Real-time Passenger Information Research Articles

Mitigating airborne infection risks in public transportation: A systematic review

Airborne infections pose significant challenges to public transportation systems which can result in significant decline in ridership levels and financial stress for operators. This systematic review presents a comprehensive overview of measures and strategies employed by ground public transportation agencies to protect passengers and staff while ensuring the uninterrupted operation. This study also conducted a bibliometric analysis to provide insights into key topics, publication patterns, and major contributors in the field of airborne transmission research in public transportation. We have included studies published from January 2003 to June 2024, which reported measures and recommendations for managing public transportation to reduce virus transmission. Of the 2,848 initially identified studies, 69 met our eligibility criteria. Our review identified four key strategies to prevent virus transmission in public transportation, including air quality improvement, cleaning, mask-wearing, and social distancing in vehicles and stations. While social distancing poses a significant challenge to public transportation, the integration of crowd management techniques and technology-driven information dissemination can provide effective strategies for managing capacity. The adoption of technology-driven solutions, such as efficient filtration systems, automated mask detection mechanisms, ultraviolet disinfection devices, and real-time passenger information, is required to implement these strategies effectively. Transportation agencies can utilize an airborne infection risk calculator during pandemics and beyond to assess and mitigate the risk of airborne transmission in various modes of transportation. Lessons from the Covid-19 pandemic underscored the need for developing advanced technologies to enhance passenger and staff safety in public transportation vehicles and stations.

Mitigating airborne infection risks in public transportation: A systematic review

Airborne infections pose significant challenges to public transportation systems which can result in significant decline in ridership levels and financial stress for operators. This systematic review presents a comprehensive overview of measures and strategies employed by ground public transportation agencies to protect passengers and staff while ensuring the uninterrupted operation. This study also conducted a bibliometric analysis to provide insights into key topics, publication patterns, and major contributors in the field of airborne transmission research in public transportation. We have included studies published from January 2003 to June 2024, which reported measures and recommendations for managing public transportation to reduce virus transmission. Of the 2,848 initially identified studies, 69 met our eligibility criteria. Our review identified four key strategies to prevent virus transmission in public transportation, including air quality improvement, cleaning, mask-wearing, and social distancing in vehicles and stations. While social distancing poses a significant challenge to public transportation, the integration of crowd management techniques and technology-driven information dissemination can provide effective strategies for managing capacity. The adoption of technology-driven solutions, such as efficient filtration systems, automated mask detection mechanisms, ultraviolet disinfection devices, and real-time passenger information, is required to implement these strategies effectively. Transportation agencies can utilize an airborne infection risk calculator during pandemics and beyond to assess and mitigate the risk of airborne transmission in various modes of transportation. Lessons from the Covid-19 pandemic underscored the need for developing advanced technologies to enhance passenger and staff safety in public transportation vehicles and stations.

Smart Cities and Intelligent Transport Systems

The integration of technology into cities and transportation networks has the potential to improve the quality of life for residents, reduce congestion and pollution, and increase the overall efficiency of urban cities and their transportation system. Smart cities use technology to improve the efficiency and sustainability of urban areas. This can include things like smart lighting, the internet of things (IoT), energy management, artificial intelligence and smart transportation systems. An intelligent transport system is a component of a smart city that uses technology, to improve the efficiency and safety of the transportation network. This can include things like traffic management systems, real-time passenger information, and intelligent traffic signals. Together all smart cities and ITS can help to reduce congestion, improve air quality, and make cities more liable to residents. Intelligent transport systems (ITS) can revolutionise the way people commute in metro cities. ITS offer a wide range of approaches to providing multiple transportation types, advanced infrastructure, and traffic mobility management solutions. It uses several electronics, wireless and communication technologies to provide consumers with access to a smarter, safer, and fast way to travel around the city

Development of a Mode Choice Model for Bus Rapid Transit in Santa Clara County, California

