Department
College of Engineering, King SAUD University
Kingdom of Saudi Arabia
Abstract Intelligent Public Transportation Systems (IPTS) are
a subsystem of Intelligent Transportation Systems (ITS), which
aim to control public transportation networks, to maintain their
performance, and to provide users (passengers and decision
makers) with up-to-date information about trips and network
operating conditions. To reach these aims, IPTS rely on several
technologies that can be embedded within different control
architectures. This paper introduces IPTS components and
technologies, identifies the different types of data captured from
the transportation network and exchanged between IPTS
components, and shows ways to integrate technological
components and data within IPTS architectures. A section is
dedicated to review architectural design of some developed IPTS
to control public transportation networks. Finally, some
challenges are discussed and further research directions are
Keywords Intelligent Transportation Systems; public
transportation; technologies; architectures;
I. I
City life and urbanization have introduced mobility
problems and raised issues concerning transportation of both
people and goods. Public transport (also known as public
transportation or public transit) refers to shared passenger
transport service, which is available for use by the general
public. Public transport modes include buses, trolleybuses,
trams and trains, rapid transit (metro/subways/undergrounds
etc.) and ferries. Public transport between cities is dominated
by airlines, coaches, and intercity rail. High-speed rail
networks are being developed in many parts of the world.
Despite the spread and success of implementing public
transport networks, it is becoming more and more difficult to
guarantee high levels of quality of service for users, for
example in terms of punctuality and frequency of shuttles. This
difficulty is due, on the one hand to the continuous
urbanization, which makes transportation networks grow in
size and, on the other hand, to the ever increasing complexity
of managing transportation networks. Implementing new
intelligent decision support and control systems is becoming
necessary both to manage public transportation networks, and
to assist authorities, who are investing in new means,
infrastructures, information and control systems to improve
mobility in cities.
Intelligent Transportation Systems (ITS) have been
introduced to take full advantage of the existing public
transportation infrastructure, and to enhance its efficiency,
effectiveness and attractiveness. ITS are defined as the
application of advanced communication systems, information
processing, control and electronics technologies to improve the
transportation system and to save lives, time and money [1].
ITS for public transportation, also called Intelligent Public
Transportation Systems (IPTS)[2], rely on many innovative
technologies, which fostered their development and
implementation. For example, Geographical Information
Systems (GIS) help in designing new routes and shuttles.
Automatic Vehicle Location Systems (AVLS) rely on Global
Positioning Systems (GPS) to localize transportation means
and vehicles. Traveler Information Systems (TIS) provide users
with real-time information about the state of the network. IPTS
also allow for the integration of Decision Support Systems
(DSS), which suggest regulation strategies and control
decisions to maintain the performance of the network. All of
these information systems and technologies share, process and
exchange several types of data provided by dierent detection
devices, and advanced technologies, such as global positioning
satellites (GPS) and sensor networks.
Although a few works, such as [3] and [2], discussed
technologies used in the field of public transportation network
management, these works are limited to the presentation of
technical aspects and only present technologies to capture data
from the network. These works do not discuss how
technologies and information systems can be integrated within
IPTS architectures, what kind of data and how this data can be
exchanged through the different IPTS subsystems to achieve
the common and ultimate goal of controlling the transportation
network and optimizing its performance.
Therefore, the aim of our paper is to fill this gap by
presenting an updated review of innovative technologies used
in IPTS. We particularly highlight how required data is
captured. We describe how integration between IPTS data and
components is achieved within architectures that are able to
suggest suitable regulation strategies and control decisions to
reach the ultimate goal of controlling the transportation
network and optimizing its performance. Therefore, the
purpose of this paper is not to analyze existing IPTS but rather
to present its different components, architectural layers, and
enabling information and communication technologies. The
paper is organized as follows: Section 2 introduces the
intelligent public transportation systems (IPTS). Section 3
presents different communication and information technologies
integrated in IPTS. Section 4 reviews works suggesting
architectures to integrate these technologies within Intelligent
Public Transportation Systems (IPTS). We conclude by
discussing some challenges and highlighting further research
directions related to IPTS design and implementation issues.
The European Union (EU) Directive 2010/40/EU defines
ITS as systems in which information and communication
technologies are applied in the field of road transport to
manage infrastructure, vehicles, users (passengers and decision
makers), traffic flows and mobility within cities, and to
interface with other modes of transport. According to this
definition, ITS are made of several subsystems including:
Advanced Traffic Management Systems: ATMS act on
traffic signals to control traffic flows and to enhance
mobility in cities.
