发表SCI/EI检索论文160余篇，主持或参与4部中文著作（含国内第一本汽车智能安全领域专著《汽车智能安全》、智能网联汽车领域专业教材《智能网联汽车》等），参著2部英文著作，授权国家发明专利180余项，制定国家/行业标准8项，论文总引用超过30000次，受邀在重要国际/国内会议做大会主旨或特邀报告20余次。

部分论文

[1] Xie S, Chen S, Zheng J; Tomizuka M, Zheng N, Wang J. From Human Driving to Automated Driving: What Do We Know About Drivers?[J]. IEEE Transactions on Intelligent Transportation Systems, 2022,7(23): 6189 – 6205.

[2] Wang J, Huang H, Li K, Li J. Towards the Unified Principles for Level 5 Autonomous Vehicles. Engineering 2021; 7:1313–25.

[3] Zheng X, Huang H, Wang J, Zhao X, Xu Q. Behavioral decision‐making model of the intelligent vehicle based on driving risk assessment. Comput-Aided Civ Infrastruct Eng 2021;36:820–37.

[4] 王建强,郑讯佳,黄荷叶.驾驶人驾驶决策机制遵循最小作用量原理[J].中国公路学报,2020,33(4): 155-168.

[5] Wang J, Huang H, Li Y, Zhou H, Liu J, Xu Q. Driving risk assessment based on naturalistic driving study and driver attitude questionnaire analysis[J], Accident Analysis & Prevention, 2020, 145: 105680.

[6] Huang H, Wang J, Fei C, Zheng X, Yang Y, Liu J, et al. A probabilistic risk assessment framework considering lane-changing behavior interaction. Sci CHINA Inf Sci 2020; 63:190203.

[7] Huang H, Zheng X, Yang Y, Liu J, Liu W, Wang J. An integrated architecture for intelligence evaluation of automated vehicles[J]. Accident Analysis & Prevention, 2020, 145: 105681.

[8] Li Y, Zheng Y, Morys B, Pan S, Wang J, Li K. Threat Assessment Techniques in Intelligent Vehicles: A Comparative Survey. IEEE Intelligent Transportation Systems Magazine, 2020, 13(4): 71-91.

[9] Xie,G.,Gao,H., Qian, L.,Huang, B., Li, K., & Wang, J*. Vehicle trajectory prediction by integrating physics-and maneuver-based approaches using interactive multiple models[J]. IEEE Transactions on Industrial Electronics,2018,65(7)：5999-6008 2

[10] Li Y, Zheng Y, Wang J*, Kodaka, K.,  & Li, K. Crash probability estimation via quantifying driver hazard perception[J]. Accident Analysis & Prevention, 2018,116：116-125

[11] Hongbo Gao, Bo Cheng, Jianqiang Wang*, Keqiang Li. Object Classification using CNN-Based Fusion of Vision and LIDAR in Autonomous Vehicle Environment[J]. IEEE Transactions on Industrial Informatics,2018,14(9)：4224-4231

[12] Li Y, Wang J*, Wu J. Model calibration concerning risk coefficients of driving safety field model[J]. Journal of Central South University, 2017,24(6)：1494-1502

[13] Xiaofei Li, Lingxi Li, Fabian Flohr, Jianqiang Wang, Hui Xiong, Morys Bernhard, Shuyue Pan, Dariu M. Gavrila, and Keqiang Li*. A Unified Framework for Concurrent Pedestrian and Cyclist Detection[J].  IEEE Transactions on Intelligent Transportation Systems, 2017, 18(2): 269-281

[14] Xiaoyuan Wang*, Jianqiang Wang, Zhenxue Liu, Yaqi Liu, and Jingheng Wang. Study on Reverse Reconstruction Method of Vehicle Group Situation in Urban Road Network Based on Driver-Vehicle Feature Evolution[J]. Mathematical Problems in Engineering, 2017, 2017:1-14

[15] Xie G,Zhang X, Gao H*, Qian, LJ, Wang,JQ . Situational Assessments Based on Uncertainty-Risk Awareness in Complex Traffic Scenarios[J]. Sustainability, 2017, 9(9):1582

[16] Jianqiang Wang, Chenfei Yu, Shengbo Eben Li*, Likun Wang. A Forward Collision Warning Algorithm With Adaptation to Driver Behaviors[J]. IEEE Transactions On Intelligent Transportation Systems. 2016，17(4), 1157-1167

