This paper describes the use of a new pervasive sensors network, developed at Newcastle, in the context of the project MESSAGE, jointly funded by EPRSC and the DfT, to evaluate automatically the impacts of traffic demand management strategies on congestion and the environment. Analysis of the calibrated data from static (located on street furniture) and mobile (in car) pervasive sensors, called motes, deployed in a case study area (Gateshead) will be presented. Next the mechanism by which the mote data are used to validate parameters of traffic simulation models (flows, queues, travel times, etc) across the urban network will be shown. A simple dispersionmodel that uses the emissions estimation from the traffic micro-simulation is validated using pervasive sensor data collected along the links in the study area. Results presented in this paper are at an early stage but will highlight the benefits of pervasive sensors and how they can complementlegacy systems through covering detection gaps in existing urban networks.
Samenvatting