journal article·2021-05-28Open access

Use of Pupil Area and Fixation Maps to Evaluate Visual Behavior of Drivers inside Tunnels at Different Luminance Levels—A Pilot Study

Li Qin, Qi-Lei Cao, Arturo S. Leon, Ying-Na Weng, Xu-Hua Shi

Applied Sciences· Volume 11· Issue 11

Abstract

This study reports the results of a pilot study on spatiotemporal characteristics of drivers’ visual behavior while driving in three different luminance levels in a tunnel. The study was carried out in a relatively long tunnel during the daytime. Six experienced drivers were recruited to participate in the driving experiment. Experimental data of pupil area and fixation point position (at the tunnel’s interior zone: 1566 m long) were collected by non-intrusive eye-tracking equipment at three luminance levels (2 cd/m2, 2.5 cd/m2, and 3 cd/m2). Fixation maps (color-coded maps presenting distributed data) were created based on fixation point position data to quantify changes in visual behavior. The results demonstrated that luminance levels had a significant effect on pupil areas and fixation zones. Fixation area and average pupil area had a significant negative correlation with luminance levels during the daytime. In addition, drivers concentrated more on the front road pavement, the top wall surface, and the cars’ control wheels. The results revealed that the pupil area had a linear relationship with the luminance level. The limitations of this research are pointed out and the future research directions are also prospected.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Human-Automation Interaction and Safety · Safety Warnings and Signage · Traffic and Road Safety

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Information Science and Engineering, Ningbo University, Ningbo 315211, China

School of Computer Science and Technology, Shandong Technology and Business University, Yantai 264003, China

Department of Civil and Environmental Engineering, College of Engineering and Computing, Florida International University, Miami, FL 33174, USA

Ningbo Leesten Technology Co., Ltd., Ningbo 315000, China

Funding

ZHEJIANG PROVINCIAL NATURAL SCIENCE FOUNDATION OF CHINA · NATIONAL NATURAL SCIENCE FOUNDATION OF CHINA · MAJOR SCIENCE AND TECHNOLOGY SPECIAL PROJECT IN JIANGBEI DISTRICT, NINGBO CITY

References (57)

