Effectiveness of link and path information on simultaneous adjustment of dynamic O-D demand matrix

The paper deals with the adjustment of time-dependent Origin-destination (O-D) demand matrix, which is the fundamental input of ITS application for traffic predictions. The usual problem is to search for temporal O-D matrices that are "near" an a priori estimate (seed matrices) and that best fit traffic counts. However information on link flows is not fully effective in describing the state of the network; recent technologies for tracking vehicles provide a new kind of information on route travel times that can integrate usual information on traffic flows at count sections. Objective: The object of the paper is to analyse the effectiveness of different types of information in the off-line simultaneous adjustment of dynamic O-D demand, starting from seed matrices with different degrees of reliability.