Journal of Rail Transport Planning & Management最新文献_第10页

Pedestrian small group behaviour and evacuation dynamics on metro station platform 地铁站台行人群体行为与疏散动态

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100387

Qi Zhang, Jing Qu, Yanzhe Han

{"title":"Pedestrian small group behaviour and evacuation dynamics on metro station platform","authors":"Qi Zhang, Jing Qu, Yanzhe Han","doi":"10.1016/j.jrtpm.2023.100387","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100387","url":null,"abstract":"<div><p>Crowd at metro stations is usually a mixture of individuals and small groups of families or friends. However, limited research has focused on small group behaviours for metro safe evacuation evaluation and planning. In this study, a field observation at metro stations and a questionnaire survey were conducted to reveal the small group behaviour characteristics with different decision patterns and compactness. A cellular automaton (CA) based simulation model was proposed to reproduce small group behaviours of independent or joint decision pattern, with loose or close contact, reflecting the real-time trade-off between individual efficiency and group coherence. Impacts of small group behaviours on crowd dynamics were investigated by simulation experiments under diverse scenarios. Simulation experiments revealed that joint decision pattern and close contact of small groups were more likely to lead to longer evacuation time, lower average speed and stronger interference on the individuals. Deviations of estimated evacuation time due to small group behaviours were investigated and found to be common and widespread with different group decision pattern and compactness, congestion levels, proportions of groups in the crowd and exit layouts.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100387"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49727477","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Solving the train dispatching problem via deep reinforcement learning 利用深度强化学习解决列车调度问题

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100394

Valerio Agasucci , Giorgio Grani , Leonardo Lamorgese

{"title":"Solving the train dispatching problem via deep reinforcement learning","authors":"Valerio Agasucci , Giorgio Grani , Leonardo Lamorgese","doi":"10.1016/j.jrtpm.2023.100394","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100394","url":null,"abstract":"<div><p>Every day, railways experience disturbances and disruptions, both on the network and the fleet side, that affect the stability of rail traffic. Induced delays propagate through the network, which leads to a mismatch in demand and offer for goods and passengers, and, in turn, to a loss in service quality. In these cases, it is the duty of human traffic controllers, the so-called dispatchers, to do their best to minimize the impact on traffic. However, dispatchers inevitably have a limited depth of perception of the knock-on effect of their decisions, particularly how they affect areas of the network that are outside their direct control. In recent years, much work in Decision Science has been devoted to developing methods to solve the problem automatically and support the dispatchers in this challenging task. This paper investigates Machine Learning-based methods for tackling this problem, proposing two different Deep Q-Learning methods(Decentralized and Centralized). Numerical results show the superiority of these techniques respect to the classical linear Q-Learning based on matrices. Moreover the Centralized approach is compared with a MILP formulation showing interesting results. The experiments are inspired on data provided by a U.S. class 1 railroad.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100394"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49752658","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Onboard train speed optimization for energy saving using the prediction of block clearing times under real-time rescheduling 实时重调度下基于路段清理时间预测的列车速度节能优化

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100392

Alexandra Liebhold , Shota Miyoshi , Nils Nießen , Takafumi Koseki

{"title":"Onboard train speed optimization for energy saving using the prediction of block clearing times under real-time rescheduling","authors":"Alexandra Liebhold , Shota Miyoshi , Nils Nießen , Takafumi Koseki","doi":"10.1016/j.jrtpm.2023.100392","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100392","url":null,"abstract":"<div><p><span>Energy-saving driving is crucial during railway operation, especially in case of disturbances that require timetable rescheduling. This paper presents a method for the dynamic onboard tuning of energy-efficient speed profiles after the real-time train rescheduling process under a fixed block signaling system for mixed traffic. Similar to the idea of connected driver advisory systems, trains constantly communicate with a central </span>traffic management system<span>. After the rescheduling process, this system provides recommended time corridors for the passing of block signals that depend on the predicted clearing times of the block sections. These recommendations are then used for individual energy optimization of single train runs by avoiding unnecessary braking in front of block signals and maximizing cruising distances. The method is tested and evaluated on a representative line segment of the ELVA, the Railway Signaling Lab at RWTH Aachen University under realistic conditions. Energy consumptions are compared for different prediction time horizons at which the recommendations are available to the train's onboard system. In the examined test case of two trains, the energy-consumption could be decreased by up to 53% compared to operation without any rescheduling system. Thus, the proposed method is able to reduce energy consumption significantly.</span></p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100392"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49752677","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Statistical learning for train delays and influence of winter climate and atmospheric icing 列车延误及冬季气候和大气结冰影响的统计学习

