Transport Research International Documentation (TRID)

Organizational support in structurally isolated work environments: Experiences of New Zealand bus drivers during the pandemic

Fri, 14 Aug 2026 15:04:42 GMT

Bus driving is a structurally isolated and psychologically demanding occupation that became increasingly challenging during the COVID-19 pandemic. Previous research has largely focused on occupational stressors, with less attention given to how work demands are managed, and how organizational support is experienced and accessed in isolated work environments. This study examines how bus drivers in New Zealand managed demanding working conditions and responded to workplace support during the pandemic. This study adopted a qualitative interpretive design. Semi-structured interviews were conducted with 62 participants comprising drivers, managers, supervisors and trade union representatives across five bus operators and two unions in New Zealand. Data were analyzed using reflexive thematic analysis. Four interrelated themes emerged from the thematic analysis: intensified job demands, limited and inaccessible supervisory support, peer relationships as informal coping resources, and adaptive coping under constraint. Psychological strain developed not only from demanding working conditions, but also from how organizational support was experienced in practice. Support perceived as delayed, inconsistent or inaccessible failed to function as a meaningful resource. In response, drivers relied on peer relationships and strong personal strategies to manage the operational demands in the absence of formal organizational support. The study highlights the importance of understanding organizational support as a relational and situational process rather than a formally available resource in structurally isolated work environments. It suggests that improving occupational well-being in such work settings requires systems that are accessible, responsive and grounded in frontline work realities.

Bus and Truck Drivers from Third Countries

Thu, 30 Jul 2026 16:33:38 GMT

n recent years, the EU has grappled with a pressing challenge within its road transport sector: a severe and escalating shortage of professional commercial truck and bus drivers driven by the aging of existing drivers and the lack of sufficient young ones. The shortage of commercial drivers poses a challenge not only to the EU road transport sector but to the wider EU economy and trade. The sustainability and growth of this vital sector are at stake. The wider impact on logistics and supply chains cannot be underestimated. As the average driver’s age continues to rise, there is a pressing need for strategic interventions to attract new talent and ensure the continued functioning of essential transport services. Next to opening the profession to young and more diverse people (e.g. more women), another strategic initiative to address this challenge involves exploring global talent through the recruitment of drivers from third countries willing to work in the EU. This approach, outlined in the European Commission’s “Skills and Talent Mobility package” of November 2023, recognises that the EU's future competitiveness is closely tied to its ability to attract skilled professionals from around the world. Considering the growing demand for skilled workers, the EU acknowledges that its domestic workforce alone cannot meet this demand, making the managed legal migration of jobseekers from third countries a crucial component in addressing labour shortages. In this context, the European Commission launched this study to gain more insights into the conditions of employment of drivers from third countries in the EU and into the knowledge and skills they have. The study aims to collect information on procedures and requirements that third-country nationals encounter in EU Member States to be employed by EU operators, with a view to share good practices. In addition, this study looks at the set of skills and certificates that professional bus and truck drivers from 23 selected third countries are expected to have and compares them with the EU’s minimum requirements for professional drivers. The objective of this study is to collect and present relevant information that may inform a debate with a view to facilitate the integration of professional drivers from third countries into the EU labour market.

Association between scheduling attributes and unsafe behaviors of bus drivers: Considering unobserved heterogeneity and temporal instability

Tue, 21 Jul 2026 09:49:51 GMT

Mitigating unsafe driving behaviors among public transport drivers is vital for enhancing operational safety. Existing studies have mainly focused on identifying unsafe behaviors, whereas the role of organizational and managerial attributes, particularly shift scheduling, remains insufficiently understood. Using one year of real-world operational data from a bus company in China, this study examines how driver characteristics, scheduling attributes (work profiles and route properties), and environmental conditions are associated with unsafe driving behaviors and how these associations vary across quarters. Unsafe behaviors were classified via incidence rate ratios (IRRs) into three types: operational safety violations, impaired driving states, and regulatory non-compliance. To jointly capture fixed marginal effects, unobserved heterogeneity, and quarterly instability, a Random Parameters Logit Model with Heterogeneity in Means and Variances (RPLMV) is developed and combined with global and local temporal stability tests. This approach identifies significant fixed effect associations, two random parameters—annual safety violations ≥ 2 and age > 50 years—and five variables associated with mean and variance heterogeneity. The results reveal pronounced quarterly variability and complex association patterns arising from the interaction between scheduling conditions, subgroup sensitivities, and operating environments. These findings support an integrated management framework combines baseline controls with targeted interventions, operationalized through scheduling, route optimization, and quarter-specific safety interventions. This study contributes methodological innovation by embedding heterogeneity modeling within a temporal stability framework and offers practical guidance for precision risk management and targeted dispatch in public transport systems.

