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Toll road crash severity using mixed logit model incorporating heterogeneous mean structures Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-18 Subasish Das, Monire Jafari, Ahmed Hossain, Rohit Chakraborty, Mahmuda Sultana Mimi
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. Con...
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Cooperative lane-changing in mixed traffic: a deep reinforcement learning approach Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-18 Xue Yao, Zhaocheng Du, Zhanbo Sun, Simeon C. Calvert, Ang ji
Deep Reinforcement Learning (DRL) has made remarkable progress in autonomous vehicle decision-making and execution control to improve traffic performance. This paper introduces a DRL-based mechanis...
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Heterogeneous vehicle scheduling with precedence constraints Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-08 Ruiyou Zhang, Zhujun Liu, Ilkyeong Moon
The problem of heterogeneous vehicle scheduling with precedence constraints is inspired by the transportation service in tourism areas. Tourists must take the shuttle vehicles provided by the areas...
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A synchronization-constraints-based dual bands method of traffic signal optimization Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-06 Kai Lu, Guanghui Xu, Xiaofeng Xie, Jianmin Xu, Yinhai Wang
This paper presents a synchronization-constraints-based dual bands method of traffic signal optimization for multiple traffic flows. The synchronization coefficient, traffic volume ratio, synchroni...
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A comparison of the accumulation-based, trip-based and time delay macroscopic fundamental diagram models Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-05 Yunping Huang, Jianhui Xiong, Shu-Chien Hsu, Agachai Sumalee, William Lam, Renxin Zhong
Macroscopic fundamental diagram (MFD) is widely applied in network modelling and management, such as route guidance and vehicle relocation, which are formulated as generalised dynamic traffic assig...
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In loving memory of Professor Richard Allsop: a great loss to HKSTS and the transportation community Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-05 S. C. Wong
Published in Transportmetrica A: Transport Science (Ahead of Print, 2024)
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Headway regularity as an attribute for classifying bus drivers Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-05 Yerly Martínez-Estupiñan, Felipe Delgado, Juan Carlos Muñoz
Different indices have been proposed in the literature to characterize headway regularity. These metrics aggregate the headway variability for a service, but none can be directly associated with a ...
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Correlation-based feature selection and parallel spatiotemporal networks for efficient passenger flow forecasting in metro systems Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-04-04 Cong Xiu, Shuguang Zhan, Jinyi Pan, Qiyuan Peng, Zhiyuan Lin, S.C. Wong
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...
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An improved alternating direction method of multipliers for solving deterministic user equilibrium Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-03-15 Honggang Zhang, Zhiyuan Liu, Xiangyang Xu, Xinyuan Chen, Yunchi Wu, Pan Liu
An improved alternating direction method of multipliers (iADMM) algorithm is proposed for solving the deterministic user equilibrium (DUE) problem. The iADMM algorithm introduces a key improvement ...
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An efficient hyperpath-based algorithm for the capacitated transit equilibrium assignment problem Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-03-11 Wenxin Liang, Zhandong Xu, Jun Xie, Xiaobo Liu, Yuting Feng
This paper studied the capacitated transit equilibrium assignment problem (CTEAP), which particularly accounts for the capacity effect that impacts passengers' route choices in a transit network. S...
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Cooperative design of feeder bus and bike-sharing systems Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-02-28 Miaoqing Hu, W. Y. Szeto, Yue Wang
Feeder services, which provide travellers effective access from local areas to trunk-line systems, are essential, especially when the long-haul trunk routes are designed with large spacing between ...
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Measuring robustness in uncertain topologies: a study of on-demand bus networks Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-02-15 Jin-Yang Li, Jing Teng, Hui Wang
Ensuring the robustness of bus networks is essential for delivering reliable and efficient mobility services to passengers. This paper addresses the challenge of assessing the robustness of on-dema...
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Uncertainty-aware human-like driving policy learning with deep Bayesian inverse reinforcement learning Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-02-15 Di Zeng, Ling Zheng, Xiantong Yang, Yinong Li
The application of deep reinforcement learning in driving policy learning for automated vehicles is limited by the difficulty of designing reward functions. Most existing inverse reinforcement lear...
