Vehicle Localization in GPS-Denied Scenarios Using Arc-Length-Based Map Matching
Abstract
Automated driving systems face challenges in GPS-denied situations. To address this issue, kinematic dead reckoning is implemented using measurements from the steering angle, steering rate, yaw rate, and wheel speed sensors onboard the vehicle. However, dead reckoning methods suffer from drift. This paper provides an arc-length based map matching method that uses a digital 2D map of the scenario in order to correct drift in the dead reckoning estimate. The kinematic model’s prediction is used to introduce a temporal notion to the spatial information available in the map data. Results show reliable improvement in drift for all GPS-denied scenarios tested in this study. This innovative approach ensures that automated vehicles can maintain continuous and reliable navigation, significantly enhancing their safety and operational reliability in environments where GPS signals are compromised or unavailable.
Fields of Study & Subjects
Autonomous Vehicle Technology and Safety
Automated Road and Building Extraction
Video Surveillance and Tracking Methods
Publication details
- Journal / source
- IEEE Transactions on Intelligent Transportation Systems
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 27
- Issue
- 4
- Pages
- 4924–4929
- Publication date
- 12 January 2026
- Language
- EN