Traffic State Detection Based on Equipped Vehicle Data

Abstract

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.