This session includes bus automation and electrification, bus reliability and quality service, bus travel time and dwell time studies for bus operations, design, and applications. The bus automation and electrification have been promoted in recent years to provide more convenient service for passengers and shape the green future for the public. Bus travel time an dwell time studies enhance the bus reliability and quality service. Audiences who are interested in bus transit operations, technology, and applications are welcome to join this session.
Investigating the subline frequency setting problem for autonomous minibusses under demand uncertainty
Konstantinos Gkiotsalitis (firstname.lastname@example.org), University of TwenteShow Abstract
Marie Schmidt, Erasmus Universiteit Rotterdam
Evelien van der Hurk, Danmarks Tekniske Universitet
Over the last years, several pilots with autonomous minibusses operating in urban environments have been initiated. Unlike regular bus services, autonomous minibusses serve a limited number of stops and have more flexible schedules since they do not require drivers. This allows the operation of a line through a combination of sublines, where a subline serves a subset of consecutive stops in the same order as the original line. This paper studies the subline frequency setting problem under uncertain passenger demand. We present a frequency setting model that assigns autonomous minibusses to sublines in order to minimize operational costs and passenger waiting time costs. Passenger waiting time costs may depend on the combination of several lines whose frequencies cannot be perfectly aligned for each passenger journey. We present a new estimation of the expected waiting for passengers to improve the accuracy of the passenger waiting time costs. The model is originally formulated as a MINLP and it is reformulated as a MILP that can be easily solved to global optimality. Further, we explicitly consider the uncertainty of passenger demand in the optimization process by formulating stochastic and robust optimization models, respectively. The performance of the stochastic and robust optimization models is tested under various passenger demand scenarios in a bi-directional autonomous minibus line operating in Frankfurt, Germany. Our analysis shows that a stochastic optimization design has the best on-average performance and a robust design the most stable performance.
Integrating Public Transportation and Shared Autonomous Mobility for Equitable Transit Coverage: A Cost-Efficiency Analysis in Allegheny County
Allante Whitmore (email@example.com), Carnegie Mellon UniversityShow Abstract
Constantine Samaras, Carnegie Mellon University
Chris Hendrickson, Carnegie Mellon University
H. Scott Matthews, Carnegie Mellon University
Gabrielle Wong-Parodi, Stanford University
As new transportation technology emerges in the form of shared automated mobility, transit agencies should consider how integrating autonomous vehicles and shuttles into the existing transit system affects equity. Operation and acquisition costs for shared, automated mobility modes managed by public transit agencies are uncertain as very few deployments have occurred to date. This study identifies unmet service need based on transit dependence and sociodemographic information to perform a cost analysis on the operation of shared autonomous vehicles (SAVs) and autonomous shuttles as a part of a public transit system in southwestern Pennsylvania. The results suggest it is feasible to operate SAVs and shuttles into a public transit system at, on average, lower costs than buses. Lower operating costs and ease of implementation reduces the entry barrier for agencies. For the public transit system used as a case study, transit coverage improved for 52% of the transit-dependent population and transit service improved for 67% of the census block groups with the greatest unmet need.
Using BEAM Software to Simulate the Introduction of On-Demand, Automated, And Electric Shuttles for Last Mile Connectivity in Santa Clara County
Gary Hsueh, CHS Consulting GroupShow Abstract
David Czerwinski, San Jose State University
Cristian Poliziani, University of Bologna
Despite growing interest in low-speed automated shuttles, pilot deployments have only just begun in a few places in the U.S., and there is a lack of studies that estimate the impacts of a widespread deployment of automated shuttles designed to supplement existing transit networks. This project estimated the potential impacts of automated shuttles based on a deployment scenario generated for a sample geographic area: Santa Clara County, California. The project identified sample deployment markets within Santa Clara County using a GIS screening exercise; tested the mode share changes of an automated shuttle deployment scenario using BEAM, an open-source beta software developed at the Lawrence Berkeley National Laboratory to run traffic simulations with MATSim; elaborated the model outputs within the R environment; and then estimated the related impacts. The main findings have been that the BEAM software, despite still being in its beta version, was able to model a scenario with the automated shuttle service: this report illustrates the potential of the software and the lessons learned. Regarding transportation aspects, the model estimated automated shuttle use homogeneously in the county, with a higher rate of use in the downtown San José area. The shuttles would be preferred mainly by people who had been using gasoline-powered ride hail vehicles for A-to-B trips or going to the bus stop, as well as walking trips and a few car trips directed to public transport stops. As a result, the shuttles contributed to a small decrease in emissions of air pollutants, provided a competitive solution for short trips, and increased the overall use of the public transport system. The shuttles also presented a solution for short night trips—mainly between midnight and 2 am—when there are not many options for moving between points A and B. The conclusion is that the automated shuttle service increases accessibility to public transit as well as providing a good solution in certain contexts.
