A method of vehicle motion prediction and collision risk assessment with a simulated vehicular cyber physical system

Transportation Research Part C: Emerging Technologies

Volumn 47, Issue P2, 2014, Pages 179-191

  Wu, Chaozhong ^a,b   Peng, Liqun ^a,b   Huang, Zhen ^a   Zhong, Ming ^a,b   Chu, Duanfeng ^a,b  

^a WUHAN UNIVERSITY OF TECHNOLOGY   (China)

^b BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS   (China)

Author keywords

Collision avoidance; Driver behavior; Risk assessment; Vehicle path prediction; Vehicular cyber physical system

Indexed keywords

ACCIDENTS; COLLISION AVOIDANCE; CYBER PHYSICAL SYSTEM; EMBEDDED SYSTEMS; FORECASTING; MOTION ESTIMATION; RISK ASSESSMENT; ROADS AND STREETS; SAFETY DEVICES; TRAFFIC CONTROL;

COLLISION AVOIDANCE SYSTEMS; COLLISION RISK ASSESSMENT; DRIVER BEHAVIOR; KALMAN FILTER ALGORITHMS; PATH PREDICTION; RECEIVER OPERATING CHARACTERISTIC CURVE ANALYSIS; ROAD TRAFFIC SAFETY; VEHICLE COLLISIONS;

ROAD VEHICLES;

COLLISION AVOIDANCE; EARLY WARNING SYSTEM; KALMAN FILTER; MODELING; RISK ASSESSMENT; ROAD TRANSPORT; TRANSPORTATION SAFETY;

EID: 85027936472     PISSN: 0968090X     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.trc.2014.07.002     Document Type: Article

References (33)

