A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays

This paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed traffic to an exclusive bus lane, using a big data approach. The main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many different situations with a high degree of spatial and temporal detail. These data allow ready adjustment of calculations to the specific reality measured in each case. In this way, we propose a novel methodology of general application to estimate the potential passenger savings instead of using simulation or analytical methods already present in the literature. For that purpose, in the first place, a travel time prediction model per vehicle trip has been developed. It has been calibrated and validated with a historical series of observations in real-world situations. This model is based on multiple linear regression. The estimated bus delay is obtained by comparing the estimated bus travel time with the bus travel time under free-flow conditions. Finally, estimated bus passenger time savings would be obtained if an exclusive bus lane had been implemented. An estimation of the passenger's route in each vehicle trip is considered to avoid average value simplifications in this calculation. A case study is conducted in A Coruña, Spain, to prove the methodology's applicability. The results showed that 18.7% of the analyzed bus trips underwent a delay exceeding 3 min in a 2,448 m long corridor, and more than 33,000 h per year could have been saved with an exclusive bus lane. Understanding the impact of different factors on transit and the benefits of a priority bus system on passengers can help city councils and transit agencies to know which investments to prioritize given their limited budget.

Enhancing service quality of rural public transport during the COVID-19 pandemic: a novel fuzzy approach

In order to encourage the use of public transportation, it is necessary to make it more appealing to commuters by conducting frequent Service Quality (SQ) evaluations and modifications. Understanding passengers' expectations of public transportation are important, and evaluating the SQ is an essential tool for assessing the overall performance of the public transportation system. The purpose of the present study was to examine the expectations and perceptions of core passengers regarding SQ in public bus transportation. By surveying 598 passengers in rural public transportation in India, the study results are illustrated and further discussed to guide possible bus SQ improvements in rural areas. In addition, the impact of these expectations and perceptions on satisfaction levels of rural public bus transportation services are explored by applying the Interval-Valued Pythagorean Fuzzy (IVPF). The outcomes of the survey indicated significant disparities among expectations and perceptions of passengers, as well as widespread dissatisfaction with the delivery of bus services in rural areas as a whole. The dependability and adaptiveness of the bus service have been critical in describing the overall quality of bus services in rural areas, and best practices from around the world were used to develop a set of recommendations for transportation operators and local officials. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

Why are Hanoi students giving up on bus ridership?

University students are regarded as a readily available market segment for public transport. In Hanoi, as elsewhere, they constitute a large portion of bus passengers. However, one portion has been quitting buses, and the reasons were so far unknown. Nor was it clear whether they planned on retuning. Through a survey of more than 800 students in seven higher education institutions, this study aimed to find the answers to these questions. The study revealed that bus ridership was determined by socio-demographic variables (year of studies, household income, employment status, motorcycle ownership), environmental variables (home-university distance), and psychological variables (convenience, bus staff behaviour, risk of sexual harassment, reliability and health, image and status). A negative disruptor such as the fear of Covid-19 infection had little effect on the decision to continue riding buses. Meanwhile, the prospect of riding 'clean and green' electric buses, which were introduced in a pilot program, was a positive disruptor that may lead a portion of students to return to public transport.

Origin Destination Estimation Carrying over Rolling Proximity Identifiers with RSSI

Origin destination (OD) data describing passengers' flows is essential for improving bus route operational efficiency. Manual collection of OD data is still conducted, so automatic OD data acquisition using the internet of things (IoT) is desired. One method utilizes Bluetooth beacon identifiers to understand passengers' flows while considering their privacy. Still, while random MAC addresses can estimate the number of devices there, they are insufficient for generating ODs. In contrast, in response to the COVID-19 pandemic, the government promoted the exposure notification system to prevent secondary infection. The smartphone app exchanges short-term identifiers called Rolling Proximity Identifiers (RPIs), updated every 15 minutes. This research aims to realize tracking during bus rides with only a few RPIs carryovers, since bus rides are only about an hour long at most. We evaluated the system on a bus in Kyoto City and successfully tracked passengers for 55 minutes, the experiment's maximum length. © 2022 IEEE.

