Development and Demonstration of a Cost-Effective In-Vehicle Lane Departure and Advanced Curve Speed Warning System

Hayee, M. Imran; Hussain, Shah; Faizan, Muhammad · 2018 · ROSA P / Minnesota. Dept. of Transportation. Research Services & Library

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Summary

This research addresses the need for cost-effective Advanced Driver-Assistance Systems (ADAS) to reduce crashes caused by unintentional lane departures and excessive speed on curves. Existing Lane Departure Warning Systems (LDWS) often rely on camera or optical sensors, which suffer from performance degradation in harsh weather or with irregular lane markings. Alternatively, GPS-based systems requiring lane-level digital maps are complex and expensive. The study proposes a novel method using a standard GPS receiver and road-level digital maps to detect lane drift and provide advance curve warnings, leveraging the high relative accuracy of GPS despite its lower absolute position accuracy. The methodology involves two primary algorithms. The LDWS algorithm compares the vehicle’s instantaneous heading, derived from consecutive GPS coordinates, against a reference road direction extracted from standard digital mapping databases. It calculates the instantaneous lateral distance and accumulates this value over time; if the accumulated lateral distance exceeds a specific threshold, a lane departure is detected. The system distinguishes intentional lane changes by monitoring for saturation in lateral distance. The Advance Curve Warning System (ACWS) utilizes the same reference road direction to estimate road curvature and determine an advisory speed. It calculates a "safe distance" based on the vehicle’s current speed, the advisory speed, and a safe deceleration rate including driver reaction time. If the vehicle exceeds the advisory speed, the system issues a warning at this calculated safe distance. The algorithms were implemented on Dedicated Short-Range Communication (DSRC) devices and evaluated through extensive field tests on straight and curved road segments. Field test results demonstrated that the proposed LDWS detected true lane departures with nearly 100% accuracy on both straight and curved sections, with no missed detections. However, the system generated false alarms approximately 10% of the time, primarily on sharp curved sections where the vehicle remained in its lane. The ACWS successfully issued advance curve warnings with advisory speeds at safe distances ahead of the curves. The authors noted that modifications to the lane departure algorithm showed potential to reduce the frequency of false alarms on curves. The significance of this work lies in providing a robust, low-cost alternative to camera-based and high-resolution map-dependent ADAS systems. By utilizing widely available road-level map data and standard GPS hardware, the system offers a practical solution for reducing crashes associated with lane drifting and curve-related accidents. The findings suggest that relative GPS accuracy is sufficient for lateral drift detection, enabling the deployment of effective safety systems without the need for expensive infrastructure or complex sensor fusion.

Key finding

The proposed GPS-based system detected true lane departures with nearly 100% accuracy but produced false alarms approximately 10% of the time, mostly on sharp curves.

Methodology

field_study

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via bulk_ingest_rosap on 2026-05-23 (6 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

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• lane positioning