Monash University, Institute of Transport Studies: World Transit Research (WTR)
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How does artificial intelligence usage affect the safety behavior of bus drivers? A double-edged sword study
No full textThis study aims to provide a framework for understanding the mechanism by which artificial intelligence (AI) usage affects the safety behavior of bus drivers through cognitive appraisal theory. We examined data from 555 bus drivers at three-time points. Our findings indicate that AI usage is positively related to both safety self-efficacy and job insecurity, which in turn are linked to safety behavior. Safety self-efficacy and job insecurity mediate the relationship between AI usage and safety behavior. Additionally, we found that trait resilience moderates the positive relationship between AI usage and safety self-efficacy, as well as the relationship between AI usage and job insecurity. Furthermore, trait resilience moderates the indirect effect of AI usage on safety behavior through safety self-efficacy and job insecurity. The results suggest that AI usage has two faces, both enhancing and impairing the safety behavior of bus drivers. These findings are crucial for management theory and practice
Electric bus fleet charging management: A robust optimisation framework addressing battery ageing, time-of-use tariffs, and energy consumption uncertainty
No full textThe large-scale adoption of electric buses offers sustainable and reliable transportation, but it poses challenges in designing appropriate charging strategies to accommodate the operation requirements of the fleets. The optimisation of those strategies is crucial to avoid disrupting daily operations due to insufficient energy for trips, aiming to minimise operational costs and grid overload because of coincident peak demand. This work introduces a robust optimisation model to provide solutions accounting for uncertainties in energy consumption, enabling operators to establish cost-effective and resilient charging plans. The model includes features such as battery ageing, time-of-use tariffs, vehicle-to-grid (V2G), and operational constraints. We propose a reformulation approach to solve the model and deal with its computational complexity. An illustrative case study is conducted using real-world data from a mid-sized city in Portugal. The findings indicate significant cost reductions through coordinated charging, with deterministic and robust models achieving 37 % and 12 % reductions, respectively, compared to a business-as-usual charging scenario. Further, V2G activities generate additional revenue, also emphasizing the importance of considering degradation costs to reduce battery capacity fade. Additionally, the effectiveness of the robust approach in addressing energy consumption uncertainty is demonstrated, offering operators a flexible method to adapt to various operational contexts and improve bus transportation service reliability
Does transit-oriented development (TOD) influence perceived safety and mode choice?
No full textTransit-oriented development (TOD) is an established urban planning principle for increasing public transport (PT) use. However, whether TOD enhances perceived safety and increases PT use remains an open question. This study analyzes the link between mode choice, perceived safety, and TOD dimensions on a large dataset covering the Greater Copenhagen area in Denmark. Using survey data and site observations, we first estimate multiple linear regression models to show which TOD dimensions enhance individuals’ perceived safety at train stations. Then, using large-scale travel survey data encompassing 21,844 trips between 2009 and 2018, including various user socioeconomic variables, we estimate a mode choice model in which TOD score and perceived safety are used as explanatory variables. Our results provide empirical evidence showing that the safety dimension of TOD significantly increases perceived safety and that perceived safety at both the home and activity ends of the trip influences the likelihood of an individual choosing PT. Only a higher TOD score at the activity end significantly increases PT use, whereas park-and-ride lots at the activity end reduce it and make cycling less attractive at both trip ends. Distance to the nearest stations/stops and service headway have a significant influence on mode choice at both ends of the trip. These results indicate that dense urban development around stations supports PT use and cycling more strongly than allocating space to park-and-ride lots. Our results are important for policymakers seeking to use TOD guidelines to increase individuals’ perceived safety and PT use in cities
The affects and emotions of everyday commutes in Kolkata: shaping women’s public transport mobility
No full textPublic transport inherently involves encounters with other people. For women, negotiating everyday overcrowded, unsafe, and unreliable conditions is a major barrier to accessing public transport mobility that triggers emotions. Using qualitative research methods – in-depth interviews and visual surveys – this study delves beyond understanding the barriers and looks at the affective realm to comprehend how affects and emotions shape accessibility, acceptability, and affordability of public transport for women in Kolkata. The disruptive affects of overcrowded, unsafe, and unreliable conditions produce emotional ordeals, increase travel time and costs, and restrict mobility. The sense of despair that emerges compels women to adjust, accept, and even opt out of overcrowded, unsafe, and unreliable public transport more often than not. This paper argues that affects, emotions, reactions, and consequences are entangled and impact the accessibility, acceptability, and affordability of public transport. The contribution of this paper lies in bringing to the fore the need for feminist inquiries into gendered mobility inequalities and the role of affects and emotions therein
Disrupted intermodality: Examining adaptation strategies to public transport e-scooter bans in Barcelona
No full textElectric scooters (e-scooters) have changed urban mobility by offering a dynamic solution to the critical “first and last mile” problem, connecting individuals from their homes to public transport and their final destinations. Despite their growing popularity, e-scooters navigate through a landscape of shifting legal frameworks, highlighting the urgency for policies that not only harness their potential but also address their inherent challenges. This study aims to shed light on the intermodal practices and demographics of e-scooters users in Barcelona, explores the potential impacts of regulatory changes on established transport habits, and assesses the adaptability of users to changing transportation options. Through a self-reported survey of 311 private e-scooter users, we find a notable prevalence of young men from lower socioeconomic backgrounds engaging in intermodal travel, primarily for employment purposes. To better understand how e-scooter riders integrate the device in their daily mobility strategies, we introduce the Intermodality Ratio (IR). A Generalized Linear Model (GLM) is then used to identify key demographic, socioeconomic, and geographic predictors of the IR, revealing place of residence as the most significant factor influencing intermodal behavior. Finally, we analyze participants’ anticipated behavioral shifts in response to the upcoming ban using a Multinomial Logistic Regression (MLR) model, which explores the sociodemographic factors affecting the likelihood of adopting alternative transport strategies. These findings contribute to the limited understanding of e-scooter utilization and intermodal practices, particularly within the context of public transit, offering insights into how transport policies can more effectively accommodate emerging mobility solutions
