Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Extensive Model and Matheuristic Algorithm for the Train Platforming Problem with Two-Train-Capacity Tracks: A Case Study of Prague Central Station
No full textThis paper provides a deeper insight into the train platforming problem (TPP). Many studies have focused on different versions of train scheduling and routing problems, and most of them assume that the platform track’s capacity is one train. However, especially in busy and complex railway stations, most platform tracks are divided into two parts, allowing two trains to simultaneously share the same platform track for passenger boarding/alighting. This results in more efficient train assignment to the platform tracks. In addition, consideration of the track capacity makes the problem more difficult because directions of trains are problematic. Motivated by this challenge, we consider the TPP with two-train-capacity tracks. We first describe the problem in detail and then propose a mixed-integer programming model. The objective of the considered problem is to minimize the total weighted train delays, which are defined as the difference between the departure times calculated by the mathematical model (M1) and the scheduled departure times of the trains in the timetable. Because of the NP-hard nature of the problem, the proposed M1 may not find feasible solutions for large-size problems. Thus, a matheuristic algorithm (MA) is developed to solve large-size problems. We used randomly generated test problems to demonstrate the performance of the proposed M1 and MA. Experimental results showed that MA outperforms M1 in both solution quality and solution time. Additionally, a case study was conducted at the central station of Prague, Czechia
A comparison of factors influencing the safety of pedestrians accessing bus stops in countries of differing income levels
No full textPedestrian fatalities comprise a quarter of all traffic deaths in Low-and-Middle-Income Countries (LMICs). The use of safer modes of transport such as buses can reduce road trauma as well as air pollution and traffic congestion. Although travelling by bus is safer than most other modes, accessing bus stops can be risky for pedestrians. This paper systematically reviews factors contributing to the safety of pedestrians near bus stops in countries of differing income levels. The review included forty-one studies from high (20), upper-middle (13) and lower-middle income countries (8) during the last two decades. The earliest research was conducted in high-income countries (HICs), but research has spread in the last decade. The factors influencing pedestrian safety fell into three groups: (a) characteristics of road users, (b) characteristics of bus stops and (c) characteristics of the road traffic environment. Pedestrians near bus stops are frequently exposed to a high risk of collisions and fatalities due to factors such as unsafe pedestrian behaviours (e.g., hurrying to cross the road), lack of bus stop amenities such as safe footpaths, high traffic speeds and traffic volumes, multiple lanes, and roadside hazards (e.g., parked cars obscuring pedestrians). Road crash statistics are commonly used to identify unsafe bus stops in HICs but the unavailability and unreliability of data have prevented more widespread use in LMICs. Future research is recommended to focus on surrogate safety measures to identify hazardous bus stops for pedestrians
Utilizing electric bus depots for public Charging: Operation strategies and benefit analysis
No full textThe uneven distribution of public charging infrastructure poses significant challenges for private electric vehicles (EVs). Many Chinese city bus depots have abundant chargers for electric buses (EBs), often unused during daytime operations. This study proposes an innovative mechanism to utilize bus depot chargers for private EVs, prioritizing the charging demands of EBs. Uncertainty in EB and EV charging demand, EV arrival time are considered. The objective is to maximize bus company revenue through a two-stage stochastic model. Practical applicability is demonstrated through a real-world bus depot case in Shanghai with 127 EBs and 376 private EVs. The results show that allocating 58% of the charging power and 30% of the chargers to the public from 10:00 to 24:00 meets 97.54% of the private EVs’ charging demand. The bus operator faced a charging cost of 10,747 CNY, while now it expects a profit of 1733 CNY with the project running
Understanding information needs for seamless intermodal transportation: Evidence from Germany
No full textCities worldwide are seeking to enhance their sustainable mobility by reducing individual motorized transportation. While intermodal mobility – combining multiple transportation modes in one journey – is a key solution, individuals encounter challenges initiating intermodal journeys owing to the proliferation of mobility services. Providing accurate information at the right time is crucial amidst this complexity. While research has examined information needs for each mobility mode independently, the relationships between modes, phases, and information needs have barely been empirically investigated. Through a sequential mixed-method approach involving a literature review and a survey of \u3e500 participants, this study identifies and validates the concept of phase- and mode chain-sensitive information needs. The findings provide initial insights, emphasizing phase relationships, mode chain relationships, and the interplays between phases and mode chains — a holistic understanding. This research can guide the design of more effective traveler information systems, aiding the shift toward sustainable urban mobility
CoMoDe-Matrix: introducing the contextual sustainable mobility decisions matrix
No full textIndividual decisions are pivotal to sustainable mobility. However, the disciplines of mobility research, sustainability research, and behavioral science typically explore this topic in isolation. For instance, there is no comprehensive framework for individual mobility decisions, and existing frameworks exhibit several significant shortcomings. Based on an integrative review of existing frameworks, this article therefore integrates concepts from all three perspectives into a novel framework, the CoMoDe-Matrix. The proposed framework emphasizes the importance of the decision context (i.e. private or professional context) and of differentiation between various decision types. Its integrative nature makes the framework a valuable tool for interdisciplinary mobility research, providing a cohesive foundation which could be applied, for instance, in systematic evidence syntheses. Furthermore, it offers practical guidance for policymakers seeking to promote sustainable mobility decisions
Integrating Autonomous Busses as Door-to-Door and First-/Last-Mile Service into Public Transport: Findings from a Stated Choice Experiment
