Rear Vehicle Tracking on a Smart E-Scooter
- Authors
- Alai, Hamidreza; Jeon, Woongsun; Alexander, Lee; Rajamani, Rajesh
- Issue Date
- May-2023
- Publisher
- IEEE
- Citation
- 2023 AMERICAN CONTROL CONFERENCE, ACC, v.2023-May, pp 1735 - 1740
- Pages
- 6
- Journal Title
- 2023 AMERICAN CONTROL CONFERENCE, ACC
- Volume
- 2023-May
- Start Page
- 1735
- End Page
- 1740
- URI
- https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/70152
- DOI
- 10.23919/ACC55779.2023.10156621
- ISSN
- 0743-1619
2378-5861
- Abstract
- This paper develops an active sensing system for protection of an e-scooter from car-scooter collisions. The objective is to track the trajectories of cars behind the e-scooter and predict any real-time danger to the e-scooter. If the danger of being hit by a car is predicted, then a loud horn-like audio warning is sounded to alert the car driver to the presence of the scooter. A low-cost single-beam laser sensor is chosen for measuring the positions of cars behind the scooter. The sensor is mounted on a stepper motor and the region behind the scooter is scanned to detect vehicles. Once a vehicle is detected, its trajectory is tracked in real-time by using feedback control to focus the orientation of the laser sensor in real-time so as to make measurements of the right front corner of the vehicle. A nonlinear vehicle model and a nonlinear observer are used to estimate the trajectory variables of the tracked car. The estimated states are used in a receding horizon controller that controls the real-time position of the laser sensor to focus on the vehicle. The developed system is implemented on a Ninebot e-scooter platform. Simulation results with multiple vehicle maneuvers show that the closed-loop system is able to accurately track trajectories of rear vehicles that can pose a danger to the e-scooter.
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Collections - College of ICT Engineering > School of Electrical and Electronics Engineering > 1. Journal Articles
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