Overview
The city of Rennes is the central hub of communications in Britain region, connecting with the neighbouring regions of Lower Normandy and Pays de la Loire. Rennes is served by a network of highways, railways and also has an airport, located southwest of the town.
Public authorities play an important role to boost sustainable mobility practices aimed in particular to reduce the use of private cars and to develop the use of public transport, alone or in combination with other transport modes.
Intermodality facilitates a more efficient and integrated use of different means of transport for users. The provision of coordinated services - both in space and time - is a fundamental prerequisite for offering well-functioning and appealing transport services to users.
Spatio-temporal data generated by advanced ticketing system provide precise information in terms of mobility traceability, since all trips can be recorded and analysed. These data offer interesting inputs for better monitoring mobility patterns and improve intermodality, being complementary to mobility investigations conventionally used (such as Moving Household Survey, origin-destination survey, etc.).
The project aimed at using ticketing data and information, in order to develop a well-defined number of databases as tools to better analyse different existing transport modes, to improve the understanding of the use of each mode, their drivers and obstacles to encourage the use of public transport and soft mobility modes (foot, bike sharing, etc.).
The project has been divided into six specific tasks:
- State of the art
- Description, collection and arrangement of data
- Exploratory analysis of data
- Comparative analysis of ticketing data
- Intermodality
- Analysis of mobility behaviours and impact of the weakness of the transport system
The ticketing data have the advantage of being available without a dedicated development (unlike surveys). This considerable amount of spatio-temporal data put the problem of modelling in a new methodological context for assessing mobility patterns, and intermodality in particular. The field analysis is more extended, since the information collected is distributed along the network and include all transport modes that manage ticketing systems. Several keywords can be evoked to describe this new methodological context: spatial data, longitudinal data, mass data, time tracking.
Funding
Results
The applications developed within the project contributed to achieve the following results:
- More precise comprehension of spatio-temporal patterns related to the use of different modes of transport, thanks to exploratory data analysis
- Support for the planning and design of transport offers (location of interconnection points, attractiveness of nodes, planning of public transport, bike-sharing stations)
- Assistance in the operation of transport modes in connection (traffic of bike stations, grids TC interval timetables, joint with the park and ride)
- Definition of obstacles that hinder a wider diffusion of intermodality
- Understanding of the overall reliability of the transport system