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A Scheduling Plan Model for Metro Crew Incorporating Fatigue and Biological Rhythms Read chapter Read first chapter

2023 | OriginalPaper | Chapter

Drivers’ Visual Characteristics of Urban Expressway Based on Eye Tracker

Authors : Tianjun Feng, Ziwen Zhao, Xiujuan Tian

Published in: Green Transportation and Low Carbon Mobility Safety

Publisher: Springer Nature Singapore

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Abstract

In order to compare and analyze the visual characteristics of drivers in the congested and unblocked state of urban expressways, real vehicle tests were carried out on the eastern expressway in Changchun City using the German Dikablis eye tracker and its supporting D-Lab software. The test data was processed by using descriptive statistical analysis and non-parametric inspection methods to quantify the impact of congestion on the driver’s visual characteristics. The results show that drivers mainly obtain traffic information by gaze when driving on the expressway, and the gaze points are mostly concentrated on the road vehicles; the driver’s gaze duration and scan duration in the congested state account for the highest proportions in the 200–250 ms and 0–25 ms time periods, respectively; the average gaze duration and the average scan duration of the drivers in the congested state were higher than those in the unblocked state. The driver's gaze duration and saccade duration in the two states are significantly different, and the Mann–Whitney U test results are less than 0.05; the pupil area changes more drastically in the congested state, and the pupil area change rate is 38.67%.

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Literature
1.
Wang Y (2019) Exploring the problems and solutions of the urban express way. Constr Des Eng 10:61–62
2.
Zhang XQ, Xie ZJ, Du ZH et al (2019) Analysis on traffic characteristics of short distance travel on urban expressway. Technol Highway Transport 35:116–122
3.
Quiroga CA (2000) Performance measures and data requirements for congestion management systems. Transport Res C-Emer 8(1–6):287–306CrossRef
4.
Okamura H, Watanabe S, Watanabe T (2000) An empirical study on the capacity of bottlenecks on the basic suburban expressway sections in Japan. In: Proceedings of the 4th international symposium on highway capacity, vol 12, pp 120–129
5.
He SL (2012) Analyze the mechanism of urban road traffic congestion with the theory of supply and demand. J People's Publ Secur Univ China (Sci Technol) 18:48–52
6.
Wada T, Fukumoto J, Ohtsuki K et al (2011) A novel real-time recognition method of vehicular traffic congestion by VANET. IEICE Trans Commun 94(1):55–63CrossRef
7.
Wu K, Chen Y, Ma J, Bai S et al (2017) Traffic and emissions impact of congestion charging in the central Beijing urban area: a simulation analysis. Transport Res D-Tr E 51:203–215CrossRef
8.
Angelelli E, Arsik I, Morandi V et al (2016) Proactive route guidance to avoid congestion. Transport Res B-Meth 94:1–21CrossRef
9.
Li G, Lai W, Sui X et al (2020) Influence of traffic congestion on driver behavior in post-congestion driving. Accident Anal Prev 141:105508CrossRef
10.
Li ZM (2000) Traffic engineering, 2nd edn. China Communications Press, Beijing, p 11
11.
Qin L, Dong LL, Xu WH et al (2018) Influence of vehicle speed on the characteristics of driver’s eye movement at a highway tunnel entrance during day and night conditions: a pilot study. Int J Environ Res Public Health 15:656CrossRef
12.
Calvi A, De Blasiis MR, Guattari C (2012) An empirical study of the effects of road tunnel on driving performance. Procedia Soc Behav Sci 53:1098–1108CrossRef
13.
14.
Zheng XJ, Li ZH, Zhang Y (2018) Eye movement research and development of driving safety. Technol Innov Manag 39:50–59
15.
Cooper JM, Medeiros-Ward N, Strayer DL (2013) The impact of eye movements and cognitive workload on lateral position variability in driving. Hum Factors 55:1001–1014CrossRef
16.
Yekhshatyan L, Lee JD (2012) Changes in the correlation between eye and steering movements indicate driver distraction. IEEE T Intell Transp 14:136–145CrossRef
17.
Lin L, Huang C, Ni X et al (2015) Driver fatigue detection based on eye state. Technol Health Care 23:S453–S463CrossRef
18.
Qi WW (2014) Characteristics research for driver’s physiology and lane changing in congested state of urban road. PhD Thesis, Harbin Institute of Technology, China, July
19.
20.
21.
Li ZH (2018) Modeling analyses on driver’s gazing behavior based on real vehicle eye movement experiment. Sci Technol Eng 18:312–317
22.
Choi IH, Jeong CH, Kim YG (2016) Tracking a driver’s face against extreme head poses and inference of drowsiness using a hidden Markov model. Appl Sci 6(5):137CrossRef
23.
Hu YQ, Liu HX, Zhu T et al (2017) Research on visual characteristics of drivers driving through extremely long expressway tunnel. J China Saf Sci 27:31–36
24.
Ye JG (2017) Study on the driver's eye movement and psychological characteristics and its application in landscape construction in mountainous freeway. MD Thesis, Chongqing Jiaotong University, China, June
25.
Zhu DC (2018) Research on the effects of expressway ramp environmental factors on driver’s physiological characteristics and behaviors. MD Thesis, South China University of Technology, China, June
26.
Qi W, Pei Y, Song M et al (2013) Pattern analysis of driver’s “pressure-state-response” in traffic congestion. Discrete Dyn Nat Soc
27.
CJJ 129:2009. Specification for design of urban expressway
28.
Hu JB, Li R, Ma Y (2014) Safety threshold evaluation method for expressway tunnel lighting in entrance section. J China Highway Transport 27:92–99
29.
Zhao L (2008) Two-lane highway alignment research based on driver's psychological and physiological reaction. PhD Thesis, Beijing University of Technology, China, July
Metadata
Title
Drivers’ Visual Characteristics of Urban Expressway Based on Eye Tracker
Authors
Tianjun Feng
Ziwen Zhao
Xiujuan Tian
Copyright Year
2023
Publisher
Springer Nature Singapore
Book
Green Transportation and Low Carbon Mobility Safety

Print ISBN: 978-981-19-5614-0

Electronic ISBN: 978-981-19-5615-7

Copyright Year: 2023

DOI
https://doi.org/10.1007/978-981-19-5615-7_23

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