GCD‑L: A Novel Method for Geometric Change Detection in HD Maps Using Low‑Cost Sensors

作     者：Peng Sun Yunpeng Wang Peng He Xinxin Pei Mengmeng Yang Kun Jiang Diange Yang 

作者机构：Autonomous Driving TechnologyBaidu IncBeijingChina School of Vehicle and MobilityTsinghua UniversityLee Shau Kee Building No A639Beijing 100084China 

出 版 物：《Automotive Innovation》 (汽车创新工程（英文）)

年 卷 期：2022年第5卷第3期

页      面：324-332页

核心收录：

学科分类：0808[工学-电气工程] 07[理学] 0802[工学-机械工程] 0701[理学-数学] 0823[工学-交通运输工程] 

基　　金：sponsored by the National Natural Science Foundation of China-52102426,U1864203 and 61773234 the Project Funded by China Postdoctoral Science Foundation-2019M660622. 

主　　题：Autonomous driving HD Maps Lane line Change detection 

摘      要：Updating high-definition maps is imperative for the safety of autonomous vehicles.However,positional changes in lane lines are hard to be detected in a timely manner due to a limited number of expensive surveying vehicles over a large geo-graphic area.Herein,a novel method is proposed to detect the geometric changes of lane lines using low-cost sensors,such as consumer-grade global navigation satellite system(GNSS)hardware receivers and cameras.The proposed framework geometric change detection using low-cost sensors(GCD-L)and algorithm change segment compare(CSC),which are based on the lane width between the curb line and the adjacent leftmost lane line,can perceive the positional changes of the leftmost lane line on highway and expressway roads.The effectiveness of the proposed method is verified by evaluating it on a real-world typical urban ring road dataset.The experimental results show that 71%detected change segments are valid with only two round crowdsourced maps.