CA3065617C - Method for predicting car-following behavior under apollo platform - Google Patents

Method for predicting car-following behavior under apollo platform Download PDF

Info

Publication number
CA3065617C
CA3065617C CA3065617A CA3065617A CA3065617C CA 3065617 C CA3065617 C CA 3065617C CA 3065617 A CA3065617 A CA 3065617A CA 3065617 A CA3065617 A CA 3065617A CA 3065617 C CA3065617 C CA 3065617C
Authority
CA
Canada
Prior art keywords
car
following
acceleration
velocity
difference
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CA3065617A
Other languages
English (en)
French (fr)
Other versions
CA3065617A1 (en
Inventor
Rong FEI
Shasha Li
Haozheng Wu
Fang Liu
Aimin Li
Yu Tang
Zhanmin Wang
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Xian University of Technology
Original Assignee
Fei Rong
Li Shasha
Wang Zhanmin
Wu Haozheng
Xian University of Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Fei Rong, Li Shasha, Wang Zhanmin, Wu Haozheng, Xian University of Technology filed Critical Fei Rong
Publication of CA3065617A1 publication Critical patent/CA3065617A1/en
Application granted granted Critical
Publication of CA3065617C publication Critical patent/CA3065617C/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING OR COUNTING
    • G06NCOMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computing arrangements using knowledge-based models
    • G06N5/04Inference or reasoning models
    • G06N5/048Fuzzy inferencing
    • YGENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02TCLIMATE CHANGE MITIGATION TECHNOLOGIES RELATED TO TRANSPORTATION
    • Y02T10/00Road transport of goods or passengers
    • Y02T10/10Internal combustion engine [ICE] based vehicles
    • Y02T10/40Engine management systems

Landscapes

  • Engineering & Computer Science (AREA)
  • Software Systems (AREA)
  • Theoretical Computer Science (AREA)
  • Data Mining & Analysis (AREA)
  • Artificial Intelligence (AREA)
  • Computational Linguistics (AREA)
  • Fuzzy Systems (AREA)
  • Evolutionary Computation (AREA)
  • Physics & Mathematics (AREA)
  • Computing Systems (AREA)
  • General Engineering & Computer Science (AREA)
  • General Physics & Mathematics (AREA)
  • Mathematical Physics (AREA)
  • Automation & Control Theory (AREA)
  • Traffic Control Systems (AREA)
CA3065617A 2019-09-27 2019-12-19 Method for predicting car-following behavior under apollo platform Active CA3065617C (en)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
CN201910924643.8A CN110750877B (zh) 2019-09-27 2019-09-27 一种Apollo平台下的车辆跟驰行为预测方法
CN201910924643.8 2019-09-27

Publications (2)

Publication Number Publication Date
CA3065617A1 CA3065617A1 (en) 2021-03-27
CA3065617C true CA3065617C (en) 2022-07-19

Family

ID=69277307

Family Applications (1)

Application Number Title Priority Date Filing Date
CA3065617A Active CA3065617C (en) 2019-09-27 2019-12-19 Method for predicting car-following behavior under apollo platform

Country Status (2)

Country Link
CN (1) CN110750877B (zh)
CA (1) CA3065617C (zh)

