<?xml version="1.0" encoding="utf-8"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>TRB Publications Index</title><link>http://pubsindex.trb.org/</link><atom:link href="http://pubsindex.trb.org/common/TRIS Suite/feeds/rss.aspx?tc=NN%3AAeghb" rel="self" type="application/rss+xml" /><description></description><language>en-us</language><copyright>Copyright © 2015. National Academy of Sciences. All rights reserved.</copyright><docs>http://blogs.law.harvard.edu/tech/rss</docs><managingEditor>tris-trb@nas.edu (Bill McLeod)</managingEditor><webMaster>tris-trb@nas.edu (Bill McLeod)</webMaster><image><title>TRB Publications Index</title><url>http://pubsindex.trb.org/Images/PageHeader-wTitle.png</url><link>http://pubsindex.trb.org/</link></image><item><title>Bayesian Network Investigation of Passengers with Disabilities’ Satisfaction with Public Bus Transportation</title><link>http://pubsindex.trb.org/view/2659297</link><description><![CDATA[Public transportation plays a vital role in promoting environmental sustainability and providing convenient transportation for the public. However, individuals with disabilities encounter significant challenges while using public transportation, necessitating an evaluation of their satisfaction levels to address the barriers they face and ensure social equality. Therefore, in this study, a questionnaire survey was conducted on people with disabilities using public bus transportation in Istanbul, Türkiye, and Bayesian network (BN) analysis was used to identify the most relevant factors affecting passenger satisfaction. Based on the findings, increasing bus frequency, improving accessibility, and adequacy of spaces designated for passengers with disabilities, and enhancing security measures are recommended. This study’s contribution lies in introducing a BN model to visualize probabilistic reasoning among factors, offering scenarios to reduce dissatisfaction levels, and identifying key factors affecting passenger satisfaction, demonstrating practical implications. In particular, the results provide a framework that can guide policy makers and transportation providers in translating statistical findings into concrete improvements in accessibility, service reliability, and passenger safety, enhancing the real-world travel experiences of people with disabilities.]]></description><pubDate>Tue, 27 Jan 2026 09:19:18 GMT</pubDate><guid>http://pubsindex.trb.org/view/2659297</guid></item><item><title>Pythagorean Fuzzy Decision-Making Framework for Sustainability Assessment of Intercity Bus Terminals</title><link>http://pubsindex.trb.org/view/2606621</link><description><![CDATA[Sustainability assessments of intercity bus terminals are increasingly important because of their environmental, social, and infrastructural impacts on urban systems. However, existing studies mainly focus on urban transport and often overlook tangible infrastructure aspects. This study addresses this gap by proposing an integrated sustainability assessment methodology tailored for intercity bus terminals, incorporating the novel “Tangibles” dimension alongside economic, environmental, and social pillars. A hybrid multi-criteria decision-making (MCDM) framework is developed, combining Pythagorean Fuzzy Stepwise Weight Assessment Ratio Analysis (PF–SWARA) and Pythagorean Fuzzy Technique for Order Preference by Similarity to Ideal Solution (PF–TOPSIS) to handle uncertainty and subjectivity in expert evaluations. The methodology is applied to seven intercity bus terminals in Istanbul, Türkiye. The results reveal that safety and security-related criteria received the highest importance weights, highlighting the critical role of secure infrastructure in sustainable terminal evaluation. Sensitivity and comparative analyses confirm the robustness and adaptability of the proposed model. This study contributes a novel decision support tool for sustainable transportation infrastructure planning and offers practical guidance for terminal development policies. Future research may explore applying the model in different geographic contexts and extending the analysis with alternative distance metrics.]]></description><pubDate>Mon, 06 Oct 2025 16:08:16 GMT</pubDate><guid>http://pubsindex.trb.org/view/2606621</guid></item><item><title>Effects of Price on Transport Equity: New Evidence from Long-Distance Travel in Vietnam</title><link>http://pubsindex.trb.org/view/2587119</link><description><![CDATA[This paper investigates the impact of price on transport equity in Vietnam. Utilizing data from a comprehensive survey of 2754 passengers who selected passenger cars, intercity buses, railways, or airplanes, the study conducts inequity indicator-based analyses to examine variations in fare (or price for passenger cars) equity across these long-distance travel modes. The findings reveal that intercity buses offer more equitable fares compared to alternative options, highlighting the significant role fare equity plays in mode choice preferences. Specifically, passengers are more likely to choose intercity buses over railways and airplanes because of their more equitable fare structures. In contrast, regional rail services exhibit considerable horizontal inequity, as their fares are generally more expensive than those of intercity buses and even passenger cars. In addition, fare equity varies by region within Vietnam. Notably, both intercity buses and rail services are less attractive in the Northern Midlands and Mountains because of high ticket prices, reflecting regional spatial inequities. This study provides valuable insights into how fare equity influences mode choice for long-distance travel in Vietnam and offers guidance for fare policy and transportation planning by emphasizing the importance of equitable fare structures.]]