Advanced Rural Transportation Systems: ARTS focus
on traffic management in rural environments.
Commercial Vehicle Operation Systems: CVOS monitor
commercial vehicles, trucks and vans using satellite
based navigation systems.
Advanced Public Transportation Management Systems
(APTMS), also called Intelligent Public Transportation
Systems (IPTS) [2] or Advanced Pubic Transportation
Systems (APTS) [4]: these systems rely on a set of
advanced communication, information processing,
control and electronics technologies to control public
transportation networks.
In this paper, we only focus on Intelligent Public
Transportation Systems, which we refer to as IPTS. Our
purpose is to present technologies used in IPTS and to discuss
architectural aspects to show how these technologies can be
integrated within a control system.
IPTS are intended to analyze and evaluate the status of
transportation networks, to detect disturbances (such as
accidents, technical problems, traffic congestion, etc.) that can
affect prescheduled timetables and make them deviate from
their expected performance and/or behavior, and to suggest
efficient regulation strategies and control decisions to maintain
the performance of the network. IPTS provide users with up-to-
date information about the status of transportation networks.
The development and implementation of IPTS improves the
quality of service of public transportation networks and
promotes the use of public transportation means in cities, thus
contributing to reduce congestion and pollution and to improve
mobility. Several measures of effectiveness of IPTS were
proposed and detailed in [5]. These measures include indicators
about safety, mobility, efficiency, productivity, energy,
environment, and customer satisfaction. To reach high levels of
Quality of Service, IPTS rely on a wide variety of technologies
and applications that can be grouped in five main categories:
1. Automatic Vehicle Location Systems: AVLS provide
decision makers with real-time information about
vehicles, such as location, speed and direction of
vehicles, and information about delays due to
disturbances, such as traffic congestion, accidents, bad
weather conditions, or road repair work.
2. Traveler Information Systems: TIS provide passengers
with real-time information about the operating
conditions of the network, such as scheduled shuttles and
arrival and departure times of vehicles.
3. Automatic Passenger Counters: APC count on-board
passengers and those waiting for vehicles at stop
4. Geographic Information Systems: GIS allow an instant
mapping and follow up of the progress of vehicles on
their routes. GIS also allow for the design and
implementation of new routes and shuttles.
5. Decision Support Systems: DSS assist decision makers
in controlling the transportation network by suggesting
control decisions and regulation strategies when
unexpected events or deviations from expected
performance and/or behavior occur.
These technologies will be presented in more detail in the
following section.
Several technologies allow IPTS to retrieve data from
multiple sensor systems, to supervise and control the
transportation network. Information and communication
technologies are widely used in IPTS. Vehicles, stations,
operation centers and other transportation infrastructure are
equipped with recent technologies including tracking systems
(such as GPS or radio navigation), infrared beams, wireless
equipment and communication infrastructure (GSM and GPRS
networks). These communication systems enable vehicles,
passengers and decision makers to interact with the different
components of the IPTS as illustrated in figure 1.
These technological devices enable decision makers to
monitor the network performance and to make suitable control
decisions to insure good operating conditions. This section
identifies and presents information and communication
technologies integrated within an IPTS.
GPS satellite
Operation Center
DSS :decision Support System, AVL : Automatic Vehicle Location,
TIS : Traveler Information System, VMS : Variable Message Sign,
APC: Automatic Passenger Counter, GIS : Geographic Information
System, CCTV: Closed Circuit TeleVision
Figure 1. Intelligent Transportation system
A. Automatic Vehicle Location Systems
Automatic Vehicle Location Systems (AVLS) provide
information regarding the exploitation of a transportation
network. In the scientific literature, such systems are often
referred to under several names, such as Automatic Vehicle
Monitoring Systems AVMS [6], Automatic Vehicle Location
AVL [7], Exploitation Aid System EAS [8-9] or Exploitation
Support System ESS [10]. In this paper, we refer to these
systems as AVLS.
Such systems give a global overview of a transportation
network and provide real time information through the use of
several vehicle location and tracking technologies. Data
provided by AVLS includes updated states of timetable
execution, delays, and vehicles in advance. The
implementation of AVLS has greatly facilitated the task of
decision makers because AVLS can monitor real-time
operation of a public transportation network and process a very
large amount of network information.
