Abstract
This study aims to reduce the severity of injuries caused by and the frequency of rear-end vehicle collisions. A better collision prediction method is proposed by means of millimeter-wave radar sensors able to rapidly detect potential collisions and alert drivers. Implementation of the system would bring about a reduction in accidents and potentially reduce the severity of the accidents that cannot be avoided. The proposed collision avoidance system adopted millimeter-wave radar sensors to collect information on vehicle’s rear surroundings. The designed experimental device has several unique features. The device has a wide monitoring range, incorporates a continuous detection process, and contains a rapid warning system. A series of real-world experiments were performed on cars (Model: Tercel 1.5, Toyota) to demonstrate the monitoring efficiency and warning frequency of this device under several operating conditions. This study furthered the development of a safe technology for avoidance of rear-end collisions, and this offers a novel system which can be used in a variety of vehicles to reduce the frequency of rear-end vehicle collisions.
Similar content being viewed by others
References
Alonso, J. D., Vidal, E. R., Rotter, A. and Muhlenberg, M. (2008). Lane-change decision aid system based on motion-driven vehicle tracking. IEEE Trans. Vehicular Technology 57, 5, 2736–2746.
Brembeck, J. and Winter, C. (2014). Real-time capable path planning for energy management systems in future vehicle architectures. Proc. IEEE Intelligent Vehicles Symp. (IV), Dearborn, Michigan, USA.
Distner, M., Bengtsson, M. and Broberg, T. (2009). City safety-a system addressing rear-end collisions at low speeds. Proc. 21st Int. Technical Conf. Enhanced Safety of Vehicles, Stuttgart, Germany.
Galvani, M., Biral, F. and Nguyen, B. M. (2014). Four wheel optimal autonomous steering for improving safety in emergency collision avoidance manoeuvres. Proc. 13th Int. Workshop on Advanced Motion Control, Yokohama, Japan.
Gehrig, S. and Stein, F. (2007). Collision avoidance for vehicle-following systems. IEEE Trans. Intelligent Transportation Systems 8, 2, 233–244.
Hassanzadeh, M., Lidberg, M. and Keshavarz, M. (2012). Path and speed control of a heavy vehicle for collision avoidance manoeuvres. Proc. IEEE Intelligent Vehicles Symp. (IV), Alcala de Henares, Spain.
Isermann, R., Mannale, R. and Schmitt, K. (2012). Collision-avoidance systems PRORETA: Situation analysis and intervention controltem. Control Engineering Practice 20, 11, 1236–1246.
Knoll, P. M. (2006). Predictive safety systems: Convenience-collision mitigation-collision avoidance. SAE Paper No. 2006-21-0082.
Kuo, Y. C., Pai, N. S. and Li, Y. F. (2011). Vision-based vehicle detection for a driver assistance system. Computers & Mathematics with Applications 61, 8, 2096–2100.
Lemelson, J. H. and Pedersen, R. D. (1999). GPS Vehicle Collision Avoidance Warning and Control System and Method. U.S. Patent No. 5,983,161.
Liu, J. F., Su, Y. F., Ko, M. K. and Yu, P. N. (2008). Development of a vision-based driver assistance system with lane departure warning and forward collision warning functions. Digital Image Computing: Techniques and Applications, Canberra, Australia.
Nehaoua, L. and Nouveliere, L. (2012). Back stepping based approach for the combined longitudinal-lateral vehicle control. Proc. IEEE Intelligent Vehicles Symp. (IV), Alcala de Henares, Spain.
Oh, C., Kang, Y. S., Youn, Y. and Konosu, A. (2008). Development of probabilistic pedestrian fatality model for characterizing pedestrian-vehicle collisions. Int. J. Automotive Technology 9, 2, 191–196.
Qualizza, G. K. (1993). Vehicle Collision Avoidance System. U.S. Patent No. 5,235,316.
Sato, T. and Akamatsu, M. (2008). Preliminary study on driver acceptance of multiple warnings while driving on highway. Proc. IEEE SICE Annual Conf., Tokyo, Japan.
Sengupta, R., Rezaei, S., Shladover, S. E., Misener, J. A., Dickey, S. and Krishnan, H. (2007). Cooperative collision warning systems: Concept definition and experimental implementation. J. Intelligent Transportation Systems 11, 3, 143–155.
Sivaraman, S. and Trivedi, M. M. (2013). Looking at vehicles on the road: A survey of vision-based vehicle detection, tracking, and behavior analysis. IEEE Trans. Intelligent Transportation Systems 14, 4, 1773–1795.
Tak, S., Woo, S. and Yeo, H. (2016). Study on the framework of hybrid collision warning system using loop detectors and vehicle information. Transportation Research Part C: Emerging Technologies, 73, 202–218.
Takahashi, A. and Asanuma, N. (2000). Introduction of Honda ASV-2 (advanced safety vehicle-Phase 2). Proc. IEEE Intelligent Vehicles Symp., Dearborn, Michigan, USA.
Tan, H. S. and Huang, J. (2006). DGPS-based vehicle to vehicle cooperative collision warning: Engineering feasibility viewpoints. IEEE Trans. Intelligent Transportation Systems 7, 4, 415–428.
Teng, T. L., Le, T. K. and Ngo, V. L. (2010). Injury analysis of pedestrians in collisions using the pedestrian deformable model. Int. J. Automotive Technology 11, 2, 187–195.
Wang, P. W., Wang, L., Li, Y. H. and Guo, W. W. (2015). Improved cooperative collision avoidance (CCA) model considering driver comfort. Int. J. Automotive Technology 16, 6, 989–996.
You, F., Zhang, R. and Lie, G. (2015). Trajectory planning and tracking control for autonomous lane change maneuver based on the cooperative vehicle infrastructure system. Expert Systems with Applications 42, 14, 5932–5946.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Chen, YS., Chiu, SC. & Hsiau, SS. Safe Technology with a Novel Rear Collision Avoidance System of Vehicles. Int.J Automot. Technol. 20, 693–699 (2019). https://doi.org/10.1007/s12239-019-0065-0
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12239-019-0065-0