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This paper presents the design and evaluation of an emergency driving support (EDS) algorithm. The control objective is to assist driver's collision avoidance maneuver to overcome a hazardous situation. To support driver, electrically controllable chassis components such as motor driven power steering (MDPS) and differential braking and surrounding sensor systems such as radar and camera are used. The EDS algorithm is designed for 3 parts: monitoring, decision, and control. The proposed EDS algorithm recognizes a collision danger using minimum lateral acceleration to avoid collision and time-to-collision (TTC) and driver's intention using sensor systems. The control mode is determined using the indices from monitoring process and the collision avoidance trajectory is derived with trapezoidal acceleration profile (TAP).

CW/CA (Collision Warning /Collision Avoidance) Systems have been an active research and development area as interests and demands for the advanced vehicle increase. A CW/CA ‘Hardware-in-the-Loop Simulation (HiLS)’ system has been designed and used to test a CW/CA algorithm, radar sensors, and warning displays under realistic operating conditions in the laboratory. A CW/CA algorithm has two parts. One is a distance decision algorithm that determines the critical warning and braking distance and the other is a brake control algorithm for collision avoidance. The CW/CA HiLS system consists of a controller in which a DSP chip is installed, a preceding vehicle simulator, a radar sensor and a warning display. The controller calculates velocities of the preceding and following vehicles, relative distance and relative velocity of the vehicles using vehicle simulation models. The relative distance and velocity are applied to the vehicle simulator that is controlled by a DC motor.

This paper presents a longitudinal control algorithm for an adaptive cruise control (ACC) with collision avoidance (CA) in multiple vehicle traffic situations. The proposed algorithm consists of a multi-target tracking filter, a primary target selection algorithm and an integrated ACC/CA system. The multi-target tracking filter is used to smooth the sensor signal, and makes it possible to apply to a control system. The primary target selection algorithm decides an in-lane target and provides the information to an integrated ACC/CA system in order to drive a subject vehicle smoothly and improve safety in complex traffic situations. Finally, the integrated ACC/CA system computes the desired acceleration. The performance and safety benefits of the multi-vehicle ACC/CA system is investigated via simulations using real data on driving. Simulation results show that the response of multi-vehicle ACC/CA system is more smooth and safer at a change of traffic situations.