Let's Connect
Follow Us
Watch Us
(+385) 1 2380 262
journal.prometfpz.unizg.hr
Promet - Traffic&Transportation journal

Accelerating Discoveries in Traffic Science

Accelerating Discoveries in Traffic Science

Login Submit

PDF
PUBLISHED
27.08.2024
DOI
https://doi.org/10.7307/ptt.v36i4.485
ISSUE
2024 (Vol 36), Issue 4
LICENSE
Copyright (c) 2024 Runzhao BEI, Hongliang WAN, Zhigang DU, Ting HUANG, Lei HAN, Jialin MEI
Creative Commons 4.0 logo
This work is licensed under a
Creative Commons Attribution-NonCommercial-
NoDerivatives 4.0 International License.

Analysis and Adjustment of Vehicle Trajectories in the Entrance Area of Freeway Tunnels: from the Perspective of Visual Guiding System

Authors:

Runzhao BEI
Wuhan University of Technology, School of Transportation and Logistics Engineering

Hongliang WAN
Wuhan University of Science and Technology, School of Automobile and Traffic Engineering

Zhigang DU
Wuhan University of Technology, School of Transportation and Logistics Engineering

Ting HUANG
Guizhou Transportation Planning Survey & Design Academe

Lei HAN
Wuhan University of Technology, School of Transportation and Logistics Engineering

Jialin MEI
Wuhan University of Technology, School of Transportation and Logistics Engineering

Keywords:tunnel entrance zone, traffic safety, visual guiding, driving behaviour, vehicle trajectory

Abstract

This study aims to quantitatively assess the adjustment effects of various visual guiding schemes on the abrupt change of vehicle trajectory. A driving simulation experiment was conducted using five simulated scenes: (1) baseline (actual situation), (2) pavement (road studs), (3) low position (flexible guideposts), (4) high position (warning alignment signs and retroreflective arches) and (5) multilayer (combination of all devices). Raw data, including vehicle positions, steering wheel angles and lateral offset, were collected. Based on these data, the gradual change degree of vehicle trajectory (G) and average steering wheel angle (SWAav) were computed to quantitatively evaluate the extent of vehicle trajectory deviation and the stability of steering wheel operations respectively. These two evaluation indicators were then translated into trajectory gradualness (TG) and operation stability (OS), respectively, to assess the adjustment effects of different visual guiding schemes. The study results demonstrate that road studs perform a certain degree of enhancement on operation stability (OS). Flexible guideposts exhibit the best effects on operation stability (OS). Additionally, the combination of warning alignment signs and retroreflective arches demonstrate the best regulation of trajectory gradualness (TG). Multilayer visual guiding system achieves the optimal trajectory gradualness (TG) and operation stability (OS).