Show source-provided references
1. Optical design of tunnel lighting with white light-emitting diodes10.1364/AO.53.00H114 ↗
2. Island Megalopolises: Tunnel Systems as a Critical Alternative in Solving Transport Problems10.1016/j.eng.2018.02.001 ↗
3. Dynamic luminance tuning method for tunnel lighting based on data mining of real-time traffic flow10.1016/j.buildenv.2020.106844 ↗
4. Transportation Department (2021, May 19). Statistical Bulletin on the Development of the Transportation Industry in 2020, Available online: https://xxgk.mot.gov.cn/2020/jigou/zhghs/202105/t20210517_3593412.html.
5. Robatsch, K., and Nussbaumer, C. (2007, January 27–30). Comparative analysis of safety in tunnel. Proceedings of the Young Researchers Seminar, Brno, Czech Republic.
6. Amundesen, F.H., and Engelbrektsen, A. (2009). Studies on Norwegian Road Tunnels II. An Analysis on Traffic Accidents in Road Tunnels, Vegdirektoratet, Road and Traffic Department, Traffic Department, Traffic Safety Section.
7. Accident Rates in Road Tunnels and Social Cost Evaluation10.1016/j.sbspro.2012.09.870 ↗
8. Characteristics of traffic accidents in Chinese freeway tunnels10.1016/j.tust.2008.08.004 ↗
9. Beard, A.N., and Marlair, G. (2005). A History of Fire Incidents in Tunnels. The Handbook of Tunnel Fire Safety, ICE Publishing.10.1680/hotfs.31685 ↗
10. Research on distribution characteristics of traffic accidents in expressway tunnel
11. Han, X., Shao, Y., Pan, B., Yu, P., and Li, B. (2019). Evaluating the impact of setting delineators in tunnels based on drivers’ visual characteristics. PLoS ONE, 14.10.1371/journal.pone.0225799 ↗
12. Zhang, W., Dai, J., Pei, Y., Li, P., Yan, Y., and Chen, X. (2016). Drivers’ Visual Search Patterns during Overtaking Maneuvers on Freeway. Int. J. Environ. Res. Public Health, 13.10.3390/ijerph13111159 ↗
13. Qin, L., Dong, L.-L., Xu, W.-H., Zhang, L.-D., and Leon, A.S. (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, 15.10.3390/ijerph15040656 ↗
14. Chang, X., Li, H., Rong, J., Qin, L., and Zhao, X. (2020). Spatiotemporal Characteristics of Vehicle Trajectories in a Connected Vehicle Environment—A Case of an Extra-Long Tunnel Scenario. IEEE Syst. J., 1–12.
15. Human behaviour in severe tunnel accidents: Effects of information and behavioural training10.1016/j.trf.2012.09.001 ↗
16. Eye movements: The past 25years10.1016/j.visres.2010.12.014 ↗
17. Analysis of Drivers’ Eye-Movement Characteristics When Driving around Curves10.1155/2015/462792 ↗
18. Study on the Influence of Driving Experience on Visual Characteristic10.1155/2013/790813 ↗
19. Study on driver’s fixation variation at entrance and inside sections of tunnel on highway10.1155/2014/273427 ↗
20. The Information That Drivers Use: Is it Indeed 90% Visual?10.1068/p251081 ↗
21. Mannering, F. (2007, January 21–25). The effect of interstate speed limits on driving speeds: Some new evidence. Proceedings of the 86th Annual Meeting of the Transportation Research Board, Washington, DC, USA. Paper No. 07-0120.
22. Energy optimization of road tunnel lighting systems10.3390/su7079664 ↗
23. The impact of tunnel design and lighting on the performance of attentive and visually distracted drivers10.1016/j.aap.2012.01.019 ↗
24. Visual attention while driving: Sequences of eye fixations made by experienced and novice drivers10.1080/0014013031000090116 ↗
25. Evaluation of the impacts of traffic states on crash risks on freeways10.1016/j.aap.2012.01.020 ↗
26. Wen, H., Sun, J., Zeng, Q., Zhang, X., and Yuan, Q. (2018). The effects of traffic composition on freeway crash frequency by injury severity: A Bayesian multivariate spatial modeling approach. J. Adv. Transp.10.1155/2018/6964828 ↗
27. Akamatsu, M., Imachou, N., Sasaki, Y., Ushiro-Oka, H., Hamanaka, T., and Onuki, M. (2003, January 8–10). Simulation study on driver’s bahavior while driving through a tunnel in a rolling area. Proceedings of the DSC North America 2003, Dearborn, MI, USA.
28. Eye-movements during navigation in a virtual tunnel10.1080/00207450903170361 ↗
29. The speed control effect of highway tunnel sidewall markings based on color and temporal frequency10.1002/atr.1405 ↗
30. Xiao, D.L., Fang, Y., Zhang, Y.N., and Guo, Z.Y. (2017, January 8–10). Analysis of driving behavior at the bridge-tunnel transition section in reduced visibility situations. Proceedings of the 4th International Conference on Transportation Information and Safety (ICTIS), Banff, AB, Canada.10.1109/ICTIS.2017.8047824 ↗