Investigating Indian Commuters’ Perceived Crime Risk on Autonomous Public Buses and Ride-Pooling Services
No full textAutonomous vehicle technologies are anticipated to transform road transportation systems, promising enhanced traffic safety and efficiency across different modes, including public buses (PB) and ride-pooling services (RPS). However, in India, there is a growing security concern/fear of crime concerning conventional PB and RPS because of the recent rise in crimes committed on them. Moreover, the introduction of driverless modes of PB and RPS may further heighten commuters’ crime concerns on such services because of the absence of a driver. Thus, this study investigates the acceptance of autonomous public buses (APB) and autonomous ride-pooling services (ARPS), as well as how commuters’ characteristics influence the perceived risks of crime and victimization and their willingness to use the modes. To achieve this, a stated preference survey was designed and conducted across India. The survey resulted in 732 complete responses. The results show that socioeconomic attributes, vehicle automation, and security-related measures significantly influence commuters’ perceived fear of crime and willingness to use APB and ARPS in India. More specifically, young commuters demonstrate higher willingness to use APB and ARPS, while females exhibit lower willingness to use APB and ARPS. In addition, the presence of a security officer on these modes decreases commuters’ concerns about crime. Moreover, travel distance is positively associated with commuters’ perceived level of crime and victimization, while it has a negative relationship with their unwillingness to use APB and ARPS. APB and ARPS are yet to be introduced in India, and Indian commuters have not experienced the security concerns associated with them; thus, the results of this study can serve as the base for guideline formulation for security concerns in India. Based on the results of this study, a set of policy implications, such as female-only transit units, enhancing security measures on the automated modes, and design framework and infrastructure, were proposed. These policy implications can be instrumental in increasing the acceptability of APB and ARPS in India and other countries with similar characteristics
Research on Safety Risk Assessment of Xi\u27an Metro Operation Based on Structural Equation Model (SEM)-Matter-Element Extension Model (MEA)
No full textTo ensure the safety of Xi\u27an Metro operation and improve the level of operational safety risk management, a comprehensive evaluation model of operational safety risk of Xi\u27an Metro based on structural equation model (SEM)-matter-element extension model (MEA) was established based on 4M theory. Firstly, by analyzing both domestic and international Metro accident cases and literature, four risk factor perspectives were identified as personnel, equipment, management, and environment. Secondly, to accurately assess the safety risk of Xi\u27an Metro operation, a risk evaluation index system consisting of four primary indicators, eleven secondary indicators and forty-four observation points was established. Finally, the index weights were determined using structural equation modeling, and a comprehensive evaluation utilizing the Matter-element extension model was conducted to obtain precise safety evaluation results. The model was applied to Xi\u27an Metro Line 2, and the results indicated that the operational safety level of Xi\u27an Metro Line 2 is relatively secure. According to the evaluation results above, the findings align with the current conditions. Xi\u27an Metro operating company can utilize these results as a point of reference to propose measures that correspond to varying risks. This will effectively reduce safety risks and ensure the safe operation of Xi\u27an Metro
Exploring the nuanced correlation between built environment and the integrated travel of dockless bike-sharing and metro at origin-route-destination level
No full textAs an essential mode of last-mile connectivity for public transit, dockless bike-sharing (DBS) has garnered increasing attention in the analysis of feeder trips. However, most previous studies have primarily focused on land use attributes around stations, neglecting the influence of factors at other stages such as trip origins and route environments. To address these gaps, this study employs XGBoost and SHAP to analyze the relationship between built environment attributes and DBS-metro integrated travel at origin-route-destination level based on multi-source geographic data such as DBS trajectory data, streetscape images, and POIs. The results indicate that route-built environment factors have a stronger influence on DBS-metro integration than traditional 5D attributes. Furthermore, the influence of built environment factors is nonlinear. When the green view index is between 0.15 and 0.25, residents are attracted to using DBS to reach the metro. Moreover, this study identifies interaction effects between cycling distance and other factors. The research findings provide scientific support for operators to allocate vehicles and transportation planners to undertake community regeneration and develop sustainable transportation systems
Traffic prediction and road space optimization for the integration of dockless bike-sharing and subway
No full textThe integration of dockless bike-sharing (DBS) and subway is an effective measure to promote sustainable urban transportation. However, inaccurate traffic prediction and unreasonable road space allocation have brought a severe imbalance between supply and demand, significantly restricting its application. To address these issues, this study first employs machine learning to establish a traffic prediction model at the origin–destination level. Then, we propose a road space optimization method based on multi-source geospatial big data, aiming to compress motorized lanes and increase cycling space. Results from the Beijing case indicate: (1) The XGBoost model achieves the best prediction accuracy, with an R2 of 0.68 ± 0.04. (2) The optimization method can accurately identify high-priority areas, and compressing each motorized lane only by 0–0.41 m can achieve reasonable allocation and still meet official standards. This study will assist policymakers in identifying demand and adjusting infrastructure within the DBS-subway integration scenario, ultimately achieving sustainable transportation systems