mode of interaction between traffic control systems and road-users (one-way flow of information) to an active mode. The integration of data concerning traffic flows and individual journey plans thus makes it possible to perform optimisation of travel. This paper focuses on the issue of provision

. The focus of this research effort is to develop a tool to study the repercussions of evacuation of an entire regional transportation network recognizing the human behavior element. Neglecting these seemingly chaotic traffic flow patterns would lead to inaccurate system assessment and predictions. We study

Copenhagen to a project with Prof. Stefania Serafin. The work that we would like to do together is related to an ongoing project about a well known HCI predictive model in an audio perspective: the Fitts ’ model has been analyzed providing different audio interactive displays and interfaces

behavior in a queuing network. In this respect, we propose an activity-based predictive dynamic traffic assignment model based on a multi-agent approach with two interacting levels: the travelers ’ adaptive reaction level and the network propagation level. For the first level, traffic conditions change

20 vitally important in transportation planning and have been emphasized in several macro-level studies during the past few years. Macro-level analyses of crash prediction models have been attempted for census block groups; traffic analysis zones (TAZs); census tracts; and counties considering

Due to rapid urban developments in developing cities, the integration of land-use and transportation planning is very necessary. However, upto-date land-use and transportation interaction planning is still difficult, because of rapid urbanization and complex relationships. The lack of human

-based application that offers users a familiar and powerful data manipulation interface for evaluation of abstracted networks’ improvements and modifications, versus a base case scenario, relying largely on traffic counts. The toolkit includes a travel demand prediction module for destination, mode, time of day

ii Internet broadcasting techniques are wide spread and have been the focus off many research projects. Due to high transmission delays these systems often lack interactivity. This thesis introduces a new streaming system to deliver real-time video and audio data with low-delays across the Internet

to transfer from one mode to another during a trip from an origin to a destination. The model may be used in the transportation planning field to make predictions regarding future network activity in terms of traffic volumes and travel costs, to evaluate alternative policies for mitigating congestion

to inventory the operational experience and traffic impact information associated with all recorded incidents. The prediction module is developed to predict the information of maximum queue length and incident duration predictions. The simulation module, developed with design plans for construction, contains