Traffic state detection with floating car data in road networks

Abstract

A method for a reporting behavior at optimal costs of single vehicles (FCD: floating car data) in road networks with the aim of a high quality of traffic state recognition is presented. It is shown that based on minimum two FCD messages the substantial information of a typical traffic incident in a traffic center can be recognized. The two relevant periods of such an obstruction of traffic in road networks are the periods, in which either a travel time increase takes place due to congestion emergence or a travel time decrease because of congestion dissolution. A statistic analysis already shows the high quality of the reconstruction of the actual travel times in the net with 1.5% equipped FCD vehicles and a reduction of the FCD message sending of the vehicles by suppression of redundant incident information. Incidents with at least 20 min duration can be recognized with a probability of 65% with an penetration rate of 1.5% FCD vehicles within the whole amount of vehicles, whereby the FCD vehicles send only in each incident case two messages per event.