Families Citing this family (28)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111476491A (zh) * 2020-04-10 2020-07-31 北京工业大学 一种城市交通场景中的车辆运动模拟分析方法
CN111674394B (zh) * 2020-06-09 2023-04-11 南京工业职业技术学院 一种能实现微观调控的自动驾驶跟驰保持方法
CN111907523B (zh) * 2020-06-30 2024-03-12 山东小雨汽车科技有限公司 一种基于模糊推理的车辆跟驰寻优控制方法
CN111968372B (zh) * 2020-08-25 2022-07-22 重庆大学 一种考虑主观因素的多车型混合交通跟驰行为仿真方法
CN112193245B (zh) * 2020-09-24 2021-09-03 同济大学 一种考虑驾驶员模糊感知的深度学习跟驰预测方法
CN112580149B (zh) * 2020-12-22 2023-05-26 浙江工业大学 基于生成对抗网络和驾驶时长的车辆跟驰模型生成方法
CN113066282B (zh) * 2021-02-26 2022-05-27 北京航空航天大学合肥创新研究院(北京航空航天大学合肥研究生院) 一种面向混行环境下车辆跟驰耦合关系建模方法及系统
CN112793572B (zh) * 2021-03-19 2022-06-03 成都安智杰科技有限公司 一种自适应巡航控制方法、装置、电子设备和存储介质
CN113112022A (zh) * 2021-04-06 2021-07-13 清华大学 智能汽车队列人-车-路系统多智能体联合建模方法
CN113325691B (zh) * 2021-04-29 2022-07-12 西安交通大学 一种无人车双闭环纵向控制方法、系统及设备
CN113779864B (zh) * 2021-08-06 2024-04-26 同济大学 面向自动驾驶汽车的运行设计区域构建方法和装置
CN113657676B (zh) * 2021-08-19 2024-05-14 燕山大学 一种考虑多维度驾驶人特性的制动反应时间预测方法
CN114023108B (zh) * 2021-11-02 2023-06-09 河北工业大学 一种混合交通流变道模型及变道仿真方法
CN113928314B (zh) * 2021-11-17 2023-11-10 吉林大学 一种冰雪路面条件下考虑前后车的自动驾驶车辆跟驰控制方法
CN114169444B (zh) * 2021-12-09 2024-03-05 合肥工业大学 车辆跟驰工况下考虑风险势场分布的驾驶风格分类方法
CN114328465B (zh) * 2022-01-04 2024-07-30 吉林大学 一种针对人机共驾测试的侧方插入场景提取方法
CN114537391A (zh) * 2022-02-24 2022-05-27 同济大学 一种基于预报观测器的车辆跟驰伺服控制方法及系统
CN114516328B (zh) * 2022-03-08 2024-02-27 武汉科技大学 一种智能网联环境下基于规则的车队跟驰模型方法
CN115099128B (zh) * 2022-05-30 2023-07-07 同济大学 一种异常驾驶行为识别与致因分析方法和系统
CN114932552B (zh) * 2022-05-31 2024-03-26 西安理工大学 协作机器人主动动作决策方法、系统、设备及存储介质
CN115019508B (zh) * 2022-06-13 2023-09-29 华南理工大学 基于机器学习的道路监控车流仿真方法、装置、设备及介质
CN115195821B (zh) * 2022-06-14 2023-09-26 同济大学 一种后车跟驰行为控制方法、装置及存储介质
CN115171380B (zh) * 2022-07-01 2023-05-12 广西师范大学 一种抑制网络攻击造成车联网拥塞的控制模型和方法
CN115440036B (zh) * 2022-08-26 2023-08-29 同济大学 一种车辆跟驰关系管理与角色实时配置方法
CN115195728A (zh) * 2022-08-30 2022-10-18 重庆长安汽车股份有限公司 一种车辆跟车控制方法、系统、设备及存储介质
CN115629606B (zh) * 2022-10-17 2024-08-23 清华大学 对抗信息下车辆的跟车控制方法、装置、车辆及存储介质
CN116386346A (zh) * 2022-12-13 2023-07-04 中南大学 车辆跟驰运行风险状态判定方法、系统及设备
CN117311366B (zh) * 2023-11-21 2024-02-13 南京禄口国际机场空港科技有限公司 一种应用于机场草坪的割草机的路径控制方法、系统及存储介质

