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Decentralized spreading of ephemeral road incident information between vehicles 在车辆之间分散传播短暂的道路事故信息
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-01-02 DOI: 10.1080/15472450.2022.2095206
Wenyan Hu , Stephan Winter , Kourosh Khoshelham

Ephemeral incidents, or events in traffic or on the roadside that have only local and short-term impact on road safety and road capacity, are noteworthy for vehicles nearby—especially those approaching and planning to pass by. We study ways to communicate detected ephemeral incidents between connected vehicles, comparing various decentralized (vehicle-to-vehicle) communication strategies and weighing with established centralized mechanisms with regard to efficiency and broadcasting redundancy. The strategies are implemented in a simulation using realistic road networks, travel routes and traffic. We identify the strategy that achieves up to 100% success rate in transmitting incident messages to the affected vehicles under each scenario, while minimizing broadcast redundancy. In general, decentralized vehicle-to-vehicle communication strategies show strong potential to transmit incident messages efficiently and effectively.

对于附近的车辆,尤其是那些正在接近或计划经过的车辆来说,短暂事件,即交通中或路边发生的、对道路安全和道路通行能力只有局部和短期影响的事件,是值得注意的。我们研究了互联车辆间通信检测到的短暂事件的方法,比较了各种分散式(车对车)通信策略,并在效率和广播冗余方面对现有的集中式机制进行了权衡。我们利用现实的道路网络、行驶路线和交通流量对这些策略进行了模拟。我们确定了在每种情况下向受影响车辆发送事故信息的成功率高达 100% 的策略,同时将广播冗余降至最低。总体而言,分散式车对车通信策略在高效率、高效益地传输事故信息方面显示出强大的潜力。
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引用次数: 0
A methodology for generating driving styles for autonomous cars 生成自动驾驶汽车驾驶风格的方法
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-01-02 DOI: 10.1080/15472450.2022.2109417
Rafael Peralta , Israel Becerra , Ubaldo Ruiz , Rafael Murrieta-Cid

This work is about the generation of driving styles for autonomous cars. Here, we propose a definition of driving style based on the partition of controller parameters for self-driving vehicles. The main contributions of this work are the following. 1) A methodology based on the controllers’ parameters for creating comfortable driving styles that can be used as autonomous cars’ operation modes. 2) A proposal to use virtual reality as a testbed for the evaluation of driving styles by users. 3) As an illustration of our methodology, we determine and evaluate distinguishable driving styles by partitioning the time-to-collision parameter of the Intelligent Driver Model (IDM) controller using the Just Noticeable Difference (JND). 4) A proposal of four driving styles that are equally preferable among passengers.

这项工作是关于自动驾驶汽车驾驶风格的生成。在此,我们提出了基于自动驾驶汽车控制器参数分区的驾驶风格定义。这项工作的主要贡献如下。1) 基于控制器参数的方法论,用于创建可用作自动驾驶汽车运行模式的舒适驾驶风格。2) 建议使用虚拟现实技术作为用户评估驾驶方式的试验平台。3) 作为我们的方法论的说明,我们通过使用 "可注意到的差异"(JND)对智能驾驶员模型(IDM)控制器的碰撞时间参数进行分区,来确定和评估可区分的驾驶风格。4) 提出乘客同样喜欢的四种驾驶方式。
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引用次数: 0
Machine learning based real-time prediction of freeway crash risk using crowdsourced probe vehicle data 利用众包探测车数据,基于机器学习实时预测高速公路碰撞风险
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2024-01-02 DOI: 10.1080/15472450.2022.2106564
Zihe Zhang , Qifan Nie , Jun Liu , Alex Hainen , Naima Islam , Chenxuan Yang

Real-time prediction of crash risk can support traffic incident management by generating critical information for practitioners to allocate resources for responding to anticipated traffic crashes proactively. Unlike previous studies using archived traffic data covering a limited highway environment such as a segment or corridor, this study uses a statewide live traffic database from HERE to develop real-time traffic crash prediction models. This database provides crowdsourced probe vehicle data that are high-resolution real-time traffic speed for the entire freeway network (nearly 2,000 miles) in Alabama. This study aims to use machine learning models to predict crash risk on freeways according to pre-crash traffic dynamics (e.g., mean speed, speed reduction) along with static freeway attributes. Traffic speed characteristics were extracted from the HERE database for both pre-crash and crash-free traffic conditions. Random Forest (RF), Support Vector Machine (SVM) and Extreme Gradient Boosting (XGBoost) were developed and compared. Separate models were estimated for three major crash types: single-vehicle, rear-end, and sideswipe crashes. The model prediction accuracy indicated that the RF models outperform other models. Models for rear-end crashes are found to have greater accuracy than other models, which implies that rear-end crashes have a significant relationship with pre-crash traffic dynamics and are more predictable. The traffic speed factors that are ranked high in terms of feature importance are the speed variance and speed reduction prior to crashes. According to partial dependence plots, the rear-end crash risk is positively related to the speed variance and speed reductions. More results are discussed in the paper.

