Monash University, Institute of Transport Studies: World Transit Research (WTR)
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Integrated demand-oriented and energy-efficiency train timetabling and rolling stock circulation planning for an urban rail transit line
No full textSaving energy has both significant environmental benefits and economic advantages. As the urban rail transit network and its consumed energy continue to expand, it is crucial to optimize the energy-saving operation scheme of trains. Energy-saving train operation often requires longer section running times, which is obviously not conducive to the quality of passenger service. In order to ensure passenger service quality when pursuing the decrease of the train’s energy consumption and rolling stocks’ operation cost, this paper proposes an integrated optimization model of the demand-oriented and energy-efficiency train timetable and rolling stock circulation plan for urban rail transit. Its objective is to minimize train net energy consumption, rolling stock utilization cost, as well as passenger waiting time and travel time. Specifically, the net energy consumption is defined as the difference between train required traction energy consumption and regenerative braking energy utilization. To efficiently solve this large-scale mixed integer nonlinear model, we design a solution algorithm combining Variable Neighborhood Search (VNS) and CPLEX, in which seven different neighborhood structures are constructed. Based on the data of Guangzhou Metro Line 13, we have verified the effectiveness and performance of the model and algorithm through numerical experiments of various scales, as well as through comparisons with other algorithms and models. The results demonstrate that the timetable and rolling stock circulation plan obtained by VNS can reduce net energy consumption by 9.55 %, rolling stock utilization cost by 9 %, and passenger waiting time by 4.77 %, and their travel time by 0.87 % compared to the current timetable
On the spatio-temporal optimization for the charging scheduling of battery electric buses
No full textBattery electric buses (BEBs) play a crucial role in advancing energy efficiency, reducing emissions, and fostering sustainable public transport. Opportunity charging technology has proven effective in alleviating BEB range anxiety. As BEB networks expand, designing an optimized charging schedule that accounts for spatio-temporal complexities becomes essential. This paper proposes an innovative optimization scheme that leverages the spatio-temporal characteristics of BEB networks. By employing variable charging power, the scheme balances TOU with grid loads. The problem is formulated as a nonlinear, non-convex program with continuous time variables and transformed into a solvable mixed-integer linear programming model via discrete-event-based linear reconstruction. Applied to a real BEB network in Shanghai, the results demonstrate a 7.83% reduction in charging costs by improving grid peak power and a 2.42% cost reduction by increasing charging piles across terminals
Scaling up public transport usage: a systematic literature review of service quality, satisfaction and attitude towards bus transport systems in developing countries
No full textUrban sprawl driven by urbanisation has contributed to a sharp rise in privately owned vehicles and competition for restricted resource space. The utilisation of private vehicles has increased, particularly in developing countries, and this phenomenon leads to many negative externalities, including traffic congestion and emissions. To encourage the use of sustainable modes such as public transport, it is essential for policymakers and transport authorities to carefully examine the determinants influencing public transport usage and apply successful policies and procedures. This review offers a valuable understanding of the contemporary knowledge regarding the determinants influencing bus transport usage. It systematically reviews 104 papers published since 2000 on service quality, satisfaction, and attitudes towards bus transport. The review shows that safety, security, comfort, reliability and accessibility are the most substantial determinants shaping users\u27 views on service quality and satisfaction. This is particularly evident in situations like waiting at the bus stop, being on board the bus, and specific instances while walking to their destination. The results indicate that challenges with first-mile and last-mile connectivity are apparent, and further exploration in the context of developing countries is needed to understand these challenges, necessitating further investigation. It also demonstrates instrumental aspects such as convenience and social-symbolic aspects such as social standing, influencing attitudes towards public transport usage. It concludes by suggesting potential paths for future research and discusses the impacts of the results on policy decisions
Integrated train rescheduling and speed management in a railway network: A meso-micro approach based on direct multiple shooting and alternating direction method of multipliers
