Vehicle Localization Using Radar Calibration with Disconnected GPS

2021 ◽  
Author(s):  
Jeong Sik Kim ◽  
Woo Young Choi ◽  
Yong Woo Jeong ◽  
Chung Choo Chung
Keyword(s):  
Vehicle Localization ◽  
Radar Calibration

High Precision Vehicle Localization based on Tightly-coupled Visual Odometry and Vector HD Map

2020 ◽  
Author(s):  
Tuopu Wen ◽  
Zhongyang Xiao ◽  
Benny Wijaya ◽  
Kun Jiang ◽  
Mengmeng Yang ◽  
...  
Keyword(s):  
High Precision ◽  
Visual Odometry ◽  
Vehicle Localization ◽  
Tightly Coupled

Fail Safe Process of Vehicle Localization for Reliability Improvement of LV3 Autonomous Driving

2021 ◽  
Vol 22 (2) ◽  
pp. 529-535
Author(s):  
Kyungil Seo ◽  
Jaehoon Lee ◽  
Je-young Lee ◽  
Kyongsu Yi
Keyword(s):  
Autonomous Driving ◽  
Vehicle Localization ◽  
Reliability Improvement ◽  
Fail Safe

Deterministic Optimality for Robust Vehicle Localization Using Visual Measurements

2021 ◽  
pp. 1-14
Author(s):  
Yanmei Jiao ◽  
Yue Wang ◽  
Xiaqing Ding ◽  
Minhang Wang ◽  
Rong Xiong
Keyword(s):  
Vehicle Localization ◽  
Visual Measurements

scholarly journals Online Local Path Planning on the Campus Environment for Autonomous Driving Considering Road Constraints and Multiple Obstacles

2021 ◽  
Vol 11 (9) ◽  
pp. 3909
Author(s):  
Changhyeon Park ◽  
Seok-Cheol Kee
Keyword(s):  
Path Planning ◽  
Driving Simulator ◽  
Autonomous Driving ◽  
Campus Environment ◽  
Vehicle Localization ◽  
Time Operation ◽  
National University ◽  
Planning Algorithm ◽  
Path Planning Algorithm ◽  
Multiple Obstacles

In this paper, an urban-based path planning algorithm that considered multiple obstacles and road constraints in a university campus environment with an autonomous micro electric vehicle (micro-EV) is studied. Typical path planning algorithms, such as A*, particle swarm optimization (PSO), and rapidly exploring random tree* (RRT*), take a single arrival point, resulting in a lane departure situation on the high curved roads. Further, these could not consider urban-constraints to set collision-free obstacles. These problems cause dangerous obstacle collisions. Additionally, for drive stability, real-time operation should be guaranteed. Therefore, an urban-based online path planning algorithm, which is robust in terms of a curved-path with multiple obstacles, is proposed. The algorithm is constructed using two methods, A* and an artificial potential field (APF). To validate and evaluate the performance in a campus environment, autonomous driving systems, such as vehicle localization, object recognition, vehicle control, are implemented in the micro-EV. Moreover, to confirm the algorithm stability in the complex campus environment, hazard scenarios that complex obstacles can cause are constructed. These are implemented in the form of a delivery service using an autonomous driving simulator, which mimics the Chungbuk National University (CBNU) campus.

Directional borehole radar calibration

2009 ◽  
Vol 67 (4) ◽  
pp. 352-360 ◽  
Author(s):  
O. Borchert ◽  
K. Behaimanot ◽  
A. Glasmachers
Keyword(s):  
Borehole Radar ◽  
Radar Calibration
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