Transportmetrica A-Transport Science最新文献

Customised bus service design considering flexible vehicle size and transfer incentivization 考虑到灵活的车辆尺寸和换乘激励措施的定制公交服务设计

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-08-10 DOI: 10.1080/23249935.2024.2388618

Jianbiao Wang , Tomio Miwa , Dawei Li , Takayuki Morikawa

引用次数: 0

In loving memory of Professor Richard Allsop: a great loss to HKSTS and the transportation community 深切缅怀理查德-艾尔索普教授：香港科技学院和交通运输界的重大损失

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-04-06 DOI: 10.1080/23249935.2024.2338993

S. C. Wong (Professor)

引用次数: 0

Correlation-based feature selection and parallel spatiotemporal networks for efficient passenger flow forecasting in metro systems 基于相关性的特征选择和并行时空网络用于地铁系统的高效客流预测

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-04-04 DOI: 10.1080/23249935.2024.2335244

Cong Xiu , Shuguang Zhan , Jinyi Pan , Qiyuan Peng , Zhiyuan Lin , S.C. Wong

{"title":"Correlation-based feature selection and parallel spatiotemporal networks for efficient passenger flow forecasting in metro systems","authors":"Cong Xiu , Shuguang Zhan , Jinyi Pan , Qiyuan Peng , Zhiyuan Lin , S.C. Wong","doi":"10.1080/23249935.2024.2335244","DOIUrl":"10.1080/23249935.2024.2335244","url":null,"abstract":"<div><div>This paper presents a novel framework for predicting metro passenger flow that is both interpretable and computationally efficient. The proposed method first uses a correlation-based spatiotemporal feature selection strategy (Cor-STFS) to identify the optimal input scheme for the prediction model, effectively reducing unnecessary interference. The framework then introduces a new multivariate passenger flow prediction architecture called STA-PTCN-BiGRU, which combines a spatiotemporal attention (STA) mechanism, parallel temporal convolutional networks (PTCN), and bidirectional gated recurrent units (BiGRU) to capture the dynamic internal patterns of passenger flow. By utilising parallel computing, this architecture significantly reduces resource consumption. The effectiveness of the proposed approach is evaluated using four datasets from the Shanghai Metro. Experimental results show that the new method outperforms baseline approaches in terms of root mean square error (RMSE), mean absolute error (MAE), and symmetric mean absolute percentage error (SMAPE), achieving average reductions of 9.98%, 8.08%, and 13.29% in these metrics, respectively.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140594901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Logistics vehicle routing optimisation with synchronised transfer 同步转移的物流车辆路线优化

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-05-23 DOI: 10.1080/23249935.2024.2355954

Shuai Wang , Xiaoning Zhu , Siyu Zhuo , Pan Shang

引用次数: 0

Diversity-oriented dynamic ensemble selection approach for multi-class road traffic injury severity predictions with interpretable insights 面向多样性的多类别道路交通伤害严重程度预测的动态集成选择方法

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2025-08-06 DOI: 10.1080/23249935.2025.2542283

Kamran Aziz , Feng Chen , Inamullah Khan , Zahid Ullah , Mona Jamjoom , Muhammad Imran Khan

