基于拥堵预测的路径规划算法研究.pdfVIP

第

53

卷第

3

期电子科技大学学报

Vol.

53No.

3

2024年5月Journal

of

University

of

Electronic

Science

and

Technology

of

China

May

2024

基于拥堵预测的路径规划算法研究

*

杨海芬，张

辉，蒋贤皓，林水生

（电子科技大学

信息与通信工程学院，成都

611731）

摘要随着城市出行车辆数的急剧增加，城市交通路网拥堵日益严重，因此研究路网通行效率最大化、个人通行时间和

路径最优化具有重要意义。目前智慧交通大多采用周期性监测拥堵并重新规划路径的方法，这类方法得到的最优路径往往导

致下次重规划的绕行，不利于全局的最优化。该文提出一种基于拥堵预测的路径规划算法，通过分析大量历史交通流数据的

时空相关性预测未来时刻的交通流参数，再通过熵权法和模糊综合判定得出拥堵状态分级，之后综合考虑当前时刻和未来时

刻拥堵状况从而规划出更加合理的路径。仿真结果表明，与基于重规划的动态路径规划算法相比，该算法在行驶时间上减

少5.35%，在行驶距离上减少11.72%。

关键词智慧交通；拥堵预测；路径规划；时空相关；模糊判定

中图分类号TN919

文献标志码A

DOI10.12178/1001-0548.2022333

Research

on

Route

Planning

Based

on

Congestion

Prediction

*

YANG

Haifen,

ZHANG

Hui,

JIANG

Xianhao,

and

LIN

Shuisheng

(School

of

Information

and

Communication

Engineering,

University

of

Electronic

Science

and

Technology

of

China,

Chengdu

611731,

China)

AbstractWith

the

rapid

increase

of

vehicles,

the

road

network

has

become

increasingly

congested.

It

is

of

great

significance

to

study

the

maximization

of

road

network

traffic

efficiency,

personal

traffic

time

and

path

optimization.

The

existing

methods

periodically

monitor

congestion

and

replan

paths.

The

previous

path

obtained

by

this

kind

of

algorithm

often

leads

to

the

detour

of

the

next

replanning,

which

is

not

conducive

to

the

global

optimization.

This

paper

proposes

a

path

planning

algorithm

based

on

congestion

prediction.

By

analyzing

the

temporal

and

spatial

correlation

in

a

large

number

of

historical

traffic

flow

data,

the

traffic

flow

parameters

at

the

future

ti