One of the first forms of vehicle tracking technologies
being used was the ground based radio system (GBR). It
determines location based on the reception of signals and the
associated timings from various transceivers. As reported in
[11], the accuracy of this system is not consistent especially in
urban areas as they are highly susceptible to radio frequency
and electromagnetic interference from power lines and
substations in urban and industrial areas.
Signpost and Odometer were also among the primary
technologies used for vehicle tracking. With this technology,
receivers are placed on vehicles, while transmitters are placed
along vehicle routes. Vehicles transmit a low-powered signal
as they pass by these transmitters, and the mileage is noted.
AVLS based on this technology have some drawbacks. For
example, Signpost transmitters require periodic maintenance
(to replace battery for example). Furthermore, the creation of
new routes requires the placement of new transmitters.
Due to limitations of GBR and Signpost/Odometer
technologies and with the development of applications in
electronics and digital communications, Global Positioning
Systems (GPS) became the most popular systems for vehicle
tracking [12]. GPSs are space-based satellite navigation
systems that provide location and time information in all
weather, anywhere on Earth. This system was developed by US
department of defense to serve the military need to locate
vehicles. The system uses a total of 24 satellites [19]. In
transportation systems, vehicles are equipped with a GPS
antenna, which communicates with four or more satellites to
give the location of the vehicle.
Galileo is another global navigation satellite system
developed by the European Union to provide high-precision
positioning independently from the American GPS. Some
European IPTS use this navigation system such as CIVITAS
[14]. Satellite based navigation systems give a good precision
only with the presence of line of sight between the receiver and
satellites. Otherwise, the signal will be attenuated and, thus,
vehicles cannot be tracked. Due to this limitation, RFID
technology is also used as vehicle tracking systems [15].
Other technologies are integrated in IPTS to locate vehicles
in the network. For example, Closed Circuit TeleVision
(CCTV) are coupled with image processing techniques to
monitor vehicles in the public transportation network of
London by the use of 2000 cameras installed in the routes and
stations [16].
B. Traveler Information Systems
ITS for public transport integrate technologies to provide
information to travelers or to operation centers. A “Traveler” is
defined as a person who changes location by any transportation
mode. Some authors also consider vehicle drivers as travelers
[17], while others only consider passengers as travelers [2].
The main goal of Traveler Information Systems (TIS), also
referred to as Real-time Passenger Information System RTPIS
[18], is to provide real time information to travelers about the
state and operating conditions of the network, such as vehicles
arrival time, and assist them to allow informed pre-trip and en
route decision making.
According to Adler and Blue [19], two generations of TIS
exist. The first one is the Variable Message Signs (VMS) that
provides information about vehicles. VMS are used in stations
to provide travelers with important information about the
network, such as vehicle waiting time or presence of incidents.
Data are sent to VMS via communication infrastructure, such
as GSM [53] or wireless network [20].
The second generation is the Advanced Traveler
Information System (ATIS), which uses recent technologies,
such as internet or mobile phones, to provide information about
traffic conditions, route guidance and en route traveler
information in a more real time manner.
Several TIS were developed to assist travelers in making
pre-trip and en route travel decisions, such as Intelligent
Traveler Information Systems ITIS by Adler and Blue [19],
Path2Go by Zhang et al. [21], and work by Praveen et al. [22].
RAPID is another commercial TIS developed by Sigtec
company using SMS, web and street displays. RAPID solution
incorporates an AVLS system to send up-to-date information
about vehicle arrival times to passengers.
To provide more efficient data on vehicle travel or arrival
time estimates to passengers, TIS are based on AVLS [23. For
example, SITREPA [24] is an IPTS which integrates an AVLS
and TIS and tested in the city of Leiria (Portugal). As other
IPTS, SITREPA acquires data from AVLS and provides
information to satisfy the needs of different actors in the
public-transportation system as passengers or decision makers.
C. Automatic Passenger Counters
Automatic Passenger Counters (APC) are systems that
count on-board passengers and those waiting for vehicles at
stop stations. Such information can be used to analyze the
global performance of the transportation system [25]. It can be
used to calculate average vehicle travel speeds and dwell times
[26]. APC can interface with AVLS to provide transit agencies
with transit origin-destination data [26].