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Equilibrium condition-based optimization models for network-wide travel time estimation using limited observed data Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-01-31 Shuhan Cao, William H. K. Lam, Keqin Liu, Hu Shao, Mei Lam Tam, Ting Wu
This paper presents a series of optimisation models to estimate network-wide travel times under equilibrium conditions. The proposed models estimate the upper and lower bounds (ULB) of the maximum ...
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Integrated physical and service network design of suburban rail under the coordination of urban rail Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-01-22 Xinmei Chen, Virginie Lurkin, Dian Wang, Qiyuan Peng, Siyu Tao
Motivated by a released official policy in China to promote the development of suburban rail within metropolitan areas, this paper investigates the suburban rail network design problem by integrati...
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Optimising hierarchical emergency logistics network under ambiguous demand and transportation cost Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-01-02 Qi Wang, Yankui Liu, Hongliang Li
This article studies the response problem of an emergency logistics network with a decision hierarchy relationship under uncertainty. To account for the partial distribution information about uncer...
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Response time of mixed platoons with traditional and autonomous vehicles in field trials: impact assessment on flow stability and safety Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2024-01-02 Tanmay Das, Ishtiak Ahmed, Billy M. Williams, Nagui M. Rouphail
This study investigates the response times of autonomous vehicles (AVs) equipped with adaptive cruise control (ACC) and traditional human-driven vehicles (TVs) in mixed traffic scenarios. The prima...
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Operationalizing modular autonomous customised buses based on different demand prediction scenarios Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-12-21 Rongge Guo, Saumya Bhatnagar, Wei Guan, Mauro Vallati, Shadi Sharif Azadeh
This paper presents a novel framework for customised modular bus systems that leverages travel demand prediction and modular autonomous vehicles to optimise services proactively. The proposed frame...
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Efficient asymmetric reposition strategy of rolling stock for urban rail transit systems Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-12-20 Qian Zhu, Yun Wang, Pan Shang, Xiaoning Zhu
Balancing energy efficiency with high-quality service on urban rail lines with highly asymmetric passenger demand is a crucial yet challenging issue. This paper proposes an efficient asymmetric rol...
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Lane management for asymmetric mixed traffic flow on bidirectional multi-lane roadways Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-12-18 Yuan Zheng, Min Xu, Shining Wu, Shuaian Wang
To manage the bidirectional asymmetric mixed traffic flow with connected and automated vehicles (CAVs) and human-driven vehicles, the study proposes a lane management (LM) model based on the joint ...
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Analysis of discretionary lane-changing behaviours of autonomous vehicles based on real-world data Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-11-30 Xiao (Luke) Wen, Chunxi Huang, Sisi Jian, Dengbo He
This study aims to quantify the impact of discretionary lane-changing (DLC) on following vehicles (FVs) in the target lane using real-world dataset. The Waymo Open Dataset is used to identify the d...
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Flexible facility requirements for strategic planning of airport passenger terminal infrastructure Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-11-30 Manuel Waltert, Edgar Jimenez Perez, Romano Pagliari
Facility requirements determine how and when the capacity of airport passenger terminal facilities is adjusted over time to meet expected demand. Given high levels of uncertainty inherent in long-t...
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Personalised incentives with constrained regulator's budget Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-11-23 Lucas Javaudin, Andrea Araldo, André de Palma
We consider a regulator driving individual choices towards increasing social welfare by providing personal incentives. We formalise and solve this problem by maximising social welfare under a budge...
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Coordinated logistics with trucks and drones for premium delivery Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-11-17 Dongwook Kim, Chang Seong Ko, Ilkyeong Moon
Last-mile delivery, the final stage of the delivery process before a package arrives at a customer's address, has emerged as an important business opportunity for inland transportation. As people's...
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Applying an improved calibration method in the safety evaluation framework for the open tolling system Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-20 Seung-oh Son, Kyeongju Kwon, Juneyoung Park, Mohamed Abdel-Aty
This study proposed an improved calibration method in the safety evaluation framework and analysed the safety effect of installing the open road tolling (ORT) system. Although the ORT system in Sou...