碰撞风险的实时预测可以为交通事故管理提供支持,为从业人员分配资源以积极应对预期的交通事故提供重要信息。与以往使用覆盖有限高速公路环境(如路段或走廊)的存档交通数据的研究不同,本研究使用 HERE 的全州实时交通数据库来开发实时交通事故预测模型。该数据库提供的众包探测车辆数据是阿拉巴马州整个高速公路网络(近 2000 英里)的高分辨率实时交通速度。本研究旨在使用机器学习模型,根据碰撞前的交通动态(如平均车速、车速降低)以及高速公路的静态属性来预测高速公路上的碰撞风险。从 HERE 数据库中提取了碰撞前和无碰撞交通状况下的车速特征。开发并比较了随机森林 (RF)、支持向量机 (SVM) 和极端梯度提升 (XGBoost)。针对三种主要碰撞类型(单车碰撞、追尾碰撞和侧擦碰撞)分别估算了模型。模型预测准确性表明,RF 模型优于其他模型。追尾碰撞事故模型的准确性高于其他模型,这意味着追尾碰撞事故与碰撞前的交通动态有重要关系,并且更容易预测。就特征重要性而言,排名靠前的交通速度因素是速度方差和碰撞前速度降低。根据偏倚图,追尾碰撞风险与速度方差和速度降低呈正相关。本文讨论了更多结果。
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引用次数: 4
DAnoScenE: a driving anomaly scenario extraction framework for autonomous vehicles in urban streets DAnoScenE:城市街道自动驾驶车辆异常驾驶场景提取框架
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-12-14 DOI: 10.1080/15472450.2023.2291680
Yuening Hu, Dan Zhao, Ying Wang, Guangming Zhao
Autonomous vehicles (AVs) hold great potential to improve traffic safety. However, urban streets present a dynamic environment where unforeseen and complex scenarios can arise. The establishment of...
自动驾驶汽车(AV)在改善交通安全方面具有巨大潜力。然而,城市街道是一个动态环境,可能会出现不可预见的复杂情况。建立...
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引用次数: 0
Modified Gipps model: a collision-free car following model 改良吉普斯模型:无碰撞汽车跟随模型
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-12-12 DOI: 10.1080/15472450.2023.2289149
Dhwani Shah, Chris Lee, Yong Hoon Kim
Car following (CF) models are used in microscopic traffic simulation tools to help assess the effects of a new road design or to assess the effect of change in traffic flow. In 1981, Gipps develope...
微观交通模拟工具中使用的汽车跟随(CF)模型可帮助评估新道路设计的效果或交通流量变化的影响。1981 年,吉普斯开发了汽车跟随模型。
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引用次数: 0
An efficient data-driven method to construct dynamic service areas from large-scale taxi location data 从大规模出租车位置数据构建动态服务区的高效数据驱动方法
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-12-06 DOI: 10.1080/15472450.2023.2289123
Minh Hieu Nguyen, Soohyun Kim, Sung Bum Yun, Sangyoon Park, Joon Heo
Service area analysis is crucial for determining the accessibility of public facilities in smart cities. However, the acquisition of service areas using conventional approaches has been limited. Fi...
服务区分析对于确定智慧城市公共设施的可达性至关重要。然而,使用传统方法获取服务区的范围有限。服务区分析
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引用次数: 0
Advisory versus automated dynamic eco-driving at signalized intersections: lessons learnt from empirical evidence and simulation experiments 信号交叉口的咨询与自动动态生态驾驶:从经验证据和模拟实验中吸取的教训
IF 3.6 3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-12-04 DOI: 10.1080/15472450.2023.2289118
Evangelos Mintsis, Eleni I. Vlahogianni, Evangelos Mitsakis, Georgia Aifadopoulou
Research in the field of dynamic eco-driving has been primarily coupled with connected and automated vehicles which are equipped with automation functions that can accurately execute energy-efficie...
