Traffic situation estimator for Adaptive Cruise Control

Abstract

A traffic situation estimator capable of analyzing driving behavior utilizing an image analysis-based tracking module is presented. The behavior is analyzed by using a state machine driven counter to estimate the traffic rhythm and determine if the detected vehicles are approaching, getting away, have been overtaken or have overtaken the ego-vehicle. Depending on the result, the traffic situation estimator suggest different reactions, either to drive faster, slower or optionally suggest to overtake vehicles ahead to help the driver to follow the traffic rhythm which in turn will improve safety and energy efficiency. The proposed approach is implemented in a smart-phone and has shown good performance while testing the application on a two-lane highway.