Bus Rapid Transit (BRT) is an enhanced bus service that offers many of the same service attributes as rail transit, such as specialized vehicles, large stations, real-time passenger information, and more frequent and reliable operations. The Santa Clara Valley Transportation Authority (VTA) intends to develop an integrated BRT network throughout Santa Clara County, California, to provide high quality service to areas not well served by the VTA Light Rail (LRT) system. Past research showed that many transit agencies in North America considered BRT the same as LRT in their demand models, and a few agencies treated BRT and local bus identically. Realistic BRT ridership forecasts are essential for selecting and sizing facilities, preparing service plans, estimating capital and operating costs, and assessing cost-effectiveness. This study applied the results of the transit preference survey in a Market Research Model prepared for the VTA and built the improved mode choice model that explicitly included the BRT mode in the VTA demand model. Instead of considering BRT the same as either LRT or local bus, the improved VTA model with an explicit BRT mode is expected to forecast more reasonable future BRT boardings. Eleven scenarios in the BRT strategic plan for Santa Clara County were developed using the BRT forecast results from the improved VTA model.

Bus Rapid Transit Plans in New York’s Capital District

The Capital District Transportation Authority (CDTA) is seeking to implement Bus Rapid Transit service in the NY 5 corridor, which runs for 16.5 miles between Albany and Schenectady. The benefits of BRT will be to improve service for current riders, draw new riders to the system, help spur economic revitalization in the corridor, provide key nodes for new development, and improve the image of transit in the Capital District as a whole. When fully in place, the key features of BRT on NY 5 will include limited-stop service, substantial passenger facilities and amenities at each station, real-time passenger information, improved pedestrian environment, park-and-ride opportunities, priority treatment at intersections, queue jumpers at key points, off-vehicle fare collection, and a specific brand image to distinguish BRT from other bus services. The cumulative impact of these types of improvements—in travel time, passenger comfort, passenger information, and image—will lead to an increase in transit ridership in the NY 5 corridor. Based on experience at other North American transit agencies that have implemented BRT, an increase of 22 percent to 29 percent is expected, depending on the ultimate travel time savings that is achieved.

Development of a Mode Choice Model for Bus Rapid Transit in Santa Clara County, California

Bus Rapid Transit (BRT) is an enhanced bus service that offers many of the same service attributes as rail transit, such as specialized vehicles, large stations, real-time passenger information, and more frequent and reliable operations. The Santa Clara Valley Transportation Authority (VTA) intends to develop an integrated BRT network throughout Santa Clara County, California, to provide high quality service to areas not well served by the VTA Light Rail (LRT) system. Past research showed that many transit agencies in North America considered BRT the same as LRT in their demand models, and a few agencies treated BRT and local bus identically. Realistic BRT ridership forecasts are essential for selecting and sizing facilities, preparing service plans, estimating capital and operating costs, and assessing cost-effectiveness. This study applied the results of the transit preference survey in a Market Research Model prepared for the VTA and built the improved mode choice model that explicitly included the BRT mode in the VTA demand model. Instead of considering BRT the same as either LRT or local bus, the improved VTA model with an explicit BRT mode is expected to forecast more reasonable future BRT boardings. Eleven scenarios in the BRT strategic plan for Santa Clara County were developed using the BRT forecast results from the improved VTA model.

Modeling the performance of passenger public transportation service in Salatiga City

Abstract The Public transportation system is one of the main indicators to show the increase in efficiency and productivity of a city. Meanwhile, the public transportation services in Salatiga City were observed to be averagely good but have some classic obstacles such as the absence of bus stops to pick up passengers and non-determination of the fare to be paid by the passengers per kilometer. This study was, therefore, conducted to model the performance of public transportation in Salatiga City. The results showed that 9 fleets with a route length of 6.2 km which has a load factor of 72% because Tamansari – Blotongan is one of the routes most traveled by the passengers are sufficient for the needs of the passengers. It was also discovered that 70% of the people prefer public transportation due to its cheapness, 55% fastness, and 77.5% because it is safe while 10% were found to be satisfied with the waiting time. Moreover, a real-time passenger information system was observed to have the ability to determine the position of public transport passengers while the Radio Frequency Identification Device (RFID) network was able to estimate the number of passengers currently limited due to the COVID-19 pandemic. The first section in your paper

