Modeling of Speed in Vehicles Entering Two-Way Suburban Tunnels by Adaptive Neuro Fuzzy Inference System

Document Type : Technical Report

Authors

1 Ph.D. Student, Civil Engineering Department, Payam Noor University, Tehran, Iran

2 Associate Professor, Faculty of Engineering, Payam Noor University, Tehran, Iran

3 Assistant Professor, Faculty of Engineering, Payam Noor University, Tehran, Iran

Abstract

The behavior of drivers on the roads is elicited from the state of the surrounding environment. The author's research shows that the vehicle starts to decelerate at a certain distance from the tunnel when it is observed, and they have the lowest speed when reaching the beginning of the tunnel. As soon as the tunnel is passed, the vehicle increases speed again in a certain length. The main purpose of this study is to model the speed of vehicles entering suburban tunnels based on the speed changes before entering the tunnel using the neuro-fuzzy network. Then, to validate the designed model, the data of 30 different drivers were used who travel in the same conditions by a Renault Logan vehicle with a manual transmission system. Using the Pearson correlation analysis method, the relationship between the variables of the speed of entrance to tunnel and changes in vehicle speed was investigated. The value of the correlation coefficient is equal to -0.7, which means the strong negative correlation between the two variables. The results show that the neuro-fuzzy network method has the ability to predict speed changes with a high accuracy based on the initial speed of entrance to the tunnel. The results of this study are used to analyze the behavior of drivers in suburban tunnels. Due to the importance of abrupt speed changes in an unusual way, especially on two-way routes, the safety of tunnels can be increased by reducing the stressors in drivers.

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Main Subjects


[1]     T. R. S. o. M. Tunnels, SWOV, The Netherlands: SWOV Fact Sheet, 2009.
[2]     C. Nussbaumer, "Comparative analysis of safety in tunnels," Young Reaserchers Seminar, Brno, 2007. doi: 10.1080/10798587.2014.934595.
[3]     L. Lu, J. Lu, Y. Xing, C. Wang and F. Pan, Statistical analysis of traffic accidents in Shanghai River Crossing Tunnels and Safety Countermeasures, Hindawi Publishing Corporation, 2014, pp. 1-7. doi: 10.1155/2014/824360.
[4]     F. Amundsen and A. Engebresten, "Studies on Norwegian Road Tunnels II," in An Analysis in Road Tunnels 2001-2006, Oslo, Norway, Road and Traffic Depart, 2009. doi: 10.1016/S0886-7798(00)00024-9.
[5]     F. Amundsen and G. Ranes, "Studies on traffic accidentin norwegian road tunnels," Tunn. Undergr. Space Technol, pp. 3-11, 2000. doi: 10.1016/S0886-7798(00)00024-9.
[6]     K. Lemke, "Road Safety in tunnels," Transp. Rec. 1940, pp. 170-174, 2000, doi: 10.3141/1740-22.
[7]     A. Jahantabi, M. Keymanesh and S. A. Razavian Amri, "Assessing Driver Behavior in Arterial Two-Way Tunnels," Quarterly Journal of Transportation Engineering, 2019.
[8]     B. Shirgir and H. Hassanpour, "Analysis of Traffic Factors Affecting the Accidents in the Urban Tunnel Entry Areas (Case Study: Resalat Tunnel)," Modares Civil Engineering journal, vol. 19 (1), pp. 105-116, 2019.
[9]     Q. Hou, A. P. Tarko and X. Meng, "Analyzing crash frequently in freeway tunnels: A correlated random parameters approach," Accident Analysis and Prevention, pp. 94-100, 2018. doi: 10.1016/j.aap.2017.11.018.
[10]   M. Soleymani Kermani and A. Namazian Jam, "Modifying PIARC’s Linear Model of Accident Severity Index to Identify Roads' Accident Prone Spots to Rehabilitate Pavements Considering Nonlinear Effects of the Traffic Volume," Journal of Rehabilitation in Civil Engineering, vol. 4, no. 2, pp. 45-51, 2016.
[10]   Z. Ma, C. Shao and S. Zhang, "Characteristics of Traffic Accidents in Chinese freeway tunnels," pp. 350-355, 2009. doi: 10.1016/j.tust.2008.08.004.
[11]   M. M. Chatzimichailidou and I. M. Dokas, "RiskOAP: Introducing and applying a methodology of risk self-awareness in road tunnel safety," Accident Analysis and Preventation, pp. 118-127, 2016. doi: 10.1016/j.aap.2016.02.005.
[12]   S. Bassan, "Sight distance and horizental curve aspects in the design of road tunnels," Tunnelling and Underground Space Technology, vol. 45, pp. 214-226, 2015. doi: 10.1016/j.tust.2014.10.004.
[13]   E. E. Miller and L. N. Boyle, "Driver Behavior in Road Tunnels," Transportation Research Record, vol. 2518, pp. 60-67, 2015. doi: 10.3141/2518-08.
[14]   J. Yeung and Y. Wong, "Road Traffic Accidents in Singapore expressways tunnels," Tunn. Undergr. Space Technol. 38, pp. 534-541, 2013. doi: 10.1016/j.tust.2013.09.002.
[15]   A. Calvi, M. R. De Blasiis and C. Guattari, "An Empirical Study of the effects of Road Tunnel on Driving Performance," in Sustainability of Road Infrastructures, Rome Italy, 2012. doi: 10.1016/j.sbspro.2012.09.959.
[16]   A. SHIMOJO and H. TAKAGI, "A simulation Study of Driving Performance in Long Tunnel," 1995.
[17]   "Google Earth," 2019. [Online]. Available: https://www.google.com/maps.
[18]   Q. Meng and X. Qu, "Estimation of rear-end vehicle crash frequencies in urban road tunnels," pp. 254-263, 2012. doi: 10.1016/j.aap.2012.01.025.
Volume 10, Issue 1 - Serial Number 25
February 2022
Pages 88-100
  • Receive Date: 27 August 2020
  • Revise Date: 20 January 2021
  • Accept Date: 26 June 2021
  • First Publish Date: 26 June 2021