Road intersections are considered to be bottlenecks for urban transportation whose impacts are longer travel times and wasted human resources. In this paper we focus on vehicle to vehicle communications (V2V) that allow exchanging data between vehicles. Considering that vehicles are controlled by drivers (not autonomous), we do not pretend to take control of them, nor is the goal to avoid collision or improve safety, as is often done elsewhere. By eliminating the potential overlaps of vehicular trajectories coming from all opposing directions at an intersection, our aim is to demonstrate the potential of communication between vehicles in a complex roundabout and test the connexion strength of that network. We test it on a synthetic trace that reproduces a real traffic flow at a roundabout in Creteil (France).

Vehicular networks reflect user mobility behavior and present complex microscopic and macroscopic mobility patterns. Microscopic mobility is often simplified in macroscopic systems and we argue that its impact is too largely neglected. Notwithstanding improvements in realistically modeling and predicting mobility, few vehicular traces -especially complex microscopic ones -are available to validate such models. In this paper, we present a realistic synthetic dataset of vehicular mobility over two daily traffic peaks in a small area: the Europarc roundabout in the town of Creteil, France. We outline how the description and comprehensive representation of local mobility at an intersection, such as the roundabout chosen here, is important for any interpretation made of it.

Intelligent transportation systems that distribute information between roadside infrastructures and vehicles are one of the most promising solutions to the problem of traffic congestion. When most existing ITS solutions are centralized and information-complete, we propose PDLAISa Partial, Decentralized and Locally Autonomous Strategy, tested with an application called Smooth Way, allowing drivers to customize and improve their travel time and/or fuel consumption when traveling. Our study shows that, with only 2% of independently equipped intersections, a global improvement in the fuel consumption induces a reduction of 10% of the total travel time and 25% of the global waiting time. Local decisions with pertinent partial knowledge of the network are still 5 − 7% close to the performance of a centralized solution.

Route planning in a vehicular network is a well known problem. Static solutions for finding a shortest path have proven their efficiency, however in a dynamic network such as a vehicular network, they are confronted to dynamic costs (travel time, consumption, waiting time, ...) and time constraints (traffic peaks, ghost traffic jam, accidents ...). This is a practical problem faced by several services providers on traffic information who want to offer a realistic computation of a shortest path. This paper propose a model based on the communication between vehicles (Vehicle to Vehicle: V2V) to reduce the time spend by travels taking into account the travel time registered and exchanged between vehicles in real time. In our model, vehicles act as ants and they choose their itineraries thanks to a pheromone map affected by the phenomenon of evaporation. The presented algorithms are evaluated in real world traffic networks and by modeling and simulating extreme cases such as accidents, act of terrorism and disasters.

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