Uncovering Probabilistic Crash Risk Among Coach Drivers Using a Bayesian Network Based on Violation and Crash Records

Fri, 17 Jul 2026 08:40:49 GMT

Passenger transport is frequently associated with high-fatality crashes, highlighting the need for enhanced risk management. However, most risk-assessment approaches rely on cross-sectional data and fail to capture the cumulative nature of unsafe driving patterns. This study developed a static Bayesian network and a dynamic Bayesian network using violation and crash records from 9,894 coach drivers in Shanghai (2021–2024) to examine causal factors and cumulative crash risk. Overall, 14.75% of drivers were involved in one crash and 6.64% were involved in multiple crashes, while 24.83% committed one violation and 53.95% committed repeated violations. Violations were classified into five categories covering unsafe conditions and behavioral faults. A static Bayesian network identified a key causal pathway: License type/Company size → Passenger-transport violations → Roadway maneuver violations → At-fault crash. Sensitivity analysis showed large variability in crash probability (0.063–0.152), with no violations and consistently compliant operations as the strongest protective factors. Granger causality analysis identified habitual violation patterns (p<0.05), including improper lighting use and poor speed control, which were associated with increased subsequent crash risk. These findings informed an empirical dynamic Bayesian network, which achieved strong performance (Mean Absolute Error = 1.56%, Mean Relative Error = 19.02%) and over 80% predictive consistency. Overall, the study provides a behaviorally interpretable and temporally grounded approach for identifying high-risk drivers, enabling dynamic risk classification and supporting proactive safety-management strategies in coach-transport operations.

“It's not just a matter of getting technology into buses”: An activity-centred approach to bus drivers’ work sustainability in an age of automation

Tue, 30 Jun 2026 09:45:06 GMT

Background: In the context of current challenges facing public passenger transport, automation is presented as a leading solution for achieving more efficient, safer, and more sustainable mobility. This is reflected in the growing number of pilot projects and trials with automated buses across Europe. Yet, debates on automated public transport are often dominated by either technocentric perspectives or concerns about passenger acceptance. Objective: This study adopts a perspective that has been insufficiently considered in research on automated public transport: the viewpoint of bus drivers. This neglect has meant that drivers’ work experience and their knowledge of the issues affecting public transport remain residual. Methods: A qualitative research design was employed, involving bus drivers from a public transport company in a metropolitan area of Portugal. Discussion sessions were organised as spaces for dialogue and reflection on work activity and its potential evolution with automation. Results: Four main themes emerged, illustrating the constraints that shape drivers’ current work and how these have contributed to the deterioration of job quality. Building on this, the drivers projected their probable future work with automated buses, showing that this transition intersects with much more than technology alone. It requires attention to working conditions, occupational risks, bus scheduling, and even urban planning. Conclusions: As investment in automated public transport grows, promising to redefine drivers’ work, our results help identify key organisational and policy factors that need to be addressed to promote sustainable work and secure a worker-led just transition to automation in public transport for bus drivers.

Impact of noise on school bus drivers’ visual reaction time: An experimental approach with road safety implications Noise and Reaction Time

Tue, 30 Jun 2026 09:45:04 GMT

Background: Fast reaction time is essential for safe and effective driving. Objective: The objective of this research was to ascertain the visual reaction time of school bus drivers and the effect of additional noise on this time.Methods28 volunteer professional school bus drivers were included in the study. Each participant was in both the experimental and control groups. Vehicle simulation was used to determine the reaction time of the participants. The participants’ throttle response time was measured in the presence and absence of an 85 dBA (A-weighted decibels) supplemental noise. The Wilcoxon rank-order sign test and linear mixed-effects regression models were used for the statistical analysis. Results: The reaction time of the participants without additional noise was calculated to be 0.10 ± 0.02 (0.06–0.15 s). It was found that the noise statistically increased the reaction time of the participants. Conclusions: The additional noise in the vehicle has been shown to have a detrimental effect on the reaction time of school bus drivers, thereby impacting their cognitive functions. The findings emphasise the practical significance of noise control strategies in both occupational and transportation contexts, with the objective of enhancing safety and cognitive efficiency.

