Jean-Patrick Lebacque

Multi-anticipative Car-Following Behaviour: Macroscopic Modeling

In this work we will deal with a macroscopic model of multi-anticipative car-following behaviour i.e. driving behaviour taking into account several vehicles ahead. Some empirical studies have suggested that drivers not only react to the closest leader vehicle but also anticipate on traffic conditions further ahead. Using a recent mathematical result of homogenization for a general class of car-following models (and also available for multi-anticipative models), we will deeply investigate the effects of multi-anticipation at the microscopic level on the macroscopic traffic flow. To investigate multi-anticipation behaviour may be fundamental to understand better cooperative traffic flow dynamics.

Traffic modeling and real-time control for metro lines. Part I - A max-plus algebra model explaining the traffic phases of the train dynamics

We present in this article a traffic flow model for metro lines. It is a discrete event model written in the max-plus algebra, where the traffic dynamics take into account time constraints such as minimum train inter-station running times, minimum train dwell times on platforms, and minimum safety times between successive trains. We show that the dynamics admit a unique stable stationary regime. Moreover, the asymptotic average train time-headway, dwell time, as well as safe-separation time, are derived analytically, as functions of the number of moving trains on the metro line. This derivation allows the comprehension of the traffic phases of the train dynamics.

On the robust guidance of users in road traffic networks

We present in this article a model for the guidance of users in raod traffic networks. It is well known since decades that a path with a reliable travel time can be obtained by maximizing, over the different possible paths, the probability of realizing a travel time less than a given time budget. We propose here an adaptation of this approach, in order to introduce robustness in the selection of the optimal path. A robust path here is a path that is not likely to change during the travel, and that admits acceptable alternative detours in case of failure.

A vehicle-to-infrastructure communication based algorithm for urban traffic control

We present in this paper a new algorithm for urban traffic light control with mixed traffic (communicating and non communicating vehicles) and mixed infrastructure (equipped and unequipped junctions). We call equipped junction here a junction with a traffic light signal (TLS) controlled by a road side unit (RSU). On such a junction, the RSU manifests its connectedness to equipped vehicles by broadcasting its communication address and geographical coordinates. The RSU builds a map of connected vehicles approaching and leaving the junction. The algorithm allows the RSU to select a traffic phase, based on the built map. The selected traffic phase is applied by the TLS; and both equipped and unequipped vehicles must respect it. The traffic management is in feedback on the traffic demand of communicating vehicles. We simulated the vehicular traffic as well as the communications. The two simulations are combined in a closed loop with visualization and monitoring interfaces. Several indicators on vehicular traffic (mean travel time, ended vehicles) and IEEE 802.11p communication performances (end-to-end delay, throughput) are derived and illustrated in three dimension maps. We then extended the traffic control to a urban road network where we also varied the number of equipped junctions. Other indicators are shown for road traffic performances in the road network case, where high gains are experienced in the simulation results.

Traffic modeling and real-time control for metro lines. Part II - The effect of passenger demand on the traffic phases

We present traffic flow and control models for the train dynamics in metro lines. In a first model we introduce the effect of passenger demand on the train dwell times at platforms. We recall that, if this effect is not well controlled, then the traffic is unstable. Then we propose a second traffic control model which deals with this instability, by modifying the control of the train dwell times at platforms. We show that the dynamic system admits a unique stable asymptotic regime, and calculate by numerical simulations the asymptotic average train time-headway as a function of the number of moving trains. By that, we obtain the traffic phases of the train dynamics, giving the effect of the passenger travel demand on the frequency of the metro line, under the proposed control model. Finally, we draw some conclusions, and give a direction for the upcoming research.

A simulation-based model for dynamic traffic assignment on guided vehicles

This article presents a simulation-based model to dynamic assignment of guided vehicles over a parallel network. The simulation was constructed while following a routing game model and has been implemented on the multiagent simulation platform JADE. The model follows an integrated assignment simulation framework which assigns guided vehicles, that communicate with a coordinator agent related to the infrastructure, on the network in order to minimize the total travel time of each vehicle while keeping the network in an equilibrated or near-equilibrated state.