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Explore the lane change trajectory pattern driven by full-time domain trajectory data

Journal of Traffic and Transportation engineering(English Edition) 2024年

作者： Min Zhang Yuhan Nie Bo Wang Chi Zhang Yuming Zhou Yijing Zhao School of Transportation engineering， Chang'an University engineering research center of highway infrastructure digitalization， ministry of education School of highway Chang'an University School of Civil and Environmental engineering， Nanyang Technological University

Due to the increasing density and complexity of the highway network， a deep understanding of the characteristics of lane changing (LC) behavior is crucial for road refinement design. The emergence of full time domain trajectory big data provides unprecedented opportunities for in-depth research on highway safety geometry design. This article proposes a method framework for extracting LC trajectory patterns to explore the combination trajectory patterns during the LC process. This article achieves subdivision in driving mode detection by using the Adaptive Pruned Exact Linear Time (APELT) algorithm to detect change points， taking into account the short sequence features of LC. In order to achieve the classification of segmented fragments， we report a clustering technique based on similarity matching (SM)， which can effectively avoid the problem of excessive distortion in similarity measurement. The results indicate that APELT technology has certain advantages in F1 score and accuracy of LC pattern recognition， which is more in line with reality. The kappa score based on similarity matching is greater than 0.8， indicating high accuracy of pattern recognition. This study provides a novel data mining method for a comprehensive understanding of lane changing behavior under full time domain big data， which will provide reference for road design in complex scenes.

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Analysing taxi customer-search behaviour using Copula-based joint model

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Transportation Safety and Environment 2022年第1期4卷 49-62页

作者： Helai Huang Zhenyuan Fang Yiwei Wang Jinjun Tang Xin Fu Smart Transportation Key Laboratory of Hunan Province School of Traffic and Transportation EngineeringCentral South UniversityChangsha 410075China School of Transportation engineering Chang’an UniversityXi’an 710064China engineering research center of highway infrastructure digitalization Ministry of EducationXi’an 710064China

The drivers of vacant taxis tend to cruise the road network searching new passengers,which leads to additional traffic congestion,air pollution and other *** study introduces a Copula-based joint model to analyse destination selection and route choice behaviour in the customer-search process.A multinomial logit model is used to analyse the destination selection behaviour,and a path size logit model is used to explore the routes choice ***,the joint model applied Copula function is then established to analyse the correlation between these two *** destination customer generation rate,destination distance,route customer generation rate,path travel time,cumulative intersection delay,path size and route length are selected as explanatory *** taxis trajectory data were collected by global positioning system in Xidan District of Beijing City from September 2014 to February *** the log-likelihood,Bayesian information criterion as evaluation indexes to measure the fitting result,the joint model applied Copula function has the highest *** effect of explanatory variables on customer search behaviour is discussed based on the parameter estimation *** results of this study are helpful to understand the customer-search behaviour of taxi drivers to reduce operating costs and improve the efficiency of the taxi operation system.

关键词： customer-search behaviour destination selection route choice model Copula function taxi trajectory data

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New innovations in pavement materials and engineering:A review on pavement engineering research 2021

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Journal of Traffic and Transportation engineering(English Edition) 2021年第6期8卷 815-999页