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Empirical study of the effects of physics-guided machine learning on freeway traffic flow modelling: model comparisons using field data Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-20 Zhao Zhang, Yun Yuan, Mingchen Li, Pan Lu, Xianfeng Terry Yang
Recent studies have shown the successful implementation of classical model-based approaches (e.g. macroscopic traffic flow modelling) and data-driven approaches (e.g. machine learning – ML) to mode...
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Artificial intelligence in automatic passenger counting: cost-efficient validation using the partitioned equivalence test Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-18 David Ellenberger, Michael Siebert
In Automatic Passenger Counting (APC), the demand for very low errors has been fueled by applications like revenue sharing, which amounts to massive annual sums. As a consequence, APC validation co...
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The optimal solution to the energy-efficient train control in a multi-trains system–Part 2: the optimality and the uniqueness Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-18 Yu Rao, Xiaoyun Feng, Qingyuan Wang, Pengfei Sun
When a train travels in a multi-trains system, the power flow of other trains and the track grades make up the spatial–temporal area (STA) for the train. Finding the optimal solution for the energy...
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The optimal solution to the energy-efficient train control in a multi-trains system-part 1: the algorithm design Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-18 Yu Rao, Xiaoyun Feng, Qingyuan Wang, Pengfei Sun
When a train travels in a multi-trains system, the power flow of other trains and the track grades make up the spatial–temporal area (STA) for the train. Finding the optimal solution for the energy...
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Joint operation planning of drivers and trucks for semi-autonomous truck platooning Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-09 Yilang Hao, Zhibin Chen, Jiangang Jin, Xiaotong Sun
Semi-autonomous truck platooning, a futuristic and promising traveling mode of trucks on highways, has received extensive attention as autonomous driving gains more maturity. Under the semi-autonom...
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Assessing transportation network redundancy by integrating route diversity and spare capacity Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-10-11 Zijian Wang, Xiangdong Xu, Yuchuan Du
In this paper, we develop a new transportation network redundancy measure by integrating the route diversity and spare capacity dimensions, which have been demonstrated as two complementary dimensi...
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Convexity and global optimisation of lane-based fixed-time signal model for delay minimisation at an isolated intersection Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-30 Haiming Hao, Hui Jin
Lane-based fixed-time signal is basic to various signal control strategies. It performs well in maximizing road capacity, but is faced with significant challenge in minimizing traffic delay. This s...
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Optimal vehicle capacity and dispatching policy considering crowding in public bus transit services Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-21 Reza Mahmoudi, Saeid Saidi, S. C. Wirasinghe
This study investigates the often overlooked impact of on-board crowding on operational and user costs in public transit systems, specifically within a many-to-many bus transit line with varying de...
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Mapping the spatial organisation of air transport network by WENA-MLST analysis Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-22 Chengliang Liu, Bangjuan Wang, Hong Zhang
Due to the airline hubs’ organisation such as linkage, hierarchical structure, and hub-and-spoke remains a mystery at a global scale. Thereby, the research aims to unravel the spatial organisation ...