></description><pubDate>Mon, 11 Aug 2025 16:30:52 GMT</pubDate><guid>http://pubsindex.trb.org/view/2587119</guid></item><item><title>Implementation of the National Intercity Bus Atlas</title><link>http://pubsindex.trb.org/view/2577107</link><description><![CDATA[This report documents the purposes and methods of implementing and maintaining the National Intercity Bus Atlas, an online interactive map and database of the nation’s intercity bus network. The report provides (1) a detailed account of data collection, training, and engagement activities used to instruct transportation service providers on the benefits of having their data on the Intercity Bus Atlas and (2) instructions on how to submit data using General Transit Feed Specification (GTFS), a user-facing platform for presenting transit schedule and route information. Further, the report documents potential applications of the Intercity Bus Atlas data in planning and policymaking. The report will be useful to state department of transportation (DOT) planners and intercity bus service providers seeking to develop and maintain the interactive online atlas of intercity bus transit services within the United States.]]></description><pubDate>Mon, 21 Jul 2025 09:59:53 GMT</pubDate><guid>http://pubsindex.trb.org/view/2577107</guid></item><item><title>Causal Graph Discovery for Urban Bus Operation Delays: A Case Study in Stockholm</title><link>http://pubsindex.trb.org/view/2499458</link><description><![CDATA[Bus delays significantly affect urban public transportation by reducing operational efficiency and incurring high costs. Understanding the causes of these delays is essential for developing targeted mitigation strategies. While traditional research focuses on correlation-based analysis, it often fails to uncover the underlying causal mechanisms. This study examines various causal graph discovery algorithms combined with structural equation models (SEMs) to infer the causal relationships among factors that affect bus delays. These algorithms generate causal graphs for bus delays, revealing the interrelations and impacts of various operational factors. SEM is used to quantify the causal effects. This study evaluates the performance of these algorithms from the perspectives of both the statistical data fitting and the causal relationships generated. A case study is conducted using General Transit Feed Specification (GTFS) data from frequent bus routes in Stockholm, Sweden. The validation results demonstrate the effectiveness of data-driven causal discovery models in identifying causal links, particularly when combined with domain knowledge. The empirical analysis shows the complexity of factors contributing to bus delays, emphasizing the necessity of integrating causality into bus delay analysis. For example, a high correlation between origin delay and bus arrival delay (coefficient?=?0.63) does not indicate direct causation, and a strong causation between dwell time and arrival delay does not imply a higher correlation (coefficient?=?0.12). Comparing variable importance with linear regression (LR) reveals notable differences; origin delay, which is often overlooked by previous studies, is significant in the causal graph model (standardized coefficient?=?0.601) but ranks much lower in LR (standardized coefficient?=?0.003). These insights underscore the importance of automated, data-driven causal discovery in enhancing decision-making processes and improving the efficiency and reliability of transit services.]]></description><pubDate>Thu, 06 Feb 2025 15:45:28 GMT</pubDate><guid>http://pubsindex.trb.org/view/2499458</guid></item><item><title>Why Did the Inflection Point of Bus Ridership Occur in China in 2014? Origins from the Effect of the Ride-Hailing Service</title><link>http://pubsindex.trb.org/view/2483217</link><description><![CDATA[Although rapid construction of public transit infrastructure has continued in China in recent years, there has been a significant decline in bus ridership since 2014. To investigate this trend, we conducted a statistical analysis for 24 cities in China, using fixed-effects panel regression to examine the relationships between bus ridership and significant factors from 2000 to 2019. Our analysis revealed that the emergence of ride-hailing services was probably the most significant contributor to the decline in bus ridership, reducing it by 33% from 2014 to 2019. This finding suggests that ride-hailing services have caused an inflection point in bus ridership. Furthermore, we found that gross domestic product (GDP) negatively moderates the effect of ride-hailing services on bus ridership, with cities of lower economic status experiencing a more significant decline in ridership, owing to the development of ride-hailing services. Our research provides valuable insights for policymakers and relevant departments when addressing transit ridership loss and transit system development issues.]]