[1] 张佐, 张毅, 姚丹亚. 车路协同自动驾驶:交通系统呈现全面智能化走向[J]. 前沿科学, 2019(2):56-60.ZHANG Z, ZHANG Y, YAO D Y. Vehicle infrastructure cooperation system and auto-pilot:The traffic system presents a comprehensive intelligent trend[J]. Frontier Science, 2019(2):56-60. (in Chinese)
[2] PEI H X, ZHANG Y, TAO Q H, et al. Distributed cooperative driving in multi-intersection road networks[J/OL]. (2021-05-11). IEEE Transactions on Vehicular Technology. DOI:10.1109/TVT.2021.3079272.
[3] PEI H X, FENG S, ZHANG Y, et al. A cooperative driving strategy for merging at on-ramps based on dynamic programming[J]. IEEE Transactions on Vehicular Technology, 2019, 68(12):11646-11656.
[4] KHATIB O. Real-time obstacle avoidance for manipulators and mobile robots[C]//IEEE International Conference on Robotics and Automation. St. Louis, USA, 1985:500-505.
[5] OROZCO-ROSAS U, MONTIEL O, SEPÚLVEDA R. Mobile robot path planning using membrane evolutionary artificial potential field[J]. Applied Soft Computing, 2019, 77:236-251.
[6] KUMAR P B, RAWAT H, PARHI D R. Path planning of humanoids based on artificial potential field method in unknown environments[J]. Expert Systems, 2019, 36(2):1-12.
[7] AZZABI A, NOURI K. An advanced potential field method proposed for mobile robot path planning[J]. Transactions of the Institute of Measurement and Control, 2019, 41(4):3132-3144.
[8] NI D H. A unified perspective on traffic flow theory. Part Ⅰ:The field theory[J]. Applied Mathematical Sciences, 2013, 7:1929-1946.
[9] NI D H. A unified perspective on traffic flow theory. Part Ⅱ:The unified diagram[J]. Applied Mathematical Sciences, 2013, 7:1947-1963.
[10] GAO K, YAN D, YANG F, et al. Conditional artificial potential field-based autonomous vehicle safety control with interference of lane changing in mixed traffic scenario[J]. Sensors, 2019, 19(19):4199.
[11] 李林恒, 甘婧, 曲栩, 等. 智能网联环境下基于安全势场理论的车辆跟驰模型[J]. 中国公路学报, 2019, 32(12):76-87.LI L H, GAN J, QU X, et al. Car-following model based on safety potential field theory under connected and automated vehicle environment[J]. China Journal of Highway and Transport, 2019, 32(12):76-87. (in Chinese)
[12] 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[J]. 中国公路学报, 2016, 149(1):109-118.WANG J Q, WU J, LI Y. Concept, principle and modeling of driving risk field based on driver-vehicle-road interaction[J]. China Journal of Highway and Transport, 2016, 149(1):109-118. (in Chinese)
[13] 吴剑. 考虑人-车-路因素的行车风险评价方法研究[D]. 北京:清华大学, 2015.WU J. Research on driver-vehicle-road factors considered driving risk evaluation method[D]. Beijing:Tsinghua University, 2015. (in Chinese)
[14] JI J, KHAJEPOUR A, MELEK W W, et al. Path planning and tracking for vehicle collision avoidance based on model predictive control with multiconstraints[J]. IEEE Transactions on Vehicular Technology, 2019, 66(2):952-964.
[15] TIAN Y, PEI H X, ZHANG Y. Path planning for CAVs considering dynamic obstacle avoidance based on improved driving risk field and A* algorithm[C]//5th International Conference on Information Science, Computer Technology and Transportation (ISCTT). Shenyang, 2020:281-286.
[16] RASEKHIPOUR Y, KHAJEPOUR A, CHEN S K, et al. A potential field-based model predictive path-planning controller for autonomous road vehicles[J]. IEEE Transactions on Intelligent Transportation Systems, 2017, 18(5):1255-1267.
[17] 刘帅. 基于安全场的智能汽车个性化换道决策与规划算法研究[D]. 长春:吉林大学, 2019.LIU S. A personalized lane-changing decision-making and trajectory planning method based on safety field for intelligent vehicles[D]. Changchun:Jilin University, 2019. (in Chinese)
[18] 陈虹, 申忱, 郭洪艳, 等. 面向动态避障的智能汽车滚动时域路径规划[J]. 中国公路学报, 2019, 32(1):166-176.CHEN H, SHEN C, GUO H Y, et al. Moving horizon path planning for intelligent vehicle considering dynamic obstacle avoidance[J]. China Journal of Highway and Transport, 2019, 32(1):166-176. (in Chinese)
[19] ARAVD H. A time based analysis of road user behaviour in normal and critical encounters[D]. Delft:Technische Universiteit Delft, 1990.
[20] KHRAPAK S A, IVLEV A V, MORFILL G E, et al, Scattering in the attractive Yukawa potential:Application to the ion-drag force in complex plasmas[J]. IEEE Transactions on Plasma Science, 2004, 32(2):555-560.
[21] 赵建辉, 高洪波, 张新钰, 等. 基于时间延迟动态预测的自动驾驶控制[J]. 清华大学学报(自然科学版), 2018, 58(4):432-437.ZHAO J H, GAO H B, ZHANG X Y, et al. Automatic driving control based on time delay dynamic predictions[J]. Journal of Tsinghua University (Science and Technology), 2018, 58(4):432-437. (in Chinese)
[22] DAI C H, ZONG C F, CHEN G Y. Path tracking control based on model predictive control with adaptive preview characteristics and speed-assisted constraint[J]. IEEE Access, 2020, 8(1):184697-184709.
[23] 胡满江, 徐彪, 秦洪懋, 等. 基于MPC的多车纵向协同避撞算法[J]. 清华大学学报(自然科学版), 2017, 57(12):1280-1286.HU M J, XU B, QIN H M, et al. MPC based longitudinal coordinated collision avoidance for multiple connected vehicles[J]. Journal of Tsinghua University (Science and Technology), 2017, 57(12):1280-1286. (in Chinese)
[24] 王鑫, 徐祖华, 赵均, 等. 基于梯度特征的分布曲线模型预测控制算法[J]. 清华大学学报(自然科学版), 2019, 59(5):403-408.WANG X, XU Z H, ZHAO J, et al. Gradient feature-based model predictive control algorithm of distribution processes[J]. Journal of Tsinghua University (Science and Technology), 2019, 59(5):403-408. (in Chinese)
