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Field studies to investigate safety distance violation with a low-cost observation system

Published: 01 September 2015 Publication History

Abstract

Statistics show that safety distance violation is a major cause of traffic accidents with reasons including high vol-ume of traffic, aggressive driving, inattention/distraction and, in particular, an underestimation of braking distances at certain speeds [2]. To sort out this important safety prob-lem, modern premium cars are equipped with adaptive cruise control (ACC) systems. Nevertheless, the majority of consumer cars is still not provided with such a system and a later retrofit is often impossible. In this work, we are picking up on that issue and introducing a low-cost warning system based on simple distance measurements. The implementation on a Smartphone and preliminary user stud-ies have shown that such a system is capable of real-time traffic observation and feedback to the driver (in the form of bimodal visual and auditory warnings). Study results further suggest that its application enhances the perception of minimal inter-car distances and, with it, improves road safety. Future work includes performance and accuracy improve-ments as well as a large scale field test.

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BT.com. 2014. Braking distances 'underestimated'.{online}. (August 2014). http://home.bt.com/lifestyle/motoring/motoringnews/braking-distances-underestimated-11363926929159.
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Yuan-Lin Chen, Kun-Yuan Shen, and Shun-Chung Wang. 2013. Forward collision warning system considering both time-to-collision and safety braking distance. In 8th IEEE Conference on Industrial Electronics and Applications (ICIEA). pp. 972--977.
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Rob Fergus, Pietro Perona, and Andrew Zisserman. 2003. Object Class Recognition by Unsupervised Scale-Invariant Learning. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, Vol. 2. pp. 264--271. http://www.robots.ox.ac.uk/~vgg
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Maryam Merrikhpour, Birsen Donmez, and Vittoria Battista. 2014. A field operational trial evaluating a feedback--reward system on speeding and tailgating behaviors. Transportation research part F: traffic psychology and behaviour 27 (2014), 56--68.
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Marcos Nieto, Jon Arròspide Laborda, and Luis Salgado. 2011. Road environment modeling using robust perspective analysis and recursive Bayesian segmentation. Machine Vision and Applications 22, 6 (2011), pp. 927--945.
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Ola Svenson, Gabriella Eriksson, Paul Slovic, C. K. Mertz, and Tina Fuglestad. 2012. Effects of main actor, outcome and affect on biased braking speed judgments. Judgment and Decision Making 7, 3 (May 2012), pp. 235--243.
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Bing-Fei Wu, Ying-Han Chen, Chung-Hsuan Yeh, and Yen-Feng Li. 2013. Reasoning-Based Framework for Driving Safety Monitoring Using Driving Event Recognition. IEEE Transactions on Intelligent Transportation Systems (T-ITS) 14, 3 (September 2013), pp. 1231--1241.

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  • (2022)A Survey on the combined use of IoT and Edge AI to improve Driver Monitoring systems2022 7th International Conference on Smart and Sustainable Technologies (SpliTech)10.23919/SpliTech55088.2022.9854220(1-6)Online publication date: 5-Jul-2022

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cover image ACM Other conferences
AutomotiveUI '15: Adjunct Proceedings of the 7th International Conference on Automotive User Interfaces and Interactive Vehicular Applications
September 2015
172 pages
ISBN:9781450338585
DOI:10.1145/2809730
Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 2015

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Author Tags

  1. advanced cruise control
  2. distance observations
  3. driving safety
  4. on-road study

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AutomotiveUI '15

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Overall Acceptance Rate 248 of 566 submissions, 44%

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  • (2022)A Survey on the combined use of IoT and Edge AI to improve Driver Monitoring systems2022 7th International Conference on Smart and Sustainable Technologies (SpliTech)10.23919/SpliTech55088.2022.9854220(1-6)Online publication date: 5-Jul-2022

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