Family Cites Families (24)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1719354A (zh) * 2005-05-08 2006-01-11 上海交通大学 车辆跟驰运动的加速度控制方法
CN1876461A (zh) * 2006-07-06 2006-12-13 上海交通大学 车辆跟驰驾驶的速度差-间距控制方法
CN101264762A (zh) * 2008-03-21 2008-09-17 东南大学 车辆跟驰运动的速度控制方法
CN101694742A (zh) * 2009-06-16 2010-04-14 同济大学 重大公路交通基础设施运行安全控制方法
CN102991498A (zh) * 2011-12-19 2013-03-27 王晓原 基于多源信息融合的驾驶员跟驰行为模型
CN102662320A (zh) * 2012-03-05 2012-09-12 吴建平 一种基于模糊数学的车辆跟驰模拟方法
US10510256B2 (en) * 2014-10-20 2019-12-17 Robert Brandriff Vehicle collision avoidance system and method
CN105788238B (zh) * 2016-01-07 2018-08-28 南京航空航天大学 基于量子门和自适应控制的类弹簧车辆跟驰模型建立方法
CN105809106B (zh) * 2016-02-23 2019-02-26 北京理工大学 基于机器视觉的车辆队形跟驰检测方法
CN106407563B (zh) * 2016-09-20 2020-03-27 北京工业大学 一种基于驾驶类型和前车加速度信息的跟驰模型生成方法
CN106803226A (zh) * 2017-01-23 2017-06-06 长安大学 考虑最优速度记忆及后视效应的车辆跟驰建模方法
CN108573600B (zh) * 2017-03-10 2022-02-08 重庆邮电大学 一种驾驶员行为诱导与局部交通流优化方法
WO2018207199A1 (en) * 2017-05-06 2018-11-15 Ramana Soothram Venkata Automatic vehicle & driver tracking system with intelligent traffic management
CN107103749B (zh) * 2017-05-19 2020-03-10 长安大学 车联网环境下跟驰交通流特性建模方法
CN107452201B (zh) * 2017-07-24 2020-05-08 重庆大学 一种考虑前车换道驶离时后车的跟驰加速度确定方法及跟驰行为建模方法
CN107507408B (zh) * 2017-07-24 2020-07-24 重庆大学 一种考虑前车换道汇入过程的跟驰加速度及跟驰行为建模方法
CN107507245A (zh) * 2017-08-18 2017-12-22 南京阿尔特交通科技有限公司 一种车辆跟驰轨迹的动态采集方法及系统
US10902336B2 (en) * 2017-10-03 2021-01-26 International Business Machines Corporation Monitoring vehicular operation risk using sensing devices
CN107544254B (zh) * 2017-10-12 2020-04-14 北京航空航天大学 一种期望安全裕度跟驰模型的自适应动态滑模控制方法
CN108495330B (zh) * 2018-03-09 2019-11-08 清华大学 一种车-车信息交互通信的碰撞预警可靠性测试方法
CN108944943B (zh) * 2018-07-11 2020-04-14 北京航空航天大学 一种基于风险动态平衡理论的弯道跟驰模型
CN109213148B (zh) * 2018-08-03 2021-05-28 东南大学 一种基于深度强化学习的车辆低速跟驰决策方法
CN109858738A (zh) * 2018-12-19 2019-06-07 青岛科技大学 一种车辆跟驰状态驾驶员情感动态特征提取及辨识方法
CN109978260B (zh) * 2019-03-26 2023-02-21 重庆邮电大学 混合交通流下网联车跟驰行为预测方法

Also Published As

Publication number Publication date
CN110750877B (zh) 2024-05-03
CA3065617A1 (en) 2021-03-27
CN110750877A (zh) 2020-02-04

Similar Documents

Publication Publication Date Title
CA3065617C (en) Method for predicting car-following behavior under apollo platform
US11899411B2 (en) Hybrid reinforcement learning for autonomous driving
Gil et al. Surrogate model based optimization of traffic lights cycles and green period ratios using microscopic simulation and fuzzy rule interpolation
CN110362910B (zh) 基于博弈论的自动驾驶车辆换道冲突协调模型建立方法
WO2022052406A1 (zh) 一种自动驾驶训练方法、装置、设备及介质
Odeh et al. A hybrid fuzzy genetic algorithm for an adaptive traffic signal system
Ali et al. An adaptive method for traffic signal control based on fuzzy logic with webster and modified webster formula using SUMO traffic simulator
CN114919578B (zh) 智能车行为决策方法、规划方法、系统及存储介质
Wei et al. Game theoretic merging behavior control for autonomous vehicle at highway on-ramp
Liu et al. A three-level game-theoretic decision-making framework for autonomous vehicles
Shamsi et al. Reinforcement learning for traffic light control with emphasis on emergency vehicles
Rais et al. Decision making for autonomous vehicles in highway scenarios using Harmonic SK Deep SARSA
Farrag et al. STIMF: a smart traffic incident management framework
Liu et al. Graph reinforcement learning application to co-operative decision-making in mixed autonomy traffic: Framework, survey, and challenges
Kensbock et al. Scenario-based decision-making, planning and control for interaction-aware autonomous driving on highways
Zhao et al. A survey on deep reinforcement learning approaches for traffic signal control
Dong et al. Lane-changing trajectory control strategy on fuel consumption in an iterative learning framework
WO2024118997A1 (en) Prediction model with variable time steps
Yuan et al. From Naturalistic Traffic Data to Learning-Based Driving Policy: A Sim-to-Real Study
CN115116240A (zh) 一种无信号灯交叉路口车辆协同控制方法及系统
CN114701517A (zh) 基于强化学习的多目标复杂交通场景下自动驾驶解决方法
Wang et al. Iterative Learning-Based Cooperative Motion Planning and Decision-Making for Connected and Autonomous Vehicles Coordination at On-Ramps
Hegde et al. Design of AI-Based Lane Changing Models in Connected and Autonomous Vehicles: a Survey.
Nagayoshi et al. Reinforcement Learning Approach for Adaptive Negotiation-Rules Acquisition in AGV Transportation Systems
Bhattacharyya Modeling Human Driving from Demonstrations