Bus Network Design and Frequency Setting in the Post-COVID-19 Pandemic: The Case of London

A transit network design frequency setting model is proposed to cope with the postpandemic passenger demand. The multiobjective transit network design and frequency setting problem (TNDFSP) seeks to find optimal routes and their associated frequencies to operate public transport services in an urban area. The objective is to redesign the public transport network to minimize passenger costs without incurring massive changes to its former composition. The proposed TNDFSP model includes a route generation algorithm (RGA) that generates newlines in addition to the existing lines to serve the most demanding trips, and passenger assignment (PA) and frequency setting (FS) mixed-integer programming models that distribute the demand through the modified bus network and set the optimal number of buses for each line. Computational experiments were conducted on a test network and the network comprising the Royal Borough of Kensington and Chelsea in London. © 2023 American Society of Civil Engineers.

Combined Effect of Changes in Transit Service and Changes in Occupancy on Per-Passenger Energy Consumption

Many transit providers changed their schedules and route configurations during the COVID-19 pandemic, providing more frequent bus service on major routes and curtailing other routes, to reduce the risk of COVID-19 exposure. This research first assessed the changes in Metropolitan Atlanta Rapid Transit Authority (MARTA) service configurations by reviewing the prepandemic versus during-pandemic General Transit Feed Specification (GTFS) files. Energy use per route for a typical week was calculated for pre-pandemic, during-closure, and post-closure periods by integrating GTFS data with MOVES-Matrix transit energy and emission rates (MOVES signifying MOtor Vehicle Emission Simulator). MARTA automated passenger counter data were appended to the routes, and energy use per passenger-mile was compared across routes for the three periods. The results showed that the coupled effect of transit frequency shift and ridership decrease from 2019 to 2020 increased route-level energy use for over 87% of the routes and per-passenger-mile energy use for over 98% of the routes. In 2021, although MARTA service had largely returned to pre-pandemic conditions, ridership remained in an early stage of recovery. Total energy use decreased to about pre-pandemic levels, but per-passenger energy use remained higher for more than 91% of routes. The results confirm that while total energy use is more closely associated with trip schedules and routes, perpassenger energy use depends on both trip service and ridership. The results also indicate a need for data-based transit planning, to help avoid inefficiency associated with over-provision of service or inadequate social distancing protection caused by under-provision of service. © National Academy of Sciences: Transportation Research Board 2022.

Public transport workers and COVID-19 risk: a cohort study in Italy

IntroductionPublic transport workers have never stopped working during the COVID-19 pandemic. Despite the high personal contact with the public, studies in this job category on COVID-19 risk are scarce.Material and MethodsWe aimed to fill in this knowledge gap by investigating a cohort of over 2,000 employees of the Regional public transport sector in Sardinia, Italy. Incident COVID-19 cases were identified between 1 September 2020 – 6 May 2021 by real-time reverse transcription-polymerase chain reaction tests performed on nasopharyngeal swabs during periodic occupational health surveillance. We applied the age- and gender-specific COVID-19 incidence rates in the regional population at the same time frame to the correspondent strata of the study cohort to calculate the expected COVID-19 events. Age- and gender-adjusted relative risks (RRs) of COVID-19 and relative 95% confidence intervals (95% CIs) were estimated as the ratio between the observed and the expected events for the overall cohort and in two sub-cohorts: bus drivers and the rest of the workers (including administrative staff).ResultsMale bus drivers showed an increased COVID-19 risk (RR = 1.4, 95% C.I. 1.07 – 1.79). There was no excess risk among the rest of the personnel. Women were too few to allow reliable risk estimates.ConclusionsOur study suggests an excess risk of COVID-19 among bus drivers even in a relatively low incidence area, which could imply inadequacy of occupational preventive measures. Further larger studies, with detailed information on occupational and personal determinants, are warranted to disentangle the underlying causal factors and focus preventive strategies.

Bus Crowdedness Sensing System Based on Carbon Dioxide Concentration

Crowdedness sensing of buses is playing an important role in the disease control of COVID-19 and bus resource scheduling. This research analyzes the relationship between carbon dioxide concentration, bus environment and the number of passengers by linear regression. Our prototype system collects the data of bus environment and carbon dioxide concentration to estimate the number of passengers in real time. By collecting the sensing data from a shuttle bus of university campus, we experimentally evaluate the feasibility and sensing performance of the crowdedness estimation model. © 2022 Owner/Author.