The first generation of APC was based on manual ride
checks to collect the necessary data on boarding and alighting
activities. Recently, communication technologies are widely
used to develop more efficient APC. Such technologies include
treadle mats and infrared beams, which recognize passengers
when the beam is broken. Computer imaging is also used,
which is based on intelligent image detection systems to
recognize and count on board passengers [16]. [27] evaluated
the performance, in terms of accuracy and precision, of on-
board camera and other APC systems. They reported that
camera systems are more precise than on-board ride checkers.
D. Geographic Information Systems
Geographic Information Systems (GISs) capture, store,
manipulate, analyze, manage, and present all types of
geographical data related for example to vehicle route design
[27]. The first task of a GIS is to code data collected by
tracking systems, such as GPS or Galileo systems (see
subsection A). Thus, the connection of GIS to GPS allows
instant mapping and follow up of the progress of vehicles on
their routes, and localization of disturbances on the
transportation network [29]. In many ITS, GIS is also used for
analyzing the traffic flow [30], for evaluating and ranking
vehicle service [31] and for transportation network design [32].
In the last few decades, researches focused on automating the
route-planning process using GIS technology [33]. Some
commercial GIS software, such as ArcGIS [34] or MapInfo
[35], exist and can be used to develop digital maps and to
realize basic GIS functions.
E. Decision Support Systems
Decision support systems (DSS), also called Scheduling
and Dispatching Software [36], have two main objectives:
timetable establishment and control strategies building.
The first common objective of DSS is the establishment of
efficient transportation timetables that satisfy passengers, who
expect high levels of quality of service, in terms of timely and
regular shuttles. Transportation timetables are initially
established taking into account information about forecasts of
traffic conditions, rush hours, demand for transportation, etc.
[6]. Several works use either exact [37] or heuristic [38]
methods to determine timetables that optimize one or several
objectives, such as minimizing total trip time or cost [39],
minimizing passenger waiting time, or minimizing passenger
in-vehicle time [38].
However, during the execution of pre-established
timetables, disturbances may appear that can make these
timetables deviate from their expected course, causing them
either to be delayed or to become obsolete [40]. When they
occur, such disturbances like accidents, traffic congestion,
absence of personnel, bad weather conditions, etc., degrade the
expected performance of the transportation network, decrease
its expected quality of service, yield to passenger
dissatisfaction, and may cause the appearance of congestion at
stations or on transportation pathways. Consequently, decision
makers have to monitor the execution of pre-established
timetables, and to make reaction decisions in order to bridge
the gap between pre-established timetables and really executed
The second objective of DSS is to maintain the
performance of pre-established timetables at acceptable levels.
DSS have to analyze incoming data from Automatic Vehicle
Location systems (AVLS) and Automatic Passenger Counters
(APC) in order to detect serious delays of vehicles. When such
is the case, DSS have to suggest suitable control decisions and
regulation strategies to eliminate or at least reduce deviation
from predefined timetables. Several works suggested control
decisions; including holding strategies [37-49] and stop
skipping strategies [39]. DSS can receive information from
special equipment, such as panic buttons. In some cities like
Washington DC in USA [41] or La Rochelle in France [42],
stations are equipped with panic buttons that can be activated
by passengers, operators or drivers to alert passengers and
operation centers to take immediate action.
According to [43], DSS must integrate three main phases:
Diagnostics phase: it consists in monitoring and
analyzing the transportation network to detect
disturbances, anomalies and deviations from expected
performance and/or behavior using AVLS.
Decision construction phase: the system suggests
control decisions and regulation strategies for the
detected disturbances, anomalies and deviations.
Decision evaluation phase: control decisions and
regulation strategies are evaluated using simulation
[44] or exact methods [45] to select the best alternative
to be applied.
Several studies were proposed to design DSS to control
public transportation networks, such as TRSS [6], MASDAT
[46], SMAST [47], and systems by Masmoudi et al. [9],
and [48], and [49]. Such systems receive information from
AVLS, TIS and APC via radio or other communication
technologies, such as cellular phones or modems.
Several studies were proposed to design IPTS architectures.
Davidsson et al. [50] pointed out that, at least until year 2005,
64% of the existing research focused mainly on design issues
and architectural aspects. These architectures integrate a
variety of information systems that receive data from sensors.
