Incentive-Based Multi-objective Fractional Optimization for EV Navigation System with Successive Update

Shun Maeda, T. Hayakawa, J. Imura, Hideaki Tanaka, Y. Mae
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Abstract

An EV navigation system for drivers to choose one of the route candidates depending on the drivers' preference is developed. The approach is incentive based and the route candidates are obtained through multi-objective optimization. The navigation system computes the optimal routes under the varying traffic conditions and successively checks if the selected route is relevant. In the case where the projective route is forced to change in the middle of traveling, the way of calculating the amount of partial incentive is proposed for the segments passed by.
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逐次更新电动汽车导航系统的激励多目标分数优化
开发了一种电动汽车导航系统,使驾驶员能够根据自己的驾驶偏好在备选路线中进行选择。该方法基于激励,通过多目标优化获得候选路径。导航系统在不同的交通条件下计算出最优路线,并依次检查所选路线是否相关。在行驶中途被迫改变投影路线的情况下,提出了对所经过路段的部分激励量的计算方法。
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