引入驾驶风格的熵权法多属性换道决策模型

为改善AHP换道模型需要主观赋权的问题，在分析换道决策机理及换道决策属性的基础上，提出引入驾驶风格的熵权法多属性换道决策模型.在不同空间占有率D 下对模型进行仿真，获得不同驾驶风格、多种车道分隔方式下的平均换道动机概率和平均换道成功概率. 分析发现，驾驶风格对平均换道动机概率和平均换道成功概率产生显著影响的空间占有率分别为(0.10, 0.85)和(0.30, 0.85)，其中，激进驾驶风格的概率最大，保守的概率最小. 说明该模型能响应驾驶风格偏好的影响，熵权法在多车道元胞自动机换道决策模型中的适用性较强.

Multi-attributes Lane-changing Decision Model Based on Entropy Weight with Driving Styles

AHP lane-changing model needs subjective weight. In order to address the problem, the lane-changing decision mechanism and attributes are analyzed, and a multi-attribute lane change decision model based on entropy weight with driving styles is proposed. The model is simulated with different space availability D . The average lane-changing motivation probability and success probability are obtained under different driving styles and different lane demarcation patterns. The result shows that driving styles have impacts on the average probability of lane-changing motivation and lane-changing success in the range of (0.10, 0.85) and (0.30,0.85), in which the probability of radical driving style is the largest while the probability of conservative driving style is the smallest. It shows that the model can respond to the influence of driving style preference. And the entropy weight has better applicability in the multi-lane cellular automaton lane-changing decision model.