Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Li, Shenglin; Yoon, Hwan-Sik

doi:10.3390/s23073661

Vehicle Localization in 3D World Coordinates Using Single Camera at Traffic Intersection

Journal Article · Fri Mar 31 00:00:00 EDT 2023 · Sensors

DOI:https://doi.org/10.3390/s23073661· OSTI ID:1967510

Li, Shenglin;

Optimizing traffic control systems at traffic intersections can reduce the network-wide fuel consumption, as well as emissions of conventional fuel-powered vehicles. While traffic signals have been controlled based on predetermined schedules, various adaptive signal control systems have recently been developed using advanced sensors such as cameras, radars, and LiDARs. Among these sensors, cameras can provide a cost-effective way to determine the number, location, type, and speed of the vehicles for better-informed decision-making at traffic intersections. In this research, a new approach for accurately determining vehicle locations near traffic intersections using a single camera is presented. For that purpose, a well-known object detection algorithm called YOLO is used to determine vehicle locations in video images captured by a traffic camera. YOLO draws a bounding box around each detected vehicle, and the vehicle location in the image coordinates is converted to the world coordinates using camera calibration data. During this process, a significant error between the center of a vehicle’s bounding box and the real center of the vehicle in the world coordinates is generated due to the angled view of the vehicles by a camera installed on a traffic light pole. As a means of mitigating this vehicle localization error, two different types of regression models are trained and applied to the centers of the bounding boxes of the camera-detected vehicles. The accuracy of the proposed approach is validated using both static camera images and live-streamed traffic video. Based on the improved vehicle localization, it is expected that more accurate traffic signal control can be made to improve the overall network-wide energy efficiency and traffic flow at traffic intersections.

Sponsoring Organization:: USDOE

Grant/Contract Number:: EE0009210

OSTI ID:: 1967510

Alternate ID(s):: OSTI ID: 2418083

Journal Information:: Sensors, Journal Name: Sensors Journal Issue: 7 Vol. 23; ISSN SENSC9; ISSN 1424-8220

Publisher:: MDPI AGCopyright Statement

Country of Publication:: Switzerland

Language:: English

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