Impacts of real-time information levels in public transport: A large-scale case study using an adaptive passenger path choice model

Public transport services are often uncertain, causing passengers’ travel times and routes to vary from day to day. However, since door-to-door passenger delays depend on both intended and realised routes, they are difficult to calculate, as opposed to vehicle delays which can be derived directly from the widely available Automated Vehicle Location (AVL) data of the public transport system. In this study we use three months of such historical AVL data to calculate corresponding realised routes and passengers delays in a large-scale, multi-modal transport network by formulating and implementing an adaptive passenger path choice model in an agent-based scenario of Metropolitan Copenhagen with 801,719 daily trips. The proposed model allows analysing five different levels of real-time information provision, ranging from no information at all to global real-time information being available everywhere. The results of more than 258 million (positive or negative) passenger delays show that variability of passengers’ travel time is considerable and much larger than that of the public transport vehicles. It is also shown that obtaining global real-time information at the beginning of the trip reduces passengers delay dramatically, although still being inferior to receiving such along the trip. Additionally, being able to automatically obtain real-time passenger information while walking and being on-board public transport services is found not to lead to considerable improvements compared to acquiring such information manually while waiting at stops, although slight benefits are demonstrated in supplementary models run with pseudo-intelligent vehicle delay forecasting.

Bus passenger path choices after consulting ubiquitous real-time information

Ubiquitous real-time passenger information (URTPI) enables public transport (PT) users to make better travel choices at both pre-trip and en-route stages. A significant amount of URTPI usage is evident in the existing literature. This study investigates the impact of URTPI on bus passenger path choice. To this end, a bus passenger survey was conducted in the City of Edinburgh, UK, and a total of 1645 completed responses were collected. More than half of the survey participants used at least one source of ubiquitous information. The survey results reveal that about 55% of the URTPI users changed at least one aspect of their trip. Changing the time of departure from the start and boarding time are the two most popular actions taken by bus passengers after consulting URTPI. Passengers’ decisions are influenced by information on bus arrival time, bus route, and walking distance. The study demonstrates the potential impact of the change in passenger choices on PT demand distribution. We find that the demand distribution for bus runs could potentially be changed by 17% and for bus lines by 15%. The overall network demand distribution could be affected in 42% of cases as a result of consulting URTPI. This study advocates that transport planners and operators should take the potential impact of URTPI into account to make better predictions of PT demand distribution.

Use of ubiquitous real‐time bus passenger information

Ubiquitous real-time passenger information (URTPI) enhances the perceived quality of service of public transport and enables travellers to make better pre-trip and en-route travel choices. The study presents an exploratory study of the use of URTPI. The authors analyse the popularity of this kind of information, of the sources through which it is disseminated, and of the contents that it conveys. In particular, the authors are interested in the effects of trip characteristics and socio-demographic features of passengers. The findings are based on 1645 responses collected through a bus passenger survey in the city of Edinburgh, UK. The authors find that access to URTPI is particularly related to the perceived length of the trips and age of the traveller. The most popular source of URTPI is bespoke apps providing information on bus arrival times, although non-residents require more detailed information. The study paves the way for further investigations into the impact of information on passengers' choices.

Smart Commuter Line (KRL) using IoT and SOA in Indonesia

Commuter line (KRL) one of the better public transportation for commuter people in Indonesia especially in Jabodetabek (Jakarta, Bogor, Depok, Tangerang, Bekasi). Passenger satisfaction is the one of the service quality factor in KRL. There is no real time passenger information in both train and station, the situation make an unpredictable activity for passenger that want to use or wait the commuter line (KRL). Most of passenger cannot enter the train because the crowded passenger. KRL management cannot manage train capacity and train time management to meet passenger needs. This paper proposed a smart commuter line system to provide real time passenger information using IoT by count people using Markov Random Field framework and integrate all KRL enterprise system using SOA to support data integration.