动态生态驾驶领域的研究主要与联网和自动化车辆相结合,这些车辆配备了自动化功能,可以准确地执行节能…
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引用次数: 0
How spatial features affect urban rail transit prediction accuracy: a deep learning based passenger flow prediction method 空间特征如何影响城市轨道交通预测精度:基于深度学习的客流预测方法
3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-11-12 DOI: 10.1080/15472450.2023.2279633
Shuang Li, Xiaoxi Liang, Meina Zheng, Junlan Chen, Ting Chen, Xiucheng Guo
AbstractUrban rail transit is an integral part of public transit, and has been extensive built in China. Previous studies have proved that the spatial features are closely related to rail transit ridership, considering a fundamental role of short-term passenger flow forecast in the urban rail operation, it is meaningful to explore how these factors affect the prediction accuracy. This study aims to find a way to improve prediction accuracy by considering spatial features of stations based on deep learning. Therefore, a CNN-LSTM model capturing the spatial and temporal features was applied and Suzhou (China) was choosing as a case study to explore the influence of three spatial features, namely relative position, location, and land use, on the prediction accuracy. The predict model used can extract spatiotemporal features and accurately predict the citywide stations, and the results show that, for the relative position, the inbound and outbound flow prediction errors of transfer stations and middle stations are the lowest, respectively. As for locational features, the more distant the station is from the city center, the more accurate the results are. For stations where land use is dominated by work and living services, the predictions are more accurate. The error rate is higher for stations whose services are mainly tourism, transportation, and leisure services. This study’s results can help operators predict the short-term passenger flow of target stations based on different demands and optimize their services on this basis.Keywords: CNN-LSTMpassenger flowprediction accuracyspatiotemporal featuresurban rail transit AcknowledgementsThe authors are grateful for the dataset from Suzhou rail transit Group Co., Ltd, and we are grateful for the advice of Prof. Ziyuan Pu.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research is supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province (project number: KYCX22_0271).
城市轨道交通是公共交通的重要组成部分,在中国得到了广泛的建设。已有研究证明,空间特征与轨道交通客流量密切相关,考虑到短期客流预测在城市轨道交通运营中的基础性作用,探讨这些因素对预测精度的影响具有重要意义。本研究旨在寻找一种基于深度学习的方法,通过考虑台站的空间特征来提高预测精度。因此,采用CNN-LSTM模型捕捉时空特征,并以中国苏州为例,探讨相对位置、地理位置和土地利用三个空间特征对预测精度的影响。所建立的预测模型能够提取时空特征,准确预测全市范围内的站点,结果表明:对于相对位置,中转站的进站流量预测误差最小,中转站的出站流量预测误差最小;在区位特征方面,站点离市中心越远,结果越准确。对于那些土地使用以工作和生活服务为主的车站,预测更为准确。以旅游、交通和休闲服务为主的站点错误率较高。研究结果可以帮助运营商根据不同需求预测目标站点的短期客流,并在此基础上优化服务。关键词:cnn - lstm客流预测精度时空特征城市轨道交通致谢本文作者感谢苏州轨道交通集团有限公司提供的数据集,并感谢朴子源教授的建议。披露声明作者未报告潜在的利益冲突。本研究由江苏省研究生科研与实践创新计划(项目编号:KYCX22_0271)资助。
{"title":"How spatial features affect urban rail transit prediction accuracy: a deep learning based passenger flow prediction method","authors":"Shuang Li, Xiaoxi Liang, Meina Zheng, Junlan Chen, Ting Chen, Xiucheng Guo","doi":"10.1080/15472450.2023.2279633","DOIUrl":"https://doi.org/10.1080/15472450.2023.2279633","url":null,"abstract":"AbstractUrban rail transit is an integral part of public transit, and has been extensive built in China. Previous studies have proved that the spatial features are closely related to rail transit ridership, considering a fundamental role of short-term passenger flow forecast in the urban rail operation, it is meaningful to explore how these factors affect the prediction accuracy. This study aims to find a way to improve prediction accuracy by considering spatial features of stations based on deep learning. Therefore, a CNN-LSTM model capturing the spatial and temporal features was applied and Suzhou (China) was choosing as a case study to explore the influence of three spatial features, namely relative position, location, and land use, on the prediction accuracy. The predict model used can extract spatiotemporal features and accurately predict the citywide stations, and the results show that, for the relative position, the