Traffic State Detection Based on Equipped Vehicle Data

被引：0

作者：

Shi, Yun-feng ^{[1
]}

Yang, Li-cai ^{[1
]}

Hao, Shen-xue ^{[1
]}

机构：

[1] Shandong Univ, Dept Control Sci & Engn, Jinan, Shandong, Peoples R China

来源：

2016 INTERNATIONAL CONFERENCE ON ELECTRICAL ENGINEERING AND AUTOMATION (ICEEA 2016) | 2016年

关键词：

Traffic state; Smart-phone; KHDD; Smart vehicle; Traffic congestion;

D O I：

暂无

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

To detect traffic state using Smart-phone equipped vehicles (for short, equipped vehicles) data is popular in recent years. Calculating the average speed of all equipped vehicles simply is no longer reasonable without considering random distribution of equipped vehicles. In this paper, a new method of detecting traffic state based on equipped vehicle data was presented. Inspired by information entropy theory, the key homogeneous distribution degree (KHDD) can be obtained, which contributes to correct the detection error caused by the random distribution of equipped vehicles. In simulations, the results show the validity of the proposed method to detect traffic state under the different KHDD.

引用

页数：6

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