Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Effects of European Rail Traffic Management System Onboard Version on Running Time, Driver Target Braking, and Driver Workload
No full textDuring the development of the European Rail Traffic Management System (ERTMS), several changes and improvements have been made to the driver–machine interface (DMI). The intention is to refine the train driver support by adding, removing, or clarifying signal information. In ERTMS Baseline 3, major DMI changes have been made between onboard versions 3.4 and 3.6. This includes clarification about speed targets and a simplified color strategy for target speed monitoring. This paper presents the effects of the DMI version shift on running time, driver target braking toward a European Train Control System target, and driver workload. In an electrical multiple unit train driver simulator, 39 student train drivers tested two different DMI versions on a 16 km railway line. In addition, the drivers rated the driver task workload using the NASA Task Load Index. From the results of this study, it can be concluded that drivers, despite a longer braking phase, go faster with version 3.6 than with version 3.4. The running time difference was about 1%. Although the driving task was short, with a low workload demand, the train driver workload was clearly affected by the onboard version, such that with the later version (3.6), the workload was statistically significantly lower
Integrated optimization of demand-oriented timetabling and rolling stock circulation planning with flexible train compositions and multiple service routes on urban rail lines
No full textThis study investigates an integrated train operation plan problem with flexible train compositions and multiple service routes, which allows trains to couple, decouple and turn around at intermediate turnaround stations based on virtual coupling technology. An integrated optimization model for demand-oriented train timetables and rolling stock circulation plans is developed with the consideration of train service routes and the number of train services, by minimizing both passenger waiting time and operation costs. Specifically, with the path-based space–time network representation, we formulate a novel rolling stock circulation model, which accounts for coupling and decoupling operations and stabling track capacity constraints with lower complexity than the assignment model. In addition, we improve the linear dynamic passenger flow loading model, which extends the operational application with multiple service routes and characterizes various passenger waiting behaviors. To solve the proposed model, an adaptive simulated annealing (ASA) algorithm is designed to obtain high-quality solutions using flow-oriented and random operators. Lastly, the performance of the proposed models and algorithms is verified by small-scale numerical experiments. Then, the efficiency of the proposed approaches is further demonstrated through a real-world case study based on Beijing Subway Changping Line, showing a 42% reduction in total passenger waiting time, a decrease of 16 rolling stock, and a 10% reduction in variable operation costs compared to the current operation mode
Joint optimization for crowd evacuation and vehicle scheduling at multimodal transportation hubs
No full textTransportation hubs are critical nodes that accommodate substantial passenger flows, which will lead to significant congestion during peak hours, predictable events (e.g., holiday, extreme weather) or emergencies (e.g., operational disruption). It is crucial to design a collaborative evacuation strategy that fully utilizes the multimodal transportation capacities at hubs. Considering the impact of various transportation operations on crowd evacuation, this paper proposes a mixed-integer linear programming model that integrates pedestrian flow assignment and multimodal vehicle scheduling to efficiently evacuate the crowd. In the model, a demand-switching strategy among modes is incorporated, and various operational characteristics of transportation modes including departure times and fleet sizes are optimized for vehicle scheduling. Throughout the evacuation process, pedestrian dynamics are formulated by the cell transmission model (CTM). To solve the large-scale problems, a tailored Variable Neighborhood Search (VNS) algorithm based on decomposition is developed, where the subproblem is reconstructed on a time-expanded network to accelerate the solution process. The effectiveness of the proposed method model and algorithm are validated through a series of numerical experiments. The results show that the tailored VNS algorithm can effectively solve large-scale problems within a reasonable timeframe. The case study also demonstrates that the demand-switching strategy could optimize the use of available transportation resources, reducing the clearance time for taxis by 17.2%. Furthermore, the findings highlight the importance of adapting evacuation strategies to different emergency scenarios. This approach can be potentially applied to enhance emergency crowd management responses at transportation hubs
Resilient bus services design in a multimodal network with uncertain metro system disruption