Sensing Technologies for Crowd Management, Adaptation, and Information Dissemination in Public Transportation Systems: A Review

Management of crowd information in public transportation (PT) systems is crucial, both to foster sustainable mobility, by increasing the user's comfort and satisfaction during normal operation, as well as to cope with emergency situations, such as pandemic crises, as recently experienced with coronavirus disease (COVID-19) limitations. This article presents a taxonomy and review of sensing technologies based on the Internet of Things (IoT) for real-time crowd analysis, which can be adopted in the different segments of the PT system (buses/trams/trains, railway/metro stations, and bus/tram stops). To discuss such technologies in a clear systematic perspective, we introduce a reference architecture for crowd management, which employs modern information and communication technologies (ICTs) in order to: 1) monitor and predict crowding events;2) implement crowd-aware policies for real-time and adaptive operation control in intelligent transportation systems (ITSs);and 3) inform in real time the users of the crowding status of the PT system, by means of electronic displays installed inside vehicles or at bus/tram stops/stations and/or by mobile transport applications. It is envisioned that the innovative crowd management functionalities enabled by ICT/IoT sensing technologies can be incrementally implemented as an add-on to state-of-the-art ITS platforms, which are already in use by major PT companies operating in urban areas. Moreover, it is argued that, in this new framework, additional services can be delivered to the passengers, such as online ticketing, vehicle access control and reservation in severely crowded situations, and evolved crowd-aware route planning. © 2001-2012 IEEE.

Seating System in Indian Public Transport

Public transportation is a crucial part of our everyday lives, also, moving from one place to another is fraught with problems. The number of people using public transportation has increased, increasing transportation demand among the general population. Because of the COVID-19 outbreak, it is difficult for people to travel around the city without fear of contracting the disease;in this situation, people always wish for a better hygiene system and a low infection rate in the city. As a result, the primary goal of the study is to research and develop a viewpoint on the public transportation seating system, that is relevant to the Indian setting and attitude of following rules and regulations. Many things have been tried in the past to ensure the safety of travelers, and they have not proven as beneficial as they should be after following COVID-19 recommendations. The goal is to enhance the comfort and safety of passengers as well as give people easy access to the public transportation that is most widely used, like auto-rickshaws and buses. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

COVID-19 transmission in U.S. transit buses: A scenario-based approach with agent-based simulation modeling (ABSM)

The transit bus environment is considered one of the primary sources of transmission of the COVID-19 (SARS-CoV-2) virus. Modeling disease transmission in public buses remains a challenge, especially with uncertainties in passenger boarding, alighting, and onboard movements. Although there are initial findings on the effectiveness of some of the mitigation policies (such as face-covering and ventilation), evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways, boarding and alighting patterns, and seating capacity control. This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic in USA, in which it brings crucial insights on combating current and future epidemics. We use an agent-based simulation model (ABSM) based on standard design characteristics for urban buses in USA and two different service frequency settings (10-min and 20-min headways). We find that wearing face-coverings (surgical masks) significantly reduces onboard transmission rates, from no mitigation rates of 85% in higher-frequency buses and 75% in lower-frequency buses to 12.5%. The most effective prevention outcome is the combination of KN-95 masks, open window policies, and half-capacity seating control during higher-frequency bus services, with an outcome of nearly 0% onboard infection rate. Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design, which is crucial to ensuring passenger safety. The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies. © 2023

Impacts of COVID-19 on Bus Ridership and Recovery Trends in Syracuse, New York

COVID-19 had serious repercussions on public transportation throughout the USA. The aftermath of the peak of the crisis marked the path towards a slow and gradual recovery characterizing the shift to a new normal. Given the limited information on the recovery trends of public transportation, this paper compares the actual ridership and bus supply data for the years of 2019 and 2020 to study the timeline impacts of the pandemic on the bus system of the mid-sized city of Syracuse, NY. A data-driven analysis is presented across the city's bus routes, university bus routes, and categorical bus stops. Various census tract socio-demographic data are also correlated with passenger activity changes and mapped using ArcGIS. The findings show that overall bus ridership in 2020 fell by 70%, on average, during the three months that followed the onset of the pandemic. Since the lifting of the initial restrictions, concerns about using public transportation had partially been alleviated;however, passengers remained reluctant with ridership decline stabilizing at approximately 55% during the last four months of the year. While bus lines serving the university area, which houses a high percentage of youth, were severely affected by the pandemic, passenger activity near hospital stops were less affected and those near major supermarkets/ hypermarkets seemed unaffected, showing a surge especially in the two months that followed the onset of the pandemic. Passenger activity at census tracts having low poverty levels mostly located on the outskirts of the city of Syracuse were the least affected tracts in the last six months of 2020. It is anticipated that the insights presented will help service planners in preparing for similar future events by better understanding what stops and routes are deemed essential during a public health crisis and how the socio-demographics impacted the recovery after restrictions were removed. [ FROM AUTHOR]

