无人驾驶条件下的共享停车供需匹配模型及其对应遗传算法
Parking Space Sharing Supply-Demand Matching Model and the Designated Genetic Algorithm Based on Autonomous Vehicles
DOI: 10.12677/AAM.2022.112081, PDF,    国家自然科学基金支持
作者: 崔允汀, 何胜学*：上海理工大学管理学院，上海
关键词: 共享停车；无人驾驶车辆；二次分配；遗传算法；Parking Space Sharing； Autonomous Vehicle； Quadratic Assignment； Genetic Algorithm
摘要: 尽管利用无人驾驶车辆在停车过程中可灵活移位的特征能有效提升共享泊位的利用率，但是停车过程中频繁地调换泊位势必增加用车成本和事故风险。为化解上述矛盾，构建了以移车次数和移车距离最小为优化目标，以满足可接受的停车需求为约束的无人驾驶条件下共享停车供需匹配优化模型。新模型具有纯整数二次规划特征，可视为一类特殊的二次分配问题。考虑到问题的NP-hard特性，设计了一种带有个体自主优化能力的改进遗传算法对其加以求解。数值实验分析验证了新模型和算法的有效性。本研究为利用无人驾驶提升共享停车服务水平提供了新思路和新方法。
Abstract: Though making use of the feature of autonomous vehicle that is changing parking spaces freely during parking can effectively improve the utilization of shared parking spaces, the frequently changing parking spaces during parking will surely increase the cost of using car and the risk of accidents. To solve the above conflict, the paper proposed a supply-demand matching optimization model for driverless vehicles with minimizing the total number and distance of changing the parking space as objective and satisfying the acceptable parking demand as constraints. The new model has the feature of a pure integer quadratic programming and is a special type of quadratic assignment problem. In view of the NP-hard characteristic of the problem, this paper designed a modified genetic algorithm with an individual’s self-improvement to solve the new model. Numerical experiments verified the effectiveness of the new model and the new algorithm. This research offers a new idea and a new method for improving the service level of shared parking with autonomous driving.
文章引用：崔允汀, 何胜学. 无人驾驶条件下的共享停车供需匹配模型及其对应遗传算法[J]. 应用数学进展, 2022, 11(2): 756-768. https://doi.org/10.12677/AAM.2022.112081

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