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Influence mechanism of visual perception of edge rate lines cycle length on driver’s speed

    Bing Liu Affiliation
    ; Shunying Zhu Affiliation
    ; Hong Wang Affiliation
    ; Jing Xia Affiliation
    ; Naikan Ding Affiliation

Abstract

It is known that the installation of edge rate lines can help reduce driving speed. Theoretically, higher edge rate density leads to higher perception speed, so as the effect of speed reduction. However, there has not been a successful evaluation of appropriate design cycle length requirements. A series of experiments were taken on the straight sections on Hangrui highway in China. The cycle length was separately set in different values of 16, 8, 4, 2 and 1 m. The results showed that cycle length had significantly influence on the speed reduction effect. When the length of spatial edge rate line in each cycle λ equalled to the value of 16, 8, 4, 2 m, the effect of speed reduction was significantly enhanced as λ decreased. Percent of average speed reduction was 0.8, 3.0, 5.8 and 7.4%, respectively. However, when λ = 1 m, speed reduction effect was weaker than λ = 2 m, reduction percent of average speed was 5.2%. Then, relations between acceleration and average edge rate was analysed. When temporal frequency of edge rate lines fell in (10 Hz, 19 Hz], the braking deceleration of drivers increased as the temporal frequency increased, which conformed to the relation between temporal frequency and perception speed; when temporal frequency was lower than 10 Hz, some drivers will speed up. It may be related to the threshold of perception speed difference; when temporal frequency was higher than 19 Hz, some drivers will speed up. It may be related to flicker fusion phenomenon. According to the experiments results, edge rate lines cycle length for future implementations should be determined by the speed distribution of the target road.


First published online 19 August 2020

Keyword : driver, speed, edge rate, cycle length, driver’s speed perception, speed reduction, road experiment, temporal frequency

How to Cite
Liu, B., Zhu, S., Wang, H., Xia, J., & Ding, N. (2021). Influence mechanism of visual perception of edge rate lines cycle length on driver’s speed. Transport, 36(1), 38-45. https://doi.org/10.3846/transport.2020.12372
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Mar 19, 2021
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References

AASHTO. 2011. A Policy on Geometric Design of Highways and Streets. American Association of State Highway and Transportation Officials (AASHTO). 934 p.

ATSSA. 2006. Low Cost Local Road Safety Solutions. American Traffic Safety Services Association (ATSSA). 48 p. Available from Internet: https://safety.fhwa.dot.gov/intersection/other_topics/fhwasa09027/resources/Low%20Cost%20Local%20Road%20Safety%20Solutions.pdf

Carmel, D.; Lavie, N.; Rees, G. 2005. Neural correlates of conscious flicker perception, Journal of Vision 5(8): 768. https://doi.org/10.1167/5.8.768

Denton, G. G. 1980. The influence of visual pattern on perceived speed, Perception 9(4): 393–402. https://doi.org/10.1068/p090393

Ding, N.; Zhu, S. Y.; Wang, H.; Jiao, N. 2019. Effects of reverse linear perspective of transverse line markings on car-following headway: a naturalistic driving study, Safety Science 119: 50–57. https://doi.org/10.1016/j.ssci.2018.08.021

Ding, N.; Zhu, S.; Wang, H.; Jiao, N. 2017a. Effects of edge rate of the designed line markings on the following time headway, Scientia Iranica 24(4): 1770–1778. https://doi.org/10.24200/sci.2017.4268

Ding, N.; Zhu, S.; Wang, H.; Jiao, N. 2017b. Following safely on curved segments: a measure with discontinuous line markings to increase the time headways, Iranian Journal of Science and Technology, Transactions of Civil Engineering 41(3): 351–359. https://doi.org/10.1007/s40996-017-0072-1

François, M.; Morice, A. H. P.; Bootsma, R. J.; Montagne, G. 2011. Visual control of walking velocity, Neuroscience Research 70(2): 214–219. https://doi.org/10.1016/j.neures.2011.02.003

Godley, S. T.; Triggs, T. J.; Fildes, B. N. 2000. Speed reduction mechanisms of transverse lines, Transportation Human Factors 2(4): 297–312. https://doi.org/10.1207/STHF2-4_1

Hallmark, S. L.; Knickerbocker, S.; Hawkins, N. 2013. Transverse speed bars for rural traffic calming, Tech Briefs (February): 1–3.

Liu, B.; Zhu, S.; Wang, H.; Cheng, L. 2013. Optimization design and experiment on plane layout of edge line marking for speed reduction, in TRB 92nd Annual Meeting Compendium of Papers, 13–17 January 2013, Washington, DC, US, 1–18.

Longo, M. R.; Lourenco, S. F. 2007. Spatial attention and the mental number line: evidence for characteristic biases and compression, Neuropsychologia 45(7): 1400–1407. https://doi.org/10.1016/j.neuropsychologia.2006.11.002

Martín, A.; Décima, A. P.; Barraza, J. F. 2017. Perception of speed, distance, and TTC of familiar objects, Psychology & Neuroscience 10(3): 261–272. https://doi.org/10.1037/pne0000100

MassSAFE. 2004. Report on Passive Speed Control Devices. University of Massachusetts, US.

NHTSA. 2017. Traffic Safety Facts 2015: a Compilation of Motor Vehicle Crash Data from the Fatality Analysis Reporting System and the General Estimates System. Report DOT HS 812 384. National Highway Traffic Safety Administration (NHTSA), US Department of Transportation, Washington, DC, US. 238 p. Available from Internet: https://crashstats.nhtsa.dot.gov/Api/Public/ViewPublication/812384

Rakha, H. A.; Katz, B. J.; Duke, D. 2006. Design and evaluation of peripheral transverse bars to reduce vehicle speed, in TRB 85th Annual Meeting Compendium of Papers CD-ROM, 22–26 January 2006, Washington, DC, US, 1–14.

Recarte, M. A.; Nunes, L. M. 1996. Perception of speed in an automobile: estimation and production, Journal of Experimental Psychology: Applied 2(4): 291–304. https://doi.org/10.1037/1076-898X.2.4.291

Retting, R. A.; McGee, H. W.; Farmer, C. M. 2000. Influence of experimental pavement markings on urban freeway exitramp traffic speeds, Transportation Research Record: Journal of the Transportation Research Board 1705: 116–121. https://doi.org/10.3141/1705-17

Saffarian, M.; De Winter. J. C. F.; Senders, J. W. 2015. Measuring drivers’ visual information needs during braking: a simulator study using a screen-occlusion method, Transportation Research Part F: Traffic Psychology and Behaviour 33: 48–65. https://doi.org/10.1016/j.trf.2015.07.001

Shen, H.; Shimodaira, Y.; Ohashi, G. 2005. Speed-tuned mechanism and speed perception in human vision, Systems and Computers in Japan 36(13): 1–12. https://doi.org/10.1002/scj.20369

Thompson, P. 1982. Perceived rate of movement depends on contrast, Vision Research 22(3): 377–380. https://doi.org/10.1016/0042-6989(82)90153-5

TMB PSM. 2017. Annual Statistics of Road Traffic Accidents of People’s Republic of China 2016. Traffic Management Bureau of the Public Security Ministry (TMB PSM), China, Beijing (in Chinese).

Waldin, N.; Waldner, M.; Viola, I. 2017. Flicker observer effect: guiding attention through high frequency flicker in images, Computer Graphics Forum 36(2): 467–476. https://doi.org/10.1111/cgf.13141