Designing boarding limit strategy by considering stop-level fairness amid the COVID-19 outbreak

Bus operators have to make trade-offs between transporting more passengers and maintaining social distancing to reduce ridership congregation amid Corona Virus Disease 2019 (COVID-19) outbreak. The traditional bus boarding mode could easily lead passengers fully occupy the bus available capacity at one stop, and it would prevent subsequent passengers from boarding. It is crucial to establish a new operating mode and strategy to ensure all passengers have opportunities to ride and to collaboratively optimise the bus timetable. In this paper, the boarding limit strategy that considers the fairness of passenger boarding probability is proposed to address the inequitable problem with minimise the passenger travel time and the number of stranded passengers. The coupling relationship between bus dwell time and passenger flow is used to collaboratively optimise the bus timetable. Case studies are conducted to illustrate the performance of the boarding limit strategy in improving passenger boarding equity. © 2023 Hong Kong Society for Transportation Studies Limited.

COVID-19 environmental and operational impact for public transport in Kuwait.

The corona virus disease pandemic (COVID-19) is one of the recent issues that spread in the world, which disrupted life, impacted the economy, and led to heavy losses, whether for government sectors or private companies. This paper focuses on the Kuwait public transport company KPTC and Kuwait Airways' experience during the pandemic, since they incurred major losses due to the decline of their users. Public transport is a place to catch COVID-19, as it is subjected to the use of a large number of passengers daily within a small closed environment. The causes that led to the spread of the virus among public transport users and develop solutions to limit its spread and preserve public transport pioneer's safety were discussed in the paper. Additionally, the environmental impact resulting from the reduction of public transportation using was also addressed. Data was obtained from the KPTC, Kuwait Airways office, the Ministry of Health (MOH) database, and the Environment Public Authority (EPA) database. A questionnaire was distributed to public transport users to determine the reasons for the decline in its user's number and their aspirations to reconsider their use and ensure their satisfaction. For airplane data, the risk of importation of COVID-19 was calculated. For KPTC data, COVID-19 impact on the emissions generated per passenger-km was computed where the emissions were estimated by MOVES. The survey responses were statically analyzed using the chi-square test on the SPSS program, and they were compared to numerical analysis results. The results showed the impact of COVID-19 on people's willingness to use public transportation which was associated with the increase in the number of buses to implement social distancing has negatively affected the environment. Thus, a comprehensive strategy solution was presented consisting of three basic approaches: providing a healthy, risk-free environment for public transportation users, achieving social distancing at a low cost to offset the losses, and ensuring a healthy environment.

Special Issues Brief: How Region 2 States Are Leveraging Innovative Strategies to Address Critical Shortages of Education Personnel

This special issues brief provides an overview of the education workforce shortage trends both nationally and in Region 2 states (Connecticut, New York, and Rhode Island). The brief also highlights examples of how Region 2 states are innovating to address these shortages and provides additional considerations for strategies to address shortages in both the short term and the long term.

Impacts of COVID-19 on Bus Ridership and Recovery Trends in Syracuse, New York

COVID-19 had serious repercussions on public transportation throughout the USA. The aftermath of the peak of the crisis marked the path towards a slow and gradual recovery characterizing the shift to a new normal. Given the limited information on the recovery trends of public transportation, this paper compares the actual ridership and bus supply data for the years of 2019 and 2020 to study the timeline impacts of the pandemic on the bus system of the mid-sized city of Syracuse, NY. A data-driven analysis is presented across the city's bus routes, university bus routes, and categorical bus stops. Various census tract socio-demographic data are also correlated with passenger activity changes and mapped using ArcGIS. The findings show that overall bus ridership in 2020 fell by 70%, on average, during the three months that followed the onset of the pandemic. Since the lifting of the initial restrictions, concerns about using public transportation had partially been alleviated;however, passengers remained reluctant with ridership decline stabilizing at approximately 55% during the last four months of the year. While bus lines serving the university area, which houses a high percentage of youth, were severely affected by the pandemic, passenger activity near hospital stops were less affected and those near major supermarkets/hypermarkets seemed unaffected, showing a surge especially in the two months that followed the onset of the pandemic. Passenger activity at census tracts having low poverty levels mostly located on the outskirts of the city of Syracuse were the least affected tracts in the last six months of 2020. It is anticipated that the insights presented will help service planners in preparing for similar future events by better understanding what stops and routes are deemed essential during a public health crisis and how the socio-demographics impacted the recovery after restrictions were removed.

