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Target Vehicle Selection Algorithm for Adaptive Cruise Control Based on Lane-changing Intention of Preceding Vehicle

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Chinese Journal of Mechanical Engineering 2021年第5期34卷 390-407页

作者： Jun Yao Guoying Chen zhenhai gao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130022China

To improve the ride comfort and safety of a traditional adaptive cruise control(ACC)system when the preceding vehicle changes lanes,it proposes a target vehicle selection algorithm based on the prediction of the lane-changing intention for the preceding ***,the Next Generation Simulation dataset is used to train a lane-changing intention prediction algorithm based on a sliding window support vector machine,and the lane-changing intention of the preceding vehicle in the current lane is identified by lateral position ***,according to the lane-changing intention and collision threat of the preceding vehicle,the target vehicle selection algorithm is studied under three different conditions:safe lane-changing,dangerous lane-changing,and lane-changing ***,the effectiveness of the proposed algorithm is verified in a co-simulation *** simulation results show that the target vehicle selection algorithm can ensure the smooth transfer of the target vehicle and effectively reduce the longitudinal acceleration fluctuation of the subject vehicle when the preceding vehicle changes lanes safely or cancels their lane change *** the case of a dangerous lane change,the target vehicle selection algorithm proposed in this paper can respond more rapidly to a dangerous lane change than the target vehicle selection method of the traditional ACC system;thus,it can effectively avoid collisions and improve the safety of the subject vehicle.

关键词： Lane-changing intention Target vehicle selection Support vector machine Adaptive cruise control

Brain-like Intelligent Decision-making Based on Basal Ganglia and Its Application in Automatic Car-following

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Journal of Bionic Engineering 2021年第6期18卷 1439-1451页

作者： Tianjun Sun zhenhai gao Zhiyong Chang Kehan Zhao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun130022China College of Automotive Engineering Jilin UniversityChangchun130022China College of Biological and Agricultural Engineering Jilin UniversityChangchun130022China College of Materials Science and Engineering Jilin UniversityChangchun130022China

The anthropomorphic intelligence of autonomous driving has been a research hotspot in the ***,current studies have not been able to reveal the mechanism of drivers'natural driving ***,this thesis starts from the perspective of cognitive decision-making in the human brain,which is inspired by the regulation of dopamine feedback in the basal ganglia,and a reinforcement learning model is established to solve the brain-like intelligent decision-making problems in the process of interacting with the *** this thesis,first,a detailed bionic mechanism architecture based on basal ganglia was proposed by the consideration and analysis of its feedback regulation mechanism;second,the above mechanism was transformed into a reinforcement Q-learning model,so as to implement the learning and adaptation abilities of an intelligent vehicle for brain-like intelligent decision-making during car-following;finally,the feasibility and effectiveness of the proposed method were verified by the simulations and real vehicle tests.

关键词： Brain-like intelligent decision-making Dopamine in basal ganglia Reinforcement learning Longitudinal autonomous driving

Experimental and Numerical Study of Cervical Muscle Contraction in Frontal Impact

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Automotive Innovation 2019年第2期2卷 93-101页

作者： zhenhai gao Zhao Li Hongyu Hu Fei gao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun 130000China School of Public Health Jilin UniversityChangchun 130000China College of Biological and Agricultural Engineering Jilin UniversityChangchun 130000China

In a crash situation,drivers typically make evasive maneuvers before an upcoming impact,which can affect the kinematics and injury during *** purpose of the current study was to investigate the response and effect of drivers’cervical muscles in a frontal impact.A crash scenario was developed using a vehicle driving simulator,and 10 volunteers were employed to drive the simulator at 20 km/h,50 km/h,80 km/h and 100 km/***(EMG)was recorded from the sternocleidomastoideus(SCM),splenius cervicis(SPL)and trapezium(TRP)muscles using a data acquisition system,and the level of muscle activation was calculated.A numerical study was conducted using data collected in the *** results revealed that the cervical muscles were activated during drivers’protective *** activity of cervical muscles before impact was greater than that during normal *** activity increased with driving speed,with the SCM and TRP exhibiting larger increases than the *** kinematics and load of the driver were influenced by muscle *** the collision,the head of an active model stretched backward,while the passive model kept the head *** low-speed impact,the torque and shear of the cervical muscle in the active model were much lower than those in the passive model,while the tension of the cervical muscle was higher in the active model compared with the passive *** results indicated that the incidence of cervical injury in high-speed impact is complex.

关键词： Cervical injury Frontal impact Active muscle force Driving simulator

Hierarchical Parking Path Planning Based on Optimal Parking Positions

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Automotive Innovation 2023年第2期6卷 220-230页

作者： Yaogang Zhang Guoying Chen Hongyu Hu zhenhai gao State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchunJilinChina

Automated valet parking(AVP)has attracted the attention of industry and academia in recent ***,there are still many challenges to be solved,including shortest path search,optimal time efficiency,and applicability of algorithm in complex *** this paper,a hierarchical AVP path planner is proposed,which divides a complete AVP path planning into the guided layer and the planning layer from the perspective of global *** guided layer is mainly used to divide a complex AVP path planning into several simple path plannings,which makes the hybrid A*algorithm more applicable in a complex parking *** planning layer mainly adopts different optimization methods for driving and parking path *** proposed method is verified by a large number of simulations which include the verification of the optimal parking position,the performance of the planner for perpendicular parking,and the scalability of the planner for parallel parking and inclined *** simulation results reveal that the efficiency of the algorithm is increased by more than 20 times,and the average path length is also shortened by more than 20%.Furthermore,the planner overcomes the problem that the hybrid A*algorithm is not applicable in complex parking scenarios.

