Establishing Style-Oriented Driver Models by Imitating Human Driving Behaviors

IEEE Transactions on Intelligent Transportation Systems

Volumn 16, Issue 5, 2015, Pages 2522-2530

  Xu, Li ^a   Hu, Jie ^a   Jiang, Hong ^b,c   Meng, Wuqiang ^c  

^a ZHEJIANG UNIVERSITY   (China)

^b FORD MOTOR COMPANY   (United States)

^c Ford Motor Research and Engineering (Nanjing) Co Ltd   (China)

Author keywords

distal learning control; Driver model; driving cycle test; driving style; PCMLP; VTD

Indexed keywords

AUTOMOTIVE INDUSTRY; HUMAN COMPUTER INTERACTION; VEHICLES;

DRIVER MODELING; HUMAN DRIVING BEHAVIOR; INTELLIGENT TRANSPORTATION; INVERSE MODELING; LEARNING CONTROL; MULTI-LAYERED PERCEPTRON; REAL-WORLD DRIVINGS; SPEED FOLLOWING;

BEHAVIORAL RESEARCH;

EID: 84959570286     PISSN: 15249050     EISSN: None     Source Type: Journal    
DOI: 10.1109/TITS.2015.2409870     Document Type: Article

References (29)

1. J. Zhang et al. "Data-driven intelligent transportation system: A survey," IEEE Trans. Intell. Transp. Syst., vol. 12, no. 4, pp. 1624-1639, Dec. 2011.
2. D. Filev, J. Lu, and K. Prakah-Asante, "Real-time driving behavior identification based on driver-in-the-loop vehicle dynamics and control," in Proc. IEEE Int. Conf. Syst., Man, Cybern., San Antonio, TX, USA, 2009, pp. 2020-2025.
3. M. Kondo, "Directional stability (when steering is added)," J. Soc. Autom. Eng. Jpn., vol. 5/6, p. 9, 1953.
4. M. Plochl and J. Edelmann, "Driver models in automobile dynamics application," Veh. Syst. Dyn., vol. 45, no. 7/8, pp. 699-741, 2007.
5. K. F. Kraiss and H. Küttelwesch, "Teaching neural networks to guide a vehicle through an obstacle course by emulating a human teacher," in Proc. Int. Joint Conf. Neural Netw., San Diego, CA, USA, 1990, pp. 333-337.
6. A. G. Fadeh, A. Fahim, and M. Elgindy, "Neural network and fuzzy logic applications to vehicle systems: Literature survey," Int. J. Veh. Des., vol. 18, no. 2, pp. 132-193, 1997.
7. K. F. Kraiss and H. Kuttelwesch, "Identification and application of neural operator models in a car driving situation," in Proc. 5th IFAC/IFIP/IFORS/IEA Symp. Anal., Des. Eval. Man-Mach. Syst., Seattle, WA, USA, 1991, pp. 121-126.
8. T. Fujioka, K. Nomura, K. Takubo, and D. H. Chung "Driver model using neural network system," in Proc. 6th Int. Pacific Conf. Autom. Eng., 1991, vol. 2, pp. 931-938.
9. C. C. MacAdam and G. E. Johnson, "Application of elementary neural networks and preview sensors for representing driver steering control behavior," Veh. Syst. Dyn., vol. 25, no. 1, pp. 3-30, 1996.
10. C. C. MacAdam, Z. Bareket, P. Fancher, and,R. Ervin "Using neural network to identify driving style and headway control behavior of drivers," Veh. Syst. Dyn. Suppl., vol. 28, pp. 143-160, 1998.
11. I. Kageyama, A. Arai, and T. Nomura, "An analysis of driver's control algorithm using neural network modeling," Veh. Syst. Dyn. Suppl., vol. 33, pp. 122-130, 2000.
12. K. Inata, P. Paksincharoensak, and M. Nagai, "Driver behavior modeling based on database of personal mobility driving in urban area," in Proc. ICCAS, Seoul, Korea, 2008, pp. 2902-2907.
