| 考虑驾驶员舒适度的纯电动公交柔性调度优化 |
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| 引用本文： | 胡永仕、杨悠悠、张阳.考虑驾驶员舒适度的纯电动公交柔性调度优化[J].福建工程学院学报,2021,0(3):230-235. |
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| 作者姓名： | 胡永仕、杨悠悠、张阳 |
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| 作者单位： | 福建工程学院交通运输学院 |
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| 摘 要： | 为克服公交调度优化模型中纯电动公交车受续航里程约束、未考虑驾驶员舒适度的不足，提出了人-车固定模式的纯电动公交车柔性调度优化方法。采用休憩时长为衡量驾驶员舒适度的指标，将保证驾驶员舒适度产生的负面边际效应量化为延误成本，以公交企业总成本最小为目标构建优化调度模型，引入改进的粒子群算法求解。改进算法通过调整粒子群算法的位置和更新机制解决传统粒子群算法易陷入局部极值的问题，进一步提高算法精度。实验结果表明，柔性调度优化方法能有效降低公交企业的总运营成本，具有一定的实用性。
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| 关 键 词： | 纯电动公交车 驾驶员 公交调度 改进的粒子群算法 |
Flexible scheduling optimization of pure electric buses considering driver comfort |
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| HU Yongshi,YANG Youyou,ZHANG Yang.Flexible scheduling optimization of pure electric buses considering driver comfort[J].Journal of Fujian University of Technology,2021,0(3):230-235. |
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| Authors: | HU Yongshi YANG Youyou ZHANG Yang |
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| Institution: | School of Transportation, Fujian University of Technology |
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| Abstract: | In order to overcome the shortcomings of the traditional bus scheduling optimization model, i.e., the pure electric bus in the traditional bus scheduling model is constrained by the mileage and does not consider the driver’s comfort, a flexible scheduling optimization method was proposed for pure electric buses with fixed man-vehicle mode. The method first used the driver’s rest time as the index to measure driver comfort, quantified the negative marginal effect caused by ensuring the driver comfort into the delay cost, and then constructed the optimal scheduling model with the goal of minimizing the total cost of public transport enterprises. Finally, the improved particle swarm optimization algorithm (PSO) was introduced to solve the problem. By adjusting the position and update mechanism of PSO, the improved algorithm solved the problem that traditional PSO is easy to fall into local extremum, and further improved the accuracy of the algorithm. The experimental results show that the flexible scheduling optimization method could effectively reduce the total operating cost of public transport enterprises, and had certain practicability. |
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| Keywords: | pure electric buses drivers bus scheduling improved particle swarm optimization |
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