Real-Time Lane Detection and Rear-End Collision Warning System on a Mobile Computing Platform

Samuel Jia Wei Tang; Kok Yew Ng; Boon How Khoo; Jussi Parkkinen

doi:10.1109/COMPSAC.2015.171

Real-Time Lane Detection and Rear-End Collision Warning System on a Mobile Computing Platform

Samuel Jia Wei Tang, Kok Yew Ng, Boon How Khoo, Jussi Parkkinen

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

11 Citations (Scopus)

Abstract

Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rearend collision warning system for drivers on the road. The Android-based application uses image-processing algorithms coupled with the monoscopic camera on the smartphone as the main sensor to perform lane and vehicle detections. The novelty of this work lies in the use of the monocular vision of the camera to estimate the distance with the vehicle up ahead. The system is able to distinguish unintentional lane departure and if the driver is traveling too close to the vehicle ahead. An acoustic warning will notify the driver of a potential accident.

Original language	English
Title of host publication	Unknown Host Publication
Publisher	IEEE
Pages	563-568
Number of pages	698
ISBN (Electronic)	978-1-4673-6564-2
DOIs	https://doi.org/10.1109/COMPSAC.2015.171
Publication status	Published - 24 Sep 2015
Event	2015 IEEE 39th Annual International Computers, Software & Applications Conference - Duration: 17 Apr 2015 → …

Conference

Conference	2015 IEEE 39th Annual International Computers, Software & Applications Conference
Period	17/04/15 → …

Keywords

mobile application
lane detection
vehicle detection
distance estimation
real-time

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10.1109/COMPSAC.2015.171

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Profiles

Mark Ng

mark.ng@ulster.ac.uk

School of Engineering - Lecturer in Mechatronics Engineering and Control
Faculty Of Computing, Eng. & Built Env. - Lecturer

Person: Academic

Cite this

Tang, S. J. W., Ng, K. Y., Khoo, B. H., & Parkkinen, J. (2015). Real-Time Lane Detection and Rear-End Collision Warning System on a Mobile Computing Platform. In Unknown Host Publication (pp. 563-568). IEEE. https://doi.org/10.1109/COMPSAC.2015.171

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title = "Real-Time Lane Detection and Rear-End Collision Warning System on a Mobile Computing Platform",

abstract = "Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rearend collision warning system for drivers on the road. The Android-based application uses image-processing algorithms coupled with the monoscopic camera on the smartphone as the main sensor to perform lane and vehicle detections. The novelty of this work lies in the use of the monocular vision of the camera to estimate the distance with the vehicle up ahead. The system is able to distinguish unintentional lane departure and if the driver is traveling too close to the vehicle ahead. An acoustic warning will notify the driver of a potential accident.",

keywords = "mobile application, lane detection, vehicle detection, distance estimation, real-time",

author = "Tang, {Samuel Jia Wei} and Ng, {Kok Yew} and Khoo, {Boon How} and Jussi Parkkinen",

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doi = "10.1109/COMPSAC.2015.171",

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AB - Accident prevention systems have recently been a part of many modern cars to reduce injuries and casualties on the road. However, the high cost of components and equipment have limited such safety systems to higher-end and luxury vehicles. This paper proposes an economical method of using a smartphone application for real-time lane detection and rearend collision warning system for drivers on the road. The Android-based application uses image-processing algorithms coupled with the monoscopic camera on the smartphone as the main sensor to perform lane and vehicle detections. The novelty of this work lies in the use of the monocular vision of the camera to estimate the distance with the vehicle up ahead. The system is able to distinguish unintentional lane departure and if the driver is traveling too close to the vehicle ahead. An acoustic warning will notify the driver of a potential accident.

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