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A toll-based approach for regulating hazmat transportation network considering boundedly rational route choice Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-15 Honggang Zhang, Wei Wang, Zhiyuan Liu
This paper introduces a novel toll charge to regulate transportation of hazardous materials (hazmat), taking into account that carriers are bounded rational decision-makers. In the case of bounded rationality, the route choice behaviour of carriers is described based on the link-based perception error model. Then, a novel bi-level programming model is developed, which aims to minimise both total tolls
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A multiclass simulation-based dynamic traffic assignment model for mixed traffic flow of connected and autonomous vehicles and human-driven vehicles Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-14 Behzad Bamdad Mehrabani, Jakob Erdmann, Luca Sgambi, Seyedehsan Seyedabrishami, Maaike Snelder
Connected and Autonomous Vehicles (CAVs) may exhibit different driving and route choice behaviours compared to Human-Driven Vehicles (HDVs), which can result in a mixed traffic flow with multiple classes of route choice behaviour. Therefore, it is necessary to solve the Multiclass Traffic Assignment Problem (TAP) for mixed traffic flow. However, most existing studies have relied on analytical solutions
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Variable speed limit modelling to improve traffic safety and efficiency of mixed traffic flow by a two-stage framework Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-07 Jieling Jin, Helai Huang, Ye Li, Gongquan Zhang, Yuxuan Dong, Bo Zhou, Hongli Xue
A two-stage variable speed limits (VSL) modelling framework is proposed to enhance traffic safety and efficiency at freeway bottlenecks with mixed traffic flow comprising both human-driven and autonomous vehicles. The first-stage macroscopic VSL control framework is based on an extended cell transmission model (ECTM) and a VSL optimal control model. The ECTM serves as a traffic state predictor and
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Coordinated flow model for strategic planning of autonomous mobility-on-Demand systems Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-05 Jiangbo (Gabe) Yu, Michael F. Hyland
High-quality strategic planning of autonomous mobility-on-demand (AMOD) systems is critical for the success of the subsequent phases of AMOD system implementation. To assist in strategic AMOD planning, we propose a dynamic and flexible flow-based model of an AMOD system. The proposed model is computationally fast while capturing the state transitions of two coordinated flows (i.e. co-flows): the AMOD
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Multi-period emergency vehicle fleet redistribution and dispatching Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-03 Zheyi Tan, Lu Zhen, Zhiyuan Yang, Lilan Liu, Tianyi Fan
This research paper delves into the intricate task of redistributing and dispatching emergency vehicles across multiple periods, while considering the unpredictable occurrence time and locations of traffic accidents. To address this challenge, we propose a two-stage stochastic programming model aimed at minimising the expected penalty cost in the face of various random scenarios. In the first stage
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Timing co-evolutionary path optimisation method for emergency vehicles considering the safe passage Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-09-01 Jiabin Wu, Yifeng Lin, Weiwei Qi
Emergency vehicles encounter traffic accidents at intersections of the network frequently, which seriously threatens the lives of rescue teams and patients. To improve the driving safety and travel efficiency of emergency vehicles, this study proposes a new method of timing co-evolutionary path optimisation for emergency vehicles based on the safety evaluation of intersections in an uncertain environment
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Extension of a static into a semi-dynamic traffic assignment model with strict capacity constraints Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-08-24 Luuk Brederode, Lotte Gerards, Luc Wismans, Adam Pel, Serge Hoogendoorn
To improve the accuracy of large-scale strategic transport models in congested conditions, this paper presents a straightforward extension of a static capacity-constrained traffic assignment model into a semi-dynamic version. The semi-dynamic model is more accurate than its static counterpart as it relaxes the empty network assumption, but, unlike its dynamic counterpart, maintains the stability and
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Safe and efficient manoeuvring for emergency vehicles in autonomous traffic using multi-agent proximal policy optimisation Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-08-16 Leandro Parada, Eduardo Candela, Luis Marques, Panagiotis Angeloudis
Manoeuvring in the presence of emergency vehicles is still a major issue for vehicle autonomy systems. Most studies that address this topic are based on rule-based methods, which cannot cover all possible scenarios that can take place in autonomous traffic. Multi-Agent Proximal Policy Optimisation (MAPPO) has recently emerged as a powerful method for autonomous systems because it allows for training
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Bifurcation control based on improved intelligent driver model considering stability and minimum gasoline consumption Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-08-07 Liyou Li, Weilin Ren, Rongjun Cheng