TravelBot: Utilising social media dialogue to provide journey disruption alerts

Use of social media in the public transport sector is rapidly increasing, driven by both passenger demand, and recognition by transport operators of the insights that social media enables. This paper explores the potential for utilising social media (specifically, the Twitter platform) to provide personalised information to public transport passengers, drawing from lessons learned from related studies. The Tweeting Travel study developed an understanding of the types of dialogues that can unfold on social media between passengers and a simulated travel advice system and then used this to shape development of the TravelBot system. This system provided users with real-time passenger information, including details of relevant travel disruptions that were automatically extracted from social media posts. A user evaluation of a TravelBot trial is presented, findings of which showed that participants highly valued the service and the information it provided, with most indicating a strong desire for the system to continue operation. These findings reveal the potential offered by social media for more personalised communication between public transport operators and their passengers, as well as indicating an efficient method by which this communication may be enabled.

Data ratcheting and data-driven organisational change in transport

This article explores the process by which intelligent transport system technologies have further advanced a data-driven culture in public transport and traffic control. Based on 12 interviews with transport engineers and fieldwork visits to three control rooms, it follows the implementation of Real-Time Passenger Information in Dublin and the various technologies on which it is dependent. It uses the concept of ‘data ratcheting’ to describe how a new data-driven rational order supplants a gradualist, conservative ethos, creating technological dependencies that pressure organisations to take control of their own data and curate accessibility to outside organisations. It is argued that the implementation of Real-Time Passenger Information forms part of a changing landscape of urban technologies as cities move from a phase of opening data silos and expanded communication across departments and with citizens towards one in which new streams of digital data are recognised for their value in stabilising novel forms of city administration.

User perception of transfers in multimodal urban trips: A qualitative study

The aim of this article is to identify the factors affecting user perception of transfers in order to reduce the penalty associated with transfers. Policy makers can thus concentrate on the most relevant factors to achieve a more effective investment of public funds. We carried out an extensive review of the literature and identified a total of 45 factors. A qualitative study was then conducted in two Spanish cities, Vitoria and Madrid, consisting of various focus groups stratified by age. The results indicate that a combination of factors influence the perception of transfers. Time spent during transfers, both walking and waiting, is the main penalty associated with transfers. However, the provision of real-time passenger information helps reduce the perceived waiting time. Differences were found between cities and age groups. Two new factors were identified, mainly in Madrid: mental effort and activity disruption. We, therefore, advise policy makers to concentrate their efforts on providing real-time information to passengers, improving the frequency and reliability of services, and designing transfer areas to ensure continuity between transport modes and between information and communication systems.

Build an app and they will come? Lessons learnt from trialling the GetThereBus app in rural communities

Real-time passenger information (RTPI) systems have been identified as having benefits in terms of passenger willingness to travel by public transport and their satisfaction levels with services provided. The lack of this amenity in rural areas, however, may hamper public transport use, thus reinforcing patterns of over-reliance on personal vehicles. To explore the potential impacts of providing RTPI in rural areas, a smartphone application (GetThereBus) was developed to allow rural bus passengers to share real-time public transport data, and access real-time and timetable information. Through user testing of GetThereBus, this work aimed to address questions related to the impact of the limited availability of rural digital infrastructure on the provision of RTPI; the potential for crowdsourced information to supplement published timetable information given digital limitations; and the potential impacts of such a system on the traveller experience. This study describes the GetThereBus development and evaluation phases. The authors found it was possible to design and develop a system that overcame many of the technological limitations experienced in rural areas, and users reported a positive response to the system. However, despite a campaign of user engagement, it proved difficult to recruit and motivate sufficient users to provide the data needed to achieve area-wide coverage.