></description><pubDate>Fri, 27 Dec 2024 15:28:30 GMT</pubDate><guid>http://pubsindex.trb.org/view/2483217</guid></item><item><title>Development of a Comprehensive Safety Evaluation Mechanism for the Highway Bus Industry</title><link>http://pubsindex.trb.org/view/2446939</link><description><![CDATA[A suitable mechanism for evaluating the safety of the highway bus industry is crucial for ensuring public transportation safety in a country. In this study, we have combined indices from the Compliance Safety Accountability (CSA) program of the Federal Motor Carrier Safety Administration (FMCSA) in the US, the safety evaluation of renting buses in Japan, and some existing safety evaluation methods in Taiwan to develop a new safety evaluation mechanism for the highway bus industry. This paper introduces a two-stage decision making approach that includes the use of fuzzy analytic hierarchy process (Fuzzy AHP) and machine learning techniques such as decision trees, support vector machines, and random forests to develop this mechanism. The data used in this research were collected from the internet and directly from highway bus transportation companies. We calculated the safety performance of each company and assigned them different safety ranks. Compared with the causes of accidents in Taiwan, the results of this study showed that work hours, driver fitness, and administrative penalties are the three most important sub-attributes that affect the safety rank of the company.]]></description><pubDate>Thu, 31 Oct 2024 09:20:25 GMT</pubDate><guid>http://pubsindex.trb.org/view/2446939</guid></item><item><title>Pay and Working Conditions in the Long-Distance Truck and Bus Industries: Assessing for Effects on Driver Safety and Retention</title><link>http://pubsindex.trb.org/view/2441686</link><description><![CDATA[This Consensus Study Report considers how compensation methods and working conditions in the long-distance for-hire trucking and intercity bus industries may affect the safety performance and retention of industry drivers. To conduct the study, the National Academies appointed an interdisciplinary committee whose members possess expertise in commercial motor carrier operations, safety regulation, transportation economics, statistics, freight planning, and transportation logistics. The report is organized into seven chapters. Chapter 1 provides an introduction. Chapter 2 provides background on the long-distance for-hire truckload (TL) sector and its operations and describes the truck driver workforce. It also describes the regulatory environment for the long-distance trucking industry by providing an overview of the main bodies of pertinent federal regulations governing safety and labor standards. Chapter 3 also provides background by describing the types of compensation used in the long-distance TL sector, distinguishing between piece rate forms of compensation and non-piece rate forms. The chapter also describes the work requirements and conditions experienced by drivers in the long-distance TL sector. Chapter 4 focuses on driver retention in the long-distance TL sector and explains the role that compensation methods, working conditions, and complex economic forces can have on the rates of driver retention and turnover. Chapter 5 reviews the research and empirical evidence about how compensation methods, non-wage rewards, and work conditions can affect safety in the long-distance TL sector. Issues associated with driver compensation, safety, and retention in the intercity bus industry are considered in Chapter 6, albeit to only a limited degree because of a dearth of information. Chapter 7 summarizes the key conclusions from the study and contains the committee’s recommendations pertaining to follow-on research. This chapter concludes with ideas for research and data collection that the Federal Motor Carrier Safety Administration (FMCSA) could pursue to further the recommendations.]]></description><pubDate>Sat, 19 Oct 2024 16:17:37 GMT</pubDate><guid>http://pubsindex.trb.org/view/2441686</guid></item><item><title>Intercity Buses: Planning for a Post-Pandemic Paradigm</title><link>http://pubsindex.trb.org/view/2338705</link><description><![CDATA[Intercity buses have struggled to make a comeback after the COVID-19 pandemic. What changes do operators need to implement to navigate the post-pandemic world and lure travelers back? In this article, the author offers insights into the complexities facing the intercity bus segment of the transportation industry. Topics discussed include electrifying buses, bus stop locations and bus stop regulations, and street design and the allocation of curb space.]]