  Major cause of midvehicle collision is due to the distraction of drivers in
both the Front and rear-end vehicle witnessed in dense traffic and high speed
road conditions. In view of this scenario, a crash detection and collision
avoidance algorithm coined as Midvehicle Collision Detection and Avoidance
System (MCDAS) is proposed to evade the possible crash at both ends of the host
vehicle. The method based upon Constant Velocity (CV) model specifically,
addresses two scenarios, the first scenario encompasses two sub-scenario
namely, a) A rear-end collision avoidance mechanism that accelerates the host
vehicle under no front-end vehicle condition and b) Curvilinear motion based on
front and host vehicle offset (position), whilst, the other scenario deals with
parallel parking issues. The offset based curvilinear motion of the host
vehicle plays a vital role in threat avoidance from the front-end vehicle. A
desired curvilinear strategy on left and right sides is achieved by the host
vehicle with concern of possible CV to avoid both end collisions. In this
methodology, path constraint is applicable for both scenarios with required
direction. Monte Carlo analysis of MCDAS covering vehicle kinematics
demonstrated acute discrimination with consistent performance for the collision
validated on simulated with real-time data.