关键词： Automated valet parking Path planning Hybrid A* Visibility graph Shortest path

Lane changing assistance strategy based on an improved probabilistic model of dynamic occupancy grids

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Frontiers of Information Technology & Electronic Engineering 2021年第11期22卷 1492-1504页

作者： Zhengcai YANG zhenhai gao Fei gao Xinyu WU Lei HE State Key Laboratory of Automotive Simulation and Control Jilin UniversityChangchun130022China School of Automotive Engineering Hubei University of Automotive TechnologyShiyan442002China

Lane changing assistance in autonomous vehicles is a popular research topic. Scene modeling of the driving area is a prerequisite for lane changing decision problems. A road environment representation method based on a dynamic occupancy grid is proposed in this study. The model encapsulates the data such as vehicle speed, obstacles, lane lines, and traffic rules into a form of spatial drivability probability. This information is compiled into a hash table, and the grid map is mapped into a hash map by means of hash function. A vehicle behavior decision cost equation is established with the model to help drivers make accurate vehicle lane changing decisions based on the principle of least cost, while considering influencing factors such as vehicle drivability, safety, and power. The feasibility of the lane changing assistance strategy is verified through vehicle tests, and the results show that the lane changing assistance system based on a probabilistic model of dynamic occupancy grids can provide lane changing assistance to drivers taking into consideration the dynamics and safety.

关键词： Occupancy grids Probabilistic model Lane changing assistance

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基于逆向强化学习的纵向自动驾驶决策方法

汽车工程 2022年第7期44卷 969-975页

作者：高振海闫相同高菲吉林大学汽车仿真与控制国家重点实验室长春130022

基于人类驾驶员数据获得自动驾驶决策策略是当前自动驾驶技术研究的热点。经典的强化学习决策方法大多通过设计安全性、舒适性、经济性相关公式人为构建奖励函数,决策策略与人类驾驶员相比仍然存在较大差距。本文中使用最大边际逆向强... 详细信息

基于人类驾驶员数据获得自动驾驶决策策略是当前自动驾驶技术研究的热点。经典的强化学习决策方法大多通过设计安全性、舒适性、经济性相关公式人为构建奖励函数,决策策略与人类驾驶员相比仍然存在较大差距。本文中使用最大边际逆向强化学习算法,将驾驶员驾驶数据作为专家演示数据,建立相应的奖励函数,并实现仿驾驶员的纵向自动驾驶决策。仿真测试结果表明:相比于强化学习方法,逆向强化学习方法的奖励函数从驾驶员的数据中自动化的提取,降低了奖励函数的建立难度,得到的决策策略与驾驶员的行为具有更高的一致性。

关键词：自动驾驶决策算法强化学习逆向强化学习

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汽车椅面倾角对驾驶员乘坐舒适性的影响分析

湖南大学学报（自然科学版） 2017年第8期44卷 43-49页

作者：高振海高菲沈传亮程悦吉林大学汽车仿真与控制国家重点实验室吉林长春130022 中国第一汽车集团公司技术中心吉林长春130011

考虑到车用座椅椅面倾角变化对驾驶员乘坐舒适性的影响,开展了不同身材驾驶员在不同椅面倾角下的人体骨肌力学特性的仿真分析与实验测试.首先基于人体骨肌力学软件分别建立了第5,50,95百分位中国男性驾驶员在驾驶姿态下的骨肌力学模型;... 详细信息

考虑到车用座椅椅面倾角变化对驾驶员乘坐舒适性的影响,开展了不同身材驾驶员在不同椅面倾角下的人体骨肌力学特性的仿真分析与实验测试.首先基于人体骨肌力学软件分别建立了第5,50,95百分位中国男性驾驶员在驾驶姿态下的骨肌力学模型;然后通过椅面倾角参数动态调整并结合相关性分析方法,描述了驾驶员下肢腿部不同肌肉的受力情况和激活程度;最后开展了真实驾驶员下肢肌肉肌电测试.结果表明,当座椅椅面倾角增大时,驾驶员的臀大肌、髂腰肌、半腱肌、股直肌、缝匠肌、腓肠肌、胫骨前肌肌肉激活程度较大,10°~16°为椅面倾角的理想变化区间.

关键词：汽车座椅乘坐舒适性骨肌力学模型座椅椅面倾角肌肉激活程度

仿人小脑神经网络结构的驾驶员方向控制行为建模

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汽车工程 2012年第4期34卷 288-291页

作者：高振海段立飞吉林大学汽车仿真与控制国家重点实验室长春130022

在分析驾驶员的运动控制行为特性基础上,仿照人小脑神经网络结构,建立了驾驶员对汽车方向控制行为的小脑神经网络控制模型,以此对传统的微分校正模型进行控制误差修正。在不同车速、路形和路面附着系数下的仿真结果表明,所提出的控制算... 详细信息

在分析驾驶员的运动控制行为特性基础上,仿照人小脑神经网络结构,建立了驾驶员对汽车方向控制行为的小脑神经网络控制模型,以此对传统的微分校正模型进行控制误差修正。在不同车速、路形和路面附着系数下的仿真结果表明,所提出的控制算法有高的路径跟踪精度,且对车速和道路状况等汽车行驶过程中的动态不确定性因素具有较强的适应性和鲁棒性。

关键词：驾驶员模型方向控制微分校正小脑神经网络

Research on Human-imitative Autonomous Lane-Changing Method on Highways

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Research on Human-imitative Autonomous Lane-Changing Method ...