No full textThe performance of high-speed railway systems is often affected by unavoidable disruptions, which impact the reliability of train operations and passenger satisfaction. In contrast to most existing studies, which focus on either train rescheduling or speed management in separate or sequential frameworks, this paper addresses the integrated train rescheduling and speed management problem during severe disruptions, considering power supply constraints on a bidirectional railway network. Specifically, this problem incorporates detailed train speed control into the rescheduling process and involves train rerouting strategies and flexible stops to mitigate disruption effects. To characterize the integrated problem, we develop a three-dimensional space–time-state network, where each arc corresponds to a detailed driving strategy. We then propose a mixed-integer nonlinear programming (MINLP) model to simultaneously optimize the train schedule (i.e., train order, departure and arrival times, and routes) and train speed profiles, with the goal of reducing both total passenger delays and train energy consumption. To efficiently solve the integrated model, we propose a two-stage approach based on the direct multiple shooting method and the alternating direction method of multipliers (ADMM). This approach is implemented by combining offline and online computing to meet real-time requirements. The effectiveness and efficiency of the proposed model and algorithm are verified through numerous experiments using real-world data from Chinese high-speed railways. Experimental results demonstrate that our integrated approach improves energy efficiency by an average of 19.40% in complete section blockage scenarios and 7.69% in temporary speed restriction scenarios, compared to methods that do not incorporate speed management
Research on Optimization of Maintenance Task Scheduling for Metro Systems Based on Resource Constraints
No full textOptimizing the maintenance scheduling of metro systems is a crucial task that necessitates meticulous coordination of labor, equipment, and workspaces to ensure optimal system performance and safety. A mathematical model and a two-stage teaching-learning-based optimization (TLBO)-resource operators crossover (ROC) algorithm are proposed aiming at optimizing the scheduling of maintenance tasks for metro systems. The mathematical model focuses on minimizing the makespan, which represents the total duration or time required to complete a set of tasks or activities within a project. In addition, it takes into account the need to balance the load on labor and workspaces, considering environmental constraints, limited resources, and strict scheduling requirements. A two-stage TLBO-ROC algorithm is specifically designed to enhance the scheduling process. It achieves this by iteratively updating the local best individual matrix, dividing it into groups, and adjusting the resource allocation. This algorithm effectively reduces the makespan while also achieving improved balance in the workspace load. The model and algorithm are tested on the Shenzhen metro system. Experimental results demonstrate that our proposed approach significantly reduces the makespan. In comparison to manual scheduling plans, the algorithm achieved a remarkable 28.06% reduction in the makespan. Moreover, when compared to benchmark algorithms, our proposed algorithm not only improves the makespan but also ensures more equitable occupation of workspaces by maintaining a similar balance in labor load
Real-Time Urban Traffic Monitoring Using Transit Buses as Probes
No full textReal-time urban traffic monitoring is crucial for effective smart city management. Despite the increasing number of sensors collecting large-scale datasets in real time, challenges such as privacy concerns, high capital and maintenance costs, and limited coverage persist, impeding precise network traffic monitoring. General Transit Feed Specification (GTFS) Realtime data, an emerging real-time data source generated by public transit, exhibits high potential to monitor traffic given its public accessibility, low cost, and lack of privacy concerns. This study developed a new methodology leveraging GTFS Realtime data for citywide network sensing. Specifically, the proposed methodology uncovers the typical travel patterns of buses by isolating their operational events, involving boarding and alighting passengers at bus stops. Two algorithms, the segment-trip extraction algorithm and the segment speed estimation algorithm, were developed to implement the proposed methodology. The validation process used Bluetooth data collected in Gainesville, Florida, as the ground truth, while Google Traffic data served as a benchmark for comparison. Results indicate that the space mean speed estimated from GTFS Realtime data can better capture link speed trends and variations, similar to those observed in Bluetooth data. Furthermore, bus travel times derived from GTFS Realtime data demonstrated relatively high correlations with Bluetooth data and low prediction errors compared with estimates based on Google Traffic data. The proposed methodology and findings of this study can be directly used to complement and improve existing real-time traffic monitoring technologies