Advanced driver assistance system (ADAS) plays an important role in the transition period before the full maturity of self-driving technology. In this paper, an intelligent driver model with multiple time delays (IDM-MTD) is established to describe the dynamic characteristics of vehicles equipped with ADAS. Moreover, a control term that considers the velocity difference between the current and historical
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Benchmarking the performance of urban rail transit systems: a machine learning application Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-08-02 Farah A. Awad, Daniel J. Graham, Laila AitBihiOuali, Ramandeep Singh, Alexander Barron
Urban rail transit (URT) systems operate in heterogenous environments where their performance is affected by many exogenous factors. However, conventional benchmarking methods assume homogeneity of many of these factors which could result in misleading comparisons of performance. This study provides a methodological contribution to the transit benchmarking literature through a systemic data-driven
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Integration of ridesharing and activity travel pattern generation Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-08-01 Ali Najmi, Travis Waller, Wei Liu, Taha H. Rashidi
This paper proposes a mobility system serving as an innovative platform that synchronises a ridesharing model and an Activity Travel Pattern (ATP) generator, enabling a synergistic enhancement of participants’ mobility experiences. Through system-level integration, it can significantly improve the performance of ridesharing systems while also exploring the intricate relationship between ridesharing
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A novel hybrid deep learning model with ARIMA Conv-LSTM networks and shuffle attention layer for short-term traffic flow prediction Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-26 Ali Reza Sattarzadeh, Ronny J. Kutadinata, Pubudu N. Pathirana, Van Thanh Huynh
Traffic flow prediction requires learning of nonlinear spatio-temporal dynamics which becomes challenging due to its inherent nonlinearity and stochasticity. Addressing this shortfall, we propose a new hybrid deep learning model based on an attention mechanism that uses multi-layered hybrid architectures to extract spatial–temporal, nonlinear characteristics. Firstly, by designing the autoregressive
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Modelling the lateral dimension of vehicles movement: a stochastic differential approach with applications Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-25 HongSheng Qi
A stochastic lateral movement model is proposed to address the limitations of current traffic models, which fail to capture the stochastic nature of the lateral component in vehicle movement during lane keeping and lane changing. This model incorporates a lateral noise component and a lateral movement component, with parameters that have clear physical interpretations including noise intensity, driver’s
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Graph convolutional networks with learnable spatial weightings for traffic forecasting applications Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-25 Bi Yu Chen, Yaohong Ma, Jiale Wang, Tao Jia, Xianglong Liu, William H. K. Lam
How to select a suitable spatial weighting scheme for convolutional graph neural networks (ConvGNNs) is challenging. In this study, we propose a ConvGNN, termed learnable graph convolutional (LGC) network, which learns spatial weightings between a road and its k-hop neighbours as learnable parameters in the spatial convolutional operator. A dynamic LGC (DLGC) network is further proposed to learn the
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Quality of service measurement for electric vehicle fast charging stations: a new evaluation model under uncertainties Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-24 Zhonghao Zhao, Carman K.M. Lee, Jingzheng Ren, Yungpo Tsang
This study addresses the quality of service (QoS) evaluation problem for electric vehicle (EV) fast charging stations (FCSs). With the increasing market penetration of EVs, effective service quality evaluation under different charging scenarios is a pressing and open issue for planning FCSs to accommodate non-stationary customer charging demand. Unlike previous studies, we make the first attempt to
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Integrating ride-hailing services with public transport: a stochastic user equilibrium model for multimodal transport systems Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-20 Bing Liu, Yuxiong Ji, Oded Cats
Public transport (PT) agencies are increasingly keen on integrating ride-hailing (RH) services with PT to improve overall mobility. Understanding the traffic flow distribution in the integrated system is vital for the policy decision-making and services design of such a system. We propose a stochastic user equilibrium (SUE) model for multimodal transport systems consisting of private car, PT and RH
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Exploring the joint impacts of income, car ownership, and built environment on daily activity patterns: a cluster analysis of trip chains Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-19 Elnaz Yousefzadeh Barri, Steven Farber, Hadi Jahanshahi, Ignacio Tiznado-Aitken, Eda Beyazit
Clustering activity patterns and identifying homogeneous travel behaviour through trip chain sequences offer valuable insight for transportation planners and policymakers in addressing transport equity problems and travel demand management. This study explores how income and car-ownership levels determine mobility patterns and travellers' decisions. Unlike previous studies that investigated the travel
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Spatiotemporal clustering for the impact region caused by a traffic incident: an improved fuzzy C-means approach with guaranteed consistency Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-19 Zhenjie Zheng, Zhengli Wang, Xiqun Chen, Wei Ma, Bin Ran
