Advanced Public Transportation Systems Research Articles

Policies and legislation enabling sustainable technologies in the public transport infrastructure in NEOM

AbstractIn the context of rapidly urbanizing cities, integrating sustainable technologies into public transportation systems is important. This study examines the policies and legislative frameworks of NEOM and articulates their impact on the adoption and expansion of sustainable technologies within the public transport domain. The objective is to determine whether these regulatory mechanisms facilitate or impede NEOM's sustainability ambitions. The main finding is that NEOM's current legislative and policy framework presents notable challenges. The commitment to advancing sustainable technologies is clear, tension exists between the rigidity of traditional legislative approaches and the rapidly evolving nature of technological innovation. Our analysis suggests NEOM has considerable potential to reform its policies and measures. Recalibration would ensure compatibility with sustainable practices and drive the city's vision for a sustainable and technologically advanced public transportation system. The study recommendations highlight the need for flexible, innovation‐centric legal frameworks. A more adaptable legislative approach could inform NEOM to leverage sustainable technologies more effectively, ensuring an environmentally responsible public transportation system that serves its expanding user community. Furthermore, this research offers broader implications for other emerging smart cities, underscoring the essential relationship between policy, technology, and sustainability in shaping future‐ready urban transport systems.

Extended review of multi-agent solutions to Advanced Public Transportation Systems challenges

AbstractOver the past few decades, intelligent transportation systems (ITS) have emerged as an effective way to improve the performance of transportation systems. ITS provide innovative services, enhance travel safety, provide travellers with more choices, and make transportation systems more efficient. Multi-agent systems (MAS), which define autonomous interacting entities, are suitable for modelling distributed and intelligent systems in general and ITS in particular. This paper provides an in-depth review of multi-agent systems applied to Advanced Public Transportation Systems (APTS), a subclass of ITS dedicated to managing public transportation networks. We carefully analysed 38 papers in this study, published in 19 journals during 31 years (1990–2020). We perform a synthetic analysis of the trends in this domain and a qualitative analysis focused on multi-agent systems’ dimensions and properties. We show that the MAS approach is well suited to the real-time management of disturbances thanks to their delegation process, and their pro-activeness and autonomy properties.

Performance Improvement of Packet Delay in Advanced Public Transportation System Using Multi Path UDP on Cellular Environment

Performance Improvement of Packet Delay in Advanced Public Transportation System Using Multi Path UDP on Cellular Environment

A Taxonomy for Advanced Public Transportation Systems

This study explores the development and availability of APTS (Advanced Public Transportation Systems) technologies. APTS technologies can revitalize transit by directly improving service, increasing transit efficiency and reducing operating costs, as well as by producing direct benefits for travelers such as reduced travel times, increased safety and security, and reduced stress in dealing with transit unreliability. To understand APTS impacts, this study develops a taxonomy of transit technologies and uses it to explore the availability of new technologies and their impacts. The taxonomy is based on defining the features, functions, and performance characteristics of transit technologies. Further, the implementation of new technologies can be described by their spatial, temporal, and user dimensions, i.e., where, when, and for whom is the technology implemented. These dimensions, along with the implementation context, determine the impacts of APTS technologies. To explore the availability of APTS technologies, technology suppliers were surveyed. They were asked about the features, functions, and performance of transit technologies, their testing and deployment in transit agencies, and their potential impacts on travelers and transit operators. The survey results suggest a trend toward transfer of data in real-time through electronic media and increased automation. It was found that about a dozen APTS technologies queried in the survey were commercially available for field testing. From a policy perspective, there is a need to develop a strategy that considers the individual and joint testing of two or more APTS technologies and facilitates synthesis of the resulting information. Individually, the benefits of APTS technologies may be limited, but, collectively, APTS technologies may have significant benefits. Cases of joint APTS technology implementations need to be designed, implemented and synthesized.