Bus-stop Based Real Time Passenger Information System – Case Study Maribor

Real time passenger information system is one of the key element of promoting public transport. For the successful implementation of real time passenger information systems, various components should be considered, such as: passenger needs and requirements, stakeholder involvement, technological solution for tracking, data transfer, etc. This article carrying out designing and evaluation of real time passenger information (RTPI) in the city of Maribor. The design phase included development of methodology for selection of appropriate macro and micro location of the real-time panel, development of a real-time passenger algorithm, definition of a technical specification, financial issues and time frame. The evaluation shows that different people have different requirements; therefore, the system should be adaptable to be used by various types of people, according to the age, the purpose of journey, experience of using public transport, etc. The average difference between perceived waiting time for a bus is 35% higher than the actual waiting time and grow with the headway increase. Experiences from Maribor have shown that the reliability of real time passenger system (from technical point of view) must be close to 100%, otherwise the system may have negative impact on passengers and may discourage the use of public transport. Among considered events of arrivals during the test period, 92% of all prediction were accurate. The cost benefit analysis has focused only on potential benefits from reduced perceived users waiting time and foreseen costs of real time information system in Maribor for 10 years’ period. Analysis shows that the optimal number for implementing real time passenger information system at the bus stops in Maribor is set on 83 bus stops (approx. 20 %) with the highest number of passenger. If we consider all entries at the chosen bus stops, the total perceived waiting time on yearly level could be decreased by about 60,000 hours.

지하철 실시간 운행정보 콘텐츠를 위한 디자인 가이드라인 연구 : 문헌 및 일본 도쿄전철 사례를 중심으로

지하철 실시간 운행정보 콘텐츠를 위한 디자인 가이드라인 연구 : 문헌 및 일본 도쿄전철 사례를 중심으로

Particle Filter for Reliable Bus Travel Time Prediction Under Indian Traffic Conditions

In recent times, traffic congestion has been increasing rapidly and deteriorating the quality of traffic systems in urban areas of many developed and developing countries. This became a serious problem faced by society, as many people are using private vehicles while commuting from one place to the other. One of the reasons people are shifting towards private transportation is due to lack of reliability of the public transportation systems. Attracting more travelers towards public transportation using Intelligent Transportation Systems (ITS) technologies is one way to reduce the negative impacts. In this context, prediction of bus travel time and providing information about bus arrival time to passengers accurately is a potential solution, which will help in reducing the uncertainty and waiting time associated uncertainties with public transit systems. However, for this solution to be effective, the information provided to passengers should be highly reliable. The present study proposes a model based prediction method that uses particle filtering technique for accurate prediction of bus travel times for the development of a real time passenger information system under heterogeneous traffic conditions that exist in India. The results obtained from the implementation of the above method are validated using the measured travel time. The prediction accuracy is quantified using the Mean Absolute Percentage Error (MAPE) and the performance is compared with a base approach namely, the historic average method. The quantified error in terms of MAPE is 20% for the proposed method and 37% for the historic average method, indicating the superiority of the proposed method over historic average method. Thus, it can be concluded that particle filter is a viable tool in the prediction of bus travel times.

Linking open data and the crowd for real-time passenger information

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.

Linking Open Data and the Crowd for Real-Time Passenger Information

The availability of real-time passenger information (RTPI) is a key factor in making public transport both accessible and attractive to users. Unfortunately, rural areas often lack the infrastructure necessary to provide such information, and the cost of deploying and maintaining the required technologies outside of urban areas is seen as prohibitive. In this paper we present the GetThere system developed to overcome such issues and to provide public transport users in rural areas with RTPI. An ontological framework for representing mobility information is described, along with the Linked Data approach used to integrate heterogeneous data from multiple sources including government, transport operators, and the public. To mitigate possible issues with the veracity of this data, a quality assessment framework was developed that utilises data provenance. We also discuss our experiences working with Semantic Web technologies in this domain, and present results from both a user trial and a performance evaluation of the system.