4 research outputs found
On-Board Traffic Prediction for Connected Vehicles: Implementation and Experiments on Highways
An on-board traffic prediction algorithm is pro-
posed for connected vehicles traveling on highways. The pre-
diction is based on data received from other connected vehicles
ahead in the traffic stream, leveraging the fact that a vehicle will
enter the traffic that other vehicles ahead have already met. Our
method includes traffic state estimation with Kalman filter and
prediction via traffic flow models describing the propagation of
congestion waves. The end result is an individualized speed
preview in real time up to about half a minute for the
connected vehicle executing prediction. Most importantly, the
traffic prediction was successfully implemented on board of
a real vehicle and predictions were tested in real traffic with
experiments involving connected human-driven vehicles
Traffic reconstruction using autonomous vehicles
International audienc