摘要：Abstract Introduction 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.