{"title":"Diversity-oriented dynamic ensemble selection approach for multi-class road traffic injury severity predictions with interpretable insights","authors":"Kamran Aziz , Feng Chen , Inamullah Khan , Zahid Ullah , Mona Jamjoom , Muhammad Imran Khan","doi":"10.1080/23249935.2025.2542283","DOIUrl":"10.1080/23249935.2025.2542283","url":null,"abstract":"<div><div>Accurately predicting crash injury severity in multi-class settings is vital for improving road safety, as different injury levels require tailored interventions. This study explores the effectiveness of Dynamic Ensemble Selection (DES) combined with Static Ensemble Selection (SES) classifiers for multi-class injury severity prediction. We employ diversity-driven DES methods—DES-KNN and DES-Clustering—alongside classifiers such as Extra Trees, AdaBoost, and XG-Boost. To address data imbalance, SMOTE and its variants are applied for equitable class representation. Results show that DES-KNN with XG-Boost, using SMOTE preprocessed data, achieves the best performance with a Balanced Accuracy Score of 0.56, G-Mean of 0.66, and MCC of 0.26. Additionally, LIME is used to interpret model predictions and enhance transparency by highlighting influential features. Our findings demonstrate that integrating DES with SES classifiers significantly improves predictive performance and interpretability, highlighting DES as a valuable approach for handling imbalanced multi-class crash severity data in support of sustainable transportation strategies.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146071084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Toll road crash severity using mixed logit model incorporating heterogeneous mean structures 使用包含异质平均结构的混合对数模型计算收费公路车祸严重程度

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-04-19 DOI: 10.1080/23249935.2024.2343755

Subasish Das , Monire Jafari , Ahmed Hossain , Rohit Chakraborty , Mahmuda Sultana Mimi

{"title":"Toll road crash severity using mixed logit model incorporating heterogeneous mean structures","authors":"Subasish Das , Monire Jafari , Ahmed Hossain , Rohit Chakraborty , Mahmuda Sultana Mimi","doi":"10.1080/23249935.2024.2343755","DOIUrl":"10.1080/23249935.2024.2343755","url":null,"abstract":"<div><div>The current study examined 1,465 crash observations (2017–2021) from Louisiana, identifying significant variables grouped into three major categories: drivers’, crash, and road characteristics. Considering crash injury severity as a dependent variable, we employed classic Multinomial Logit (MNL) model, and several other models to address unobserved heterogeneity in crash data including Random Parameter Logit (RPL), Random Parameter Logit with Heterogeneity in Means (RPLHM), and Random Parameter Logit with Heterogeneity in Means and Variance (RPLHMV). Our findings highlight the impact of factors such as driver gender, age, traffic violations, driver distractions, crash types, surface conditions, and roadway attributes on crash injury severity. These insights emphasise the complexity of toll road safety and inform targeted interventions to mitigate crash injury severity. Notably, male drivers and those under 25 years old increased property damage likelihood, while factors like driver distractions and lower posted speed limits reduced the likelihood of severe injuries or fatalities.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140610480","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Lane change decision prediction: an efficient BO-XGB modelling approach with SHAP analysis 车道变更决策预测：采用 SHAP 分析的高效 BO-XGB 建模方法

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-07-03 DOI: 10.1080/23249935.2024.2372020

Haobo Sun , Qixiu Cheng , Pu Wang , Yongqi Huang , Zhiyuan Liu

引用次数: 0

MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC) MicroSimACC：商用自适应巡航控制系统（ACC）潜在容量影响现场实验开放数据库

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-05-09 DOI: 10.1080/23249935.2024.2349921

Mingyuan Yang , Pablo Chon-Kan Munoz , Servet Lapardhaja , Yaobang Gong , Md. Ashraful Imran , Md. Tausif Murshed , Kemal Yagantekin , Md. Mahede Hasan Khan , Xingan (David) Kan , Choungryeol Lee

{"title":"MicroSimACC: an open database for field experiments on the potential capacity impact of commercial Adaptive Cruise Control (ACC)","authors":"Mingyuan Yang , Pablo Chon-Kan Munoz , Servet Lapardhaja , Yaobang Gong , Md. Ashraful Imran , Md. Tausif Murshed , Kemal Yagantekin , Md. Mahede Hasan Khan , Xingan (David) Kan , Choungryeol Lee","doi":"10.1080/23249935.2024.2349921","DOIUrl":"10.1080/23249935.2024.2349921","url":null,"abstract":"<div><div>Commercial availability of vehicle automation has become mainstream. Most of today’s new vehicles can perform longitudinal car following autonomously via Adaptive Cruise Control (ACC). Field experiments demonstrate that today’s commercially available ACC vehicles provide similar headways and capacities as human-driven vehicles on freeways under steady-state and free-flow conditions. However, field tests also demonstrated that the design of today’s commercially available ACC vehicles can lead to further capacity reduction when operating in non-steady-state conditions where queues are present and speeds frequently fluctuate. These experiments generated MicroSimACC, a comprehensive set of field data that encompasses full speed range car following with interruptions from lane change manoeuvres. This will benefit the research community by providing benchmark data for developing models to be integrated into microscopic simulations for more prospective analyses and planning.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140931767","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model 高速路段老龄驾驶员碰撞事故调查：采用极端梯度提升和随机参数模型的混合方法