As illustrated in figure 2, these data concern vehicles (vehicle
location, routes, direction, next station, and accidents),
passengers (waiting or on-board passengers) or other incidents
(technical problems). These data are sent to IPTS subsystems
such as DSS or TIS using communication networks as GSM,
Modem or Wireless networks. The DSS analyzes received data
to monitor the execution of pre-established timetables and
make reaction decisions in order to bridge the gap between pre-
established timetables and really executed ones.
Most of developed IPTS implement Interactive Decision
Support systems, considered as the core of an IPTS, integrating
the decision maker in the decision loop (figure 2). With respect
to the integration of decision makers in the loop, [51] identify
two types of cooperation between decision makers and decision
support systems: horizontal and vertical. In the horizontal
cooperation, decision makers and DSS dynamically share the
tasks to be per-formed. In such architecture, traffic data
provided by AVLS and APC are only analyzed by the DSS that
generates the best decision. This kind of cooperation is used in
autonomous systems in which the only task of decision makers
consists in supervising the decision making process. However,
in a vertical cooperation, DSS can be considered as a guide to
the support decisions. In such cooperation, decision makers
assist the system. Decision makers can interact with the system
in each step of the information processing or the decision
making procedure.
Several public transportation agencies over the world have
implemented intelligent transportation systems to insure a high
quality of service to passengers.
For example, [52] reported that more than 122 agencies
have implemented an IPTS in USA. They reported also that
Geographic Information Systems (GIS) and Decision Support
Systems (DSS) were the most widely used technologies.
Another example, CIVITAS [42] is an IPTS funded by the
European Commission and implemented in 60 European cities,
including La Rochelle, London or Frankfort. Within CIVITAS,
different components of Public Transport Information systems
were implemented:
TIS via boards and terminals, on and off the public
transport system, via SMS and/or e-mail
Internet services providing public transport
Over ground network map and mini map available
on board public transport vehicles and other
campaigns and information material to promote
public transport
Real-time traffic and parking information for
drivers via Variable Message Signs
Intelligent Public Transportation System
Traveler Information
Automatic Vehicle Location
Information Systems
Decision Support System
passengers number
Vehicles position, Direction
Routes, Next station
Served station
Timetable updates
Decision maker
strategy Modification
Figure 2. Information systems for IPTS
[6] developed an IPTS, named TRSS, designed according
to a vertical architecture. The system integrates an AVLS
(using GPS system), which provides vehicle tracking
information to a multi agent decision support system.
SITREPA [24] is another IPTS tested in the city of Leiria
(Portugal). The system combines GPS and RFID technologies
to locate vehicles on the network. It integrates a TIS to provide
real time information about the network.
V. C
The main objective of this paper is to identify technologies
on which intelligent public transportation systems (IPTS) rely
to control transportation networks. We identified several
technologies, such as Traveler Information Systems,
Geographic Information Systems, Automatic Vehicle Location
Systems and Decision Support Systems, which are all based on
advanced information and communication technologies. These
systems exchange different types of data, such as vehicle
location, messages, alerts and videos. With respect to existing
works, such as [2] and [3], our survey focused on highlighting
architectural integration of data and technologies rather than
presenting technical aspects of information and communication
Our literature survey shows that several directions must be
explored to improve the integration of all advanced information
systems. Due to the number of subsystems, the diversity and
the quantity of exchanged data, IPTS must insure a high
interoperability level in existing architectures. Therefore, new
subsystems must be developed and integrated in architectures,
which have to automatically analyze all type of data and detect
events that will affect the performance of the network. Thus,
they must be as generic as possible to detect any type of
disturbing event. To the best of our knowledge, this direction is
not well explored and no generic tools were proposed.
Furthermore, such subsystems must be compatible with actual
IPTS and support existing technologies without changing
developed architectures.
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... The governing technology sector which deals with the public transportation in pursuit of becoming smart and sustainable is known as the Intelligent Public Transportation System (IPTS) [19]. In this study, all five categories of solutions under IPTS were embodied particularly the Traveler Information System (TIS). ...
... Computer vision technologies [24] further improved the performance of data collection for a more accurate information. Instead of using sensors, cameras were used to obtain information such as passenger count inside the terminals and onboard the PUVs [19]. From simple information system, TIS studies started to evolve into forecasting [14], prediction, and recommendation [25,26] with the enablement of computational intelligence and introduction of big data [27]. ...