Stakeholder Preferences in Advanced Public Transportation System Planning

Transportation planning in general and planning for intelligent transportation systems (ITS) in particular are notable both for multiple goals and for multiple constituencies. In response to complex policy environments such as this, multicriteria decision analysis often was utilized to assist in the evaluation of alternative investments or policy directions. This approach is extended here to assess stakeholder valuation of broad goals of an ITS planning process, the Suburban Mobility Authority for Regional Transportation (SMART) operational field test in the metropolitan Detroit area Two levels of goals were considered: broad system-wide goals (e.g, energy savings, interagency coordination, congestion reduction) and specific service characteristics, such as advance reservations, scheduling, and reliability. Using a modified Analytical Hierarchy Process, implicit preference weights for transportation planning goals were derived, and inter- and intra-group comparisons were made. Overall, there was less variation between groups in preferences than might be expected, indicating a fair degree of common ground in desired outcomes of transit planning. The ability to provide for the trips that people request, referring both to the accommodation of trips and the match between requested and scheduled times, were important goals across various stakeholder groups. Similarly, the provision of reliable service was generally valued highly. Information provision appears to be a lower priority. Thus, to the extent that automatic scheduling and dispatch assists improved scheduling trip reservation, and routing it is likely to meet stakeholders ‘preferences.The study characterizes the various groups ‘preferences for transit service along a continuum ranging from “expansive “ to “incremental.” The expansive vision seeks to develop new forms of service for transit and paratransit customers better, while under the incremental view, consolidation of and improvements to existing service are a higher priority. The expansive position appears most clearly among citizens ‘groups, social service agencies, and business people. The business community is particularly interested in expansion of the hours of service, presumably to facilitate travel by customers or employees during evenings and weekends. The more incremental view is held by transportation professionals and SMART employees who are aware of the constraints under which they work.

Design and Development of a Bus Stop Inventory to Support an Intelligent Transportation System: The MARTA Experience

Bus stops are a critical element in any transit system. The advent of Intelligent Transportation System (ITS) technologies in the area of transit has developed a need for transit agencies to keep an up-to-date inventory of bus stop data. Unfortunately, most transit agencies do not have a bus stop inventory that can adequately support Advanced Public Transportation System (APTS) applications, and many other transit agencies do not have an inventory at all. The design, development, and maintenance of a bus stop inventory that will support an array of available APTS applications is described in this paper. Procedures used in the development of the Metropolitan Atlanta Rapid Transit Authority bus stop inventory are highlighted. The lessons learned from MARTA’s experience should be valuable to other transit agencies that are planning to or are in the process of implementing an APTS.

Evaluation of Garden State Parkway Alternate Bus Routing Field Operational Test

This study evaluates the effectiveness of the New Jersey Garden State Parkway (GSP) Alternate Bus Routing (ABR) system, an Advanced Public Transportation System (APTS). The GSP ABR Field Operational Test (FOT), which was conducted on a small portion of the parkway, was mainly concerned with real-time routing of New Jersey Transit (NJT) buses traveling the GSP to a parallel alternate route to avoid congestion on the parkway.One of the most important features of this FOT is the use of NJT buses as probe vehicles that provide real-time travel-time information to the bus routing algorithm. The use of probe vehicles for network surveillance increases the attractiveness of similar systems that can be deployed over larger networks where infrastructure-based surveillance can be prohibitively expensive. The functional evaluation of GSP ABR includes the collection and analysis of data from various sources including traffic sensors, probe vehicles, and surveys conducted among transit bus operators and system users.During the official testing period in 1997, the GSP ABR system produced accurate diversion messages, which proved the reliability of the system. However, the relatively short length of the alternate route, U.S. Route 9, and similar traffic patterns observed on both routes did not give the evaluation team the opportunity to observe scenarios where statistically significant travel-time improvements exist. This result prevented the evaluation team from reaching conclusive recommendations in terms of the effectiveness of this FOT. However, the survey results show that both transit bus operators and ABR system operators believe the system can be very beneficial if implemented in a different network.From a policy point of view, the general conclusions of the functional tests presented along with a list of lessons learned can be used in the effective design of future FOTs in the area of APTS.