13. M. Bichi et al., "Stochastic model predictive control with driver behavior learning for improved powertrain control," in Proc. 49th IEEE Conf. Decision Control, Atlanta, GA, USA, 2010, pp. 6077-6082.
14. Y. Kishimoto and K. Oguri, "A modeling method for predicting driving behavior concerning with driver's past movements," in Proc. IEEE Int. Conf. Veh. Electron. Safety, Columbus, OH, USA, 2008, pp. 132-136.
15. H. Amata, C. Miyajima, T. Nishino, M. Kitaoka, and K. Takeda, "Prediction model of driving behavior based on traffic conditions and driver types," in Proc. 21th Int. IEEE Conf. Intell. Transp. Syst., St. Louis, MO, USA, 2009, pp.1-6.
16. H.-S. Tan and J. Huang, "Experimental development of a new target and control driver steering model based on DLC test data," IEEE Trans. Intell. Transp. Syst., vol. 13, no. 1, pp. 375-383, Mar. 2012.
17. P. Hermannstadter and B. Yang, "Identification and validation of lateral driver models on experimentally induced driving behavior," in Proc. IEEE Int. Conf. Syst., Man Cybern., Seoul, Korea, 2012, pp. 1165-1170.
18. S. D. Keen and D. J. Cole, "Application of time-variant predictive control to modelling driver steering skill," Veh. Syst. Dyn., vol. 49, no. 4, pp. 527-559, 2011.
19. D. Zhang, Q. Xiao, and J. Wang, "Driver curve speed model and its application to ACC," Int. J. Autom. Technol., vol. 14, no. 2, pp. 241-247, Apr. 2013.
20. Z. Constantinescu, C. Marinoiu, and M. Vladoiu, "Driving style analysis using mining techniques," Int. J. Comput. Commun. Control, vol. 5, no. 5, pp. 654-663, 2010.
21. K. Mikami, H. Okuda, S. Taguchi, Y. Tazaki, and T. Suzuki, "Model predictive assisting control of vehicle following task based on driver model," in Proc. IEEE Int. Conf. Control Appl., Yokohama, Japan, 2010, pp. 890-895.
22. M. R. Othman, Z. Zhang, T. Imamura, and T. Miyake, "Modeling driver operation behavior by linear prediction analysis and auto associative neural network," in Proc. IEEE Int Conf. Syst., Man Cybern., San Antonio, TX, USA, 2009, pp. 649-653.
23. A. Bolovinou, A. Amditis, F. Bellotti, and T. Tarkiainen, "Driving style recognition for co-operative driving: A survey," in Proc. 6th Int. Conf. Adapt. Self-Adapt. Syst. Appl., Venice, Italy, 2014, pp. 73-78.
24. M. I. Jordan and D. E. Rumelhart, "Forward models: Supervised learning with a distal teacher," Cogn. Sci., vol. 16, no. 3, pp. 307-354, Jul. 1992.
25. L. Xu, "A locally designed multi-layer perceptron," ACTA Automatica Sinica, vol. 23, no. 3, pp. 326-331, 1997.
26. J. Yu, L. Xu, J. Jiang, and T. Zhu, "A novel neural controller for robot manipulator," in Proc. IEEE IECON 22nd Int. Conf. Ind. Electron., Control, Instrum., 1996, vol. 3, pp. 1862-1866.
27. A. Y. Ungoren and H. Peng, "An adaptive lateral preview driver model," Veh. Syst. Dyn., vol. 43, no. 4, 2005, pp. 245-259.
28. P. J.Werbos, "Neurocontrol and elastic fuzzy logic: Capabilities, concept, and applications," IEEE Trans. Ind. Electron., vol. 2, no. 40, pp. 170-180, Apr. 1993.
29. W. T. Miller III,"Real-time application of neural networks forsensor-based control of robots with vision", IEEE Trans. Syst. Sci. Cybern., vol. 19, no. 4, pp. 825-831, Jul./Aug. 1989.