... The equations for computing the utility and probability are shown in Eqs. (19) and (20). ...
Full-text available
Route recommendation continues to manifest noteworthy contributions to the intelligent transportation system field of research as it evolves through time. Early related studies helped passengers and tourists experience a more convenient travel. At the same time, these helped transport planners analyze people’s trip preferences and its correlation with the region-specific economic status in a more time-relevant data. Majority, however, require historical data and heavy data collection methods. For user quantified metrics such as route cost in terms of travel time and distance, the complexity and sparsity of preferences between travelers are persistent challenges. The strategic transit route recommendation proposed in this study takes into account multiple trip features (both quantitative and qualitative) desirability using logit model and the optimal travel time with respect to a given road traffic condition, headway, and passenger demand. The chosen area of study is the Western Visayas region of the Philippines specific to the public utility bus (PUB) and jeepney (PUJ) transit routes. The results of the research exhibited the feasibility of an optimal and strategic recommendation of public transportation route for passengers considering present time relevant trip conditions rather than relying on the historical data which are difficult to obtain, or worse, non-existent.
... This means that there is really a need to address the long time existing problems in the public transportation system of the country. IPTS motivation of transitioning public transport systems is to improve its services to passengers [17] and to aid the need of the decision makers for real-time and comprehensive information [18]. Enabling technologies [13] to support this movement include Advanced Public Transportation Management Systems (APTMS) [19], Advanced Traffic Management Systems (ATMS) [20], Automatic Vehicle Location Systems (AVLS) [1], and V2X Communication [21] [22]. ...
... The authors of the work (Elkosantini & Darmoul, 2013) conducted a study of the types of technologies that can be used to control public transport systems. The authors singled out such technologies as Traveler Information Systems, Geographic Information System, Automatic Vehicle Location System and Decision Support Systems. ...
This article is devoted to automation of search of routes of passenger flows of inhabitants of the city on the basis of routes of public transport. To do this, it is proposed to use satellite data that reflect the movement of passengers. Based on the analysis of data arrays of information on the movement of cellular subscribers and the use of message messages to determine the effectiveness of passenger routes of public transport, the article proposes to create a system of automatic search of public transport routes, which includes different classes of charts and data bases. You can use data from cellular operators to do this. This can increase the accuracy of certain traffic volumes and the ability to monitor them in real time. Reliable information on the routes of urban public transport allows to determine passenger flows and efficiently perform transport services. The main requirements for modeling the city’s passenger traffic are presented. Methods of obtaining data on determining the city’s passenger traffic and public transport are considered. Documentation for the creation of the ISASR (Intelligent System for Automation Search of Routes) project has been developed. The MVC (Model-View-Controller) architectural template was used to develop the project. Class diagrams and precedent diagrams have been developed for the model. Database structures have been created and vehicle types and user types have been defined. Algorithms for finding routes for different situations, with different latitude and longitude coordinates, as well as different number of stops and transfers have been developed.
... The goal of ITMSs is to use algorithmic machine learning to anticipate the best routes based on factors like vehicle classification, accident frequency, and traffic mobilisation patterns [11]. IPTSs are designed to manage public transportation networks, keep them working efficiently, and give consumers the most recent information on travels and network operating problems [12]. ISMSs guarantee the security of people, things, and vehicles on the road [10]. ...
Artificial intelligence (AI) is developing at a rapid rate, opening up previously unimaginable prospects to improve the performance of various industries and enterprises, including the transportation sector. AI is being used in the transportation sector to address issues such as rising travel demand, CO2 emissions, safety problems, and environmental damage. . In this digital age, it is more feasible to handle these challenges in a more effective and efficient manner due to the abundance of quantitative and qualitative data. A thorough understanding of the interactions between AI and data on the one hand, and the characteristics and factors of the transportation system on the other, is necessary for the successful use of AI. This article is a compendium of many problems affecting the transportation sector that are categorised as Intelligent Transportation Systems problems. Some of the sub-systems from Intelligent Transportation Systems that are taken into consideration are related to Traffic Management, Public Transport, Safety Management, and Manufacturing & Logistics. Finally, the overview discusses the limitations of AI applications in transportation. Keywords- Artificial Intelligence, Machine Learning, Intelligent transportation systems, Transport management systems, Traffic management, Public transport, Safety management, Manufacturing & Logistics
Conference Paper
The exploitation and management of a public transportation system (PTS) is usually considered as a complex task, which is even more challenging when various types of disturbances are considered. Although many approaches were suggested to control disturbances, only a few of them addressed the modeling and analysis of their propagation, and the evaluation of their potential impacts on the PTS entities, performance, and behavior. Without such analysis, decision making would be misled and its effectiveness/efficiency hindered. Thus, this paper presents an integrated and multi-dimensional framework firstly for disturbance propagation. The framework includes a disturbance evaluation model that takes into account bus related data and resilience index and a multi-step bus features and residual error prediction models.