A branch-and-price algorithm for integrated optimization on vehicle and crew scheduling of electric bus system

Mon, 01 Jun 2026 09:02:35 GMT

Electric buses (EBs) play a vital role in environment protection and sustainable development. Because EBs have a limited driving range and relatively long daytime charging times, it is reasonable to redeploy drivers during charging to reduce idle time in crew schedules. Network-level vehicle and crew scheduling problems should consider labor regulations, deadheading insertions, and available time slots of vehicle usage. This paper develops a mixed integer nonlinear programming (MINLP) model to formulate this integrated optimization problem under an EB’s fast charging mode. In particular, two models are built involving two dispatching modes: a driver & EB binding mode and a freely-combined mode. A customized branch-and-price (B&P) algorithm is designed to cope with both MINLP models. Numerical tests and a real-world case study verify that the freely-combined mode reduces charging events and achieves 4.42% cost savings relative to the binding mode. In large-scale scenarios, the B&P algorithm exhibits superior computational efficiency and solution quality compared to Gurobi and a grouping genetic algorithm (as another benchmark). Finally, sensitivity analysis shows that the network integration optimization scheme can reduce the operation cost by 2.83%-11.94%. EB acquisition cost (54.44%-71.40%) and charging cost (6.81%-18.85%) are the key factors affecting the total cost, and their fluctuations will significantly affect the optimal scheduling scheme.

Functional requirements for automated bus transit systems based on human driver tasks

Wed, 13 May 2026 17:01:18 GMT

Driven by advancements in automation and connectivity, this paper explores the development of automated Public Transportation (PT) systems. This study addresses the critical role of human bus drivers in ensuring safety, accessibility, and service quality, examining how their diverse responsibilities can be translated into a modular technical framework. By analyzing legal frameworks in Europe and North America and conducting expert interviews with bus drivers in Munich, Germany, we identify the main tasks human drivers perform, including passenger safety monitoring, passenger assistance, communication, vehicle control, traffic monitoring, and service operation. From these tasks, we derive a conceptual framework of functional requirements organized within a Sense-Plan-Act (SPA) model and a Service-Oriented Architecture (SOA). We propose a Public Transport Control System that integrates requirements into a high-level architecture, providing a foundation for developing systems that can operate safely and efficiently while maintaining high service quality and meeting legal standards.

Headway regularity as an attribute for classifying bus drivers

Thu, 30 Apr 2026 16:38:38 GMT

Different indices have been proposed in the literature to characterize headway regularity. These metrics aggregate the headway variability for a service, but none can be directly associated with a specific driver. This paper seeks to understand drivers' influence on a service's regularity. To do so, we propose four regularity indices related to a driver's performance and use the Hierarchical Clustering Analysis method to generate a classification of drivers according to their contribution to the headway regularity during the operation of a service. We characterize each class based on the driver's attributes such as age, years of experience as a driver, and years in the bus company, and those attributes associated with the operation, such as number of services per day and period of the day. The results show consistency in the classification obtained, with nearly 90% of drivers remaining in the same regularity classes regardless of the index.

Preferences for Choosing Automated Buses: A Discrete Choice Experiment

Mon, 27 Apr 2026 15:01:15 GMT

A Discrete Choice Experiments (DCE) was conducted to explore consumer preferences for different transportation modes (car, robo-taxi, bus or bicycle) and their willingness to pay for attributes including travel time, staff presence and role, automated driving capabilities, electric vehicles, and on-demand services. Based on 14,190 responses from 2,004 participants, the analysis showed that the presence of a human driver significantly increased the likelihood of choosing the bus over other modes. Remote supervision did not significantly increase bus choice compared to scenarios with no staff. The availability of electric buses significantly increased the proportion choosing to travel on unstaffed buses.

Identifying Leading Indicators of Bus Collision Rates through Temporal and Spatial Analysis of Operator Behaviors Within the Washington Metropolitan Area Transit Authority Compact Area

Fri, 10 Apr 2026 16:00:16 GMT

This study aims to establish leading indicators for the bus collision rate by analyzing operator behaviors and their relationship to collision incidents within the study area. Using two comprehensive datasets—the National Transit Database (NTD) reportable bus collision dataset and the bus video dataset—this research investigates temporal and spatial correlations between bus operator behaviors and bus collisions. The Auto-Regressive Integrated Moving Average with Exogenous Variables (ARIMAX) model is employed for temporal analysis to identify the relationship between bus video events and the collision rate, while spatial analysis uses the Geographically Weighted Regression (GWR) model to reveal localized patterns of risky bus operator behaviors, and their correlation with bus collisions, with the built environment considered. The ARIMAX model identifies the number of bus video events as a leading indicator of the bus collision rate. The GWR model identifies that certain bus operator behaviors such as late response to risky situations, incomplete stop at a stop sign, and eating food or drinking while the vehicle was in motion are significantly associated with the bus collision rate in certain areas, while pedestrian and cyclist interactions show high localized positive coefficients over the widest area. These findings underscore the importance of targeted safety interventions and continuous driver training to enhance transit safety. By integrating advanced statistical models, this study provides actionable insights for developing proactive measures to mitigate bus collisions and improve overall transit safety.