No full textAutonomous busses and on-demand (OD) services have the potential to improve the public transport system. However, research on potential traffic impacts is still ongoing, mainly because of a lack of existing use cases of autonomous driving as part of public transport. The availability of revealed preference data for mode choice decisions is thus very limited. Therefore, we conducted a stated choice experiment to assess mode choice preferences with regard to use cases as the main mode of transport and as the solution for the first and last mile. We also distinguished between OD and schedule-based (sched.) services. The target population of the survey is the population of Baden-Württemberg, a state in southwestern Germany. The responses of 1,434 people were analyzed using a nested logit approach. On this basis, we established exemplary utility functions and descriptively derived recommendations for efficient forms of deploying autonomous busses in addition to already existing well-developed public transport systems. It was found that, under the given conditions, public transport pass owners without a car in their household would be the most interested in using autonomous busses. Car owners without a smartphone see less benefit. It was also shown that the recruiting method of the respondents is crucial. Those reached via social media were significantly more positive than those contacted via an online panel. Further evaluations show that autonomous busses are rated similarly to existing public transport and consequently have particularly high potential on medium distances, especially if their deployment leads to shorter access routes
Designing a carbon-trading incentive scheme for mode shifts in multi-modal transport systems
No full textThe pressing need to reduce greenhouse gas emissions triggers the imperative for efficient travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which place a significant financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters shifting to using public transit. The incentive budget for PCTTI is sourced from the revenue generated through selling carbon emission reductions resulting from commuters’ travel mode shifts. To determine the optimal incentives, we developed an incentive scheme optimization model based on the Stackelberg game model. Numerical analysis reveals the significant potential of the PCTTI to reduce carbon emissions and travel costs across various scenarios within a multi-modal transportation system. This potential is evident amidst changes in the fixed costs of car travel, carbon trading prices, the use of different travel modes, the value of time, and the prevalence of electric vehicles. The advantages are most pronounced when the carbon trading price exceeds 40 CNY/ton, and when the usage of public transit, the value of time, and the proportion of electric vehicles each fall below 0.4, 50 CNY/hour, and 0.4, respectively
Assessing the influence of the COVID-19 pandemic on passengers\u27 reliance on public transport
No full textThe COVID-19 pandemic has significantly influenced travel choices and the effective functioning of public transport. However, research into the pandemic\u27s effects on public transport, specifically considering the combined impact of both risk perception and prevention tactics, remains limited. This study aims to examine the effect of COVID-19 on passengers\u27 reliance on public transport, considering their risk perception and the strategies implemented for pandemic prevention. Data for this research were gathered through a questionnaire survey conducted in Chengdu, China, in March 2022, during a major outbreak of the pandemic in the city. Employing the Theory of Planned Behavior, the study establishes a structural equation model to analyze the questionnaire data and unveil the COVID-19\u27s impact on passengers\u27 reliance on public transport. The analysis shows that people\u27s perception of infection risk has a significant impact on travel preference, and they pay attention to the convenience of public transport as well as safety. Based on the analysis, relevant suggestions are proposed from the perspectives of passengers, operators, and the government to improve the safety and efficiency of public transport
Could improving public transport accessibility reduce road traffic carbon dioxide emissions? A simulation-based counterfactual analysis
No full textImproving public transport accessibility (PTA) has been considered as an effective measure for promoting sustainable urban development. Based on the grid-level data in Nanjing, China, this paper explores the spatially heterogeneous effects of PTA on road traffic CO2 emissions using a geographically weighted random forest (GWRF) model. A simulation-based counterfactual analysis framework is further proposed to predict the intervention effects of improving PTA. Two kinds of practical interventions, adding facilities and increasing service frequency, are considered in our counterfactual prediction. The effects of improving PTA across different areas are predicted and compared. Our results indicate that the GWRF model with a properly tuned bandwidth outperforms the conventional random forest model. The results of counterfactual analysis show that improving PTA could achieve greater environmental benefits in suburb areas. With the process of urbanization in Nanjing, the population and economy has grown rapidly in suburb areas. Therefore, it is reasonable to improve public transport services in these areas. Based on our findings, PTA has potential to make a significant contribution to sustainable development of urban transportation. Moreover, our findings with respect to heterogeneous effects likely improve the efficiency of local transport policies that target such areas, helping achieve greater environmental benefits
Built environment’s nonlinear effects on mode shares around BRT and rail stations
No full textThis study investigates nonlinear associations between built environment (BE) attributes and commuting mode share within rail and bus rapid transit (BRT) catchment areas. Data from approximately 2,790 fixed guideway transit station areas across 34 metropolitan statistical areas in the United States were analyzed using a random forest approach. Results show nonlinear associations of the BE with mode share in transit catchment areas with substantial differences between rail and BRT catchment areas. Rail catchment areas exhibit greater sensitivity to the BE to reduce car dependency as compared to BRT stations. Moreover, polycentricity and population density at regional level are effective at reducing car dependency. We suggest that policymakers consider BE threshold effects and station types when adjusting land-use policies, e.g., in transit-oriented development. Additionally, BRT systems could be a useful alternative to rail in sprawling areas that do not have the compactness needed to support rail