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Mobility and access are the two essential criteria for evaluating any mode of transportation. A private vehicle comes at the top when we think about mobility and access. But an increase in the utilization of private vehicles has many drawbacks, such as an increase in traffic congestion, air pollution, fuel consumption, etc., which also affect public health. It is essential to provide an efficient public transportation system to minimize these effects, especially in urban areas. Bus transportation is one of the significant modes of transport with a good capacity compared to private vehicles, but there is a need to compromise for access. Bus transportation is an essential mode of transportation for students, faculty, and staff, especially to travel to, around, and from school and work. It is always necessary that buses reach the stop on time and service all the passengers waiting at the stop, considering peak hour demands and potential uncertainties in transportation time. To achieve such an objective, it is essential to improve the serviceability of the bus transportation network. This study focuses on improving the operations of the Florida State University (FSU) campus bus service, Seminole Express, for the “INNOVATION” bus route in Tallahassee, Florida (USA). The “INNOVATION” bus route service connects the main FSU campus with the FAMU-FSU College of Engineering and is heavily used by the FSU students. A simulation model is built using the FlexSim simulation software to emulate the operations of the “INNOVATION” bus route service to determine the required number of buses to be deployed. An excessive number of buses may increase the operational costs and idling time. In the meantime, an insufficient number of buses will cause significant waiting times at the bus stop, which are not desirable as some students may be late for their classes. The developed simulation model will assist with effectively planning the bus route connecting the main FSU campus with the FAMU-FSU College of Engineering by providing solutions with adequate waiting time and operational costs
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This paper describes a vehicle routing and scheduling system that combi-nes Geographical Information Systems (GIS) with stochastic programming models that incorporate travel time variability information. GIS provide a framework for integrating traffic networks and performance data allowing a realistic representation of the traffic network to be considered. Stochastic programming allows the variable nature of vehicle travel times to be incor-porated within routing and scheduling procedures. New automated data col-lection technology allows information on the variability of travel times in urban areas to be obtained easily. The integrated approach presented in this paper has the potential to substantially reduce the costs of distributing goods in urban areas.
Conference Paper
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In our days, it become difficult to offer high quality services, in term of punctuality, frequency and productivity with complex and unpredictable disturbances that affect public transportation schedules. The development of a regulation support system to help human operators becomes a necessity. In this paper a real time regulation support system for public transport regulation based on human immune theory is presented. Artificial immune system presents many interesting capabilities of identification, learning, memory and distributed parallel processing. This approach has a good performance in terms of convergence and quality of solutions which are proven and shown through tests and results.
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The public-transportation sector is in constant development, yet the operating companies need to improve the quality of service they provide to passengers. In order to achieve this goal, they have to increase passenger security, comfort, information access, the destinations offered and extended service schedules. These improvements are very expensive to any public-transportation operator; the companies’ sustainability will be compromised. This paper describes an Intelligent Transportation System (ITS) that allows public-transportation companies to implement Real-Time Information to Passenger System (RTPI), that also provides monitoring and management tools to optimize service management and administration. The SITREPA System includes a hardware and software combined system that acquires data from vehicles and provides information to the needs of different actors in the public-transportation environment. We have designed a system that with low complexity and with an affordable cost, adequate for most small and medium passenger operator enterprises. The result of the implemented prototype in test scenarios showed that this system can be an important tool to passengers and can improve public-transportation management services.
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In order to improve travel times for public surface transport vehicles (buses, trams, etc...), urban traffic control systems are used to give priority to public transport vehicles. The main target of these strategies is to reduce the delay when crossing an intersection, for all private and public transport vehicles. However, they do not take into account buses regularity. Our objectives in this research are to regulate urban traffic but also to ensure the regularity of buses. To do, we develop a multi-agent bimodal urban traffic control strategy. This multi-agent strategy acts on traffic lights to regulate traffic, promote passage of buses, while monitoring the intervals between buses driven on a given bus route. We present a model adapted to a real traffic situation and propose new alternatives to better regulate the bimodal urban traffic between public transport (buses) and private cars.
