Abstract
In highways, lane markings are undoubtedly the most widely used landmarks for vehicle localization. However, they have a drawback in that they lack information on longitudinal position estimation and ego-lane identification. To alleviate this drawback, this paper presents a practical vehicle localization system for highways. The proposed system utilizes lane endpoints to enhance longitudinal position accuracy and road signs to improve the ego-lane identification accuracy. This system efficiently fuses the lane markings, lane endpoints and road signs along with a digital map and other low-cost sensors in a particle filter framework. Since it only uses low-cost sensors such as a monocular front-view camera, in-vehicle wheel speed and yaw rate sensors, as well as a low-end global positioning system (GPS), it is ready to mount on mass-produced vehicles. In the experiment, the proposed system was quantitatively evaluated using a dataset obtained while driving on 40 km stretch of highway, and outperformed previous approaches by showing a lateral position error of less than 0.12 m and a longitudinal position error of less than 0.25 m in terms of root mean square error (RMSE).
Highlights
In recent years, the technologies of advanced driver assistance systems (ADAS) and autonomous driving have developed rapidly
The measurement update step corrects the distribution of the vehicle state using a low-cost global positioning system (GPS), landmarks detected by the monocular frontview camera, and a digital map
The digital map was built by a mobile mapping system (MMS). 3D points were automatically acquired by the MMS and landmark locations were manually designated using the 3D points
Summary
The technologies of advanced driver assistance systems (ADAS) and autonomous driving have developed rapidly. Choi et al.: Low-Cost Precise Vehicle Localization Using Lane Endpoints and Road Signs for Highway Situations these drawbacks, methods utilizing other road surface markings such as stop lines, crosswalks, arrows, and letters have been suggested. Since those road surface markings frequently appear on urban roads, they are useful in urban situations. The proposed system has the following contributions: 1) It suggests a method that efficiently combines lane markings, lane endpoints, and road signs as landmarks for vehicle localization purposes in highway situations.
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