Abstract
Rear-end collisions are one of the most common types of road accidents, often caused by the sudden deceleration of the leading vehicle during a car-following situation. In-vehicle applications based on Augmented Reality (AR) technology could optimize the driver’s visual attention, providing new and additional visual feedback to improve the driving experience. This study has focused on a new AR application aimed at improving the safety of rear-end driving conditions, by means of different AR video and audio warnings. A driving simulator study was carried out to test the effectiveness of the proposed AR system and assess the ability of drivers to avoid rear-end collisions, with and without the AR warnings, in an urban road scenario. Significant positive effects of the AR warnings on driving speeds and road safety were observed, mainly consisting in lower speeds, decelerations and reaction times and improved surrogate measures of safety.
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References
World Health Organization: Global status report on road safety 2018 (2018). www.who.int/violence_injury_prevention/road_safety_status/2018/en. Accessed 7 Feb 2020
National Highway Traffic Safety Administration (NHTSA). Traffic Safety Facts 2015: 2015 Motor Vehicle Crashes: Overview. Washington, DC: U.S. Department of Transportation, National Highway Traffic Safety Administration (2016). https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812318. Accessed 3 Feb 2020
Naujoks, F., Grattenthaler, H., Neukum, A., Weidl, G., Petrich, D.: Effectiveness of advisory warnings based on cooperative perception. IET Intell. Transp. Syst. 9(6), 606–617 (2015)
Moussa, G., Radwan, E., Hussain, K.: Augmented reality vehicle system: left-turn maneuver study. Transp. Res. C-Emerg. 21, 1–16 (2012)
Rusch, M.L., Schall Jr., M.C., Lee, J.D., Dawson, J.D., Rizzo, M.: Augmented reality cues to assist older drivers with gap estimation for left-turns. Accident Anal. Prev. 71, 210–221 (2014)
Park, B.J., Lee, J.W., Yoon, C., Kim, K.O.: A study on augmented reality of a vehicle information using head-up display. In: 6th International Conference on IT Convergence and Security (ICITCS), Prague, Czech Republic, 26–29 September 2016
Bella, F.: Driving simulator for speed research on two-lane rural roads. Accident Anal. Prev. 40(3), 1078–1087 (2008)
Calvi, A.: Investigating the effectiveness of perceptual treatments on a crest vertical curve: a driving simulator study. Transp. Res. F-Traffic 58, 1074–1086 (2018)
Calvi, A., D’Amico, F.: Quality control of road project: identification and validation of a safety indicator. Adv. Transp. Stud. 9, 47–66 (2006)
Calvi, A., D’Amico, F., Ferrante, C., Bianchini Ciampoli, L.: Applying perceptual treatments for reducing operating speeds on curves: a driving simulator study for investigating driver’s speed behavior. In: Advances in Intelligent Systems and Computing, vol. 964, pp. 330–340 (2020)
Calvi, A.: Does roadside vegetation affect driving performance? Driving simulator study on the effects of trees on drivers’ speed and lateral position. Transp. Res. Rec. 2518, 1–8 (2015)
Calvi, A., Bella, F., D’Amico, F.: Diverging driver performance along deceleration lanes: driving simulator study. Transp. Res. Rec. 2518, 95–103 (2015)
Hayward, J.: Near misses as a measure of safety at urban intersections. PhD thesis, Department of Civil Engineering, Pennsylvania State University, University Park, PA, USA (1971)
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Calvi, A., D’Amico, F., Ferrante, C., Bianchini Ciampoli, L. (2020). Assessing the Effectiveness of Augmented Reality Cues in Preventing Rear-End Collisions: A Driving Simulator Study. In: Stanton, N. (eds) Advances in Human Aspects of Transportation. AHFE 2020. Advances in Intelligent Systems and Computing, vol 1212. Springer, Cham. https://doi.org/10.1007/978-3-030-50943-9_29
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DOI: https://doi.org/10.1007/978-3-030-50943-9_29
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