The non-linear effects of built environment on bus ridership of vulnerable people
No full textUnderstanding public transit patterns of vulnerable people, and their influencing factors is crucial for equitable transportation planning. However, few studies have explored how the impact of built environment factors and according threshold effects vary among different population groups. This paper bridges this research gap through an empirical study carried out in the City of Wuhu, a prefectural-level Chinese city. Bus ridership of three disadvantaged groups (the elderly, disabled and the low-income) and the mainstream population was obtained using smart card transaction records and bus trajectory GPS data. The non-linear effects of built environment on bus ridership of different groups were then examined and compared using Gradient Boosting Regression Trees (GBRT). The results suggested that both the importance and threshold effects of built environment variables vary among four population groups. The effect ranges of built environment variables were further identified to shed light on land-use policy-making for promoting equitable public transit
People with disabilities and transit use: Findings from nationwide data in India
No full textThe travel behaviour of people with disabilities (PWDs) has been observed to differ from that of people without disabilities despite having similar needs and wants. PWDs encounter various obstacles restricting their mobility and ability to participate in activities. In this paper, we use a large nationwide dataset covering 102,977 PWDs to understand transit usage and barriers faced by PWDs while travelling at disaggregate and aggregate levels. The analysis comprises five different models: binary logit and multinomial logit at the disaggregate level, ordinary least square regression, spatial lag model, and spatial error model at the aggregate level. Findings reveal that transit use is significantly low among female PWDs, PWDs who lost work, PWDs who need a caregiver, and regions with a high percentage of workers. It is also observed that the level of marginalised populations in a region consistently shows a negative impact on public transport usage across most disabilities
Influence of e-bikeshare on transit ridership in a medium-sized Chinese city
No full textElectric bikeshare (e-bikeshare) has rapidly expanded in medium-sized Chinese cities, but whether it is hurting or boosting transit ridership remains unclear. This study utilizes the instrumental variable method to analyze the influence of e-bikeshare on transit ridership based upon a six-month longitudinal dataset from Yancheng, China. The results demonstrate a significant negative impact, where an increase of 1% in e-bikeshare trips is associated with a decrease of 0.618 % in transit ridership. The heterogeneity analyses reveal that e-bikeshare has a weaker effect on transit ridership at BRT stops, and the adverse impact is less pronounced in unfavorable-weather situations. E-bikeshare should avoid competing directly with areas served by multiple BRT routes while increasing the availability of shared e-bikes in areas with limited transit options. Additionally, it is worth implementing differentiated scheduling strategies based on different weather situations. These insights could assist local authorities in realizing the complementary advantages of both travel modes
Valuing improvements to bus universal accessibility for visually impaired users: A case study in Santiago, Chile
No full textWhile the implementation of public transport initiatives in various countries has significantly improved universal accessibility, it\u27s important to note that they have primarily catered for individuals with physical disabilities. The needs and barriers of the visually impaired, a distinct population segment, have not received the same level of attention.
We examine three elements designed to improve universal bus accessibility for the visually impaired: audio-visual information inside buses, auditory information outside buses, and bus standardization, to contribute to the design and social evaluation of appropriate policies for this segment. We applied a stated choice survey, including perceptual indicators designed to assess the respondents\u27 ability to move independently in the city. Information from 529 individuals allowed us to estimate hybrid choice models, incorporating two latent variables associated with respondents\u27 independence (technological and mobility-wise).
We found that subjective valuations differed markedly for people with and without visual impairments and depended on gender, physical disability, occupation and car availability. Results suggest that the social worth of these measures could be substantial given the life span of urban buses. Our approach can be generalised to other countries/regions, with the potential for even higher valuations, as Santiago\u27s public transport system is better than the norm