Identifying the effects of driving parameters on stopping distance to reduce accident risks

Authors

DOI:

https://doi.org/10.15587/2706-5448.2024.295438

Keywords:

road accidents, stopping distance, driving simulator, experimental design, vehicle braking system

Abstract

The object of the research is the most important factors causing road accidents. This paper aimed to study the effects of this factors and their interactions on the stopping distance function. Understanding this function through simulation and comparing the results with mathematical models and experimental tests will help to reduce the number of road accidents. A large part of road accidents is linked to non-compliance with regulatory speed associated with vehicle braking system (grip, road and tires) and weather conditions. A speed measurement campaign on peri-urban roads was carried out to study driving behavior and compliance with speed limits in several Algerian cities. An experimental modelling of speed, anti-lock system, weather, grip and their interaction effects on the stopping distance of a vehicle using the experimental design method, combined with driving simulator tests was been conducted. The developments of experimental design with speed variation ranges (70 and 130 km/h) were necessary to study the influence of the various driving parameters on stopping distance. The mathematical model developed has been validated by the results obtained on the simulator. The experimental design method and simulator results were used to identify and define the important parameters that influence the braking distance. The results show that the stopping distance (SD) is mainly influenced by the vehicle speed (S), the weather conditions (M), and their interaction. The increase due to speed leads to an increase in the stopping distance with an estimated effect of 54.30 m. When the speed varies between its lower experimental level (70 km/h) and its higher level (130 km/h), it is estimated that the stopping distance will increase by 54.30 m. The analysis of the road speed measurement campaign, 55 % of road users do not obey the speed limits. The results obtained in this study can be applied to other countries, only the parameters need to be adjusted.

