Multisensor data fusion for OD matrix estimation

Knowledge of traffic demand at a junction is crucial for most transport systems. Generally, it is represented by an origin-destination (OD) matrix, where each element is a volume of vehicle flow between one of the OD pair of zones of a junction. This paper introduces a new method for a short-time es...

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Veröffentlicht in:2009 IEEE International Conference on Systems, Man and Cybernetics S. 3024 - 3029
Hauptverfasser: Biletska, K., Masson, M.-H., Midenet, S., Denux, T.
Format: Tagungsbericht
Sprache:Englisch
Veröffentlicht: IEEE 01.10.2009
Schlagworte:
Buildings
Cameras
Cybernetics
Equations
fuzzy linear programming
fuzzy modelling
Fuzzy sets
Linear programming
origin-destination matrix estimation
Recursive estimation
Road vehicles
Uncertainty
Yield estimation
ISBN:9781424427932, 1424427932
ISSN:1062-922X
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Zusammenfassung:Knowledge of traffic demand at a junction is crucial for most transport systems. Generally, it is represented by an origin-destination (OD) matrix, where each element is a volume of vehicle flow between one of the OD pair of zones of a junction. This paper introduces a new method for a short-time estimation of OD matrices at a signalised junction with a complex structure and fitted out with video cameras. The estimation is made by taking into account the traffic lights and by fusion of different multisensor traffic data, which are subject to imprecision and uncertainty. The method proceeds in two steps. First, vehicle conservation law, expressed in terms of undetermined system of equations, is built dynamically for a short-time period. Second, four approaches, that overcome the system indetermination and model the data imperfection, are proposed to provide the best and unique estimates of the OD matrix. An experimental study has been made with data collected at the real signalised junction.
ISBN:9781424427932
1424427932
ISSN:1062-922X
DOI:10.1109/ICSMC.2009.5345929