[17] Jianqiang Wang，Jian Wu，Xunjia Zheng，Daiheng Ni，Keqiang Li，Driving safety field theory modeling and its application in pre-collision warning system，Transportation Research Part C: Emerging Technologies，2016, 72:306-324

[18] 王建强，吴剑，李洋，基于人-车-路协同的行车风险场概念、原理及建模，中国公路学报，2016，29(1)：105~114

[19] Li, Keqiang ，Wang, Xiao，Xu, Youchun，Wang, Jianqiang*，Density Enhancement-Based Long-Range Pedestrian Detection Using 3-D Range Data，IEEE Transactions ON Intelligent Transportation Systems，2016，17(5)：1368~1380

[20] Jianqiang Wang, Shengbo Eben Li*, Yang Zheng and Xiaoyun Lu. Longitudinal collision mitigation via coordinated braking of multiple vehicles using model predictive control. Integrated Computer-Aided Engineering, 2015：171–185.

[21] Jianqiang Wang*, Jian Wu, Yang Li. The Driving Safety Field Based on Driver-Vehicle-Road Interactions [J]. IEEE Transactions on Intelligent Transportation Systems, 2015, 16(4): 2203-2214.

[22] Zhang J, Wang X, Wang J*, et al. Vehicle Group Relationship Transformation Mechanism under Dynamic and Complex Three-Lane Conditions[J]. Advances in Mechanical Engineering, 2015, 7(2): 687517.

[23] Jianqiang Wang, Yang Zheng, Xiaofei Li, Chenfei Yu, Kenji Kodakab, Keqiang Li*. Driving risk assessment using near-crash database through datamining of tree-based model. Accident Analysis and Prevention, 2015, 84：54–64.

[24] Kuang X, Wang J*, Li K. A New Method for Bus Drivers’ Economic Efficiency Assessment[J]. SAE International Journal of Commercial Vehicles, 2015, 8(2): 536-543.

[25] Jianqiang Wang, Chenfeng Xiong*, Meng Lu, et al. Longitudinal driving behavior on different roadway categories: an instrumented-vehicle experiment, data collection and case study in China[J]. IET Intell. Transp. Syst., 2015, Vol. 9, Iss. 5, pp. 555–563

[26] Xiaoyuan Wang, Jianqiang Wang*, Jinglei Zhang, Xuegang (Jeff ) Ban, Lane-changing model with dynamic consideration of driver's propensity, International Journal of Modern Physics C, Vol. 26, No. 2 (2015) 1550015

[27] Jianqiang Wang , Daiheng Ni* , and Keqiang Li , RFID-Based Vehicle Positioning and Its Applications in Connected Vehicles,  Sensors 2014, 14, 4225-4238; doi:10.3390/s140304225

[28] Enzo C. Jia, JianqiangWang, and Daiheng Ni, An Efficient Methodology for Calibrating Traffic Flow Models,Based on Bisection Analysis, Journal of Applied Mathematics, Volume 2014, Article ID 949723

[29] Wang,J., Zhang,L., Zhang,D., Li,K.  An adaptive Longitudinal Driving Assistance System Based on Driver Characteristics. IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS, VOL. 14, NO. 1, MARCH 2013，PP.1-12

[30] 王建强，王海鹏，刘佳熙，李克强，基于车路一体化的交叉口车辆驾驶辅助系统, 中国公路学报, Vol.26，No.4， July 2013，169-183

[31] Wang J, Sun X, Guo J. A Region Tracking-Based Vehicle Detection Algorithm in Nighttime Traffic Scenes. Sensors. 2013; 13(12):16474-16493.

[32] 王建强，王海鹏(S)，张磊，基于电控液压制动装置的车辆主动报警/避撞系统，吉林大学学报 (工学版)，2012，Vol.42,  No. 4,  816-822

[33] Jianqiang Wang, Haipeng Wang, Xiao-Yun Lu, Boyuan Xie. RFID-based Vehicle Positioning of Cooperative Driving Assistance Systems. AP-00267, 19th ITS World Congress, Vienna, Austria, 22/26 October 2012.

[34] 王建强，杨波，李升波，李克强. 基于高速开关阀的气压电控辅助制动装置. 交通运输工程学报，2011年 第4期

[35] 王建强，杨波，张德兆，李升波. 基于双模式执行器的商用车自适应巡航控制系统. 中国公路学报，2011.03，PP.104-112，120

[36] 王建强，张德兆，李克强，徐继福，张立国. 汽车集成式电子真空助力器系统设计. 中国公路学报, 2011年第1期

[37] Jianqiang Wang, Xiaojia Lu, Qing Xiao, Meng Lu. Comparison of Driver Classification Based on Subjective Evaluation and Objective Experiment. In Proc. 90th TRB Annual Meeting, Paper 11-3170, January 23-27, 2011, Washington D.C.

