Spatial estimating and analyse of exhaust emissions from individual transports : Assessment of the environmental performance of a demand responsive transport
The Demand Responsive Transport (DRT) is a transportation system which offers a collective use of motor vehicles, in opposite of personal vehicles use. Between the functioning of taxis and classical public transport, it offers a service that is flexible in time and space like taxis, promoting the sharing of vehicles, like public transports. It is why it is present as a solution for a sustainable mobility. In the minds, DRT are often associated to a reduction of exhaust emissions and so are developed in rural areas. However, is grouping travellers enough to make DRT gainful for environment?In this doctoral research, an assessment tool of the environmental impact of DRT systems has been developed. To ensure that choice is sustainable in the sense of sustainable development, the service must be adapted to the local context by minimising emissions of substances in the near atmosphere while maintaining a sufficient quality of service when competing against personal vehicle use. A parameter directly involved in pollutant emissions, is often overlooked in approaches: the road network. We therefore search for identify laws and thresholds relating to pollutant emissions generated by the functioning of a DRT: how the road network does it affect the environmental performance of DRT or on the skill to grouping customers in vehicles? Depending on what service features (time windows allowed)? More generally, is that the optimization of the same type of DRT is equivalent to a road network to another, from the perspective of pollutant emissions? As any integrated tool to perform this task is available, we have developed a geomatics processing to estimate the quantities of pollutants emitted on road sections within the particular functioning of DRT and to cartography it to analyse their spatial distribution. This tool combines a GIS to an exhaust emissions model that we have adapted to our questioning (GREEN-DRT).