Author Biographies

Nesrine Boulmedais, Mentouri Brothers University Constantine 1

Postgraduate Student

Laboratory of Transports and Environment Engineering

Lyes Bidi, Mentouri Brothers University Constantine 1

PhD

Institute of Applied Sciences and Techniques

Rachid Chaib, Mentouri Brothers University Constantine 1

Professor

Department of Transportation Engineering

Laboratory of Transports and Environment Engineering

Salim Boukebbab, Mentouri Brothers University Constantine 1

Professor

Department of Transport Engineering

Laboratory of Transports and Environment Engineering

Mohamed Salah Boulahlib, Mentouri Brothers University Constantine 1

Professor

Department of Transport Engineering

Laboratory of Transports and Environment Engineering

References

  1. Traumatismes dus aux accidents de la circulation (2023). World Health Organization. Available at: https://www.who.int/fr/news-room/fact-sheets/detail/road-traffic-injuries
  2. Global status report on road safety 2015 (2015). World Health Organization. Available at: https://www.afro.who.int/publications/global-status-report-road-safety-2015#:~:text=The%20Global%20status%20report%20on,rates%20in%20low%2Dincome%20countries
  3. Global Status Report on Road Safety (2017). World Health Organization. Available at: https://www.afro.who.int/sites/default/files/2017-06/vid_global_status_report_en.pdf
  4. Accidents-Bilan 2020: le moins tragique depuis trois décennies (2021). Algérie press service. Available at: https://www.aps.dz/societe/117350-accidents-bilan-2020-le-moins-tragique-depuis-trois-decennies
  5. D’Onghia, F., Delhomme, P., Dubois, N. (2008). How to Convince Drivers to Respect Speed Limits? Effects of Framing and the Presence of an Image on Attitudes about Speeding and the Intent to Respect Speed Limits. Bulletin de psychologie, 498 (6), 561–576. doi: https://doi.org/10.3917/bupsy.498.0561
  6. Podoprigora, N., Dobromirov, V., Pushkarev, A., Lozhkin, V. (2017). Methods of Assessing the Influence of Operational Factors on Brake System Efficiency in Investigating Traffic Accidents. Transportation Research Procedia, 20, 516–522. doi: https://doi.org/10.1016/j.trpro.2017.01.084
  7. Statistical report n°: 830, national car park at 31/12/2017 (2017). National Statistics Office, Algiers.
  8. Boughédaoui, M., Chikhi, S., Driassa, N., Kerbachi, R., Joumard, R. (2009). Caractérisation du parc de véhicule algérien et son usage. Environment and Transport in different contexts/Environnement et Transports dans des contextes différents, 201–208.
  9. Karwowska, E., Simiński, P. (2015). Analysis of the influence of perception time on stopping distance from the angle of psychophysical factors. Archiwum Motoryzacji, 70 (4), 59–74.
  10. Gürbüz, H., Buyruk, S. (2019). Improvement of safe stopping distance and accident risk coefficient based on active driver sight field on real road conditions. IET Intelligent Transport Systems, 13 (12), 1843–1850. doi: https://doi.org/10.1049/iet-its.2019.0322
  11. Cho, J. R., Choi, J. H., Yoo, W. S., Kim, G. J., Woo, J. S. (2006). Estimation of dry road braking distance considering frictional energy of patterned tires. Finite Elements in Analysis and Design, 42 (14-15), 1248–1257. doi: https://doi.org/10.1016/j.finel.2006.06.005
  12. Koylu, H., Tural, E. (2021). Experimental study on braking and stability performance during low speed braking with ABS under critical road conditions. Engineering Science and Technology, an International Journal, 24 (5), 1224–1238. doi: https://doi.org/10.1016/j.jestch.2021.02.001
  13. Toma, M., Andreescu, C., Stan, C. (2018). Influence of tire inflation pressure on the results of diagnosing brakes and suspension. Procedia Manufacturing, 22, 121–128. doi: https://doi.org/10.1016/j.promfg.2018.03.019
  14. Carcaterra, A., Roveri, N. (2013). Tire grip identification based on strain information: Theory and simulations. Mechanical Systems and Signal Processing, 41 (1-2), 564–580. doi: https://doi.org/10.1016/j.ymssp.2013.06.002
  15. Imprialou, M.-I. M., Quddus, M., Pitfield, D. E., Lord, D. (2016). Re-visiting crash–speed relationships: A new perspective in crash modelling. Accident Analysis and Prevention, 86, 173–185. doi: https://doi.org/10.1016/j.aap.2015.10.001
  16. Choudhary, P., Imprialou, M., Velaga, N. R., Choudhary, A. (2018). Impacts of speed variations on freeway crashes by severity and vehicle type. Accident Analysis and Prevention, 121, 213–222. doi: https://doi.org/10.1016/j.aap.2018.09.015
  17. Cheng, Z., Lu, J., Li, Y. (2018). Freeway crash risks evaluation by variable speed limit strategy using real-world traffic flow data. Accident Analysis and Prevention, 119, 176–187. doi: https://doi.org/10.1016/j.aap.2018.07.009
  18. Bergel-Hayat, R., Debbarh, M., Antoniou, C., Yannis, G. (2013). Explaining the road accident risk: Weather effects. Accident Analysis and Prevention, 60, 456–465. doi: https://doi.org/10.1016/j.aap.2013.03.006
  19. Chand, A., Jayesh, S., Bhasi, A. B. (2021). Road traffic accidents: An overview of data sources, analysis techniques and contributing factors. Materials Today: Proceedings, 47, 5135–5141. doi: https://doi.org/10.1016/j.matpr.2021.05.415