Prioritizing Bus Routes for Electrification: A GIS-based Multi-Criteria Analysis Considering Operational, Environmental and Social Benefits and Costs
Behnam Davazdah Emami, University of MinnesotaShow Abstract
Ying Song, University of Minnesota
Alireza Khani, University of Minnesota
During the past decade, the increasing amount of greenhouse gases because of fossil fuel consumption has caused humans to investigate for an alternative, Eco-friendly fuel as an effective policy to reduce air pollution and environmental problems thereof. The electrification of bus transit systems is today recognized as one of the practical solutions to achieve this goal. However, due to the limitation of electric buses and lack of charging infrastructure in urban areas, adopting the electric bus systems is not feasible in the short term. Therefore, planning an integrated strategy to implement this transformation is required to maximize the benefits and minimize the costs. This study applies a GIS-based Multi-Criteria Decision Analysis approach to determine the most suitable bus lines to convert from the existing diesel-powered system into an electric bus system. This framework appraises not only the characteristics of bus lines but also the possibility of deploying charging infrastructures in bus terminals. We use 14 criteria to evaluate several aspects of the electrification of bus transit systems from various perspectives. The Analytic Hierarchy Process(AHP) and the Technique of Order Preference Similarity to the Ideal Solution(TOPSIS) are employed to determine the criteria weights and route ranking, respectively. The results of applying the proposed approach on the bus network of Twin Cities, MN, USA is presented as a case study, which identifies the top 10 bus routes under different scenarios.
Robust Electric Bus Coordinated Charging Scheduling for a Hybrid Charging System
Run Dong, Southeast UniversityShow Abstract
Di Huang, Southeast University
Zhiyuan Liu (firstname.lastname@example.org), Southeast University
The remarkable increase in electric buses (EBs) is accelerating the process of urban electrification. This paper innovatively proposes a tailored coordinated bus charging scheduling approach for the hybrid charging station, which allows plug-in charging and battery swapping simultaneously. A deterministic optimization (DO) model and a robust optimization (RO) model are developed to design the EBs' overnight charging schedule, aiming to minimize the total charging cost under the time-of-use electricity prices. The DO model considers several constraints, including charging consistency and limited chargers. It assumes that the EB' s remaining power when it arrives at the station is deterministic. Based on the DO model, the RO model is formulated to cope with the uncertainty of the EB' s remaining power. This paper employs a "box + polyhedral" uncertainty set and develops the robust counterpart using an affine function. The duality theorem is used to transform the RO model into a computationally tractable formulation. Two numerical examples are conducted based on a random instance and a real-world case study of Nanjingnan Station, Nanjing, China. The results show that the cost of the RO model is higher than that of the DO model, which emphasizes the balance between cost-effectiveness and robustness. The real-world results indicate that the most cost-effective charging scheme is to provide 44% of the EBs with battery swapping service and assign the rest of them to plug-in charging mainly during the off-peak hours.
User Satisfaction and Service Quality Improvement Priority of Bus Rapid Transit in Belo Horizonte, Brazil
Yunhan Zheng, Massachusetts Institute of Technology (MIT)Show Abstract
Hui Kong (email@example.com), University of Minnesota, Twin Cities
Guillermo Petzhold, World Resources Institute
Mariana Barcelos, World Resources Institute
Christopher Zegras, Massachusetts Institute of Technology (MIT)
Jinhua Zhao, Massachusetts Institute of Technology (MIT)
The implementation of Bus Rapid Transit (BRT) is intended to provide higher-quality services and significantly improve rider satisfaction. Previous studies have investigated rider satisfaction and its determinants to improve BRT services as well as the comparison between BRT and conventional bus/rail transit regarding the rider satisfaction. However, many of previous studies have assumed that service attributes have linear and symmetric influences on rider satisfaction. Besides, to our knowledge, there is a lack of longitudinal analysis that examines the change in the performance and importance of different service aspects after BRT implementation. This paper analyzes the QualiÔnibus rider satisfaction survey data in Belo Horizonte, Brazil, and conducts longitudinal analyses to compare rider satisfaction and the importance of service attributes to overall satisfaction in three cases: two years prior to the BRT implementation, the year when the BRT was implemented, and three years after the BRT implementation. A combination of the ordinal logit regression approach and random forest approach is adopted, which enables a nonlinear relationship between service attributes and rider satisfaction, considers the impact effect size in determining the importance of service attributes, and captures the attitudinal randomness of different riders when rating their satisfaction. Our results show that “expenses with public transport” (i.e. fares) should be addressed first among all the attributes, and the improvement priorities of “speed”, “reliability” and “customer service” increased after the BRT opening. These findings can help policymakers fine-tune improvement strategies targeted at different types of services.