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100388

Jianfeng Wang , Roberto Mantas-Nakhai , Jun Yu

{"title":"Statistical learning for train delays and influence of winter climate and atmospheric icing","authors":"Jianfeng Wang , Roberto Mantas-Nakhai , Jun Yu","doi":"10.1016/j.jrtpm.2023.100388","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100388","url":null,"abstract":"<div><p>This study investigated the climate effect under consecutive winters on the arrival delay of high-speed passenger trains. Inhomogeneous Markov chain model and stratified Cox model were adopted to account for the time-varying risks of train delays. The inhomogeneous Markov chain modelling used covariates weather variables, train operational direction, and findings from the primary delay analysis through stratified Cox model. The results showed that temperature, snow depth, ice/snow precipitation, and train operational direction, significantly impacted the arrival delay. Further, by partitioning the train line into three segments as per transition intensity, the model identified that the middle segment had the highest chance of a transfer from punctuality to delay, and the last segment had the lowest probability of recovering from delayed state. The performance of the fitted inhomogeneous Markov chain model was evaluated by the walk-forward validation method, which indicated that approximately 9% of trains may be misclassified as having arrival delays by the fitted model at a measuring point on the train line. With the model performance, the fitted model could be beneficial for both travellers to plan their trips reasonably and railway operators to design more efficient and wiser train schedules as per weather condition.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100388"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49765889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Inequity averse optimization of railway traffic management considering passenger route choice and Gini Coefficient 考虑客运路线选择和基尼系数的铁路交通管理不公平优化

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100395

Xiaojie Luan , Xiao Sun , Francesco Corman , Lingyun Meng

{"title":"Inequity averse optimization of railway traffic management considering passenger route choice and Gini Coefficient","authors":"Xiaojie Luan , Xiao Sun , Francesco Corman , Lingyun Meng","doi":"10.1016/j.jrtpm.2023.100395","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100395","url":null,"abstract":"<div><p>Traffic management is crucial for improving the punctuality and reliability of train operations, enabling train operating companies (TOCs) to maintain their competitiveness and further increases the share and profits. A common goal of the train rescheduling problem is to minimize train delays, which fails to examine the results from the perspective of passengers. Moreover, focusing only on the punctuality performance overlooks how the delay is distributed among entities (i.e., trains, passengers, and train operating companies).</p><p>We study the train rescheduling problem with the inclusion of passenger choices and the equity concerns. A mixed-integer linear programming (MILP) model is proposed to find the optimal train schedules and the best route for passengers at the same time, with respect to the demanded equity level. Passengers choose a sequence of train services to complete their trip with the least amount of costs (i.e., delays). To evaluate the equity performance of the system, we define equity by means of Gini Coefficient and Maximal Deviation, included in the MILP model as constraints.</p><p>Experiments are conducted to explore the impacts of the objective change, i.e., from reducing train delays to reducing passenger delays, and to compare the system performance of using the two equity measures in terms of punctuality and equity. According to the results, the average passenger delay decreases by 34% when minimizing passenger delays, compared with that of minimizing train delays. Moreover, the Gini Coefficient yields less cost of equity (i.e., less increase of delays), compared to that of the Maximal Deviation.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100395"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49752170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Railway freight wagon fleet size optimization: A real-world application 铁路货运车队规模优化:一个实际应用

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100373

Miloš Milenković , Nebojša Bojović , Dmitry Abramin

引用次数: 0

Optimal resource rescheduling in classification yards considering flexible skill patterns 考虑灵活技能模式的船级社资源调度优化

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100390

Henning Preis , Tobias Pollehn , Moritz Ruf

{"title":"Optimal resource rescheduling in classification yards considering flexible skill patterns","authors":"Henning Preis , Tobias Pollehn , Moritz Ruf","doi":"10.1016/j.jrtpm.2023.100390","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100390","url":null,"abstract":"<div><p>Classification yards represent network nodes in the single-wagonload transport system. The processes are complex due to a high number of involved resources and restrictive dependencies. Decisions on job sequencing and resource allocation have a major impact on outbound delays and thus on the quality of service in the network. Due to permanent updates of arrival times and resource availabilities, a constant revision of decisions is necessary. In many cases, considering multiple qualifications of the personnel is crucial for efficient operations. This paper presents an approach for the rescheduling of processes and the assignment of resources in classification yards, which allows to determine best working schedules based on current data such that the cumulative outbound delay of all trains is minimized. Therefore, the paper presents a mixed integer program that includes all essential components (tracks, locomotives and personnel with individual skill patterns). For the real-time capable solution of the optimization problem, four different heuristic approaches based on priority rules are presented. The performance of these approaches is evaluated by a gap analysis with respect to the solutions found by CPLEX. For this purpose, real example data of an operation day of a large classification yard in Germany are used.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100390"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49759715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An evaluation of the fairness of railway timetable rescheduling in the presence of competition between train operators 列车营运商之间存在竞争时，对铁路时间表改期公平性的评估

