The week's pick
Random Articles
Reseach Article
Neural Network based ACC for Optimized safety and comfort
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 42 - Number 14 |
| Year of Publication: 2012 |
| Authors: Merry Cherian, S. Paul Sathiyan |
10.5120/5758-7873
|
Merry Cherian, S. Paul Sathiyan . Neural Network based ACC for Optimized safety and comfort. International Journal of Computer Applications. 42, 14 ( March 2012), 1-4. DOI=10.5120/5758-7873
Abstract
In recent years many studies on intelligent vehicles have been devoted to solve problem such as accident prevention, traffic flow smoothing. Adaptive Cruise Control (ACC) is used to maintain a constant safe distance between the host vehicle and the leading vehicle to avoid rear end collisions. It is an automotive feature that allows the speed of the vehicle to adapt to the traffic environment. ACC operates in distance control mode and velocity control mode. The method by which the ACC vehicle's speed is controlled is via engine throttle control and limited brake operation. The inter vehicular distance between the vehicle is measured. Desired speed is obtained from the distance measured. Neural Network Controller is trained to produce the desired acceleration and braking. In this paper, ACC is implemented using three types of Neural Network such as Back Propagation Network (BPN),Radial Basis Network (RBN) and Generalized Regression Neural Network (GRNN). Among the three it is observed that during safety conditions BPN tracks the speed better and during comfort conditions RBN acts best.
References
- Sakda Panwai, and Hussein Dia, "Neural Agent Car-following Models,"IEEE Trans. Intell. Transp. Syst. , vol 8,no. 1,pp. 60-70,March 2007.
- P. Venhovens, K. Naab and B. Adiprasito "Stop and Go Cruise Control",International Journal of Automotive Technology, Vol. 1, no. 2, pp. 61-69. 2000
- John-Jairo Martinez and Carlos Canudas-de-Wit "A Safe Longitudinal Control for Adaptive Cruise Control and Stop-and-Go Scenarios" IEEE Trans. Control Systems Technology, vol. 15, no. 2, pp. 246-258 March. 2007
- Sungwoo CHOI, Brigitte d'andr' ca-novel, Michel FLIESS, Hugues Mounier, Jorge VILLAGRA, "Model-free control of automotive engine and brake for Stop-and-Go scenarios," European control conference, 2009
- Luke Ng, Christopher M. Clark, and Jan P. Huissoon, "Reinforcement Learning of Adaptive Longitudinal Vehicle Control for Dynamic Collaborative Driving" proceedings of the IEEE Intelligent Vehicles Symposium, Eindhoven University of Technology Eindhoven, The Netherlands, June 4-6,2008
- Yang Bin, Keqieng Li, Xiaomin Lian Hiroshi Ukawa, Masatoshi Handa, Hideyuki Idonuma "Longitudinal Acceleration Tracking Control of Vehicular Stop-and-go Cruise Control System", Proceedings of the 2004 IEEE Int. Conf . Networking, Sensing & Control pp 607-612, Taiwan, March 21-23,2004
- Kyongsu Yi, Ilki Moon and Young Do Kwon "A Vehicle-to-Vehicle Distance Control Algorithm for stop Stop-and-go Control", in Conf. Rec. 2001 IEEE. Conf. Intelligent Transportation Systems, pp 478-482
- Jose' E. Naranjo, Carlos Gonzalez, Member, IEEE, Ricardo Garcia, and Teresa de Pedro "ACC+Stop&Go Maneuvers with the Throttle and Brake Fuzzy Control",IEEE Trans. Intelligent Transportation Systems. , vol. 7, no. 2,pp 213-225,June 2006
- Nassaree Benalie, Worrawut Pananuruk, Somphong Thanok, and Manukid Parnichkun "Improvement of Adaptive Cruise Control System based on Speed Characteristics and Time Headway" IEEE/RSJ Int. Conf on Intelligent Robots and Systems. , pp. 2403-2408 October 2009.
- S. Paul Sathiyan and A. Wisemin lins,"Soft Computing Based Adaptive Cruise Control",Indian Journal Of Computer Science and Engineering(IJSCE),vol 2,no. 1,pp. 68-76,2011
- Vicente Milanes, Jorge Villagra, Jorge Godoy, and Carlos Gonzalez, Member, IEEE," Comparing Fuzzy and Intelligent PI Controllers in Stop-and-Go Manoeuvres",IEEE Trans. On Control Systems Technology,pp. 1-9,2011.
- Rudwan Abdullah,Amir Hussain,Kevin Warwick,Ali Zayed, "Autonomous intelligent cruise control using a novel multiple-controller framework incorporating fuzzy-logic-based switching and tuning",ELSEVIER(2008),pp. 2727-2741.
Index Terms
Keywords