论文: [1]Nengchao Lyu, Tian Xie, Jiaqiang Wen, Yugang Wang. A real-time conflict risk prediction modeling based on causal inference and graph-model: Applied to multi-configuration expressway diversion zones [J].Transportation Research Part C: Emerging Technologies, 2025, 178,105219. [2]Zijun Du, Liu Yang, Nengchao Lyu, Yugang Wang. Predictive modeling of vehicle interaction patterns considering drivers intentions under different intelligent connected environments [J]. Expert Systems with Applications, 2025, 293, 128632 [3]Yugang Wang, Nengchao Lyu, Chaozhong Wu, Zijun Du, Haoran Wu. Investigating the Impact of HMI on Drivers' Merging Performance in Intelligent Connected Vehicle Environment [J]. Accident Analysis and Prevention, 2024, 198, 107448 [4]Yugang Wang, Nengchao Lyu, Jianghui Wen. Game Theory-Based Mandatory Lane Change Model in Intelligent Connected Vehicles Environment [J]. Applied Mathematical Modelling, 2024,132,146-165 [5]Yugang Wang, Nengchao Lyu, Jianghui Wen. Modeling Risk Potential Fields for Mandatory Lane Changes in Intelligent Connected Vehicle Environment [J]. Expert Systems with Applications, 2024, 255, Part D,124814 [6]吕能超,王玉刚,周颖,吴超仲.道路交通安全分析与评价方法综述[J].中国公路学报,2023,36(4):183-201. [7]Nengchao Lyu, Yugang Wang, Chaozhong Wu, Lingfeng Peng, Alieu Freddie Thomas. Using Naturalistic Driving Data to Identify Driving Style Based on Longitudinal Driving Operation Conditions [J]. Journal of Intelligent and Connected Vehicles,2022, 5(1):17-35. [8]Nengchao Lyu, Yugang Wang, Chaozhong Wu, Haoran Wu, Jiaqiang Wen. Exploring longitudinal driving behaviour on a freeway deceleration lane using field operational test data [J]. IET Intelligent Transport Systems, 2021,1-13. [9]Nengchao Lyu, Yugang Wang, Chaozhong Wu*. Exploring longitudinal driving behavior on a freeway deceleration lane using field operational test data [C]. Transportation Research Board 100th Annual Meeting, Walter E. Washington, 2021.1.5-29. [10]Nengchao Lyu, Yugang Wang. A car-following model based on safety margin considering ADAS and driving experience [C].第11届国际绿色智能交通系统与安全学术会议(GITSS 2020), 北京:2020.10.16-17. [11]吕能超, 王玉刚, 吴超仲*, 彭凌枫, 李见楠. 基于纵向驾驶工况的驾驶风格识别研究[C]. 第十四届全国交通运输领域青年学术会议,南京:2021.10.15-17. [12]Zijun Du, Min Deng, Nengchao Lyu, Yugang Wang. A review of road safety evaluation methods based on driving behavior [J]. Journal of Traffic and Transportation Engineering (English Edition), 2023,10(5):743-761 [13]吕能超,高谨谨,王维锋,王玉刚等. 网联环境下基于精简车头时距特性的驾驶风格分类[J].交通信息与安全,2022,40(01):116-125+168. [14]吕能超,杜子君,吴超仲,王玉刚. 多车道高速公路出口开口段安全特性分析[J].交通运输系统工程与信息,2021,21(03):120-130. [15]马天奕,文家强,王丽园,吕能超,王玉刚. 基于ADAS联网时空数据的路段交通参数估算模型[J].交通信息与安全,2021,39(01):64-75. 专利: [1]吕能超,高谨谨,王玉刚,吴超仲.基于车头时距来辨识驾驶风格的方法及系统,发明专利,CN112937592B [2]吕能超,王星,吴超仲,文家强,吴浩然,王玉刚. 面向眼动仪前向视频的交通目标自动识别与匹配的方法, 发明专利, CN113139443B [3]王玉刚,李帅奇,吴浩然, 杨正才. 一种基于多源数据融合的智能网联车辆行车风险评估方法及可视化系统,发明专利,申请号:2025106065968 [4]吕能超,杜子君,吴超仲,谢练,王玉刚. 驾驶模拟实验数据处理系统V1.0, 登记号:2021SR0800562 |