Abstract: An autonomous intelligent cruise control system was designed and simulated based on measured relative distance, speed, and acceleration. These constitute the fuzzy inputs. The results have shown that the system can be robust to noisy distance measurements and modular in structure to ease its implementation. A simple way of estimating the road condition was developed, implemented and tested in simulation. The results show that based on the measured relationship between the deceleration and brake pressure, the brake pressure output gain can be adjusted to prevent lock up of the tires and the consequent loss of stability. Two controller implementations were…tested. The first one is based on heuristic knowledge of the system using Mamdani inference system. The second model was based on offline adaptive neuro-fuzzy controller model.
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Abstract: A fuzzy logic based automatic braking system is proposed using distance and relative speed sensors as inputs and brake-pressure as output. Heuristic rules have been developed and implemented. The controller monitors the deceleration rate of the vehicle to prevent tire lock-up and the consequent loss of directional stability. The system offers the flexibility of setting the separation distance. Simulation of the controller for driving into a stationary or moving objects shows that the system is performing well. It also uses an anti lock braking system to decelerate the vehicle and a throttle on-off controller to accelerate the vehicle and maintain…a fixed separation distance and drive behind the object in a tracking mode, i.e., adjusts the speed as obstacles occur.
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