An adaptive cruise control (ACC) which was implemented on an AIT Intelligent Vehicle, a Mitsubishi Galant car, has been improved and added with more features to allow the vehicle to act with better performance compared with the previous system. An important feature of the new adaptive cruise control system is the ability to maintain a proper inter-vehicle gap based on the speed of leading vehicle and time headway (THW). To develop adaptive cruise control system, the conventional throttle valve system is modified to the drive-by-wire system which uses a DC motor to control the throttle valve position based on PD control with command compensation. In the automatic braking system, a DC motor is installed with steel cable transmission in order to pull the brake pedal to the desired level automatically by applying torque control. The brake control and velocity control have been merged together to control the speed to any desired speeds as fast as possible without jerk and steady-state error. A micro switch is installed at the brake pedal to allow the driver to take over the control of the vehicle anytime. There are three important inputs of the ACC system, speed of leading vehicle read from electronic control unit (ECU), THW set by driver, and actual gap measured from a laser scanner. The ACC processes these three inputs in order to calculate distance error and relative velocity which are used as the two inputs of a fuzzy controller. The fuzzy controller determines the desired speed command to maintain a proper gap based on current speed of the leading vehicle and the desired time headway. Experiments are conducted to evaluate the performance of the ACC system in various conditions. The results show good performance of the adaptive cruise control system.
[1]
Rajesh Rajamani,et al.
Model predictive control of transitional maneuvers for adaptive cruise control vehicles
,
2004,
IEEE Transactions on Vehicular Technology.
[2]
Richard Bishop,et al.
Intelligent Vehicle Technology and Trends
,
2005
.
[3]
W. D. Jones,et al.
Keeping cars from crashing
,
2001
.
[4]
Daniel Axehill,et al.
Adaptive Cruise Control for Heavy Vehicles : Hybrid Control and MPC
,
2003
.
[5]
Manukid Parnichkun,et al.
Adaptive cruise control for an intelligent vehicle
,
2009,
2008 IEEE International Conference on Robotics and Biomimetics.