31. Effects of Prolonged Tasks and Rest Patterns on Driver’s Visual Behaviors, Driving Performance, and Sleepiness Awareness in Tunnel Environments: A Simulator Study10.1007/s40996-018-0093-4 ↗
32. Han, X., Shao, Y., Yang, S., and Yu, P. (2020). Entropy-Based Effect Evaluation of Delineators in Tunnels on Drivers’ Gaze Behavior. Entropy, 22.10.3390/e22010113 ↗
33. How does tunnel interior color environment influence driving behavior? Quantitative analysis and assessment experiment10.1016/j.tust.2020.103320 ↗
34. Can Driving Simulators Contribute to Solving Critical Issues in Geometric Design?10.3141/2138-16 ↗
35. A study of the effects of road tunnel on driver behavior and road safety using driving simulator
36. Tunnel entrance lighting—Effect of fixation point and other factors on the determination of requirements10.1177/096032717400600102 ↗
37. Zhao, W., and Liu, H. (July, January 30). Drivers’ Visual feature variation in long-tunnel exit of expressway. Proceedings of the ICTIS 2011, First International Conference on Transportation Information and Safety, Wuhan, China.10.1061/41177(415)7 ↗
38. Shao, F., Xu, Q., Xu, X., and Ma, C. (2016, January 11–12). Measuring Safety for urban tunnel entrance and exit based on nanoscopic driving behaviors. Proceedings of the 2016 Eighth International Conference on Measuring Technology and Mechatronics Automation (ICMTMA), Macau, China.
39. Influence of spatial visual conditions in tunnel on driver behavior: Considering the route familiarity of drivers10.1177/1687814019853661 ↗
40. Research on the characteristics of driver visual behavior in highway extra-long tunnel10.1088/1755-1315/295/4/042139 ↗
41. Variations in Naturalistic Driving Behavior and Visual Perception at the Entrances of Short, Medium, and Long Tunnels10.1155/2020/7630681 ↗
42. Research on drivers’ visual characteristics in different curvatures and turning conditions of the extra-long urban underwater tunnels10.1016/j.tust.2020.103360 ↗
43. Comparative study of two visual performance based mesopic models based on reaction time and contrast threshold data
44. Evaluating Light Source Efficacy under Mesopic Conditions Using Reaction Times10.1080/00994480.1997.10748173 ↗
45. Akkil, D., and Isokoski, P. (2016, January 12–16). Accuracy of interpreting pointing gestures in egocentric view. Proceedings of the 2016 ACM International Joint Conference on Pervasive and Ubiquitous Computing, Heidelberg, Germany.10.1145/2971648.2971687 ↗
46. Ready for take-over? A new driver assistance system for an automated classification of driver take-over readiness10.1109/MITS.2017.2743165 ↗
47. Wibirama, S., and Nugroho, H.A. (2017, January 11–15). Towards understanding addiction factors of mobile devices: An eye tracking study on effect of screen size. Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS, Seogwipo, Korea.10.1109/EMBC.2017.8037353 ↗
48. Kasneci, E., Sippel, K., Aehling, K., Heister, M., Rosenstiel, W., Schiefer, U., and Papageorgiou, E. (2014). Driving with Binocular Visual Field Loss? A Study on a Supervised On-Road Parcours with Simultaneous Eye and Head Tracking. PLoS ONE, 9.10.1371/journal.pone.0087470 ↗
49. Qin, L., Dong, L.-L., Xu, W.-H., Zhang, L.-D., and Leon, A.S. (2017). An Intelligent Luminance Control Method for Tunnel Lighting Based on Traffic Volume. Sustainability, 9.10.3390/su9122208 ↗
50. Pupil dilation as a measure of processing load in simultaneous, interpretation and other language tasks10.1080/14640749508401407 ↗
51. Wickens, C.D., and Hollands, J.G. (1999). Engineering Psychology and Human Performance, Prentice-Hall.
52. Fit-for-duty test for estimation of drivers’ sleepiness level: Eye movements improve the sleep/wake predictor10.1016/j.trc.2012.07.008 ↗
53. Saccadic peak velocity as an alternative index of operator attention: A short review10.1016/j.erap.2013.09.001 ↗
54. Pupil diameter measurement errors as a function of gaze direction in corneal reflection eye trackers10.3758/s13428-013-0327-0 ↗
55. Du, Z.G., Zhu, S.Y., and Pan, X.D. (2008, January 10–12). Experimental study on visual adaptation of highway tunnel based on pupil area change. Proceedings of the National Highway Science and Technology Innovation Forum, Cairo, Egypt.
56. Use of Fixation Heat Maps to Evaluate Visual Behavior of Unfamiliar Drivers on Horizontal Curves10.3141/2458-03 ↗
57. Yuan, W., Fu, R., Guo, Y., Xue, C., and Wu, F. (2011, January 14–16). Analysis of visual fixation areas and visual transition characteristics during the driving process. Proceedings of the International Conference on Road Safety and Simulation, Indianapolis, IN, USA.