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100389

Edwin Reynolds , Matthias Ehrgott , Judith Y.T. Wang

引用次数: 0

A data-driven bi-objective matheuristic for energy-optimising timetables in a passenger railway network 客运铁路网络能量优化时刻表的数据驱动双目标数学

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100374

Matthias Villads Hinsch Als, Mathias Bejlegaard Madsen, Rune Møller Jensen

{"title":"A data-driven bi-objective matheuristic for energy-optimising timetables in a passenger railway network","authors":"Matthias Villads Hinsch Als, Mathias Bejlegaard Madsen, Rune Møller Jensen","doi":"10.1016/j.jrtpm.2023.100374","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100374","url":null,"abstract":"<div><p>Energy-efficient train timetabling (EETT) is essential to achieve the full potential of energy-efficient train control, which can reduce operating costs and contribute to a reduction in CO<span><math><msub><mrow></mrow><mrow><mn>2</mn></mrow></msub></math></span> emissions. This article proposes a bi-objective matheuristic to address the EETT problem for a railway network. To our knowledge, this article is the first to suggest using historical data from train operation to model the actual energy consumption, reflecting the different driving behaviours. The matheuristic employs a genetic algorithm (GA) based on NSGA-II. The GA uses a warm-start method to generate the initial population based on a mixed-integer program. A greedy first-come-first-served fail-fast repair heuristic is used to ensure feasibility throughout the evolution of the population. The objectives taken into account are energy consumption and passenger travel time. The matheuristic was applied to a real-world case from a large North European train operating company. The considered network consists of 107 stations and junctions, and 18 periodic timetables for 9 train lines. Our results show that for an entire network, a reduction up to 3.3% in energy consumption and 4.64% in passenger travel time can be achieved. The results are computed in less than a minute, making the approach suitable for integration with a decision support tool.</p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100374"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49727501","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Will China complete the 4.79-billion-ton railway freight transportation goal: An incremental potential research from the supply side 中国能否完成47.9亿吨铁路货运量目标:供给侧增量潜力研究

IF 3.7

Journal of Rail Transport Planning & Management Pub Date : 2023-06-01 DOI: 10.1016/j.jrtpm.2023.100385

Dajie Zuo , Qichen Liang , Rong Huang

{"title":"Will China complete the 4.79-billion-ton railway freight transportation goal: An incremental potential research from the supply side","authors":"Dajie Zuo , Qichen Liang , Rong Huang","doi":"10.1016/j.jrtpm.2023.100385","DOIUrl":"https://doi.org/10.1016/j.jrtpm.2023.100385","url":null,"abstract":"<div><p>In 2018, China's State Council proposed a 30% increase in railway freight volume (RFV) to 4.79 billion tons in 2020 over 2017. Subsequently, more than 30 provinces and cities in China have issued corresponding transportation structure adjustment plans, but the completion of this task has not been very smooth. The growth rate in 2019 is slower than that in 2018, and the incremental task in 2020 still remains 42.7%. China's railway freight transportation<span> capacity (RFTC) used to be in short supply for a long time, which has only eased in recent years. In order to explore the adaptation of China's current RFTC and incremental targets, and fully tap RFTC potential to formulate reasonable freight increment policies in the future, this article combines the simultaneous production and consumption feature of transportation sector and SBM-GRS (slack based measure-general returns to scale) data envelopment analysis to measure China's RFTC surplus space. The study found that from the supply side the incremental potential of China's railway freight turnover (RFT) is greater than that of RFV, which is caused by the imbalance of regional railway freight transportation. If the current RFV goal was replaced by RFT, RFTC input would save about 3%. This article suggests that China's future railway freight increment policy should take into account the regional imbalance of bulk cargo transportation, pay more attention to the growth of RFT, actively take advantage of railway container long-distance transportation, and make full use of overall RFTC.</span></p></div>","PeriodicalId":51821,"journal":{"name":"Journal of Rail Transport Planning & Management","volume":"26 ","pages":"Article 100385"},"PeriodicalIF":3.7,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49752254","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0