RealTime Forward Collision Alert System using Raspberry Pi Most new luxury cars often comes with some form of driving assistance systems to reduce the risk of car accidents  such as the lane departure warning system, automatic parking, antilock braking system(ABS), blind spot monitor and forward collision warning system. These systems are developed to enhance the car safety and to provide a safer driving conditions. Due to its cost and design, these systems, often are only available in luxury cars. The main purpose of this work is to propose a realtime lowcost Forward Collision Alert System (FCAS). The FCAS are able to alert drivers, when their cars are getting too close to the front vehicle by estimating the speed of the car in front, using a loud beeping sound. The FCAS is then embedded onto a Raspberry Pi for realtime. Experimental results shows that the system can reliably alert the driver, in realtime, when a moving vehicle in front position is too close.

A Method for Crash Prediction and Avoidance Using Hidden Markov Models In recent years, automotive technology has made a steady progress. In particular, Advanced Driver Assistance System (ADAS) has enabled many safety features in commercial vehicles, for instance, pedestrian detection, lane keeping assist, emergency automatic braking, etc. Although these features provide drivers with a safer operational environment, crashes still happen occasionally due to the complex road conditions and the unpredictable movement of road users including vehicles, pedestrians, bicyclists, and nonmotorized vehicles. In this paper, we aim at predicting the possibilities of crashes between vehicles on highway and implementing an appropriate active safety system to prevent the same. In particular, hidden Markov models are developed for the traffic lanes and speed change of vehicles on highway. Algorithms are developed for the prediction of crash probabilities. Simulation experiments are conducted using Matlab, the results illustrate the effectiveness of the proposed research.