SWOV Catalogus

125735

Reconstruction of Congested Traffic Patterns Using Traffic State Detection in Autonomous Vehicles Based on Kerner’s Three Phase Traffic Theory.
C 47084 (In: C 46669 CD-ROM) /72 /71 / ITRD E852855
Palmer, J. & Rehborn, H.
In: ITS in daily life : proceedings of the 16th World Congress on Intelligent Transport Systems (ITS), Stockholm, Sweden, September 21-25, 2009, 8 p.

Samenvatting In recent years the models ASDA and FOTO based on Kerner's three-phase traffic theory have been successfully applied to the detection and reconstruction of spatio-temporal congested traffic patterns using empirical data measured with stationary inductive loop detectors. Both models have been used in laboratory and online environments on highways in several countries.Another way of measuring traffic conditions in addition to stationary loop detectors is the use of either Floating Car Data (FCD) or Floating PhoneData (FPD), where the individual vehicles represent moving probes. In this paper an approach to the spatio-temporal interpretation of vehicle probedata is described. Instead of transmitting raw data to a processing centre, each probe performs beforehand a local traffic state detection according to Kerner's congested phase definitions of Synchronized Flow and WideMoving Jams and sends only these events to a processing centre or other probes. There a global aggregation of all events received by the probes isperformed in order to detect and reconstruct complete spatio-temporal congested traffic patterns. One of the most important parameters is the number of required probe vehicles in order to be able to detect and reconstructspatio-temporal congested traffic patterns with a specific quality demanded by future vehicle applications. Based on simulation environments this paper evaluates the required probe density and draws conclusions on the achievable reconstruction quality.
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