No full textDisruptions in the metro system often lead to chaos in the public transportation system due to their significant mode share. To mitigate such impacts, this study designs a multimodal public transportation network integrating metro and bus, subject to stochastic metro disruptions. With a given metro system, a two-stage stochastic programming model is formulated to design complementary bus services, catering to stochastically degradable metro capacity. Under normal metro operations, the bus services complement the metro services, but with built-in resiliency to handle potential disruptions. In the event of metro disruptions, they function as substitutes to mitigate the disruptive impact on passengers, thereby maintaining system reliability. The bus routings and service frequencies are designed to achieve social optimal by minimizing the combined costs of bus construction, operating expenses, expected total passenger costs, and unmet demand costs arising from metro disruptions. A service reliability-based solution method is adopted to solve the problem by decomposing the problem into two phases. In phase 1, given a service reliability measure, the model determines the bus routing and frequencies. Then, in phase 2, given the bus routes and frequencies, it minimizes the costs of lost demand and passenger inconvenience. A service overlapping penalty is considered to prevent substantial duplication between metro and bus services. The effectiveness of the proposed model is validated in a case study, demonstrating the advantages of considering stochastic degradable capacity and designing complementary bus services in an integrated multimodal public transportation system. Under various disruption conditions, the demand loss is reduced by over 95% compared tobenchmark cases
Service Quality and Personal Attitudes as Predictors of Overall Satisfaction with Public Buses: A Case Study in Kathmandu, Nepal
No full textThis study analyzes the effects of certain variables on bus service quality (SQ) and how SQ and personal attitudes affect satisfaction with public buses. A total of 552 responses were collected using a questionnaire that captured socioeconomic and trip characteristics, satisfaction ratings for SQ attributes, and the personal attitudes of consumers. Factor analysis was used to uncover unobserved latent features and to generate two measurement models: for SQ and for personal attitudes of bus users. Three latent variables (“information, safety and security”, “comfort”, and “accessibility/availability”) were observed that signify SQ. Simultaneously, two latent variables (perceived value, and behavioral intention and involvement) were obtained representing the attitude of customers. A structural equation modeling method was employed to compute interconnections among these variables. Information and safety and security had a major influence on SQ followed by comfort and accessibility/availability. Similarly, perceived value had a greater impact on personal attitudes than that on behavioral intention and involvement. Findings also show that evaluating overall SQ is better explained when consumers rate the service quality of buses after knowing about the various attributes. Findings revealed that the overall satisfaction of customers with bus services was influenced more by SQ-related attributes than by personal attitudes. The study also provided insights into public bus service quality improvements that must be emphasized and enhanced to increase ridership. This understanding of connections among SQ, personal attitudes, and overall satisfaction can assist transit officials in developing effective strategies and investment plans to meet the needs of passengers and boost customer satisfaction with public buses
Spatial and Temporal Variation of Subway Ridership before and during the COVID-19 Period in Beijing
No full textThe outbreak of COVID-19 in 2019 caused a huge impact on people’s lives. Uncovering the variation of public traffic daily patterns during the pre-pandemic and pandemic periods would help interpret the impact of the pandemic on people’s routine activity and promote the sustainable development of public transport systems. By collecting subway traffic data during the pre-pandemic and pandemic periods in Beijing, China, this paper analyzes the spatial and temporal variation of subway ridership and seeks to find out what sort of environment variables related to the variation of subway ridership during the two periods. The results show that the ridership of Beijing subway during the pandemic period decreased by 91.69% compared with the pre-pandemic period. On working days and non-working days during the pandemic period, the subway stations experiencing huge ridership reductions were mainly distributed within the core urban areas, while in the morning peak hours, the stations experiencing huge ridership reduction were located within suburban areas. The origin-destination stations with a large decrease in ridership were mainly distributed along the central to northern directions of Beijing but, on non-working days, they were mainly distributed along the central to northwestern directions of Beijing. The results of the regression analysis indicated that, during the pandemic period, the industrial parks were significantly positively correlated with subway ridership, while the pedestrian road network density was significantly negatively correlated with subway ridership
Examining the effect of public transit accessibility on recidivism among underage driving offenders: A multilevel zero-inflated model approach
