Abstract

Car ownership in China reached 194 million vehicles at the end of 2016. The traffic congestion index (TCI) exceeds 2.0 during rush hour in some cities. Inefficient processing for minor traffic accidents is considered to be one of the leading causes for road traffic jams. Meanwhile, the process after an accident is quite troublesome. The main reason is that it is almost always impossible to get the complete chain of evidence when the accident happens. Accordingly, a police and insurance joint management system is developed which is based on high precision BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning to process traffic accidents. First of all, an intelligent vehicle rearview mirror terminal is developed. The terminal applies a commonly used consumer electronic device with single frequency navigation. Based on the high precision BDS/GPS positioning algorithm, its accuracy can reach sub-meter level in the urban areas. More specifically, a kernel driver is built to realize the high precision positioning algorithm in an Android HAL layer. Thus the third-party application developers can call the general location Application Programming Interface (API) of the original standard Global Navigation Satellite System (GNSS) to get high precision positioning results. Therefore, the terminal can provide lane level positioning service for car users. Next, a remote traffic accident processing platform is built to provide big data analysis and management. According to the big data analysis of information collected by BDS high precision intelligent sense service, vehicle behaviors can be obtained. The platform can also automatically match and screen the data that uploads after an accident to achieve accurate reproduction of the scene. Thus, it helps traffic police and insurance personnel to complete remote responsibility identification and survey for the accident. Thirdly, a rapid processing flow is established in this article to meet the requirements to quickly handle traffic accidents. The traffic police can remotely identify accident responsibility and the insurance personnel can remotely survey an accident. Moreover, the police and insurance joint management system has been carried out in Wuhan, Central China’s Hubei Province, and Wuxi, Eastern China’s Jiangsu Province. In a word, a system is developed to obtain and analyze multisource data including precise positioning and visual information, and a solution is proposed for efficient processing of traffic accidents.

Highlights

  • The development of modern traffic has accelerated the development of the automobile market, but it causes frequent traffic accidents

  • This article focuses on designing a rapid traffic accident disposal scheme based on high precision positioning, which is further developed from our previous work [6]

  • The inputs are road map data and BeiDou Navigation Satellite System (BDS)/Global Positioning System (GPS) positioning track data of the vehicle; the output is the lane information corresponding to each BDS/GPS point as well as the abnormal characteristics reflected by a part of vehicle track data (e.g., “lane changing”)

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Summary

Introduction

The development of modern traffic has accelerated the development of the automobile market, but it causes frequent traffic accidents. The terminal uses a high precision BDS/GPS positioning algorithm and integrated navigation algorithm It supports both PPP and RTK technologies, which mainly apply single frequency and real-time PPP under the requirements of IoV products. The four sets of data form a complete evidence chain, by which the police can analyze the scene on the remote platform and accurately simulate the accident process on a high precision map. This helps the traffic police judge fault and liability remotely and improves efficiency of handling urban minor traffic accidents. Two typical actual traffic accidents among more than 30 have been selected as cases and will be explained in great detail

Related Work
Framework
Data bus layer
Vehicle
Kernel Positioning Driver
Effect
Actual Accident Cases
Findings
Conclusions
Full Text
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