1. Amditis A., Polychronopoulos A., Floudas N., Andreone L. Fusion of infrared vision and radar for estimating the lateral dynamics of obstacles. Inf. Fusion 2005, 6(2):129-141.
2. Ammoun, S., Nashashibi, F., Laurgeau, C., 2006. Real-time crash avoidance system on crossroads based on 802.11 devices and GPS receivers. In: IEEE Intelligent Transportation Systems Conference, pp. 1023-1028.
3. Chambless L.E., Diao G. Estimation of time-dependent area under the ROC curve for long-term risk prediction. Stat. Med. 2006, 25(20):3474-3486.
4. Cheok, K.C., Smid, G.E., McCune, D.J., 2000. A multisensor-based collision avoidance system with application to a military HMMWV. In: Proceedings of Intelligent Transportation Systems, pp. 288-292.
5. Ewald, A., Willhoeft, V., 2000. Laser scanners for obstacle detection in automotive applications. In: Proc. The IEEE Intelligent Vehicle Symposium, pp. 682-687.
6. Gunnarsson, J., Svensson, L., Bengtsson, F., Danielsson, L., 2006. Joint driver volition classification and tracking of vehicles, In: Proc. Nonlinear Stat. Signal Process. Workshop, pp. 95-98.
7. Hamdar, S.H., Treiber, M., Mahmassani, H.S., Kesting, A., 2008. Modeling driver behavior as sequential risk-taking task. In: 87th Meeting of the Transportation Research Board, pp. 208-217.
8. Huang W., Rong H., He J., Gong J.F. Design and implementation of distributed large vehicle collision warning system. J. Transp. Inf. Saf. 2010, 28(4):81-85.
9. Jamson A.H., Lai F.C.H., Carsten O.M.J. Potential benefits of an adaptive forward collision warning system. Transp. Res. Part C Emerg. Technol. 2008, 16(4):471-484.
10. Kaempchen N., Schiele B., Dietmayer K. Situation assessment of an autonomous emergency brake for arbitrary vehicle-to-vehicle collision scenarios. IEEE Trans. ITS 2009, 10(4):678-687.
11. Kishimoto, Y., Oguri, K., 2008. A modeling method for predicting driving behavior concerning with driver's past movement. In: IEEE International Conference on Vehicular Electronics and Safety, Columbus, pp. 132-136.
12. Kostikj, A., Kjosevski, M., Kocarev, L., 2012. Harmonized traffic stream in urban environment based on adaptive Stop&Go cruise control and its impact on traffic flow. In: IEEE International Conference on Vehicular Electronics and Safety, pp. 140-145.
13. Liu Z.Q., Wang P., Qin H.M., et al. Study on intelligent anti-collision for warning technology based on multi-information detection. China Saf. Sci. J. 2010, 20(1):153-158.
14. Li X.R., Jilkov V.P. Survey of maneuvering target tracking. Part I: Dynamic models. IEEE Trans. Aerosp. Electron. Syst. 2003, 39(4):1333-1364.
15. Lidstrom, K., Larsson, T., 2008. Model-based estimation of driver volitions using particle filter. In: IEEE Int. Conf. Intelligent Transportation Systems, pp. 1177-1182.
16. Lou J., Tan T., Hu W., Yang H., Maybank S. 3-D model-based vehicle tracking. IEEE Trans. Image Process. 2005, 14(10):1561-1569.
17. Hou D.Z., Liu G., Gao F., Li K.Q., Lian X.M. A new safety distance model for vehicle collision avoidance. Automot. Eng. 2005, 27(2):186-190.
18. Milanés V., Alonso J., Bouraoui L., Ploeg J. Cooperative maneuvering in close environments among cybercars and dual-mode cars. IEEE Trans. Intell. Transp. Syst. 2011, 12(1):15-24.
19. Mobus, R., Baotic, M., Morari, M., 2003. Multi-object adaptive cruise control. In: Proc. Int. Conf. Hybrid Systems: Computation and Control, pp. 359-374.
20. Nekoui, M., Daiheng, N., Pishro-Nik, H., Prasad, R., Kanjee, M.R., Hui, Z., Thai, N., 2009. Development of a VII-enabled prototype intersection collision warning system. In: Proc. Int. Conf. Testbeds and Res. Infrastructure for Development of Networks & Communities, pp. 1-8.
21. Petrovskaya A., Thrun S. Model based vehicle detection and tracking for autonomous urban driving. Auton. Robots 2009, 26:123-139.
22. Polychronopoulos, A., Scheunert, U., 2006. Revisiting the JDL model for automotive safety applications: the PF2 functional model. In: Proceedings of Information Fusion, pp. 1-7.
23. Polychronopoulos A., Tsogas M., Amditis A.J., Andreone L. Sensor fusion for predicting vehicles' path for collision avoidance systems. IEEE Trans. Intell. Transp. Syst. 2007, 8(3):549-562.
24. Rendon-Velez, E., Horváth, I., Opiyo, E.Z., 2009. Progress with situation assessment and risk prediction in advanced driver assistance systems: A survey. In: Proceedings of the 16th ITS World Congress, pp. 21-25.
25. Schubert R., Schulze K., Wanielik G. Situation assessment for automatic lane-change maneuvers. IEEE Trans. ITS 2010, 11(3):607-616.
26. Sorstedt J., Svensson L., Sandblom F., Hammarstrand L. A New Vehicle Motion Model for Improved Predictions and Situation Assessment. IEEE Trans. ITS 2011, 12(4):1209-1219.
27. Sukuvaara T., Nurmi P. Wireless traffic service platform for combined vehicle-to-vehicle and vehicle-to-infrastructure communications. IEEE Wirel. Commun. 2009, 16(6):54-61.
28. Tan H., Huang J. DGPS-based vehicle-to-vehicle cooperative collision warning: engineering feasibility viewpoints. IEEE Trans. Intell. Transp. Syst. 2006, 7(4):415-428.
29. Toledo-Moreo R., Zamora-Izquierdo M.A., Ubeda-Miarro B., Gomez-Skarmeta A.F. High-integrity IMM-EKF-based road vehicle navigation with lowcost GPS/SBAS/INS. IEEE Trans. Intell. Transp. Syst. 2007, 8(3):491-511.
30. Toledo-Moreo R., Zamora-lzquierdo M.A. Collision avoidance support in roads with lateral and longitudianal manuver prediction by fusing GPS/IMU and digital maps. Transp. Res. Part C Emerg. Technol. 2010, 18(4):611-625.
31. Ullah, I., Ullah, Q., Ullah, F., Shin, S.Y., 2012. Integrated collision avoidance and tracking system for mobile robot. In: International Conference on Robotics and Artificial Intelligence, pp. 68-74.
32. Wang J.Q., Wang H.P., Liu J.X., Li K.Q. Intersection vehicle driving assistance system based on vehicle to infrastructure communication. China J. Highway Transp. 2013, 26(4):169-175.
33. Wu C.Z., Wang C.Y., Yang L.B. Research on fuzzy control of lateral control in intelligent highway system. J. Highway Transp. Res. Dev. 2002, 19(2):131-133. 137.