Issues on the Application of an Advanced Public Transit System to Dial-a-Ride Service

The Federal Transit Administration‘s Advanced Public Transportation System (APTS) program consists of demonstration projects that illustrate the use of new technologies in public transit. In view of the fact that similar systems are beginning to use new technology to locate and dispatch vehicles, this article reports on a study that examined issues that must be considered in implementing new systems. Specifically, the study focused on initial parameters for the computer program, defining and accessing these parameters in relation to quality of service, and measuring rider responses to guarantee performance.The implications of these issues for service quality were examined for the APTS demonstration project in Winston-Salem, North Carolina. The study analyzed consumer response to the Mobility Manager, a Geographic Information System (GIS) applied to the site’s demand-responsive minibus service for the elderly and people with disabilities. Survey data from two questionnaires issued before and after the implementation of the Mobility Manager were utilized to examine travel behavior and perceived service quality. In addition, data from driver manifests issued after implementation of the Mobility Manager are used to clarify results.

Artificial Neural Network Travel Time Prediction Model for Buses Using Only GPS Data

Real-time and accurate travel time information of transit vehicles is valuable as it allows passengers to plan their trips to minimize waiting times. The objective of this research was to develop a dynamic artificial neural network (ANN) model that can provide accurate prediction of bus travel times to give real-time information at a given downstream bus stop using only global positioning system (GPS) data. The ANN model is trained off-line but can be used to provide real-time travel time information. To achieve this, care was taken in selecting a unique set of input-output combinations for prediction. The results obtained from the case study are promising to implement an Advanced Public Transportation System (APTS). The performance of the proposed ANN model was compared with a historical average model under two criteria: prediction accuracy and robustness. It was shown that the ANN outperformed the average approach in both aspects.

Fuzzy Comprehensive Evaluation of APTS Dispatcher Working Level Based on Cloud Model

Many cities in China have built an advanced public transportation system (APTS) in recent years. These systems cannot carry out automated dispatches but rely on the dispatcher to ensure normal operations. Based on the theory of fuzzy comprehensive evaluation, this study created a hierarchical evaluation model to evaluate the work level of the dispatcher. Firstly, a hierarchical evaluation system was established based on the data of line complexity and dispatch workload provided by the APTS. Secondly, we assigned the weight of the evaluating indicator by combing an expert scoring method and the entropy weight method. We then transformed the quantitative data into qualitative evaluation data with a cloud model. Through a comparison with the standard cloud, the work level of an APTS dispatcher can be defined. The evaluation results for 12 cities in China showed that there was no obvious connection between the working level and bus company size, but the work level was always higher in large cities. We finally obtained the standard range of the evaluation indicator through cluster analysis. This method can be used as a reference to evaluate the work level of dispatchers in other cities, and can reflect the correlation between the work level and dispatching system construction, population and city size.

Suggestive Measure Travel time and Congestion under Heterogeneous Traffic Conditions

Movement in non-rural areas effects well-being as well as traffic of that area. Greater the congested activity, worse will be the traffic impacts. These traffic impacts can be minimized by movement diminishment, or by moving more passengers from personal to alternate methods of transport with less negative effects for which a comprehensive traffic study needs to be done. In the present study, Phagwara, area of Jalandhar has been taken for such analysis. These studies can be used to control traffic jams on roads due to increment in vehicles. The study can also be used for saving time at intersections. Travel time data is an important parameter of many Intelligent Transportation Systems/Frameworks (ITS) applications. Quantity of vehicles in India has been increasing enormously resulting in blockage and pollution of urban areas during peak periods. If we can control congestion to a certain limit, things like pollution will also get minimized and there will be less accident rate due to less delay to the road users. This all is possible only when we are able to shift more passengers from their personal vehicles to public transport/ vehicles by providing them better comfort and good services. We can also provide latest technologies to the public vehicles so that the passenger gets attracted to these facilities. For achieving the goal, Advanced Public Transportation System/ Frameworks (APTS) plays a great role. ITS applications should be added to the movement circumstances in India so as to reduce the effects caused by traffic congestion. India is a developing country and has low economy rate so this is not possible for any developing country to implement in each and every city. Our main aim is to find out the traveller/ Passenger Car Unit (PCU) for many types of vehicles in non-homogeneous situations. The study shows that the traffic volume increasing enormously with non-homogeneous traffic on the roadway of Six-Laned Two-way traffic. The relation between volume of traffic and speed of vehicles represents third- and fourth-degree curve.