></description><pubDate>Tue, 20 Feb 2024 09:14:09 GMT</pubDate><guid>http://pubsindex.trb.org/view/2338705</guid></item><item><title>In-Depth Appraisal of Bus Transport Services for Sustainability Performance: A Cost–Benefit Analysis Approach</title><link>http://pubsindex.trb.org/view/2237207</link><description><![CDATA[Public transport is arguably considered the backbone of today’s urban mobility ecosystem and is generally regarded as an important element of the sustainable mobility paradigm. As systems, they comprise vast societal investment owing to the infrastructures and operations required to provide the designated service. As projects, public transport systems have financial, societal, and environmental impacts that ought to be assessed through the scope of sustainability. Through sustainability, future generations’ financial, societal, and environmental needs are not compromised to meet the present generation’s needs. Thus, sustainability assessments can assist decision makers in perceiving the impacts and implications of an existing or under-consideration system on society and deciding on corrective actions. For the case of public transport systems, such assessments can assist in evaluating the expenditure distribution of the system and suggest actions that could maximize welfare gains under financial, social, and environmental criteria. Within this scope, the current paper proposes a methodological framework for unraveling transport systems’ sustainability to reveal their spatiotemporal dependencies. The study proposes a cost–benefit analysis framework where a public transport system is segmented and assessed into three levels: stops, lines, and administrative areas. Stop and line levels incorporate essential characteristics allowing their independent evaluation. The assessment of administrative areas aggregates characteristics from previous levels, spatially distributing the public transport system’s evaluation. By incorporating additional sociodemographic data, the administrative area level’s assessment links the evaluated transport system to societal characteristics, enhancing the decision maker’s perspective. The framework is showcased with Nicosia’s public bus transport system.]]></description><pubDate>Thu, 31 Aug 2023 09:32:19 GMT</pubDate><guid>http://pubsindex.trb.org/view/2237207</guid></item><item><title>Machine Learning Applied to Public Transportation by Bus: A Systematic Literature Review</title><link>http://pubsindex.trb.org/view/2138543</link><description><![CDATA[Machine learning (ML) solutions have been proposed to make public transportation more attractive. Works that employ ML in bus transportation focus on various problems, such as travel time prediction or passenger flow prediction. These solutions look to improve elements of transportation services, such as the availability of information on passengers’ travel time and the reliability and regularity of the service. An analysis of the solutions proposed in the literature for public transportation by bus can reveal opportunities for data scientists and transportation professionals, and highlight problems that have been only slightly explored. In addition, mapping information about modeling these solutions (e.g., types of data produced by devices on the transportation network, which can be used in modeling a solution) could help beginner data scientists develop public transportation solutions. Transportation professionals can benefit from an overview of possible transportation solutions to improve transportation problems and direct government agency efforts to implement these solutions. This paper presents a survey of ML-based solutions for public bus transportation and details the modeling of these solutions (e.g., data types, ML algorithms). In addition, the problems tackled in the literature are categorized into four themes, and the solutions proposed to deal with them are schematized, highlighting problems that are little explored.]]></description><pubDate>Mon, 20 Mar 2023 09:35:40 GMT</pubDate><guid>http://pubsindex.trb.org/view/2138543</guid></item><item><title>Investigating the Relationship Between Access to Intercity Bus Transportation and Equity</title><link>http://pubsindex.trb.org/view/1943653</link><description><![CDATA[Intercity bus transportation provides essential public transit service, mainly to long-distance passengers and residents of rural areas. Although the intercity bus system can be beneficial to increase equity by providing such services to low-income people from remote rural areas, it suffers from a problem. The problem is that the socio-demographic characteristics of those disadvantaged individuals are still not crystal clear. This study aims to examine the relationship between access to intercity bus transportation and the socio-demographic characteristics of the region. This study addresses these problems through data integration and multiple regression analysis using a combination of socio-demographic variables across the U.S. The results showed that changes in the percentages of households with zero vehicles and households with an income of less than $50,000 are significantly associated with changes in the access to intercity bus transportation, and different levels of income affect access to intercity bus transportation. Among the significant variables in the model, the number of intercity bus stops can be controlled by policymakers to optimize access to intercity bus transportation. The findings demonstrate the importance of public transit for low-income households and imply that increasing bus access could help shift the spatial distribution of poverty and create more equal and inclusive communities.]]