Design of Zonal Express Bus Services to Reduce User Travel Time and Transfers Considering Demand Diversion
Sedong Moon, Seoul National UniversityShow Abstract
Dong-Kyu Kim, Seoul National University
Shin Hyung Cho (firstname.lastname@example.org), Georgia Institute of Technology (Georgia Tech)
Zonal express is an operational strategy for express transit service that only stops in the initial and final zones of its route while skipping stops in-between. Zonal express provides a service with less travel and transfer time by aggregating trip demands with similar origins, destinations, and departure times. In this study, new zonal express routes are designed in order to reduce the travel and transfer times of transit users efficiently. While previous studies have not considered demand diversions from other transportation modes, the reduction of travel time, or the number of transfers, this study develops a methodology that considers those aspects. In order to meet the purpose, the following are conducted: 1) estimation of zonal express demand, 2) clustering of demand with similar origins, destinations, and departure times, 3) selection of candidate clusters, 4) optimization of stops and routes of zonal express, and 5) selection of zonal express routes in which the benefit from reduced time and transfers outweighs the cost. The methodology is applied to an actual transportation network in Seoul, South Korea, using smartcard, car navigation, and spatial information data. As a result, 57 zonal express routes are formed, and the total benefit and cost are about $5,500 and $4,100 during peak hours in the morning, respectively, resulting in a net benefit of about $1,400. Applying for zonal express enables to efficiently operate the public transit on the area, where having high regular demand with needs of higher level of service between OD pairs.
Two-Way Transit Signal Priority for Optimizing Transit Reliability and Speed
Wen Xun Hu, University of TorontoShow Abstract
Chuhan Chen, University of Toronto
Hirotaka Ishihara, University of Toronto
Islam Taha, University of Toronto
Amer Shalaby, University of Toronto
Baher Abdulhai, University of Toronto
Transit Signal Priority (TSP) is a broadly used traffic signal control strategy designed for reducing transit delays at signalized intersections. Like the case in Toronto, conventional active TSP strategies are usually unconditional that grant priority to all detected transit vehicles. While unconditional TSP is effective in reducing signal delays, this strategy does not guarantee an improvement in transit reliability. Moreover, a simple first-come-first-served (FCFS) logic is commonly used to handle multiple priority requests, which provides priority to a direction without considering transit performance in the other direction. Instead of focusing solely on alleviating delays, this paper proposes a dual-objective two-way TSP algorithm (D2 TSP) that optimizes both transit delays and reliability (headway variability) using deep reinforcement learning (DRL). The DRL models are enhanced with a prioritization heuristic, which chooses actions to optimize the overall performance of buses operating in opposite directions. D2 TSP is trained and tested in a microsimulation environment that models a transit route segment with reliability issues in the City of Toronto, Canada. The performance of D2 TSP is compared with three baseline scenarios, one without TSP, one with the current TSP algorithm used in the field in the City of Toronto, and one using DRL models with a FCFS logic. D2 TSP demonstrates its advantages in providing an optimal and balanced solution in reducing headway variability and travel time for both directions.
Minutes Matter: A Guide to Bus Service Reliability
Alan Danaher, WSPShow Abstract
The presentation will focus on a review of research undertaken to develop the first comprehensive guidebook on addressing fixed-route bus service reliability, culminating in Transit Cooperative Research Program (TCRP) Report 215. The guidebook provides a comprehensive assessment of the following:
· How to Define and Measure reliability
· Factors impacting fixed-route bus service reliability
· Measures to quantify unreliability
· Diagnostic tools to assess extent of reliability problems,
· Potential treatments to improve reliability
· How to develop and implement an overall agency Reliability Improvement Program
· Identification of various uses of the document.
Over 150 literature sources were reviewed, along with a comprehensive international transit agency survey. Case studies for 10 large, medium and small transit agencies were also conducted. Potential treatments considered include policy, operational, technological and physical improvement strategies. For each treatment, the causes of unreliability, companion treatments, treatment tradeoffs, expected effect, capital and operating cost and ease of implementation are presented. Treatments are also broken out into four categories: actions under agency control, administrative actions with some cost, actions with significant cost, and actions that require outside jurisdictional support.
