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基于ETC大数据的智能高速公路模拟和验证系统的研究和设计

Fumin Zou^1,2, Nan Li^1,2, Feng Guo^1,2

¹Renewable Energy Technology Research Institute, Fujian University of Technology, Ningde 352100, China.

|November 29, 2023

概括

本研究引入了电子收费 (ETC) 环境的新模拟系统,改进了实时流量计算和优化. 该系统利用ETC数据的时空特征来加强交通控制和调度.

科学领域:

运输工程运输工程
计算机科学计算机科学
数据科学数据科学数据科学

背景情况:

电子收费系统 (ETC) 产生了大量的车辆轨迹数据,具有重要的应用潜力.
现有的交通模拟系统经常忽视实时道路状况,阻碍了定量分析和优化.
缺少用于ETC环境的专用模拟系统,特别是用于实时计算和整体优化.

研究的目的:

为当前ETC环境量身定制的模拟系统框架设计.
为应对ETC系统内实时流量计算和整体优化的挑战.
满足基于ETC的交通模拟相关研究的要求.

主要方法:

基于省级高速公路网络的拓结构,开发了一个模拟系统框架.
来自ETC交易数据 (Edata) 的时空特征的特征提取算法已建立,以生成模拟数据.
为快速公路交通流量控制中的决策指标提出了交通控制战略算法.
一个改进的多任务调度算法 (ETC_MTS) 被优化为实时并行.

主要成果:

开发的系统有效地使用ETC交易数据的时空特征生成模拟数据.
交通控制战略算法为交通流管理提供了有价值的决策指标.
与传统的调度算法 (SJFS,Priority,FCFS,RR) 相比,优化的ETC_MTS算法显示出更高的执行性能.

结论:

拟议的模拟系统框架适合ETC环境,可实现实时流量计算和优化.
特性提取算法对于从ETC记录中生成现实的模拟数据至关重要.
优化的ETC_MTS算法为高速公路模拟中的并行多任务提供了显著的性能改进.

关键词:

在ETC系统中,ETC系统的功能提取功能提取模拟框架的模拟框架多任务调度多任务调度时空特征是一个时空特征.交通流量控制器交通流量控制器

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