inbound and outbound flow prediction errors of transfer stations and middle stations are the lowest, respectively. As for locational features, the more distant the station is from the city center, the more accurate the results are. For stations where land use is dominated by work and living services, the predictions are more accurate. The error rate is higher for stations whose services are mainly tourism, transportation, and leisure services. This study’s results can help operators predict the short-term passenger flow of target stations based on different demands and optimize their services on this basis.Keywords: CNN-LSTMpassenger flowprediction accuracyspatiotemporal featuresurban rail transit AcknowledgementsThe authors are grateful for the dataset from Suzhou rail transit Group Co., Ltd, and we are grateful for the advice of Prof. Ziyuan Pu.Disclosure statementNo potential conflict of interest was reported by the author(s).Additional informationFundingThis research is supported by Postgraduate Research & Practice Innovation Program of Jiangsu Province (project number: KYCX22_0271).","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"37 5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135036902","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
Handling inevitable collision states by Advanced Driver Assistance Systems functions: software-in-the-loop performance assessment of an injury risk-based logic in a “lane departure” scenario 通过高级驾驶辅助系统功能处理不可避免的碰撞状态:在“车道偏离”场景下,基于伤害风险逻辑的软件在环性能评估
3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-11-08 DOI: 10.1080/15472450.2023.2277713
Michelangelo-Santo Gulino, Krzysztof Damaziak, Anita Fiorentino, Dario Vangi
AbstractThe downward trend in the number of fatalities and serious injuries related to road accidents depends on the implementation of increasingly performing Advanced Driver Assistance Systems (ADAS) in the circulating fleet. The greatest benefit of the adoption of ADASs like Autonomous Emergency Braking (AEB) consists in limiting the frequency of impacts. However, in Inevitable Collision States (ICSs), the decrease in impact closing speed guaranteed by the AEB may not reduce the Injury Risk (IR) for the occupants: IR is a function of the vehicle’s velocity change in the collision (ΔV) – a combination of impact closing speed and impact eccentricity. The work virtually analyses, in lane departure ICS scenarios, the performance of an adaptive steering and braking intervention logic based on instantaneous IR minimization. The adaptive logic reduces IR compared to the absence of intervention (down to 80 times lower) and to the AEB (down to 40 times lower) by leading the ego vehicle toward eccentric impact configurations. It is highlighted that full activation of the steer-by-wire system in 0.3 s allows the adaptive logic to also reduce the frequency of impacts; it is further evidenced that employing a function capable of modulating the braking level to minimize IR entails disadvantages from the IR perspective compared to the AEB: efficient intervention strategies on the steering are the only alternative for increasing the safety provided by high-performance ADASs. Finally, compared to previous literature, the study highlights high efficiencies of the adaptive logic in a wide range of ICS scenarios.Keywords: ΔVactuation timeautonomous emergency braking AEBimpact closing speedscan timevelocity change Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://transport.ec.europa.eu/news/road-safety-eu-fatalities-below-pre-pandemic-levels-progress-remains-too-slow-2023-02-21_en2 https://www.acea.auto/figure/average-age-of-eu-vehicle-fleet-by-country/3 EC Regulation n ° 661/20094 https://www.nissan-global.com/EN/INNOVATION/TECHNOLOGY/ARCHIVE/AUTONOMOUS_EMERGENCY_STEERING_SYSTEM/5 http://iglad.net/
