Stochastic saturation entropy model of passenger transportation structure configuration for comprehensive transportation corridor
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摘要: 为寻求系统、科学的综合运输通道最优客运分担, 提出用最大熵原理构建客运结构配置模型, 基于随机时间价值, 选择旅客广义出行时间最小的运输方式, 定义了通道内的基本路段饱和度和通道饱和熵, 设计了用于求解模型的粒子群算法。分析发现, 车外时间差、单位里程票价差、单位里程车内时间差以及旅行距离将直接影响各运输方式客运分担率的高低; 以通道饱和熵最大为目标得出的常规铁路最优定价高于现行铁路票价, 且通道饱和熵上升了15%, 说明铁路票价偏低会造成铁路客运量过于饱和; 由通道饱和熵模型得出的最优客运分担结果, 缩小了基本路段上各运输方式饱和度之间的差距, 实现了运力和运量的有效匹配。Abstract: In order to find a systematic and scientific method to optimize the passenger transportation sharing rate of comprehensive transportation corridor, a passenger transportation structure configuration model was put forward based on the maximum entropy theory.In the model, passenger chose transportation mode, so that generalized travel time based on stochastic time value was least, the saturation degree of basic links in the corridor and corridor saturation entropy were defined, and a particle swarm algorithm was designed to solve the model.Analysis result shows that the sharing rates of various transportation modes depend on the differences of out-of-vehicle times, the differences of unit distance prices, the differences of unit distance travel times and travel distances; rail optimal pricing is higher than the current one, the saturation entropy has an increase of 15%, which means that low rail pricing result in the over saturation of passenger flow; the optimal passenger transportation sharing rate can reduce the differences between the saturation degrees of various transportation modes on the basic links in the corridor, and realize the effective match between transportation demand and supply.
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表 1 各运输方式的技术参数
Table 1. Technology parameters of different transportation modes
运输方式 旅行速度vm/(km·h-1) 车外时间twm/h 单位里程票价pm/[元·(人·km)-1] 公路 100 0.4 0.30 常规铁路 120 3.0 0.12 民航 800 4.3 0.50 
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表 2 客运分布现状
Table 2. Passenger transportation distribution status
万人·a-1 OD段 北京—郑州 北京—武汉 北京—长沙 北京—广州 郑州—武汉 郑州—长沙 郑州—广州 武汉—长沙 武汉—广州 长沙—广州 公路 — — — — — — — 1.0 — — 常规铁路 1 080.0 500.0 300.0 200.0 580.0 300.0 200.0 1 400.0 500.0 2 400.0 民航 19.3 36.2 22.4 147.2 0.8 0.5 17.0 0.0 27.7 19.7 客运总量 1 099.3 536.2 322.4 347.2 580.8 300.5 217.0 1 401.0 527.7 2 419.7 旅行距离/km 689 1 225 1 587 2 294 536 898 1 605 362 1 069 707
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表 3 客运量和输送能力分布现状
Table 3. Distribution status of passenger volume and transportation capacity
基本路段 区间长度/km 客运量/(万人·a-1) 输送能力/(万人·a-1) 饱和度 公路 常规铁路 民航 公路 常规铁路 民航 公路 常规铁路 民航 北京—郑州 689 — 2 080.0 225.1 — 2 190.0 337.5 — 0.950 0.667 郑州—武汉 536 — 2 080.0 224.1 — 2 190.0 331.4 — 0.950 0.676 武汉—长沙 362 1.0 2 900.0 214.8 1.5 3 139.0 328.4 0.685 0.920 0.654 长沙—广州 707 — 3 300.0 211.6 — 3 504.0 320.5 — 0.940 0.660 注: 铁路的输送能力根据列车时刻表, 以一列车输送1 000人, 一年365天(考虑对开的列数)推算出; 民航的运量和输送能力根据《中国交通年鉴》的实际民航运量和客座率推算出来; 公路的运量和输送能力根据各城市长途汽车客运时刻表, 以一班车40人, 一年365天和客座率推算出来, 北京—郑州、郑州—武汉、长沙—广州没有长途客运。
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表 4 旅客出行分配结果
Table 4. Passenger transportation distribution result
基本路段 客运量/(万人·a-1) 饱和度 公路 高速铁路 民航 公路 高速铁路 民航 北京—郑州 — 2 181.0 124.0 — 0.786 0.368 郑州—武汉 — 2 165.0 139.0 — 0.781 0.419 武汉—长沙 1.0 1 578.0 136.0 0.685 0.481 0.416 长沙—广州 — 3 395.0 116.0 — 0.930 0.363
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