| 面向人因的车路协同系统综合测试及影响评估 |
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| 引用本文： | 赵晓华,陈雨菲,李海舰,邢冠仰,冯笑凡.面向人因的车路协同系统综合测试及影响评估[J].中国公路学报,2019,32(6):248-261. |
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| 作者姓名： | 赵晓华 陈雨菲 李海舰 邢冠仰 冯笑凡 |
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| 作者单位： | 1. 北京工业大学 北京市城市交通运行保障工程技术研究中心, 北京 100124;2. 北方工业大学 电气与控制工程学院, 北京 100144 |
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| 基金项目： | 国家自然科学基金项目（61672067） |
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| 摘 要： | 面向冬奥主干通道兴延高速，以驾驶人适应性为导向，构建一种面向人因的车路协同系统硬件在环效能测试平台，针对多种道路条件、交通状态、特殊事件等面向高速公路设计13种交通情境，从主、客观2个维度实现车路协同系统包括主观感受、高效性、安全性、生态性、舒适性、有效性6个方面的驾驶人适应性评价，分析车路协同驾驶状态下的综合评估指标及影响机理。主观评估结果显示，车路协同技术对驾驶人有积极作用，52%的被试认为车载预警信息可以使行车过程更安全。客观运行结果表明：由于车路协同状态下驾驶人对于前方道路危险状况的可预知性，导致驾驶人提前降速，运行速度降低，效率有所下降；车路协同条件下的加速度和换道次数明显减小，其安全性显著提升；由于车路协同系统避免了驾驶人对于突发危险状况的紧急制动，因此车辆的油耗、排放均明显降低，其生态性改善效果显著；归因于驾驶人对于车路协同系统熟悉程度不足，导致舒适度各系统存在不一致的结论，也表明驾驶人对于车路协同系统的接受度和信任度均有待进一步提高；驾驶人在车路协同条件下可获取不同路段的限速值和超速提示，其有效性表现出明显的优势，速度跟随比有显著提升。所构建的测试平台和指标体系为进一步深层次挖掘车路协同的作用机理奠定了基础。
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| 关 键 词： | 交通工程 高速公路 车路协同 预警系统 人因测试 驾驶人适应性 硬件在环 |
| 收稿时间： | 2019-03-31 |
Comprehensive Test and Impact Assessment for Human Factors of Connected Vehicle System |
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| ZHAO Xiao-hua,CHEN Yu-fei,LI Hai-jian,XING Guan-yang,FENG Xiao-fan.Comprehensive Test and Impact Assessment for Human Factors of Connected Vehicle System[J].China Journal of Highway and Transport,2019,32(6):248-261. |
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| Authors: | ZHAO Xiao-hua CHEN Yu-fei LI Hai-jian XING Guan-yang FENG Xiao-fan |
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| Affiliation: | 1. Beijing Engineering Research Center of Urban Transportation Operation Guarantee, Beijing University of Technology, Beijing 100124, China;2. College of Electrical and Control Engineering, North China University of Technology, Beijing 100144, China |
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| Abstract: | This work considers the winter Olympics events and takes the Xingyan Freeway as an example for application. A human-oriented connected vehicle system test platform considering driver adaptability was constructed for hardware-in-the-loop for human factors, and the influence mechanism of the comprehensive evaluation index under the connected vehicle driving state was analyzed. Subjective evaluation results show that connected vehicle technology has a positive effect on drivers, and approximately 52% of the drivers believe that warning information can make the driving process safer. The objective results show that because the driver can predict dangerous conditions ahead in the road with the state of connected vehicle, they will slow down in advance, and the speed and efficiency are reduced for the connected vehicle. Under the condition of a connected vehicle, the acceleration and number of lane changes obviously reduce, and the operation safety improves to a certain extent; further, emergency braking is avoided by drivers owing to sudden dangerous situations, thus reducing fuel consumption and emissions significantly; the overall effect on ecological improvement is significant. Owing to the lack of familiarity of the driver with the connected vehicle system, the comfort levels of various systems are inconsistent, which also indicates that the acceptance and trust degrees of the drivers to connected vehicle systems need to be further improved. In the connected vehicle state, the driver can obtain the speed limit values for that road and speeding information of different sections; the effectiveness of this state shows obvious advantages, and the speed following ratio is significantly improved. The human-oriented connected vehicle system test platform for hardware-in-the-loop presented herein verifies the comprehensive performance of the freeway connected vehicle system and demonstrates the feasibility of the method in connected vehicle tests, thus laying a foundation for further exploration of the underlying problems in the system, such as its mechanism of action. |
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| Keywords: | traffic engineering freeway connected vehicle warning system human factor test driver adaptability hardware-in-the-loop |
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