Inter-vehicle communication using fuzzy controller for safety application

Intelligent Transportation System (ITS) is a new field of study started from the mid of 1980s. It emerged most of the high technology and improvements in information system, computer science, mathematical models, communication systems, sensors, and robotic mechanism inside an Intelligent Vehicle (IV). Inter-Vehicle Communication (IVC) is the communication system within the ITS which enables the Vehicle to share information between each other in many aspects such as, current car condition, accident ahead, pre-accident alert and others. The main focus here is to construct a fuzzy controller to determine the current direction, current velocity of the vehicle and the road condition using Infrared Sensor and CMOS Camera then control the vehicle to stay within the road in some road conditions. The purpose of using the fuzzy controller is due to the highly reliable, efficiency and low complexity of the controller compare with conventional controller. Using the vehicle controlling system, we can construct a safety system to avoid any collision to the obstacle ahead and thus accident can be avoided.

[1]  Linda Z. Shi,et al.  A Fuzzy Logic Controller for Autonomous Wheeled Vehicles , 2006 .

[2]  Dzuraidah Abd. Wahab,et al.  Decision fusion of a multi-sensing embedded system for occupant safety measures , 2010 .

[3]  Mukesh Tiwari,et al.  Fuzzy Logic of Speed and Steering Control System for Three Dimensional Line Following of an Autonomous Vehicle , 2010, ArXiv.

[4]  Koren,et al.  Real-Time Obstacle Avoidance for Fast Mobile Robots , 2022 .

[5]  Nader Mohamed,et al.  Inter-vehicular Communication Systems, Protocols and Middleware , 2010, 2010 IEEE Fifth International Conference on Networking, Architecture, and Storage.

[6]  Hilmi Sanusi,et al.  VEHICLE CRASH ANALYSIS FOR AIRBAG DEPLOYMENT DECISION , 2006 .

[7]  Liping Chen,et al.  A fuzzy control strategy and optimization for four wheel steering system , 2007, 2007 IEEE International Conference on Vehicular Electronics and Safety.

[8]  Salina Abdul Samad,et al.  System Interface for an Integrated Intelligent Safety System (ISS) for Vehicle Applications , 2010, Sensors.

[9]  Murali C. Krishna,et al.  Fuzzy Logic Reasoning to Control Mobile Robot on Pre-defined Strip Path , 2008 .

[10]  Wei-Song Lin,et al.  A stable neuro-fuzzy controller for output tracking in composite nonlinear systems , 1997, 1997 IEEE International Conference on Intelligent Processing Systems (Cat. No.97TH8335).

[11]  C. Dolea,et al.  World Health Organization , 1949, International Organization.

[12]  Piero P. Bonissone,et al.  Genetic algorithms for automated tuning of fuzzy controllers: a transportation application , 1996, Proceedings of IEEE 5th International Fuzzy Systems.

[13]  Feng Xia,et al.  Fuzzy Logic Based Feedback Scheduler for Embedded Control Systems , 2005, ICIC.

[14]  M A Hannan,et al.  Sensing Systems and Algorithms for Airbag Deployment Decision , 2011, IEEE Sensors Journal.

[15]  Babak Karasfi,et al.  Application of Fuzzy Logic in Mobile Robot Navigation , 2012 .

[16]  Salina Abdul Samad,et al.  Development of an embedded vehicle safety system for frontal crash detection , 2008 .