To ensure better regulation, the emergence of Support Systems Operations (SSO) had helped the regulators. SSO allow real-time monitoring of operating a urban transport network. We consider the problem of matching supply with actual operating conditions. To do this, we propose a system for decision support that provides traffic monitoring, incident detection, diagnosis and control. This system uses two concepts of artificial intelligence: The multi-agent systems and the anytime approach. We present a model of multi-agent decision support in real time. We rely on a new approach based on progressive reasoning, to take into account real-time in a MAS: the proposed model is called SMAST (Multi-Agent System for Modeling Transport Systems). It provides users a rich environment for modeling tools and techniques according to the Geographic Information Systems GIS. Algiers city was taken as a study case. It is a very complex case for intermodal synchronization, because it includes various modes of transport. (Bus, urban train, metro, tram).
Dynamic vehicle dispatching at the transfer station can improve the transit service quality by optimizing the transfer coordination of routes. In this paper, a dynamic vehicle dispatching model is proposed that aims to minimize the total waiting time of passengers at the transfer station and the downstream stops. A prediction model based on support vector machines (SVM) is also developed to forecast the arrival time of the next vehicles at the transfer station. To reduce the disconnected cases between the transfer routes, an SVM-based model is introduced to forecast the elastic time for the estimated arrival time at the transfer station. According to the estimated arrival time and elastic time, vehicles are dispatched in a dynamic way to reduce the total waiting time of passengers. The dynamic vehicle dispatching approach at the transfer station is examined with the data of three transfer routes in the city of Dalian, China. Results show that the approach proposed in this paper can reduce the total waiting time of passengers at the transfer station and the downstream stops. DOI: 10.1061/(ASCE)TE.19435436.0000311. (C) 2012 American Society of Civil Engineers.
Conference Paper
Intelligent public transportation system is an effective way to improve the quality of our country transportation. Wireless sensor network is a novel technology made by the convergence of sensor technology, micro electro mechanism technology, wireless telecommunication technology and network technology. It is suitable to transportation scenarios for the characteristic of rapidly deployed and self organized. An improved solution combined the wireless sensor network and internet technology is presented in the article. It effectively solves three critical problems of the wireless sensor network, including energy saving, localization and communication distance. By using the low cost and high stability microchip, a high reliability and low cost intelligent public transportation system based on wireless sensor network can be easily established.
Conference Paper
Mobile platforms are now becoming a more and more important medium for providing information to travelers on the move. To improve the accuracy and relevance of the mobile traveler information, context awareness has become a active research topic. In this paper, we describe algorithms and services provided by Path2Go, a multimodal traveler information system developed by California PATH, UC Berkeley. The Path2Go activity detection algorithm, the core of the context-aware design, has made the following contributions: (1) it uses a rule-based multi-hypothesis Bayesian method for mode detection, to address the limitations of using mobile phone GPS for activity detection and increase the speed of convergence; (2) it fuses GPS data from transit vehicles and the GPS of the user's mobile phone for better activity detection; and (3) it enables several experimental services, including variable-frequency client-server communication and need-based GPS use. Field testing of the Path2Go activity detection algorithms showed reasonably good results. The Path2Go application has also been made available to the public through iPhone, Android and Windows Mobile platforms, with some of the features discussed in this paper included.
This paper introduces a system design about bus management system based on ZigBee and GSM/GPRS, which implemented the basic functions of the intelligent public transport management system, such as monitoring the time of bus arrival, departing from the bus station and reporting stations name automatically. This system can ensure punctuality of vehicles to run, improve the automation level of reporting stations and quality of public transport service. The management system has low cost and thus it is more feasible.
A new transit operating strategy is presented in which service vehicles operate in pairs with the lead vehicle providing an all-stop local service and the following vehicle being allowed to skip some stops as an express service. The underlying scheduling problem is formulated as a nonlinear integer programming problem with the objective of minimizing the total costs for both operators and passengers. A sensitivity analysis using a real-life example is performed to identify the conditions under which the proposed operating strategy is most advantageous.