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主要从事智能汽车感知算法、场景库建设以及主被动安全一体化等领域的科研教学工作,先后主持上海市科委、国家重点研发计划子课题以及校企合作等多项与本项目相关的课题研究工作,2005年获中国汽车工业科技进步三等奖,2009年获上海市科技进步三等奖,以第一作者及通讯作者身份在国内外期刊和学术会议上发表论文20 余篇,获发明及实用新型专利10 余项。
(1)主持国家重点研发计划子课题《基于路端感知的 L4 无人驾驶云端安全监管工具》
(2)主持国家重点研发计划子课题《面向复杂气象、交通流和无线环境融合的封闭场地多维测试方法及集成验证研究》
(3)主持国家重点研发计划子课题《面向自动驾驶功能研发的车路云一体化高覆盖场景库构建》
[1] LiuL, Zhang Q, Ma Z, et al. Adaptive Cruise Control System Evaluation According toHuman Driving Behavior Characteristics. Actuators, 2021, 10(5): 90. (SCI 检索)
[2] J.Zhang, Z. Ma, X. Zhu and Y. Lin, "Analysis of Driving Control Modelof Normal Lane Change based onNaturalistic Driving Data," 2019 IEEE Intelligent Transportation SystemsConference (ITSC), Auckland, New Zealand, 2019, pp. 104-109. (EI 检索)
[3] WeiH, Ma Z, Zhu X, et al. Characteristics Analysis and Classification ofLane-changing Behavior after Following Process based on China-FOT[C]// 2019IEEE Intelligent Vehicles Symposium. Paris, France: IEEE, 2019: 451-456. (EI检索)
[4] 刘瑞,马志雄,武彪,朱西产.驾驶员驾驶行为的统计学特性.同济大学学报(自然科学版).2019, 47(6): 832-841. (EI 检索)
[5] ZhengL, Z. Ma et al. RCFusion: Fusing 4-D Radar and Camera With Bird’s-Eye ViewFeatures for 3-D Object Detection[J]. IEEE Transactions on Instrumentation andMeasurement, 2023, 72: 1-14.(SCI检索)
[6] ChenS, Zheng L, Huang L, et al. UMT-net: A uniform multi-task network with adaptivetask weighting[J]. IEEE Transactions on Intelligent Vehicles, 2023, 9(1):2304-2317.(SCI检索)
[7] TanB, Ma Z, Zhu X, et al. 3-D object detection for multiframe 4-D automotivemillimeter-wave radar point cloud[J]. IEEE Sensors Journal, 2022, 23(11):11125-11138.(SCI检索)
[8] TanB, Ma Z, Zhu X, et al. Tracking of multiple static and dynamic targets for 4Dautomotive millimeter-wave radar point cloud in urban environments[J]. RemoteSensing, 2023, 15(11): 2923. (SCI检索)
[9] L. Zheng, Z. Ma, X. Zhu et al.,"TJ4DRadSet: A 4D Radar Dataset for Autonomous Driving," 2022 IEEE25th International Conference on Intelligent Transportation Systems (ITSC),Macau, China, 2022, pp. 493-498.(EI检索)
[10] Wang,J., Ma, Z., Zhu, X., Bai, J., Huang, L. Cooperative decision making forconnected automated vehicles in multiple driving scenarios. IET Intell. Transp.Syst. 17, 2131–2142 (2023).(SCI检索)
[11] S.Chen, Z. Ma, Z., Zhu et al., "MMTP: Multi-Modal Trajectory Prediction withInteraction Attention and Adaptive Task Weighting," 2022 IEEE 25thInternational Conference on Intelligent Transportation Systems (ITSC), Macau,China, 2022, pp. 486-492.(EI检索)
[12] 朱西产,魏昊舟,马志雄.基于自然驾驶数据的跟车场景潜在风险评估[J].中国公路学报,2020, 33(04): 169-181.(EI检索)
[13] Wu, B.; Ma, Z., Zhu, X., Lin, Y. Research onthe Vehicle-Behavior Boundary of Intersection Traffic Based on NaturalisticDriving Data Study. Appl. Sci. 2024, 14, 3432.(SCI检索)

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