Advanced Public Transportation System for an Urban Metro

Advanced Public Transportation System for an Urban Metro

Spatio-temporal modelling and prediction of bus travel time using a higher-order traffic flow model

Accurate bus travel time prediction in real-time is challenging, as numerous factors such as fluctuating travel demand, incidents, signals, bus stops, dwell times, and seasonal variations can affect travel time, a spatio-temporal variable. Literature that considered the spatio-temporal evolution of bus travel time adopting traffic flow theory-based models investigated one-equation models (also widely known as first-order model) predominantly while the two-equation models (commonly known as higher-order models) have not been sufficiently explored due to their complex structure, parameters to calibrate, hardship in obtaining the data, and difficulty in discretizing and solving. Motivated by this, the present study explores the suitability of higher order traffic flow models for the prediction of bus travel time. This study adopted a well-known two-equation model ‘Aw-Rascle model‘ (Aw and Rascle, 2000), which addressed most of the limitations of the previous models, and discretized using a Finite volume method to preserve the conservational properties of Partial Differential Equations (PDE). As Global Positioning System (GPS) is a widespread data source for transit systems, the identified model was rewritten in terms of speed by adopting a suitable pressure function. The discretized model was represented in the state-state-space form and integrated with a filtering technique using appropriate inputs, to facilitate real-time implementation. The performance of the proposed methodology was evaluated and compared with a first order model (Lighthill Whittam Richards (LWR) model) based approach to understand the efficacy of the higher-order models in travel time prediction. The prediction accuracy in terms of Mean Absolute Percentage Error (MAPE) was around 14% for the proposed methodology with an absolute deviation of around +/-1.2 min, which was better than the existing LWR model-based prediction method. The developed real-time prediction methodology is a promising one to be integrated with Advanced Public Transportation Systems (APTS) applications.

Developing Evaluation Framework for Intelligent Transport System on Public Transportation in Bangkok Metropolitan Regions Using Fuzzy AHP

Public transportation has been encouraged as a significant solution to overcome traffic congestion. An advanced technology, known as advanced public transport system (APTS), was introduced to enhance the effectiveness of public transportation. To support appropriate decisions on selecting application development, significant indicators representing the impacts of the proposed projects are highlighted. This study aims to determine the desirable indicators of developing APTS to achieve smart mobility using the fuzzy Analytical Hierarchy Process (fuzzy AHP) method and allocating weights to each indicator. The perception of a group of intelligent transport system (ITS) experts from three sectors in the Bangkok Metropolitan Regions (BMR) was examined to conduct a fuzzy AHP pairwise comparison. The ranking of 21 indicators categorized within six dimensions in accordance with the specific ITS master plan relating to APTS development is presented. The result presented that the safety dimension obtained the highest rank, and the three most important weight indicators are traffic accident reduction relating to public transportation, smart public transport network density and waiting time for public transportation. In addition, the perspectives towards APTS development and assessment framework development in BMR is highlighted to revise impediment of regulation and encourage integration among stakeholders. Then, the approaches of the APTS evaluation framework in BMR are proposed.

