TY - GEN
T1 - Urban dynamic origin-destination matrices estimation
AU - Bert, Emmanuel
AU - Chung, Edward
AU - Dumont, André Gilles
PY - 2008/12/1
Y1 - 2008/12/1
N2 - The aim of this paper is to explore a new approach to obtain better traffic demand (Origin- Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.
AB - The aim of this paper is to explore a new approach to obtain better traffic demand (Origin- Destination, OD matrices) for dense urban networks. From reviewing existing methods, from static to dynamic OD matrix evaluation, possible deficiencies in the approach could be identified: traffic assignment details for complex urban network and lacks in dynamic approach. To improve the global process of traffic demand estimation, this paper is focussing on a new methodology to determine dynamic OD matrices for urban areas characterized by complex route choice situation and high level of traffic controls. An iterative bi-level approach will be used, the Lower level (traffic assignment) problem will determine, dynamically, the utilisation of the network by vehicles using heuristic data from mesoscopic traffic simulator and the Upper level (matrix adjustment) problem will proceed to an OD estimation using optimization Kalman filtering technique. In this way, a full dynamic and continuous estimation of the final OD matrix could be obtained. First results of the proposed approach and remarks are presented.
KW - destination matrices estimation
KW - Dynamic traffic assignment
KW - ITS
KW - Origin
KW - Traffic demand
KW - Traffic simulation
KW - Urban network
UR - http://www.scopus.com/inward/record.url?scp=84879069354&partnerID=8YFLogxK
M3 - Conference article published in proceeding or book
AN - SCOPUS:84879069354
SN - 9781615677566
T3 - 15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
SP - 6751
EP - 6765
BT - 15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
T2 - 15th World Congress on Intelligent Transport Systems and ITS America Annual Meeting 2008
Y2 - 16 November 2008 through 20 November 2008
ER -