基于自动驾驶模块化车辆主辅功能分配的公交自适应调度方法

doi:10.13229/j.cnki.jdxbgxb.20250457

Abstract

Abstract:

In order to achieve flexible allocation of capacity resources， alleviate the waste of resources due to the imbalance between system supply and demand， and reduce the travel time loss due to vehicle stopping at stations and passenger transferring outside the vehicle， an adaptive scheduling method for bus based on AMV main-auxiliary function allocation was designed. An optimized scheduling model considering route coordination and station function division was established， with minimizing vehicle operating costs and passenger travel delays as the joint optimization objectives. A hierarchical adaptive heating particle swarm-simulated annealing algorithm was designed to solve the model. To verify the effectiveness of the model， an example test was carried out based on the bus operation data in Foshan City， and the results show that compared with the traditional fixed-capacity bus and station-responsive modular bus， the proposed model reduces the total cost of the system by about 35.62% and 6.54%， and the results of this research can help to improve the efficiency of bus operation and service quality.

Key words: engineering of communication and transportation system, AMV main-auxiliary function allocation, dispatch optimization, line coordination, hierarchical adaptive warming particle swarm-simulated annealing algorithm

CLC Number:

U491.5

Zhao-wei QU,Ming-yang WANG,Zhe WANG,Xian-min SONG,Yun-xiang ZHANG,Jing-cheng HUANG. Adaptive scheduling method for bus based on autonomous modular vehicles main⁃auxiliary function allocation[J].Journal of Jilin University(Engineering and Technology Edition), 2025, 55(9): 2946-2957.

Figures/Tables 17

Fig.1

Fig.2

Table 1

Notation for the model"

符号	定义
$L$	公交线路集合 ${L = 1,2, ?, l, ?, x, ?, y, ?, r}$ ， $l$ 为任意线路， $r$ 为线路总数
$J$	发车车次集合 ${J = 1,2, ?, j, ?, n l}$ ， $j$ 为任意车次， $n l$ 为线路 $l$ 在优化周期内总发车次数
$S$	公交站点集合 ${S = 1,2, ?, s, ?, K}$ ， $s$ 为任意站点， $K$ 为现网站点总数
$S ?$	拆合站点集合 $S ? ∈ S$ ${S ? = s ? 1, s ? 2, ?, s ? K ?}$ ， $K ?$ 为拆合站点总数
$S ˉ$	交织站点集合 $S ˉ ∈ S$ ， $K ˉ$ 为交织站点总数 ${S ˉ = s ˉ 1, s ˉ 2, ?, s ˉ a, ?, s ˉ b, ?, s ˉ K ˉ}$ ； $s ˉ + 1$ 为耦合站点， $s ˉ + 1 ∈ S ?$
$Y s$	站点 $s$ 与站点 $s + 1$ 间的距离
$H l j$	线路 $l$ 第 $j$ 辆车从始发站发车的时刻， $H l 1$ 为线路 $l$ 的首发时刻
$h l j$	线路 $l$ 发出的第 $j$ 与 $j - 1$ 辆车之间的发车间隔， $h l 1 = 0$
$T l s$	$s$ 与 $s + 1$ 两站点间的行程时间
$t l j, s$	线路 $l$ 第 $j$ 辆车到达站点 $s$ 的时间
$t D j, s$	站点 $s$ 产生的站点延误时间
$t s ˉ a, s ˉ b + 1$	车辆从交织站点 $s ˉ$ $a$ 行驶到耦合站点 $s ˉ b + 1$ 的行程时间， $a, b = 1,2, ?, K ˉ$
$ψ l, j s$	普通站点处辅助单元追赶主公交的延误时间
$E$	每名乘客的上下车时间，s/人
$τ$	辅助单元与前进单元组合的铰接延误
$W s ˉ$	由交织站点 $s ˉ$ 发出的公交驶过交织路口产生路口延误
$B s j$	站点 $s$ 发出的第 $j$ 辆车
$B s ˉ j, d$	交织站点 $s ˉ$ 发出的第 $j$ 辆公交车需要拆解到 $d$ 方向的车厢单元， $d ∈ L, δ, R$
$N l, j s$	站点 $s$ 发出的第 $j$ 辆车的车厢单元数目
$N l, j s ˉ, d$	交织站点 $s ˉ$ 发出的第 $j$ 辆公交车拆解到 $d$ 方向的车厢单元数目
$B l, j s ?, d o w n$	车辆到达拆合站点 $s ?$ 时解离的辅助单元数目
$B l, j s ?, u p$	车辆到达拆合站点 $s ?$ 时耦合的辅助单元数目
$B l, j s, c$	车辆经过普通站点 $s$ 时需要解离的辅助单元数目
$Q l, j s ˉ$	在交织站点 $s ˉ$ 的增补单元数目
$F l, j s$	车辆 $j - 1$ 和 $j$ 到达站点 $s$ 的时间间隔内乘客的累计到站人数
$A l, j s$	车辆 $j$ 到达站点 $s$ 时需要上车的乘客人数
$U l, j s$ 、 $V l, j s$	线路 $l$ 发出的第 $j$ 辆车在站点 $s$ 的实际上、下车人数
$O l, j s$	车辆 $j$ 驶离站点s的主公交承载的实际在车人数
$P j S i ˉ, d$	交织站点 $s ˉ i$ 发出的第 $j$ 辆车中换乘到方向d的乘客数
$D l, j s$	站点s未成功乘坐车辆 $j$ 产生的滞站等待人数
$v$	模块化公交车的平均行驶速度
$C$	一个车厢单元的载客容量
$N m a x$	模块化公交可悬挂的最大车厢单元数
$F N$	模块数为N的车厢单位运营成本，元/（km?节）

Table 1

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

Table 2

Operating parameters of experimental vehicle"

参数名称	参数取值
单元载客容量 $C$ /（人·节^-1）	6
最大悬挂单元 $N m a x$ /个	8
平均行驶速度 $v$ /（km·h^-1）	30
单位运营成本 $F N$ /［元·（千米节）^-1］	1.312 5
上车/下车时间 $E$ /（s·pax^-1）	3
制动启动时间 $η$ /s	5
单位时间成本 $A$ /（元·min^-1）	0.83
乘客步行速度 $v p$ /（km·h^-1）	4.5
换乘步行距离 $l 换$ /km	0.17

Table 2

Table 3

Coefficients of the solution algorithm"

参数含义	数值	参数含义	数值
初始种群规模	50	最大迭代次数	200
变异概率	0.05	交叉概率	0.5
加速因子 $g 1$ 、 $g 2$	1.4	惯性权重	0.7
降温系数	0.9	升温系数	1.1

Table 3

Fig.8

Fig.9

Fig.10

Fig.11

Fig.12

Fig.13

Fig.14

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Adaptive scheduling method for bus based on autonomous modular vehicles main⁃auxiliary function allocation

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