Mixed Methods Case Study of Bus Operator Work Preferences at the Chicago Transit Authority

Thu, 26 Mar 2026 13:38:05 GMT

Transit agencies in the U.S. have faced significant challenges in recruiting and retaining bus operators, both before and after the COVID-19 pandemic. Bus driving often involves working long hours and performing physically demanding tasks involved with operating a large commercial vehicle, while constantly interacting with the public. The physically and mentally demanding nature of the job, coupled with increased personal safety concerns, further exacerbates retention issues. Additionally, a restrictive working environment and a lack of scheduling flexibility, coupled with competitive opportunities in ride-hailing and delivery services, contribute to high turnover rates. Existing research has not sufficiently addressed the role of work scheduling in affecting bus operators’ quality of life and retention rates. In this study, we conducted focus group studies with 213 Chicago Transit Authority bus drivers and analyzed their stated preferences about work schedule characteristics, combining this analysis with revealed preference data on duty selection to gain comprehensive insights into shift desirability. Overall, drivers’ top priorities include getting enough pay hours, reducing the incidence of split shifts, having sufficient recovery time built into the schedule, avoiding relief points outside of garages, and getting weekends off. Relief points, often called reliefs, are the points where operators start or end their shifts. These findings are translated into a series of scheduling recommendations to improve bus operators’ quality of life. Specifically, the recommendations focus on increasing the use of 4-day work weeks and rostering to allow for greater consistency, more days off, and longer duties for operators.

Behavioural Factors Contributing to Offences Committed by Bus Crews in Sri Lanka's Private Bus Transport Sector

Mon, 23 Mar 2026 15:20:59 GMT

Behavioural issues among bus crews negatively impact passenger satisfaction, safety, and the overall efficiency of the public transport system. Bus crews in the private bus transport sector frequently commit offences, leading to public complaints. This study investigates the behavioural factors contributing to offences committed by both drivers and conductors in inter-provincial private bus transport in Sri Lanka. Using a quantitative research approach, a questionnaire survey was conducted to identify these behavioural factors through exploratory factor analysis. The findings reveal four key factor components: workplace conditions and operational pressures, deficiencies in crew management and training, employee welfare challenges, and stressors and behavioural tendencies. These factors play a significant role in influencing crew behaviour and leading to offences. This study provides valuable guidance for transport policymakers and both government and private sector stakeholders to enhance the quality of bus transportation and implement measures that improve the well-being of bus crews and passengers.

The effect of an active steering system on city bus drivers’ muscle activity

Wed, 18 Mar 2026 09:00:17 GMT

City bus drivers spend hours driving under time pressure, in congested traffic and in a monotonous sitting position. This leads to unhealthy working conditions, especially in terms of physical and psychological stress. The aim of this study is to investigate whether an active steering system can alleviate the musculoskeletal stress involved in maneuvering a bus. Twenty bus drivers drove a city bus equipped with the Volvo dynamic steering (VDS) support system in real traffic. Steering effort was evaluated with electromyography and with a questionnaire. Compared to baseline, VDS significantly reduced the required muscle activity by on average 15–25% while turning, and up to 68% in the part of the maneuver requiring maximum effort. The bus drivers believed that VDS will help reduce neck and shoulder problems, and they expressed a desire to have VDS installed in their own bus.

Musculoskeletal disorders among bus drivers: A systematic review and meta-analysis

Wed, 18 Mar 2026 09:00:17 GMT

Bus drivers are exposed to various health, safety, and ergonomic risks, making them vulnerable to musculoskeletal disorders (MSDs). This systematic review and meta-analysis aimed to assess the prevalence of MSDs among bus drivers. This study followed PRISMA guidelines and was registered in PROSPERO (CRD42024509249). Relevant studies were identified up to February 12, 2024, through databases including PubMed, Scopus, Web of Science, ScienceDirect, SID, ISC, and Google Scholar. Heterogeneity was assessed using the I2 index, and a random-effects model was used for meta-analysis. Data analysis was performed using STATA version 14. Out of 723 initially identified studies, 22 were included in the meta-analysis. The overall prevalence of MSDs among bus drivers was 73.87% (95% confidence interval [CI] [64.37, 83.36], I2 = 98.2%, p < 0.001). Prevalence by the body region was as follows: lower back (50.22%), neck (39.88%), shoulder (38.72%), upper back (32.42%), knee (31.74%), foot (28.29%), hip/thigh (14.86%), hand (14.74%), and elbow (9.36%). MSDs are highly prevalent among bus drivers, especially in the lower back. Given the presence of various ergonomic risk factors, it is imperative to implement comprehensive strategies, including targeted training, ergonomic assessments, accessible healthcare, and effective rehabilitation programs, to manage and mitigate the progression of MSDs in this population.