Time-to-contact control: improving safety and reliability of autonomous vehicles

Abstract

Under traditional car-following control, i.e., human drivers' behaviour, the stability condition of traffic system is not satisfied in general. For safety and reliability of autonomous vehicles, additional danger warning system must be used in the adaptive cruise control system to prevent inevitable potential collisions. One reasonable quantity of evaluating potential collisions is time to contact (TTC): how soon will potential collision occur? In this paper, we provide TTC feedback control to improve safety and reliability of autonomous vehicles, and show the effectiveness of TTC feedback. TTC can be estimated by machine vision techniques with single uncelebrated camera (i.e., passive sensors). We provide detailed mathematical analysis and algorithmic implementation. The machine vision-based TTC algorithm is pretty fast such that the whole system can be implemented on Android smartphones running in real-time. Moreover, it is not trial to estimate relative velocity by differentiating the measured distance between cars with respect to time, because inevitable measurement noise in the distance measurements will be amplified by the derivative operation. The time-to-contact-based algorithm provides an alternative approach to estimating the relative velocity, which can also be fused with measurements from other active sensors, if desired.