Fuzzy AHP – DEMATEL Methods To Investigate Passengers’ Decision Factors On Using Public City Bus In An Indonesian Region

An advanced public transportation system becomes an indicator for a country. Accordingly, it is essential that the decision-makers (DMs) conduct an initial study based on passengers’ view in order to improve the public transportation services. Since involving multi factors, the problem is often solved using the multi-criteria decision-making (MCDM) approaches. This study aims to examine significant factors on passengers decision making to use public transportation using Fuzzy AHP and DEMATEL. The Fuzzy AHP method is proposed to determine criteria weights so that significant critera are obtained, then the causal relations including the criteria are visualized using DEMATEL. This study demonstrates the integration of the two MCDM methods in a BRT system in the region of Yogyakarta, Indonesia, and invites passengers and the DMs. The result indicated that 21 criteria are identified, while the 11 significant criteria are selected based on the Fuzzy AHP weight – α-cut screening. Besides, the DEMATEL has succeeded in describing the influence relationship for the criteria, where firstly, the significant criteria are classified into cause and effect group and secondly, the two criteria, namely coverage to strategic points and on time arrival, should be put on the top priority list. This study enables the DMs to solve public transportation problems more effectively. However, the follow-up study should be carried out by including other factors such as economic and sustainability to strengthen the decision-making process.

Smart Region Mobility Framework

A smart city describes an urban setting which aims to effectively apply ICT technologies to help improve the well-being of its citizens and reduce the negative impacts of urbanization. The priority areas considered in the Global Smart City Index (SCI) by the Institute for Management Development’s (IMD) World Competitiveness Centre were key infrastructures and technologies in (1) health and safety, (2) mobility, (3) activities (e.g., recreational spaces), (4) opportunities (work and school), and (5) governance. A smart region is a term used to extend the concept of a smart city into both urban and rural settings to promote a sustainable planning approach at the regional level. A direction that must be considered is the adoption of a “Smart Region Mobility Framework” to effectively transform our urban and rural regional transportation networks. This research study focused on the development of the smart region mobility framework for an island region group in the Philippines. The smart region goal is to integrate intelligent transportation system (ITS) platforms such as advanced public transportation system (APTS), advanced traveler information system (ATIS), and advanced rural transportation system (ARTS) to the local public transportation route plans (LPTRP) of the region. The activities include the data collection, analysis, and evaluation of multimodal regional transportation networks and social services infrastructure. The transportation network modeling process follows the four-step transportation planning process of trip generation, trip distribution, modal-split analysis, and trip assignment. Based on the analysis of 6 provinces, 16 cities, and 114 municipalities included in the study, there are two cities identified as smart city candidates. One of the smart city candidates is designated as the smart city regional center. In the context of a smart region, the available social services (e.g., employment opportunities, education, and health services) in the designated smart cities can also be made accessible to connected cities/municipalities through ease of transportation and mobility services in the region. Lastly, the study presented the implementation of data flow architecture of the smart region mobility framework, and the regional traveler information system using mobile and web application services.

Building Urban Public Traffic Dynamic Network Based on CPSS: An Integrated Approach of Big Data and AI

The extensive proliferation of urban transit cards and smartphones has witnessed the feasibility of the collection of citywide travel behaviors and the estimation of traffic status in real-time. In this paper, an urban public traffic dynamic network based on the cyber-physical-social system (CPSS-UPTDN) is proposed as a universal framework for advanced public transportation systems, which can optimize the urban public transportation based on big data and AI methods. Firstly, we introduce three modules and two loops which composes of the novel framework. Then, the key technologies in CPSS-UPTDN are studied, especially collecting and analyzing traffic information by big data and AI methods, and a particular implementation of CPSS-UPTDN is discussed, namely the artificial system, computational experiments, and parallel execution (ACP) method. Finally, a case study is performed. The data sources include both traffic congestion data from physical space and cellular data from social space, which can improve the prediction performance for traffic status. Furthermore, the service quality of urban public transportation can be promoted by optimizing the bus dispatching based on the parallel execution in our framework.

