Iranian Journal of Mechanical Engineering Transactions of ISME

Iranian Journal of Mechanical Engineering Transactions of ISME

development an intelligent system for discretionary lane change behaviors in the real traffic flow

Authors
Alireza Khodayari 1
A. Ghaffari 2
abbas pourmahmoudi 3
mehrdad javadi 4
1 Department of Mechanical Engineering, Pardis Branch, Islamic Azad University
2 K. N. Toosi Univ.
3 Department of Mechanical Engineering, South Tehran Branch, Islamic Azad University, Tehran, Iran
4 mechatronics dept - islamic azad university - south tehran branch
10.30506/ijmep.2020.105281.1556
Abstract
Lane changing behaviors, due to the hidden aspects of factors involved, are considered as one of the most complicated behaviors in traffic flows. This paper proposes an intelligent system for discretionary lane change behaviors in the real traffic flow. The introduction presents a review of the research into the models of lane change behaviors. Then, a new method is proposed to determine the initial and final points of lane changing behavior in terms of time parameter. Hypotheses are then introduced to extract data on lane change behaviors from data recorded by NGSIM. An intelligent system is put forward using two control sub-systems based on fuzzy logic. Basically, this paper brings about innovative features by the utilization of time parameter during the execution of lane change behaviors and by the consideration of the impact of human and environmental factors through measurable data such as relative distance and relative speed in terms of time parameter. Finally, the results of the proposed intelligent system are compared with the behaviors of the driver in real situations. The framework of the result analysis employs error criteria and standard deviation (Variance). The said comparison indicates that the developed intelligent system outperforms the human behaviors in real situations.
Keywords
lane change
discretionary lane change
intelligent system
fuzzy logic

Subjects

[1] Tehrani, H., and Quoc Do., H., "General Behavior and Motion Model for Automated Lane Change", Intelligent Vehicles Symposium (IV), IEEE, Seoul, South Korea, (2015).
 
[2] Yangyan, G., Mathias, L., and Timothy, G., "Modified Hamiltonian Algorithm for Optimal Lane Change with Application to Collision Avoidance", MMScience Journal,pp.576-584, (2015).
 
[3] Tistarelli, M., Guarnotta, F., Rizzieri, D., and Tarocchi, F., "Application of Optical Flow for Automated Overtaking Control", Proceedings oftheSecond IEEE Workshop on Applications of Computer Vision, pp. 105-112, Sarasota, FL, USA, (1994).
 
[4]VonHolt, V., "Tracking and Classification of Overtaking Vehicles on Autobahnen", Proceedings of the Intelligent Vehicles '94 Symposium, Paris, France, 24-26 Oct, (1994).
 
[5] You, F., Zhang, R., Lie, G., Wang, H., Wen, H., and Xu, J., "Trajectory Planning and Tracking Control for Autonomous Lane Change Maneuver Based on the Cooperative Vehicle Infrastructure System", Expert Systems withApplications,Vol. 42, pp. 5932-5946, (2015).
 
[6] Batavia, P.H., Pomerleau, D.H., and Thorpe, Ch.E., "Overtaking Vehicle Detection using Implicit Optical Flow", Intelligent Transportation System,ITSC'97,IEEE Conferenceon, Boston, MA, USA, USA, (1997).
 
[7] Hatipoglu, C., Ozguner, U., and Redmill, K., "Automated Lane Change Controller Design", IEEETransactions on Intelligent Transportation Systems Vol. 4. No, 1, pp. 13-22, (2003).
 
[8] Schofield, K., "Automotive Lane Change aid", U.S. Patent No. 6,882,287, (2005).
 
[9] Ngai, D.C., and Yung, N.H., "Automated Vehicle Overtaking Based on a Multiple-goal Reinforcement Learning Framework", Intelligent Transportation Systems Conference, Seattle, WA, USA, (2007).
 
[10] Widmann, G.R., Joseph, E, S., Jr, H., and Smith, M., "Vehicle Range-based Lane Change Assist System and Method", U.S. Patent No. 7,501,938, (2009).
 [11] Nishira, H., and Kawabe, T., "Lane Change Assist System", U.S. Patent No. 8,219,298. (2012).
 
[12] Petrov, P., and Nashashibi, F., "Adaptive Steering Control for Autonomous Lane Change Maneuver", Intelligent Vehicles Symposium(IV), Gold Coast, QLD, Australia,(2013).
 
[13] Yu, Y., El Kamel, A., and Gong, G., "Modeling Overtaking Behavior in Virtual Reality Traffic Simulation System", Control Conference (ASCC), 9th Asian IEEE, Istanbul, Turkey, (2013).
 
[14] Petrov, P., and Nashashibi, F., "Modeling and Nonlinear Adaptive Control for Autonomous Vehicle Overtaking", IEEE Trans,IntelligentTransportation Systems, Vol. 15, No. 4, pp. 1643-1656, (2014).
 
[15] Du, Y., Wang, Y., and Yao Chan, Ch., "Autonomous Lane-change Controller", Intelligent Vehicles Symposium(IV), IEEE, Seoul, South Korea, (2015).
 
[16] Zhang, Y., and A.Ioannou, P., "Combined Variable Speed Limit and Lane Change Control for Highway Traffic", IEEETransactions on Intelligent TransportationSystems, Vol. 18, No. 7, pp. 1812-1823, (2017).
 
[17] Pek, C., Zahn, P., and Althoff, M., "Verifying the Safety of Lane Change Maneuvers of Self-driving Vehicles Based on Formalized Traffic Rules", 2017 IEEE Intelligent Vehicles Symposium (IV), pp.1477-1483, (2017).
 
[18] Zhou, B., Wang, Y., Yu, G., and Wu, X., "A Lane-change Trajectory Model from Drivers Vision View", Transportation Research PartC:EmergingTechnologies, Vol. 85, pp. 609-627, (2017).
 
[19] Tang, J., Liu, F., Zhang, W., Ke, R., and Zou, Y., "Lane-changes Prediction Based on Adaptive Fuzzy Neural Network", Expert Systems with Applications, Vol.  91, pp.  452-463, (2018).
 
[20] Khodayari, A., Ghaffari, A., and Kazemi, R., "A Modified Car-following Model Based on a Neural Network Model of the Human Driver Effects", IEEETransactions on Systems,Man, andCybernetics-Part A: Systems and Humans, Vol. 42, No. 6, pp. 1440-1449, (2012).

  • Receive Date 16 March 2019
  • Revise Date 06 July 2019
  • Accept Date 13 December 2020