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-06-06 DOI: 10.1080/23249935.2024.2362362

Ahmed Hossain , Xiaoduan Sun , Subasish Das , Monire Jafari , Julius Codjoe

{"title":"Investigating older driver crashes on high-speed roadway segments: a hybrid approach with extreme gradient boosting and random parameter model","authors":"Ahmed Hossain , Xiaoduan Sun , Subasish Das , Monire Jafari , Julius Codjoe","doi":"10.1080/23249935.2024.2362362","DOIUrl":"10.1080/23249935.2024.2362362","url":null,"abstract":"<div><div>Older drivers are often more susceptible to crashes due to age-related physical and cognitive limitations, particularly in complex driving environments. Considering the limited research in this area, this study focuses on investigating crashes involving older drivers on high-speed roadways (≥ 45 mph). The analysis is based on data collected from Louisiana State, encompassing 18,300 older driver-involved crashes (2017-2021). For analysis, a two-step hybrid modelling approach is employed: a) Extreme Gradient Boosting (XGBoost) is used to classify top variable features and b) Correlated Random Parameter Ordered Probit with Heterogeneity in Means (CRPOP-HM) is used to predict the likelihood of crash injury severity. . Some of the critical factors increasing the likelihood of fatal-severe or injury crashes involving older drivers on high-speed segments include the manner of collision (rear-end, right-angle, single-vehicle), primary contributing factor (violation, pedestrian action), presence of passenger (s), location type (open country, residential, business with mixed residential), and weekend.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141548599","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Improving analytic approximations of TSP tour lengths with adjustment factors 用调整因子改进 TSP 游程长度的解析近似值

IF 3.1 2区工程技术

Transportmetrica A-Transport Science Pub Date : 2026-01-02 Epub Date: 2024-05-08 DOI: 10.1080/23249935.2024.2346631

Youngmin Choi , Bruce L. Golden , Paul M. Schonfeld

{"title":"Improving analytic approximations of TSP tour lengths with adjustment factors","authors":"Youngmin Choi , Bruce L. Golden , Paul M. Schonfeld","doi":"10.1080/23249935.2024.2346631","DOIUrl":"10.1080/23249935.2024.2346631","url":null,"abstract":"<div><div>Optimizing Traveling Salesman Problem (TSP) tours requires substantial computational effort, leading researchers to develop approximations relating tour length to the number of visited points, <em>n</em>. Existing models, such as the <em>√nA</em> predictor, effectively approximate tour lengths for large-capacity vehicles but sacrifice accuracy for small <em>n</em> values relevant for most practical applications. Consequently, this study addresses this gap by proposing models with uniform node distributions, which incorporate realistic factors, such as central vs. random starting points and various service zone shapes. These factors are then integrated into a single equation, enhancing applicability. Furthermore, the exponent of n is statistically estimated to be significantly different from 0.5, challenging previous studies. Our proposed model estimates TSP tour lengths more accurately, particularly for small <em>n</em> values, and maintains accuracy for large <em>n</em> values, with errors below 3.11% for up to 600 points. This model offers a more precise and versatile alternative to current models.</div></div>","PeriodicalId":48871,"journal":{"name":"Transportmetrica A-Transport Science","volume":"22 1","pages":""},"PeriodicalIF":3.1,"publicationDate":"2026-01-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140828095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0