Abstract
Lane departure warning system (LDWS) has significant potential to reduce crashes on roads. Most existing commercial LDWSs use image processing techniques with or without Global Positioning System (GPS) technology and/or high-resolution digital maps to detect unintentional lane departures. However, the performance of such systems is compromised in unfavourable weather or road conditions e.g., fog, snow, or irregular road markings. Previously, the authors proposed and developed an LDWS using a standard GPS receiver without any high-resolution digital maps. The previously developed LDWS relies on a road reference heading (RRH) of a given road extracted from an open-source low- resolution mapping database to detect an unintentional lane departure. This method can detect true lane departures accurately but occasionally gives false alarms i.e., it issues lane departure warnings even if a vehicle is within its lane. The false alarms occur
due to the inaccuracy of RRH originated from inherent lateral error in open-source low-resolution maps. To overcome this problem, now authors propose a novel algorithm to generate an accurate RRH for a given road using a vehicle’s past trajectories on that road. The newly proposed algorithm to generate an accurate RRH
for any given road has been integrated with the previously developed LDWS and extensively evaluated in the field to detect unintentional lane departures. The field test results show that the newly developed RRH generation algorithm significantly improves the performance of the previously developed LDWS by accurately detecting all true lane departures while practically reducing the frequency of false alarms to zero.
due to the inaccuracy of RRH originated from inherent lateral error in open-source low-resolution maps. To overcome this problem, now authors propose a novel algorithm to generate an accurate RRH for a given road using a vehicle’s past trajectories on that road. The newly proposed algorithm to generate an accurate RRH
for any given road has been integrated with the previously developed LDWS and extensively evaluated in the field to detect unintentional lane departures. The field test results show that the newly developed RRH generation algorithm significantly improves the performance of the previously developed LDWS by accurately detecting all true lane departures while practically reducing the frequency of false alarms to zero.
| Original language | English (US) |
|---|---|
| Title of host publication | Proceedings of the 7th International Conference on Vehicle Technology and Intelligent Transport Systems (VEHITS 2021) |
| Editors | Karsten Berns, Markus Helfert, Oleg Gusikhin |
| Publisher | SciTePress |
| Pages | 584-593 |
| Number of pages | 10 |
| ISBN (Electronic) | 9789897585135 |
| ISBN (Print) | 978-989-758-513-5 |
| DOIs | |
| State | Published - 2021 |
| Event | 7th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2021 - Virtual, Online Duration: Apr 28 2021 → Apr 30 2021 |
Publication series
| Name | International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS - Proceedings |
|---|---|
| Volume | 2021-April |
| ISSN (Electronic) | 2184-495X |
Conference
| Conference | 7th International Conference on Vehicle Technology and Intelligent Transport Systems, VEHITS 2021 |
|---|---|
| City | Virtual, Online |
| Period | 4/28/21 → 4/30/21 |
Bibliographical note
Publisher Copyright:Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved.
Keywords
- GPS Trajectory
- Lane Departure Warning System
- Road Reference Heading