Ecomobility above all requires new behaviours

Science topics November 2013 EnergyMaterials and structures

Two of the leaders of the « Mobility » task in the IFSTTAR goals contract (2013-2016), both senior researchers, Samuel Sellam and Ludovic Leclercq, describe the Institute’s work in the area of ecomobility. This is a complex topic where the behaviour of users interacts with the management of mobility systems by operators and where we need to give a lot attention to improving each transport mode (personal or public) and optimising their combined operation (multimodality and intermodality).


« Ecomobility will improve the efficiency of transportation while at the same time reducing its energy footprint and pollutant emissions, Samuel Sellam explains briefly. “Apart from new technology – which is what provides the main potential for progress − we need to optimise present-day systems to reduce the consumption of each transport mode. But, above all, we need to change behaviours to encourage economical driving, the use of more efficient transport modes and greater use of mobility services. »


« As always, we are targeting both technologies and behaviours », Ludovic Leclercq continues. In particular, IFSTTAR is studying the reactions of drivers and how well they understand information about eco-driving. When all the technological improvements have been implemented and the goal of 2 l/100km has been achieved, progress in this area will still be possible: the gain can reach or even exceed 10% of fuel consumption (and therefore greenhouse gas emissions). « We are particularly interested in ways of exploiting the somewhat unexpected final recommendations about eco-driving that had been made by the Institute’s researchers », Samuel Sellam explains. « For example, the benefits of reaching one’s cruising speed rapidly rather than driving smoothly ». A prototype human-machine interface is currently being tested on a driving simulator with a view to visually informing drivers about the optimum driving behaviour in relation to their journey and the traffic, and testing their understanding and reactions.


With regard to operators progress all over the world is impressive, in particular in the area of optimised bus management. In this context, at Versailles IFSTTAR has tested improved centralised control of signalised intersections in order to optimise bus flow. « To take another example, in order to improve the efficiency of bus routes and reduce bus fuel consumption, we are developing an algorithm to help drivers manage their speed depending on their journey and the position of the other buses on the route » Ludovic Leclercq adds.

To optimise mobility, we need to optimise each mode of transport, and also foster intermodality to make it easy to change from one mode to another. IFSTTAR is developing techniques to provide users with a choice of multimodal journeys.


« In addition, new technology is completely revolutionising data collection, Ludovic Leclercq adds. For example, we are planning to monitor the trips of the panel of volunteers using applications on their smartphones in order to understand their behaviour and motivations. The data we will collect will also enable us to provide real-time information, the ultimate goal being for people to let their telephones choose their transport mode for them. Last, the data should help us optimise the entire system, which is particularly complex to model. » This is especially true in France where each operator manages its network locally. « Our multimodal traffic management systems already enable operators to better control their network,as is the case in Toulouse or Brussels, Samuel Sellam mentions. The ultimate aim is the integrated multimodal management of road traffic and public transport flows. We are a long way from achieving this: we know how to measure flows, but not full journeys, and we are not able to take sufficient account of how supply impacts demand or how congestion affects behaviours. » IFSTTAR is also studying the impact of new services such as bike- and car- sharing, with a particular focus on Paris, in order to analyse the motivations of users and their journeys based on data from transport managers.