></description><pubDate>Mon, 25 Apr 2022 15:35:02 GMT</pubDate><guid>http://pubsindex.trb.org/view/1943653</guid></item><item><title>Preferences toward Bus Alternatives in Rural Areas of the Netherlands: A Stated Choice Experiment</title><link>http://pubsindex.trb.org/view/1873850</link><description><![CDATA[Public transport in rural areas is under pressure because demand is low and dispersed. To reduce costs, flexible and on-demand services are often proposed as alternatives for conventional bus services. Conventional services are generally not suitable for rural areas, because the demand is low and dispersed. In this paper, a stated preference survey is designed to identify the preferences of rural bus users for alternative services. Other than the traditional bus, two other modes are included in this study: a demand responsive transport (DRT) service and an express bus service with bike-sharing services for last mile transport. Given the on-demand nature of these alternatives, flexibility- and reliability-related attributes are included in the stated preference survey. The results from the choice model indicate that the reliability and flexibility aspects do not have a large effect on the preference for the on-demand alternatives. Instead, cost, access and egress times, and in-vehicle time play a bigger role in individuals’ preferences toward the different alternatives. A sensitivity analysis shows that changes in the operational characteristics can make the on-demand alternatives more attractive. However, many bus users still prefer the conventional bus service over the on-demand alternatives.]]></description><pubDate>Wed, 25 Aug 2021 09:29:21 GMT</pubDate><guid>http://pubsindex.trb.org/view/1873850</guid></item><item><title>Scheduling a Bus Fleet for Evacuation Planning Using Stop-Skipping Method</title><link>http://pubsindex.trb.org/view/1867503</link><description><![CDATA[Sudden passenger demand at a bus stop can lead to numerous passengers gathering at the stop, which can affect bus system operation. Bus system operators often deal with this problem by adopting peer-to-peer service, where empty buses are added to the fleet and dispatched directly to the stop where passengers are gathered (PG-stop). However, with this strategy, passengers at the PG-stop have a long waiting time to board a bus. Thus, this paper proposes a novel mathematical programming model to reduce the passenger waiting time at a bus stop. A more complete stop-skipping model that including four cases for passengers’ waiting time at bus stops is proposed in this study. The stop-skipping decision and fleet size are modeled as a dynamic program to obtain the optimal strategy that minimizes the passenger waiting time, and the optimization model is solved with an improved ant colony algorithm. The proposed strategy was implemented on a bus line in Harbin, China. The results show that, during the evacuation, using the stop-skipping strategy not only reduced the total waiting time for passengers but also decreased the proportion of passengers with a long waiting time (&gt;6?min) at the stops. Compared with the habitual and peer-to-peer service strategies, the total waiting time for passengers is reduced by 31% and 23%, respectively. Additionally, the proportion of passengers with longer waiting time dropped to 43.19% by adopting the stop-skipping strategy, compared with 72.68% with the habitual strategy and 47.5% with the peer-to-peer service strategy.]]></description><pubDate>Mon, 26 Jul 2021 17:59:37 GMT</pubDate><guid>http://pubsindex.trb.org/view/1867503</guid></item><item><title>Rosa Parks: She Wouldn’t Give In, and She Wouldn’t Get Up</title><link>http://pubsindex.trb.org/view/1865305</link><description><![CDATA[On December 1, 1955, in Montgomery, Alabama, Rosa Parks took her seat in the first row behind the white section on a segregated bus. At that time Jim Crow laws reserved the bus's first 10 seats for white passengers only. The bus became crowded and the bus driver insisted the four black passengers in Rosa's row stand and make their seats available to any white riders. This brief article looks at the Montgomery Jim Crow laws related to buses, Rosa Park's decision not to give up her seat, her subsequent arrest, and the resulting Montgomery Bus Boycott led by Martin Luther King.]]></description><pubDate>Mon, 19 Jul 2021 09:40:24 GMT</pubDate><guid>http://pubsindex.trb.org/view/1865305</guid></item></channel></rss>