COVID-19 transmission in U.S. transit buses: A scenario-based approach with agent-based simulation modeling (ABSM)

The transit bus environment is considered one of the primary sources of transmission of the COVID-19 (SARS-CoV-2) virus. Modeling disease transmission in public buses remains a challenge, especially with uncertainties in passenger boarding, alighting, and onboard movements. Although there are initial findings on the effectiveness of some of the mitigation policies (such as face-covering and ventilation), evidence is scarce on how these policies could affect the onboard transmission risk under a realistic bus setting considering different headways, boarding and alighting patterns, and seating capacity control. This study examines the specific policy regimes that transit agencies implemented during early phases of the COVID-19 pandemic inUSA, in which it brings crucial insights on combating current and future epidemics. We use an agent-based simulation model (ABSM) based on standard design characteristics for urban buses in USA and two different service frequency settings (10-min and 20-min headways). We find that wearing face-coverings (surgical masks) significantly reduces onboard transmission rates, from no mitigation rates of 85% in higher-frequency buses and 75% in lower-frequency buses to 12.5%. The most effective prevention outcome is the combination of KN-95 masks, open window policies, and half-capacity seating control during higher-frequency bus services, with an outcome of nearly 0% onboard infection rate. Our results advance understanding of COVID-19 risks in the urban bus environment and contribute to effective mitigation policy design, which is crucial to ensuring passenger safety. The findings of this study provide important policy implications for operational adjustment and safety protocols as transit agencies seek to plan for future emergencies.

Research on the characteristics of regular bus trips in Guangzhou under the influence of the new crown epidemic based on multivariate data fusion

Conventional public transportation is an important part of public transportation, and it has always been the focus of urban transportation research to excavate the characteristics of public transportation and analyze residents' travel patterns. In 2020, the new crown epidemic broke out. The outbreak and continuation of the epidemic have caused shocks and challenges to conventional public transportation, and the characteristics of conventional public transportation have developed significantly. Taking Guangzhou as an example, this paper conducts bus IC card mining based on multi-source data fusion, and conducts research on the characteristics of changes in Guangzhou's regular bus travel rules under the influence of the new crown epidemic. Research shows that under the continuous influence of the epidemic, the scale of bus trips has dropped significantly, the attraction of conventional buses to commuter passengers has been weakened, special groups are important users of public transport, and the ride code has become the most important payment method. © 2022 SPIE.

The Perspective Projects Promoting Sustainable Mobility by Active Travel to School on the Example of the Southern Poland Region

The paper presents a discussion concerning the development of projects regarding active travel with the policy of sustainable mobility, with active school transport in southern Poland being taken into special consideration. The implementation of the idea of sustainable school travel planning involves linking several social groups, including traffic planners and organizers, school administrators, governments, parents, and children. This, in turn, requires considering the criteria reported by all parties when choosing a scenario for the region’s development in terms of transport solutions. The following study was based on the methodological foundations of multicriteria decision-making analysis. The research purpose of this paper is to identify and classify the actions, policies, and scenarios of active travel projects for the sustainable development of mobility based on the cities of southern Poland. The evaluation was carried out through expert methods with multicriteria decision-making tools based on the MULTIPOL (MULTI-criteria and POLicy) prospective analysis technique. It allowed for the selection of the most probable policy, which covered the six actions considered by the experts to be the most significant for the development of the active school transport system in the analyzed region. Such actions are as follows: identification of walking school bus routes, modernization of crosswalk lines, planning of walking and cycling routes to schools, promoting safety educational programs, distribution of active school transport booklets and cycling, and pedestrian skills training workshops. The paper presents a new method to evaluate the policies and actions regarding promoting sustainable (active) travel to school. The innovative approach results from assembling a mixed group of people (stakeholders) as experts. The mix of experts consisting of users (pupils and parents), practitioners, and scientist experts in this field allowed us to score policies, actions, and scenarios, enabling a wider spectrum of assessment than before.