Congestion on road networks causes severe problems in and around large cities. Since societal and environmental constraints prohibit large-scale extension of available network infrastructure, solutions need to be sought in using the existing traffic networks more efficiently. Dynamic Traffic Management (DTM) provides efficient tools to reduce the afore mentioned problems within the boundaries of a sustainable transportation system. The central research issue of the AMICI programme described in this paper is 'the development of advanced traffic management for integrated and coordinated management of mixed traffic networks'. To this end, accurate models for predicting travel behavior and its relationship with information and control, as well as traffic models to forecast future network conditions are needed to ensure high quality, efficient and consistent anticipatory information and control. Traveler behavior and its dependence on advanced traffic management measures are therefore important research topics. Behavioral research has to identify determinants of traveler's sensitivity to travel information and control. This paper provides an overview of the main results achieved within the AMICI programme so far. This in particular pertains to the impact of information on traveler behavior in uncertain conditions, including the effect of the information form, content and price. Furthermore, we will present the traffic flow models for predicting traffic flow operations in mixed networks (urban and motorway) that have been developed, as well as the approaches to integrated and coordinated control that have been developed so far. (Author/publisher)
Samenvatting