  20. Naik, B., Tung, L.-W., Zhao, S., Khattak, A. J. (2016). Weather impacts on single-vehicle truck crash injury severity. Journal of Safety Research, 58, 57–65. doi: https://doi.org/10.1016/j.jsr.2016.06.005
  21. Malin, F., Norros, I., Innamaa, S. (2019). Accident risk of road and weather conditions on different road types. Accident Analysis and Prevention, 122, 181–188. doi: https://doi.org/10.1016/j.aap.2018.10.014
  22. Heqimi, G., Gates, T. J., Kay, J. J. (2018). Using spatial interpolation to determine impacts of annual snowfall on traffic crashes for limited access freeway segments. Accident Analysis and Prevention, 121, 202–212. doi: https://doi.org/10.1016/j.aap.2018.09.014
  23. Moomen, M., Rezapour, M., Ksaibati, K. (2019). An investigation of influential factors of downgrade truck crashes: A logistic regression approach. Journal of Traffic and Transportation Engineering (English Edition), 6 (2), 185–195. doi: https://doi.org/10.1016/j.jtte.2018.03.005
  24. Gürbüz, H., Buyruk, S. (2016). The prototype design and tests of vibration controlled driver warning system from the steering wheel. International Journal of Automotive Engineering and Technologies, 5 (3), 77–84. doi: https://doi.org/10.18245/ijaet.287174
  25. Andrieux, A., Lengellé, R., Beauseroy, P., Chabanon, C. (2008). A Novel Approach to Real Time Tire-Road Grip and Slip Monitoring. IFAC Proceedings Volumes, 41 (2), 7104–7109. doi: https://doi.org/10.3182/20080706-5-kr-1001.01204
  26. Salehi, M., Noordermeer, J. W. M., Reuvekamp, L. A. E. M., Dierkes, W. K., Blume, A. (2019). Measuring rubber friction using a Laboratory Abrasion Tester (LAT100) to predict car tire dry ABS braking. Tribology International, 131, 191–199. doi: https://doi.org/10.1016/j.triboint.2018.10.011
  27. Soulmana, B., Boukebbab, S., Boulahlib, M. S. (2021). Hand position on steering wheel during fatigue and sleepiness case: driving simulator. Advances in transportation studies, 53, 69–84.
  28. de Groot, S., Centeno Ricote, F., de Winter, J. C. F. (2012). The effect of tire grip on learning driving skill and driving style: A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour, 15 (4), 413–426. doi: https://doi.org/10.1016/j.trf.2012.02.005
  29. Hault-Dubrulle, A., Robache, F., Pacaux, M.-P., Morvan, H. (2011). Determination of pre-impact occupant postures and analysis of consequences on injury outcome. Part I: A driving simulator study. Accident Analysis and Prevention, 43 (1), 66–74. doi: https://doi.org/10.1016/j.aap.2010.07.012
  30. Davenne, D., Lericollais, R., Sagaspe, P., Taillard, J., Gauthier, A., Espié, S., Philip, P. (2012). Reliability of simulator driving tool for evaluation of sleepiness, fatigue and driving performance. Accident Analysis and Prevention, 45, 677–682. doi: https://doi.org/10.1016/j.aap.2011.09.046
  31. Auberlet, J.-M., Pacaux, M.-P., Anceaux, F., Plainchault, P., Rosey, F. (2010). The impact of perceptual treatments on lateral control: A study using fixed-base and motion-base driving simulators. Accident Analysis and Prevention, 42 (1), 166–173. doi: https://doi.org/10.1016/j.aap.2009.07.017
  32. Branzi, V., Domenichini, L., La Torre, F. (2017). Drivers’ speed behaviour in real and simulated urban roads – A validation study. Transportation Research Part F: Traffic Psychology and Behaviour, 49, 1–17. doi: https://doi.org/10.1016/j.trf.2017.06.001
  33. Nichici, A., Cicală, E. F, Mee, R. (1996). Experimental data processing. Cursşiaplicaţii, Timişoara, 63.
  34. Goupy, J., Creighton, L. (2006). Introduction aux plans d'expériences-2ème édition-Livre+ CD-Rom. Hachette.
  35. Vigier, M. (1988). Pratique des plans d'experiences: methodologie Taguchi. Éditions d'Organisation.
  36. Cicală, E. F. (2005). Metoda experimentelor factoriale: proiectarea experimentelor, modelare, optimizare. Timişoara: Editura Politehnica.
Identifying the effects of driving parameters on stopping distance to reduce accident risks

Downloads

Published

2024-02-16

How to Cite

Boulmedais, N., Bidi, L., Chaib, R., Boukebbab, S., & Boulahlib, M. S. (2024). Identifying the effects of driving parameters on stopping distance to reduce accident risks. Technology Audit and Production Reserves, 1(2(75), 53–61. https://doi.org/10.15587/2706-5448.2024.295438

Issue

Vol. 1 No. 2(75) (2024): Information and control systems

Section

Systems and Control Processes

License

Copyright (c) 2024 Nesrine Boulmedais, Lyes Bidi, Rachid Chaib, Salim Boukebbab, Mohamed Salah Boulahlib

Creative Commons License

This work is licensed under a Creative Commons Attribution 4.0 International License.

The consolidation and conditions for the transfer of copyright (identification of authorship) is carried out in the License Agreement. In particular, the authors reserve the right to the authorship of their manuscript and transfer the first publication of this work to the journal under the terms of the Creative Commons CC BY license. At the same time, they have the right to conclude on their own additional agreements concerning the non-exclusive distribution of the work in the form in which it was published by this journal, but provided that the link to the first publication of the article in this journal is preserved.