[38] Wang Jianqiang, Li Shengbo, Huang Xiaoyu, and Li Keqiang，Driving Simulation Platform Applied to Develop Driving Assistance Systems，Journal of IET Intelligent Transportation System, June 2010,Volume 4, Issue 2, p.121–127.

[39] Wang, J., Zhang, D., Liu, J., Lu, M., Li, K. Multi-objective driving assistance system for intersection support. In Proceedings: 13th International IEEE Conference on Intelligent Transportation Systems, ITSC 2010, September 19-22, 2010, Madeira. PP.348-353

[40] Jianqiang WANG, Zhifeng LIU, Shichun YI, Keqiang LI. Target Vehicle Selection Based on Multi Features Fusion Method. 2010 Intelligent Vehicles Symposium, June 21-24, 2010, University of California, San Diego,CA,USA.

[41] Wang, J., Lu, M., Zhang, L., Li, K., Yamamura, T., Kuge, N., Nakagawa, T. (2010). Study of longitudinal driving behaviour using advanced data collection and analysis platform. In Proc. 89th TRB Annual Meeting, Paper 10-1472, January 10-14, 2010, Washington D.C.

[42] Jianqiang Wang, Bo Yang, Shengbo Li, Dezhao Zhang, Keqiang Li. Pneumatic electronic braking assistance system using high-speed valves. ICVES10,2010 IEEE International Conference on Vehicular Electronics and Safety, July 15-17, 2010, Qingdao, ShanDong, China，59-64

部分专利

[1] Wang J, Zheng X, Huang H, et al. A Method and Device for Quantifying Driver’s Manipulation Behavior Based on Principle of Least Action. Japan Patent, No. 2020-541837

[2] 王建强, 黄荷叶, 郑讯佳等. 行车风险辨识模型的标定方法和系统, 授权, 2018.12.10, ZL201810433365.1

[3] 王建强, 郑讯佳, 黄荷叶等. 基于最小作用量原理的驾驶人操控行为量化方法及装置, 授权, 2018.12.11, ZL201810432926.6

[4] 王建强, 郑讯佳, 黄荷叶. 基于等效力的行车风险实时评估方法及其装置, 授权, 2018.12.20, ZL201810433436.8

[5] 王建强, 黄荷叶, 郑讯佳等. 基于行车安全场的车辆智能安全决策方法, 授权, 2019.4.5, ZL201810433464.X

[6] 王建强, 赵晓聪, 郑讯佳等. 一种智能车多目标驾驶控制方法及决策系统, 授权, 2020.6.5, ZL201910672422.6

[7] 王建强, 田洪清, 黄荷叶等. 非结构化道路条件下的行车环境态势评估方法及评估装置, 授权, 2020.7.31, ZL201910796959.3

[8] 王建强, 杨奕彬, 赵晓聪等. 基于驾驶人实时风险响应的动态人机共驾驾驶权分配方法, 授权, 2020.12.25, ZL201911358599.5

[9] 王建强, 邹翀昊, 黄荷叶等. 一种考虑驾驶风格的多信号灯路口车辆通行辅助优化方法, 授权, 2021.8.27, ZL202010989747.X

[10] 王建强, 崔明阳, 杨路等. 基于车辆行为交互与道路结构耦合的碰撞风险预测方法, 授权, 2021.10.29, ZL 202110983185.2

[11] 王建强, 杨路, 崔明阳等. 极限工况下车辆失稳与碰撞综合风险评估方法及装置, 授权, 2021.11.2, ZL202110934200.4

[12] 王建强, 黄荷叶, 刘科等. 道路交通系统风险辨识的方法、设备及存储介质, 授权, 2022.9.27, ZL202110182856.5

[13] 王建强, 王裕宁, 姜竣凯等. 面向多智能体对抗场景的威胁态势评估方法、装置及设备, 授权, 2022.12.30, ZL202210051131.7

[14] 王建强, 谢杉杉, 黄荷叶等. 自动驾驶车辆的拟人化轨迹规划方法、装置、车辆及介质, 授权, 2023.1.20, ZL202210657706.X

[15] 王建强, 姜竣凯, 王裕宁等. 基于场能的多智能体对抗场景态势评估方法及装置, 授权, 2023.2.28, ZL202210115962.6