No full textPublic transit is widely recognized as essential for individuals with mobility disadvantages; however, its impact on underage driving (UAD) recidivism remains underexplored. This study employs multilevel zero-inflated models to examine whether public transit accessibility reduces the likelihood of naïve UAD offenders becoming repeat offenders. Utilizing an empirical dataset of 51,454 UAD offenders in Taiwan over an eight-year period (2014–2021), the analysis results support the hypothesis that greater accessibility to the bus transit network significantly decreases the likelihood of recidivism among naïve offenders, particularly among older adolescents. The findings also reveal that UAD offenders residing in economically disadvantaged neighborhoods are more likely to engage in subsequent offenses compared to those in more prosperous areas, underscoring the importance of enhancing transit services from a social equity perspective. Additionally, consistent with patterns observed in recidivism for other traffic offenses, male offenders and individuals with prior UAD violations are at a higher risk of repeat offenses. These results emphasize the need for targeted interventions within graduated driver licensing programs. This study highlights the significance of early identification and intervention for UAD offenders, particularly through differentiated approaches for naïve and repeat offenders. The proposed multilevel zero-inflated modeling approach proves valuable in distinguishing between offender types and offers potential for application in other traffic recidivism contexts
Referential transit prices for users of reduced fare programs
No full textStudents, elderly, handicapped, and low-income individuals can apply for reduced fare programs (RFPs) in many cities worldwide. Such programs represent specific social preferences for those groups. However, prices in RFPs are always reported as a fraction of the so-called full fare, which is presented as society\u27s willingness to favor those groups for whatever reasons. We argue that full fares are not the correct reference for comparison because special groups exhibit differences in how they use the transit system (e.g., different trip lengths, boarding times, or different occupation of vehicle space), which induces differences in marginal costs. By expanding the well-known one-line stylized transit model to admit different user types, we show that marginal cost fares depend on trip characteristics such as boarding-alighting times and/or average trip lengths. These group-specific marginal cost (first best) prices are proposed as the appropriate reference for comparison with the observed fares. This means that social preferences for special groups should be reflected by fares lower than the corresponding marginal social cost. This general theoretical framework is applied to elders and students using parameters from Santiago, Chile, where observed fares are lower than the full fare but higher than the estimated marginal social cost
Suitable placement for on-demand Transport (SPOT): A systematic approach to network integration
No full textThis paper presents a bottom-up approach to designing on-demand transport (ODT) systems, emphasising an evidence-based methodology. A critical review of existing ODT systems is conducted, focusing on identifying the most suitable market segments and environments for ODT deployment. This review forms the basis for developing a systematic methodology that integrates known success factors and best practices in the design of new systems in the pursuit of network integration. We demonstrate the scalability and transferability of the developed methodology using two case studies and show how the proposed method can support the selection of optional service areas and assess their impacts on local community. These case studies provide practical insights into the application of the methodology in diverse settings, underscoring its adaptability and effectiveness in different market conditions. The paper addresses equity issues in public transport service provision. It critically examines how existing bus services can be restructured to enhance network efficiency and social equity, particularly in underserved and disadvantaged areas
Can TOD help metro station ridership ‘early recovery’ from COVID-19? An empirical evidence from Nanjing
No full textTOD-ness, defined as the extent to which the existing conditions of TOD sites align with established TOD standards, has been shown in previous studies to have a significant correlation with metro station ridership. This paper utilizes the LightGBM model to investigate the relationship between TOD-ness and the “early recovery” of metro station ridership following the lifting of COVID-19 control measures. The study findings show: (1) At the line level, metro ridership in Nanjing has significantly rebounded following the lifting of COVID-19 control measures, particularly for non-commuting and weekend travel. At the station level, external transport hubs and major city center stations experienced the most notable recovery in ridership, while secondary urban center stations saw relatively higher increases in weekend ridership. (2) In terms of TOD-ness typology, stations with higher overall indicators and node indicators exhibited a greater number of ridership recoveries. (3) Regarding the relative importance of different indicators, factors related to place and design—such as functional mix, road network density, POI density of residences, and pedestrian shed ratio—are the more important drivers of ridership recovery for both commuting and non-commuting purposes. However, non-commuting ridership recovery is more influenced by station location and functional diversity, whereas commuting ridership recovery is more closely associated with ease of access