Using GTFS to Calculate Travel Time Savings Potential of Bus Preferential Treatments
Daniel Arias, Georgia Institute of Technology (Georgia Tech)Show Abstract
Kara Todd, Georgia Institute of Technology (Georgia Tech)
Jennifer Krieger, Georgia Institute of Technology (Georgia Tech)
Spencer Maddox, Kittelson & Associates, Inc. (KAI)
Victor Haley, Georgia Institute of Technology (Georgia Tech)
Simon Berrebi, TheTimeKeepers
Kari Watkins, Georgia Institute of Technology (Georgia Tech)
Dedicated bus lanes and other transit priority treatments are a cost-effective way to improve transit speed and reliability. However, creating a bus lane can be a contentious process that requires justification, both to the public and for frequently competitive federal grants. Additionally, more complex bus networks likely have unknown locations where transit-priority infrastructure would provide high value to riders. This analysis presents a methodology for estimating the value of bus preferential treatments for all segments of a given bus network. It calculates the passenger-weighted travel time savings potential for each inter-stop segment based on schedule padding. The input data, ridership data and GTFS trip-stop data are universally accessible to transit agencies. This study examines the 2018 Metropolitan Atlanta Rapid Transit Authority bus network and identifies a portion of route 39 on Buford Highway as an example candidate for a bus lane corridor. The results are used to evaluate the value of time savings to passengers, operating cost savings to the agency, and other benefits that would result from implementing bus lanes on Buford Highway. This study does not extend to estimating the cost of transit priority infrastructure or recommending locations based on traffic flow characteristics. However, it does provide a reproducible methodology to estimate the value of transit priority treatments and identify locations with high value, all using data that is readily available to transit agencies. Conducting this analysis provides a foundation to begin the planning process for transit priority infrastructure.
Estimating Transit Vehicle Dwell Times at Bus Stops
Taqwa Alhadidi, Al-Ahliyya Amman UniversityShow Abstract
Hesham Rakha, Virginia Polytechnic Institute and State University (Virginia Tech)
This work presents a quantitative approach to estimate the total time spent in the vicinity of a bus stop including the deceleration time, the boarding and alighting time (developed in an earlier study), the acceleration time, and re-entry time (time required to merge into the adjacent lane). Different statistical models were used to compute the deceleration, acceleration and merge times. Typical deceleration and acceleration levels were computed using kinematic equations that were then used to compute both the deceleration and acceleration times. The adopted method to estimate both the deceleration time and the acceleration time was validated utilizing transit data from Blacksburg Transit (BT) using the mean absolute percentage error (MAPE) and root mean square error (RMSE). The MAPE and RMSE values were calculated to be 0.3% and 13.3% for the deceleration time and 0.42% and 2.72% for the acceleration time, respectively. The re-entry time was estimated to be a function of the adjacent roadway traffic density using both a multiple linear regression and Bayesian regression approach. Both methods showed consistency in estimating the merge-time model coefficients. The proposed models can be integrated with transit applications to estimate transit vehicle travel times.
A Framework for Reliability-Sensitive Real-Time Bus Travel Time Prediction
Ryan Williams, University of TorontoShow Abstract
Amer Shalaby, University of Toronto
Surface transit systems face many challenges in their operation, which can result in poor schedule adherence. These challenges include traffic congestion, on-road obstructions or emergencies, compounded delays from traffic signals, and bunching. Passenger information systems that predict arrival times using real-time data from location tracking devices on transit vehicles can reduce the inconvenience caused by schedule deviations. However, real-time location data streams are often noisy, incomplete or inaccurate, requiring special consideration in real-time prediction applications. Additionally, transit may operate in conditions of high or low service reliability, which may require different treatments. This study proposes and tests a real-time prediction framework that uses measures of both service reliability and data reliability/quality to characterize conditions while making predictions sequentially and leveraging a variety of Machine Learning methods. The tests performed show that the proposed framework offers distinct advantages, while highlighting shortcomings and potential for future research.
