Cooperative Simulation Model for Driving Behavior Based on Cognition Activity Chain
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摘要: 为向车辆控制系统和智能车辆的发展提供理论参考,用主成分分析法确定多源信息对驾驶员行为决策的影响系数,用模糊积分融合算法获得驾驶员任务集聚后车辆的运行模式,并按照认知活动链将该模糊积分融合算法与跟驰模型相结合,构建了基于认知活动链的驾驶员行为协调仿真模型.此外,采用五轮仪实验系统对淄博市张周路某路段的交通流数据进行了采集,用实测数据验证了模型的有效性.Abstract: To provide a theoretical reference for the development of advanced vehicle control systems and intelligent vehicles, the principal component analysis was used to determine the influence coefficient of multi-information on driving behavior decision-making, and the fuzzy integral fusion algorithm was applied to obtain the running pattern of a vehicle after the task concentration of the driver.The fuzzy integral fusion algorithm was combined with the car-following model to construct a cooperative simulation model for the driving behavior based on cognition activity chain.Finally, the validity of the cooperative simulation model was verified by the traffic data collected from Zhangzhou road in Zibo City using the five-wheel system.
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Key words:
- driving behavior /
- raulti-infonnation fusion /
- car-following model /
- task concentration
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