作者： JTTE Editorial Office Jiaqi Chen Hancheng Dan Yongjie Ding Yangming Gao Meng Guo Shuaicheng Guo Bingye Han Bin Hong Yue Hou Chichun Hu Jing Hu Ju Huyan Jiwang Jiang Wei Jiang Cheng Li Pengfei Liu Yu Liu Zhuangzhuang Liu Guoyang Lu Jian Ouyang Xin Qu Dongya Ren Chao Wang Chaohui Wang Dawei Wang Di Wang Hainian Wang Haopeng Wang Yue Xiao Chao Xing Huining Xu Yu Yan Xu Yang Lingyun You Zhanping You Bin Yu Huayang Yu Huanan Yu Henglong Zhang Jizhe Zhang Changhong Zhou Changjun Zhou Xingyi Zhu Editorial Office of Journal of Traffic and Transportation engineering(English Edition) Chang’an UnivieristyXi’an 710064China School of Civil engineering Central South UniversityChangsha 410075China School of Civil engineering Chongqing Jiaotong UniversityChongqing 400074China Department of Structural engineering Faculty of Civil Engineering and GeosciencesDelft University of TechnologyDelft 2628 CNthe Netherlands The Key Laboratory of Urban Security and Disaster engineering of ministry of education Beijing University of TechnologyBeijing 100124China College of Civil engineering Hunan UniversityChangsha 410082China School of Civil and Transportation engineering Beijing University of Civil Engineering and ArchitectureBeijing 100044China School of Transportation Science and engineering Harbin Institute of TechnologyHarbin 150090China College of Metropolitan Transportation Beijing University of TechnologyBeijing 100124China School of Civil engineering&Transportation South China University of TechnologyGuangzhou 510641China School of Transportation Southeast UniversityNanjing 211189China Department of Civil&Environmental engineering University of WaterlooWaterlooON N2L 3G1Canada Department of Civil and Environmental engineering The Hong Kong Polytechnic UniversityHong KongChina School of highway Chang’an UniversityXi’an 710064China Institute of highway engineering RWTH Aachen UniversityAachen 52074Germany School of Transportation&Logistics Dalian University of TechnologyDalian 116024China School of Civil engineering Southwest Jiaotong UniversityChengdu 611756China Faculty of Architecture Civil and Transportation EngineeringBeijing University of TechnologyBeijing 100124China Department of Civil engineering Aalto UniversityEspoo 02150Finland Nottingham Transportation engineering center(NTEC) University of NottinghamNottingham NG72RDUK State Key Laboratory of Silicate Materials for Architectures Wuhan University of TechnologyWuhan 430070China College of Transportation Engineer

Sustainable and resilient pavement infrastructure is critical for current economic and environmental *** the past 10 years,the pavement infrastructure strongly supports the rapid development of the global social *** theories,new methods,new technologies and new materials related to pavement engineering are *** of pavement infrastructure is a typical multi-physics *** of actual coupled behaviors of traffic and environmental conditions,predictions of pavement service life become more and more complicated and require a deep knowledge of pavement material *** order to summarize the current and determine the future research of pavement engineering,Journal of Traffic and Transportation engineering(English Edition)has launched a review paper on the topic of"New innovations in pavement materials and engineering:A review on pavement engineering research 2021".Based on the joint-effort of 43 scholars from 24 well-known universities in highway engineering,this review paper systematically analyzes the research status and future development direction of 5 major fields of pavement engineering in the *** content includes asphalt binder performance and modeling,mixture performance and modeling of pavement materials,multi-scale mechanics,green and sustainable pavement,and intelligent ***,this review paper is able to provide references and insights for researchers and engineers in the field of pavement engineering.

关键词： Asphalt binder Asphalt mixture Modeling of pavement materials Multi-scale mechanics Green and sustainable pavement Intelligent pavement

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Prediction of instantaneous driving safety in emergency scenarios based on connected vehicle basic safety messages

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Journal of Intelligent and Connected Vehicles 2019年第2期2卷 78-90页

作者： Kai Yu Liqun Peng Xue Ding Fan Zhang Minrui Chen School of Transport and Logistics East China Jiao Tong UniversityNanchangChina School of Transport and Logistics East China Jiao Tong UniversityNanchangChina and Department of Civil and Environmental EngineeringUniversity of AlbertaEdmontonCanada Beijing GOTEC ITS Technology Co. Ltd and Research Institute of HighwayMOTBeijingChina Jiangxi Provincial highway Network Management center NanchangChina

Purpose–Basic safety message(BSM)is a core subset of standard protocols for connected vehicle system to transmit related safety information via vehicle-to-vehicle(V2V)and vehicle-to-infrastructure(V2I).Although some safety prototypes of connected vehicle have been proposed with effective strategies,few of them are fully evaluated in terms of the signiﬁcance of BSM messages on performance of safety applications when in ***/methodology/approach–To address this problem,a data fusion method is proposed to capture the vehicle crash risk by extracting critical information from raw BSMs data,such as driver volition,vehicle speed,hard accelerations and ***,a classiﬁcation model based on information-entropy and variable precision rough set(VPRS)is used for assessing the instantaneous driving safety by fusing the BSMs data fromﬁeld test,and predicting the vehicle crash risk level with the driver emergency maneuvers in the next short ***–Theﬁndings and implications are discussed for developing an improved warning and driving assistant system by using BSMs ***/value–Theﬁndings of this study are relevant to incorporation of alerts,warnings and control assists in V2V applications of connected *** applications can help drivers identify situations where surrounding drivers are volatile,and they may avoid dangers by taking defensive actions.

关键词： Collision avoidance system Connected vehicle Vehicle crash assessment Basic safety messages

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