References

  1. [1] Ministry of Transport of the People’s Republic of China. Statistical bulletin of transportation industry development in 2022. 2023. https://www.gov.cn/lianbo/bumen/202306/content_6887539.htm [Accessed 1th March 2024]
  2. [2] Amundsen FH, et al. Studies on traffic accidents in Norwegian road tunnels. Tunnelling and Underground Space Technology. 2000;15:3-11. DOI: 10.1016/S0886-7798(00)00024-9.
  3. [3] Kircher K, et al. The impact of tunnel design and lighting on the performance of attentive and visually distracted drivers. Accident Analysis & Prevention. 2012;47:153-161. DOI: 10.1016/j.aap.2012.01.019.
  4. [4] Ntzeremes P, et al. Quantitative risk assessment of road tunnel fire safety: Improved evacuation simulation model. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2020;6:04019020. DOI: 10.1061/ajrua6.0001029.
  5. [5] Shao X, et al. The impact of lighting and longitudinal slope on driver behaviour in underwater tunnels: A simulator study. Tunnelling and Underground Space Technology. 2022;122. DOI: 10.1016/j.tust.2022.104367.
  6. [6] Wang F, et al. Effects of visual active deceleration devices on controlling vehicle speeds in a long downhill tunnel of an expressway. Applied Sciences (Switzerland). 2021;11. DOI: 10.3390/app11156753.
  7. [7] Wan L, et al. Interactive influence analysis of tunnel lateral clearance on driving behavior using expressway field data. Journal of Advanced Transportation. 2021;2021:1-15. DOI: 10.1155/2021/5552099.
  8. [8] Du Z, et al. Safety evaluation of illuminance transition at highway tunnel portals on basis of visual load. Transportation Research Record. 2014;2458:1-7. DOI: 10.3141/2458-01.
  9. [9] Li Z, et al. Impact of the connected vehicle environment on tunnel entrance zone. Accident Analysis and Prevention. 2021;157. DOI: 10.1016/j.aap.2021.106145.
  10. [10] Han L, et al. Analysis of traffic signs information volume affecting driver’s visual characteristics and driving safety. International Journal of Environmental Research and Public Health. 2022;19. DOI: 10.3390/ijerph191610349.
  11. [11] Yonggang, et al. How eye movement and driving performance vary before, during, and after entering a long expressway tunnel: considering the differences of novice and experienced drivers under daytime and nighttime conditions. Springerplus. 2016;5:538-538. DOI: 10.1186/s40064-016-2148-y.
  12. [12] Calvi A, et al. An empirical study of the effects of road tunnel on driving performance. Procedia - Social and Behavioral Sciences. 2012;53:1099-1109. DOI: 10.1016/j.sbspro.2012.09.959.
  13. [13] Liu S, et al. Effects of lane width, lane position and edge shoulder width on driving behavior in underground urban expressways: A driving simulator study. International Journal of Environmental Research and Public Health. 2016;13. DOI: 10.3390/ijerph13101010.
  14. [14] Xu J, et al. Physiological indices and driving performance of drivers at tunnel entrances and exits: A simulated driving study. Plos One. 2020;15. DOI: 10.1371/journal.pone.0243931.
  15. [15] Zheng Z, et al. The impact of rhythm-based visual reference system in long highway tunnels. Safety Science. 2017;95:75-82. DOI: 10.1016/j.ssci.2017.02.006.
  16. [16] Jiao F, et al. Influence of different visual guiding facilities in urban road tunnel on driver’s spatial right-of-way perception. Accident Analysis and Prevention. 2022;172. DOI:10.1016/j.aap.2022.106688.
  17. [17] Du ZG, et al. Research on light environment improvement framework of highway tunnel based on visual guidance. China Journal of Highway and Transport [中国公路学报]. 2018;31:122-129. DOI: 10.19721/j.cnki.1001-7372.2018.04.015.
  18. [18] Zhao X, et al. Safety of raised pavement markers in freeway tunnels based on driving behavior. Accident Analysis & Prevention. 2020;145:105708. DOI: 10.1016/j.aap.2020.105708.
  19. [19] Jiao F, et al. Design and evaluation of visual guiding facilities along urban road tunnel horizontal curves based on vision and speed perception. Tunnelling and Underground Space Technology. 2023;133. DOI: 10.1016/j.tust.2022.104937.
  20. [20] Du Z, et al. Experimental study on the efficacy of retroreflective rings in the curved freeways tunnels. Tunnelling and Underground Space Technology. 2021;110:103813. DOI: 10.1016/j.tust.2021.103813.
  21. [21] Zhao X, et al. Evaluation of tunnel retro-reflective arch in an extra-long tunnel based on the matter-element extension method. Accident Analysis and Prevention. 2021;150. DOI:10.1016/j.aap.2020.105913.
  22. [22] Jiao F, et al. Influence of different visual guiding facilities in urban road tunnel on driver’s spatial right-of-way perception. Accident Analysis and Prevention. 2022;172. DOI:10.1016/j.aap.2022.106688.
  23. [23] Jiao F, et al. Self-explaining performance of visual guiding facilities in urban road tunnels based on speed perception. Tunnelling and Underground Space Technology. 2022;122. DOI:10.1016/j.tust.2022.104371.
  24. [24] Pike AM Laboratory-based retroreflectivity assessment of raised retroreflective pavement markers. Transportation Research Record. 2017;2612:113-120. DOI:10.3141/2612-13.
  25. [25] Chen F, et al. Analysis of the effect of decorated interior walls on drivers’ performance: From individual microbehavior to brain activation. Transportation Research Part F: Traffic Psychology and Behaviour. 2023;95:160-176. DOI:10.1016/j.trf.2023.04.009.
  26. [26] Qin X, et al. How does tunnel interior color environment influence driving behavior? Quantitative analysis and assessment experiment. Tunnelling and Underground Space Technology. 2020;98. DOI: 10.1016/j.tust.2020.103320.
  27. [27] Zhao X, et al. Safety of raised pavement markers in freeway tunnels based on driving behavior. Accident Analysis & Prevention. 2020;145. DOI: 10.1016/j.aap.2020.105708.
  28. [28] Yang Y, et al. Effectiveness of yellow color guardrail belt at freeway exits. Accident Analysis and Prevention. 2020;146. DOI: 10.1016/j.aap.2020.105737.
  29. [29] American Association of State Highway and Transportation Officials. A policy on geometric design of highways and streets 7th edition. GDHS-7. Washington, DC: IHS Markit; 2018.
  30. [30] Calvi A, et al. A driving simulator study to evaluate the effects of different types of median separation on driving behavior on 2 + 1 roads. Accident Analysis and Prevention. 2023;180. DOI: 10.1016/j.aap.2022.106922.
  31. [31] Yuan J, et al. Investigating drivers’ mandatory lane change behavior on the weaving section of freeway with managed lanes: A driving simulator study. Transportation Research Part F: Traffic Psychology and Behaviour. 2019;62:11-32. DOI: 10.1016/j.trf.2018.12.007.
  32. [32] Lyu N, et al. A field operational test in China: Exploring the effect of an advanced driver assistance system on driving performance and braking behavior. Transportation Research Part F: Traffic Psychology and Behaviour. 2019;65:730-747. DOI: 10.1016/j.trf.2018.01.003.
  33. [33] Xinhua News Agency. 395 million cars, 481 million people! The Ministry of Public Security has released national motor vehicle and driver data for 2021. 2022. https://baijiahao.baidu.com/s?id=1721654460936530972&wfr=spider&for=pc [Accessed 1th March 2024]
Show more
How to Cite
BEI, R. (et al.) 2024. Analysis and Adjustment of Vehicle Trajectories in the Entrance Area of Freeway Tunnels: from the Perspective of Visual Guiding System. Traffic&Transportation Journal. 36, 4 (Aug. 2024), 639-653. DOI: https://doi.org/10.7307/ptt.v36i4.485.

SPECIAL ISSUE IS OUT

Innovation and New Technologies in Transport and Logistics

Guest Editor: Eleonora Papadimitriou, PhD

Editors: Marko Matulin, PhD, Dario Babić, PhD, Marko Ševrović, PhD

RECENT PAPERS

Browse through the selection of our recent research
Exploring and Comparing Spatial Clusters of Pedestrian Night-Time Crashes Based on Different Street Lighting Conditions at County Spatial UnitUnderstanding the Impact of Integration Strategy of Ride-Hailing Platforms on Traveller’s Choice BehaviourOptimisation Methods for Cold Chain Logistics Path Considering Carbon Emission Costs in Time-Varying NetworksOnline Model Predictive Control for Energy-saving Train Operation in Passenger-Freight Mixed Lines

Accelerating Discoveries in Traffic Science |
2024 © Promet - Traffic&Transportation journal