Modelling Environmental Impacts of Traffic Using a New Generation of Pervasive Sensors Bell, Margaret C ; Galatioto, Fabio ; Hill, Graeme ; Namdeo, Anil
Utgivningsinformation: Bryssel ITS in daily life: 16th world congress and exhibition on intelligent transport systems and services, Stockholm 21-25 September 2009. Paper, 2009Beskrivning: 8 sÄmnen: Bibl.nr: VTI P1835:16 [World]Location: Abstrakt: 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 dispersion model 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 complement legacy systems through covering detection gaps in existing urban networks.| Aktuellt bibliotek | Status | |
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| Statens väg- och transportforskningsinstitut | Tillgänglig |
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 dispersion model 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 complement legacy systems through covering detection gaps in existing urban networks.