Analysis of global positioning system based bus travel time data and its use for advanced public transportation system applications

The rapid advancements in sensor technologies has resulted in the increased use of Automatic Vehicle Location (AVL) systems for traffic data collection. Global Position System (GPS) sensors are the most commonly used AVL system, majorly because of it being a time-tested technology and being relatively cheap. Also, many of the transportation agencies have their vehicles equipped with GPS sensors. One of the interesting challenges in the field of Intelligent Transportation Systems (ITS) is to effectively mine useful information from such large-scale database accumulated over time. The current study analyses travel time data obtained from buses fitted with GPS devices in Chennai, India to understand its variation over time and space to find the spatial and temporal points of criticality. For this, Cumulative Frequency Distribution (CFD) curves, bar charts and boxplots were used. Inter-Quartile Range (IQR) was used as a measure to quantify the variations in travel time. Analysis showed that both travel time and its variation increased approximately 10% and 40%, respectively, from 2014 to 2016. This increase was observed to be primarily concentrated in six critical intersections during morning and evening peak hours. The findings from the study were further used in demonstrating possible user applications that can improve the efficiency of public transportation systems. As part of this, a real-time bus travel time prediction method was developed using a deep learning approach, Long and Short-Term Memory (LSTM) networks. Along with this, a robust fleet management system was also developed to check the adequacy of buses along the study corridor for different time of the day.

Consideration of Users’ Needs in Regard to Planning of Intelligent Transport Solutions in an African Metropolis

Population growth rates in the least industrialized countries are the highest and will add pressure to transport systems in the future, making travel unimaginably more difficult, especially in locations where road infrastructure is already inadequate or dilapidated. It is, therefore, imperative to plan and deploy intelligent solutions that can intuitively adapt to future traffic demands and inclusively improve transport efficiency and safety. By considering modernization theory and technology transfer, the authors weigh transport system users’ perspectives on the desirability of deployable intelligent transport systems (ITSs) in an African metropolis. The study shows that users recognize the benefits of technology in improving transport performance and travel experience in the metropolis with regard to the precursory ITS solutions already in existence. Although, at different degrees of interest, the participants expressed their desire for deployable solutions in all categories and applications of ITS surveyed. For example, an advanced public transport system (APTS) and advanced traffic management system (ATMS) are more desired. An advanced vehicle communication system (AVCS) tied for the third spot with an advanced travelers’ information system (ATIS). An intelligent transport pricing system (ITPS) was rated as least desirable for a probable reason that the supply and maintenance of road infrastructure are believed to be the government’s responsibility. Differential opinions were recorded, depending on respondents’ age group, profession and most-used means of transport. The authors conclude that the metropolis, and indeed, countries, could develop user-oriented, context-specific and evidence-based ITS policies toward the goal of deploying solutions for a more efficient transport system and pleasing travel experience. The paper also provides a conceptual ITS policy framework that considers transport users’ needs in the metropolis.

A Vehicle Tracking System Using Greedy Forwarding Algorithms for Public Transportation in Urban Arterial

A vehicle tracking system assists public transportation users in their movements by providing real-time information on the locations of vehicles in transit. Public transportation in parts of developing nations, especially Nigeria is ineffective. The system is chaotic and frustrating, especially at peak traffic periods. In a bid to address the problem, a vehicle tracking system was developed as a component of an Advanced Public Transportation System to improve commuting in an urban arterial. The developed system is based on wireless technologies of the Global Positioning System (GPS) and Global System for Mobile Communication module. It records and displays real-time vehicle location using a GPS-based greedy forwarding algorithm, computes route distance information using distance-time based algorithm and radar range sensor (RRS). A pseudo-range mathematical model using the Haversine formula was adopted in determining the accurate position of an object during signal transmission from GPS satellites to the receiver message module. The minimum inversion matrix method was used for the GPS-based geometric dilution of precision (GDoP) selection of satellite approximation and distance. Atmega328P controller chip was used as the logical control unit for processing activities in the tracking system and programming in Arduino IDE using C-language. The system was deployed to a university transportation system in Nigeria: a journey to and from the Bosso and Gidan Kwano Campuses route in the Federal University of Technology, Minna. The vehicle tracking system was tested with 11 tracked satellite and minor dilution error (PDoP error = 1.9, HDoP=0.9, and VDOP=1.7) was recorded. The system is efficient and accurate in distance and time information display with a minor delay. The system would enhance fleet management schemes for urban arterial and can be adopted universally.