Abstract
Purpose Precise vehicle localization is a basic and critical technique for various intelligent transportation system (ITS) applications. It also needs to adapt to the complex road environments in real-time. The global positioning system and the strap-down inertial navigation system are two common techniques in the field of vehicle localization. However, the localization accuracy, reliability and real-time performance of these two techniques can not satisfy the requirement of some critical ITS applications such as collision avoiding, vision enhancement and automatic parking. Aiming at the problems above, this paper aims to propose a precise vehicle ego-localization method based on image matching. Design/methodology/approach This study included three steps, Step 1, extraction of feature points. After getting the image, the local features in the pavement images were extracted using an improved speeded up robust features algorithm. Step 2, eliminate mismatch points. Using a random sample consensus algorithm to eliminate mismatched points of road image and make match point pairs more robust. Step 3, matching of feature points and trajectory generation. Findings Through the matching and validation of the extracted local feature points, the relative translation and rotation offsets between two consecutive pavement images were calculated, eventually, the trajectory of the vehicle was generated. Originality/value The experimental results show that the studied algorithm has an accuracy at decimeter-level and it fully meets the demand of the lane-level positioning in some critical ITS applications.
Highlights
Precise vehicle localization is one of the basic and urgent problems for most of the intelligent transportation system (ITS) applications
The organization of this paper is as follows: in Section 2, we provide a simple literature review of the inertial navigation system (INS) assisted by the global positioning system (GPS) and the INS assisted by the vision
In addition to the camera shown in the figure, the car was installed a differential GPS (DGPS) system, and the DGPS system has a positioning accuracy of 2 m
Summary
Precise vehicle localization is one of the basic and urgent problems for most of the intelligent transportation system (ITS) applications. Many parameters associated with the working state of vehicles, such as vehicle position, velocity, acceleration and trajectory, can be obtained. These parameters are closely related to many security-themed applications in ITS. The literature (Boukerche et al, 2008) lists over 10 applications closely related to the localization in ITS, which include routing navigation, data dissemination, map localization, adapted cruise control, cooperative intersection safety, blind crossing, platooning, vehicle collision warning, vision enhancement and automatic parking. It points out that some applications such as vehicle collision warning, vision enhancement and automatic parking need sub-meter resolution. If precise localization information of all vehicles can be obtained in real-time, it will bring about revolutionary changes in future traffic
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