scholarly journals Performance Improvement of Collision Warning System on Curved Road Based on Intervehicle Communication

2015 ◽  
Vol 2015 ◽  
pp. 1-7 ◽  
Author(s):  
Hong Cho ◽  
Byeong-woo Kim
Keyword(s):  
Warning System ◽  
Relative Distance ◽  
Small Radius ◽  
Radius Of Curvature ◽  
Collision Warning ◽  
The Road ◽  
Preceding Vehicle ◽  
Curved Road ◽  
Forward Collision Warning ◽  
Intervehicle Communication

The vehicle on-board sensor based Advanced Driver Assistant System possesses limitations on a small road with a small radius of curvature because of the sensor’s inability to operate in nondetectable domains. This study suggests an Improved Cooperative Collision Warning System (ICCWS) that considers the curvature of the road and is based on intervehicle communication. To predict the radius of curvature of the road, the Arc Relative Distance (ARD), the real relative distance to a preceding vehicle on a curved road has been used. The risk of collision with the preceding vehicle is decided by calculating an index of the risk of collision on a curved road using the computed ARD. The effects of ICCWS, proposed through this simulation, have been reviewed, and the improvement in performance in following a preceding vehicle has been analyzed quantitatively via comparative analysis with the conventional forward collision warning system. Accordingly, if the estimating algorithm for curvature developed in this study is applied to a real system, the performance of following a preceding vehicle can be improved without any specific changes to the system.

scholarly journals Empirical Analysis of Safe Distance Calculation by the Stereoscopic Capturing and Processing of Images Through the Tailigator System

Sensors ◽  
2019 ◽  
Vol 19 (22) ◽  
pp. 5044
Author(s):  
Gerd Christian Krizek ◽  
Rene Hausleitner ◽  
Laura Böhme ◽  
Cristina Olaverri-Monreal
Keyword(s):  
Low Cost ◽  
Field Tests ◽  
Warning System ◽  
Collision Warning ◽  
The Road ◽  
Cost System ◽  
Straight Line ◽  
Real Value ◽  
On The Road ◽  
Forward Collision Warning

Driver disregard for the minimum safety distance increases the probability of rear-end collisions. In order to contribute to active safety on the road, we propose in this work a low-cost Forward Collision Warning system that captures and processes images. Using cameras located in the rear section of a leading vehicle, this system serves the purpose of discouraging tailgating behavior from the vehicle driving behind. We perform in this paper the pertinent field tests to assess system performance, focusing on the calculated distance from the processing of images and the error margins in a straight line, as well as in a curve. Based on the evaluation results, the current version of the Tailigator can be used at speeds up to 50 km per hour without any restrictions. The measurements showed similar characteristics both on the straight line and in the curve. At close distances, between 3 and 5 m, the values deviated from the real value. At average distances, around 10 to 15 m, the Tailigator achieved the best results. From distances higher than 20 m, the deviations increased steadily with the distance. We contribute to the state of the art with an innovative low-cost system to identify tailgating behavior and raise awareness, which works independently of the rear vehicle’s communication capabilities or equipment.

A forward collision warning system based on self-learning algorithm of driver characteristics

2020 ◽  
Vol 38 (2) ◽  
pp. 1519-1530 ◽  
Author(s):  
Chang Wang ◽  
Qinyu Sun ◽  
Zhen Li ◽  
Hongjia Zhang ◽  
Rui Fu
Keyword(s):  
Learning Algorithm ◽  
Warning System ◽  
Collision Warning ◽  
Forward Collision Warning ◽  
Self Learning

Off-Road Glance Behavior, Response Time to a Forward Collision Hazard, and Engagement Strategy Effects in Automated Driving

2017 ◽  
Vol 61 (1) ◽  
pp. 1909-1913 ◽  
Author(s):  
Mike Blommer ◽  
Reates Curry ◽  
Dev Kochhar ◽  
Rads Swaminathan ◽  
Walter Talamonti ◽  
...  
Keyword(s):  
Response Time ◽  
Automated Driving ◽  
Secondary Tasks ◽  
Collision Warning ◽  
Driving Mode ◽  
Driver Response ◽  
The Road ◽  
Behavior Response ◽  
The Face ◽  
Forward Collision Warning

Blommer et al. (2015) reported on a simulator study that investigated a driver engagement (DE) strategy designed to keep the driver-in-the-loop during automated driving in the face of two different types of secondary tasks. The method, first reported by Carsten et al. (2012), involved driving in fully automated driving mode for 6 minutes followed by 1 minute of manual driving, after which this fixed schedule was repeated several times throughout the drive. This scheduled strategy was compared to a reference condition in which different participants experienced continuous automated driving without interruptions. For each condition, some participants watched a video and others listened to the radio. All drives ended in automated driving mode with a surprise forward collision (FC) hazard to which the participant had to manually intervene. Compared to video watchers, radio listeners responded faster, looked to the road scene more, and they were more often looking forward at FC event onset. The DE strategy had no effect on radio listeners. In contrast, video watchers responded to the hazard more quickly with the scheduled strategy than without it. However, there was no reliable statistical difference between DE conditions in percent-eye-glance-time looking to the forward road scene during automated driving or in the number of drivers looking forward at FC event onset. This paper presents additional analyses of off-road eye glance behavior and finds no relationship between how long people were looking away prior to receiving a Forward Collision Warning (FCW) and driver response time (RT). About 95% of all video watching drivers glanced back to the road within 20 sec regardless of the automated driving condition. Approximately 85% of glances away from the road in the scheduled mitigation condition were 7 sec or less.

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