Traffic incidents disrupt the normal flow of vehicles and induce nonrecurrent traffic congestion. It has been well accepted that the shape of the spatiotemporal region impacted by a traffic incident should be consistent with the propagation of shockwaves. Although there has been a variety of approaches that attempt to estimate the impact region of traffic incidents, most of them are not capable of
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Traffic efficiency and fairness optimisation for autonomous intersection management based on reinforcement learning Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-19 Yuanyuan Wu, David Z. W. Wang, Feng Zhu
Autonomous Intersection Management (AIM) for high-level Connected and Automated Vehicles (CAVs) has evolved from rule-based to optimisation-based policies. However, at congested major-minor intersections, optimising solely for efficiency can negatively impact vehicle fairness. This study addresses this issue by proposing a deep reinforcement learning approach that optimises both traffic efficiency
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Kernel estimates as general concept for the measuring of pedestrian density Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-14 Jana Vacková, Marek Bukáček
The standard definition of pedestrian density produces scattered values, hence, many approaches have been developed to improve the features of the estimated density. This paper provides a review of generally applied methods and presents a general framework based on various kernels that bring desired properties of density estimates (e.g. continuity) and incorporate ordinarily used methods. The developed
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Bimodal transit design with heterogeneous demand elasticity under different fare structures Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-05 Yi Yang, Xinguo Jiang, Yusong Yan, Tao Liu, Yu Jiang
The study develops a new optimisation model to design a bimodal transit system from a microeconomic view to maximise the profit of a transit agency considering heterogeneous demand elasticity and different fare structures. Bimodal transit network parameters are optimized to better serve passenger demand. An elastic demand function is devised to include various time components and incorporate flat,
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Key factors affecting motorcycle-barrier crash severity: an innovative cluster-regression technique Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-07-03 Reuben Tamakloe, Subasish Das, Emmanuel Kofi Adanu, Dongjoo Park
Highway motorcycle-barrier crashes are uncommon but are associated with severe ramifications. Little has been done to understand the factors related to these crashes, making it difficult to establish appropriate mitigation policies. This study identifies homogeneous groups of motorcycle-barrier crashes on highways and investigates cluster-specific key factor associations and the determinants of injury
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The real-time dynamic online feeder service with a maximum headway at mandatory stops Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-06-28 Bryan David Galarza Montenegro, Kenneth Sörensen, Pieter Vansteenwegen
On the one hand, fully flexible demand-responsive feeder services efficiently tailor their service to passengers' needs. Traditional services, on the other hand, offer predictability and easier cost control. This paper considers a semi-flexible feeder service that combines positive characteristics of both traditional and fully flexible services. There are two types of bus stops in this service. Mandatory
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A projected Newton-like inertial dynamics for modeling day-to-day traffic evolution with elastic demand Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-06-26 Renxin Zhong, Xin-an Li, Qingnan Liang, Zhibin Chen, Tianlu Pan
This paper proposes a projected Newton-like inertial dynamics for modeling second-order day-to-day (DTD) traffic evolution with elastic travel demand. The proposed DTD model describes double dynamics of traffic flow and travel cost based on a class of second-order gradient-like dissipative dynamic systems. We use the projection operator to prevent the existence of negative flow, which is regarded as
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Optimal public transport timetabling with autonomous-vehicle units using coupling and decoupling tactics Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-06-15 Yaoyao Wang, Avishai (Avi) Ceder, Zhichao Cao, Silin Zhang
Fluctuating demand for public transport (PT) is one of the main reasons for unreliable PT service, and subsequent passenger frustration at being left behind at PT stops. A novel way to solve this situation is to optimally use autonomous PT vehicles with coupling and decoupling (C&D) of vehicle units to accommodate the fluctuating PT demand and reliability issues. In this way, vehicle size is added
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Estimation of stochastic link capacity and link performance function including uncertainty of driver’s behaviour Transportmetr. A Transp. Sci. (IF 3.3) Pub Date : 2023-06-01 Teppei Kato, Kenetsu Uchida, Ryuichi Tani, Kazunori Munehiro
ABSTRACT Recently, user equilibrium models with uncertainty were proposed to describe stochastic travel time in road networks. The accurate estimation of a stochastic link capacity is important for such models. This study develops a method for estimating a stochastic link capacity by considering the uncertainty of the driver’s behaviour. We postulate that the stochastic link capacity follows a lognormal