摘要与道路交通事故相关的死亡和重伤人数的下降趋势取决于在循环车队中日益执行的高级驾驶辅助系统(ADAS)的实施。采用自动紧急制动(AEB)等自动驾驶辅助系统的最大好处在于限制了碰撞的频率。然而,在不可避免的碰撞状态(ics)中,AEB保证的碰撞关闭速度的降低可能不会降低乘员的伤害风险(IR): IR是车辆在碰撞中速度变化的函数(ΔV) -碰撞关闭速度和碰撞偏心的组合。该工作虚拟分析了车道偏离ICS场景下基于瞬时红外最小化的自适应转向和制动干预逻辑的性能。与没有干预(降低了80倍)和AEB(降低了40倍)相比,自适应逻辑通过引导自我车辆进入偏心撞击配置,降低了IR。值得强调的是,在0.3秒内完全激活线控转向系统,使自适应逻辑也可以减少碰撞的频率;进一步证明,从红外角度来看,与AEB相比,采用能够调节制动水平以最小化红外的功能会带来缺点:高效的转向干预策略是提高高性能ADASs安全性的唯一选择。最后,与之前的文献相比,本研究强调了自适应逻辑在广泛的ICS场景中的高效率。关键词:ΔVactuation时间自主紧急制动aeb碰撞闭合速度扫描时间速度变化披露声明作者未报告潜在利益冲突。注1 https://transport.ec.europa.eu/news/road-safety-eu-fatalities-below-pre-pandemic-levels-progress-remains-too-slow-2023-02-21_en2 https://www.acea.auto/figure/average-age-of-eu-vehicle-fleet-by-country/3欧盟法规第661/20094号https://www.nissan-global.com/EN/INNOVATION/TECHNOLOGY/ARCHIVE/AUTONOMOUS_EMERGENCY_STEERING_SYSTEM/5 http://iglad.net/
{"title":"Handling inevitable collision states by Advanced Driver Assistance Systems functions: software-in-the-loop performance assessment of an injury risk-based logic in a “lane departure” scenario","authors":"Michelangelo-Santo Gulino, Krzysztof Damaziak, Anita Fiorentino, Dario Vangi","doi":"10.1080/15472450.2023.2277713","DOIUrl":"https://doi.org/10.1080/15472450.2023.2277713","url":null,"abstract":"AbstractThe downward trend in the number of fatalities and serious injuries related to road accidents depends on the implementation of increasingly performing Advanced Driver Assistance Systems (ADAS) in the circulating fleet. The greatest benefit of the adoption of ADASs like Autonomous Emergency Braking (AEB) consists in limiting the frequency of impacts. However, in Inevitable Collision States (ICSs), the decrease in impact closing speed guaranteed by the AEB may not reduce the Injury Risk (IR) for the occupants: IR is a function of the vehicle’s velocity change in the collision (ΔV) – a combination of impact closing speed and impact eccentricity. The work virtually analyses, in lane departure ICS scenarios, the performance of an adaptive steering and braking intervention logic based on instantaneous IR minimization. The adaptive logic reduces IR compared to the absence of intervention (down to 80 times lower) and to the AEB (down to 40 times lower) by leading the ego vehicle toward eccentric impact configurations. It is highlighted that full activation of the steer-by-wire system in 0.3 s allows the adaptive logic to also reduce the frequency of impacts; it is further evidenced that employing a function capable of modulating the braking level to minimize IR entails disadvantages from the IR perspective compared to the AEB: efficient intervention strategies on the steering are the only alternative for increasing the safety provided by high-performance ADASs. Finally, compared to previous literature, the study highlights high efficiencies of the adaptive logic in a wide range of ICS scenarios.Keywords: ΔVactuation timeautonomous emergency braking AEBimpact closing speedscan timevelocity change Disclosure statementNo potential conflict of interest was reported by the author(s).Notes1 https://transport.ec.europa.eu/news/road-safety-eu-fatalities-below-pre-pandemic-levels-progress-remains-too-slow-2023-02-21_en2 https://www.acea.auto/figure/average-age-of-eu-vehicle-fleet-by-country/3 EC Regulation n ° 661/20094 https://www.nissan-global.com/EN/INNOVATION/TECHNOLOGY/ARCHIVE/AUTONOMOUS_EMERGENCY_STEERING_SYSTEM/5 http://iglad.net/","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"3 19","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135391417","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
A hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data 基于车辆轨迹数据的分层控制框架缓解网络交通瓶颈拥塞
3区 工程技术 Q3 TRANSPORTATION Pub Date : 2023-10-30 DOI: 10.1080/15472450.2023.2270428
Lei Wei, Peng Chen, Yu Mei, Jian Sun, Yunpeng Wang
{"title":"A hierarchical control framework for alleviating network traffic bottleneck congestion using vehicle trajectory data","authors":"Lei Wei, Peng Chen, Yu Mei, Jian Sun, Yunpeng Wang","doi":"10.1080/15472450.2023.2270428","DOIUrl":"https://doi.org/10.1080/15472450.2023.2270428","url":null,"abstract":"","PeriodicalId":54792,"journal":{"name":"Journal of Intelligent Transportation Systems","volume":"13 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136104005","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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
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Journal of Intelligent Transportation Systems
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