A Study on the Commuters’ Perception of Air-Conditioned Public Bus Service: A Case Study of Kolkata
Saptarshi Sen (email@example.com), Indian Institute of Engineering Science and Technology (IIEST) ShibpurShow Abstract
Sautrik Chaudhuri, Jadavpur University
Sudip Roy, Indian Institute of Engineering Science and Technology
Passenger perception is an important aspect in measuring the prosperity of any public transport system. In most cases, the service quality of a public transport system is measured by employing indicators from the traffic engineering point of view. But often, the actual perception of the passengers may not conform to these results of the technical service level indicators. This study aims to identify the most important factors that affect the passenger satisfaction of the service provided by the public buses and determine the socio-economic characteristics of the passengers that influence the level of satisfaction. Cross tabulation analysis, followed by Spearman’s correlation analysis and Chi square testing techniques have been utilized in the process. Premium (Air Conditioned) public bus route service based in Kolkata, India has been taken up as the case study to assess its service quality from the traffic engineering point of view as well as through the passengers’ perception responses. Interpretation of the results have yielded the Waiting Time to be the most important parameter influencing the perception of the AC bus service. One of the reasons which is directly influencing the passenger perception is the passenger tolerance level to delay during journey. The other possible reasons behind such dependence have been explored and the significant relations have been established.
MAVIS: Trial of 3 Assistive Technologies To Make Public Buses Easier To Use For Persons With Disabilities
Stephen Robinson, Land Transport Authority SingaporeShow Abstract
This paper describes and presents the results of a trial of 3 assistive technologies which help make it easier for Persons with Disabilities (PWD) to use public buses. The assistive technologies were t-loop, external speakers, and a smartphone app, called MAVIS, that was specifically tailored for PWDs and provides them personalised journey information. The visually impaired or wheelchair user firstly inputs their desired trip into the app. The smartphone then communicates with the bus Fleet Management System so that the bus driver of the appropriate bus is forewarned on their driver console that a special user will be boarding or alighting at the next stop. The appropriate bus will also make an external audio announcement of its service number and destination at the boarding stop of visually impaired passengers, allowing them to locate and board the bus easily. The equipment was installed on 3 public buses in Singapore and ran successfully for 6 months. 96% of the PWD trial respondents stated that MAVIS would encourage them to take buses more often. The trial demonstrates how a Smartphone app can interact with a bus fleet management system to better empower PWDs. It also illustrates how government agencies, private industry, and user group organisations can collaborate together to develop and test innovative new solutions.
Integrated Scheduling Optimization Model with Multi-Type Bus Transit Service Patterns Considering Emissions
Jiaxin Ma, Beijing Jiaotong UniversityShow Abstract
Xumei Chen (firstname.lastname@example.org), Beijing Jiaotong University
Xiaomi Han, China Academy of Transportation Sciences
Lei Yu, Texas Southern University
Recently traffic problems such as congestion and emission have been increasing. The transit travel is considered to be one of the effective ways to relieve these problems. The attractiveness of transit travel can be improved by integrating scheduling strategies with multi-type service patterns. Therefore, a study on the integrated scheduling strategies that combine local services, skip-stop services, and short-turning services is conducted in this paper. In order to achieve the objectives of this study, two different integrated service patterns are designed. Based on the analysis of travel choice and bus emissions, the integrated scheduling models with the objective of minimizing the total costs in consideration of passengers, transit agencies, and the environment are developed. A real-world case of Bus Route 4 in Beijing is studied. The costs of the proposed strategies under the two integrated service patterns are compared with those of local services only. The results show that the total costs of two integrated service patterns are reduced significantly. Besides, although the emissions costs of the whole fleet under these patterns increase due to the frequencies’ improvement, the reduction of emissions costs per bus-kilometer exceeds 15%. Moreover, the travel time costs, especially the in-vehicle time costs, are a decisive factor in the optimization of total costs. The finding can be used by transit operation agencies to select the preferred integrated scheduling strategy and optimize the targeted service quality.
Bus Network Redesigns and Public Transit Equity Analysis: Evaluating System-wide Changes in Richmond, Virginia
Haijing Liu, University of Texas, AustinShow Abstract
Seth LaRue, University of Texas, Austin
Raviya Mysorewala, University of Texas, Austin
Mashrur Rahman, University of Texas, Austin
Timothy McCarthy, University of Texas, Austin
Alex Karner (email@example.com), University of Texas, Austin
Public transit agencies around the world are increasingly using bus network redesigns (BNRs) to reverse ongoing ridership declines, but little is known about the equity impacts of these redesigns on vulnerable populations most likely to use transit to meet their daily needs. Despite Federal Transit Administration requirements for public transit agencies to assess the equity impacts of major service changes (like BNRs), analysis results are often perfunctory and unsatisfying. The academic literature has also proposed and evaluated many different performance measures in the context of equity evaluations. In this paper, we investigate the equity impacts of a BNR undertaken in Richmond, Virginia. Using multiple different performance measures including service area and accessibility analyses shows that the redesign is largely equitable but baseline levels of accessibility for vulnerable groups remain low. These methods demonstrated here can be employed by agencies considering BNR implementation.
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