Search

International audience; This paper introduces a verification and validation (V&V) process in a product life-cycle, where we consider a V&V process as the composition of the three tasks: formal verification, simulation and experimentation. The considered application is a platoon system, a set of autonomous vehicles that move together without any material connection. The platoon system development considers the specification of the SafePlatoon project(1). Main goal of the V&V process is to put to the proof the platoon controller (Decision making unit). V&V is then a corner stone for critical functions that require zero default. Algorithm and hardware must respect some security concerns such as collision free between platoon vehicles, platoon integrity, obstacles avoidance, and etc. After a specification phase, where safety properties are defined, a classical or agile V&V cycle can be applied. In the case of SafePlatoon project, where different partners are evolving simultaneously on the models, an agile development method is used; where formal verification and benchmark simulation works together in order to improve model's safety. Formal verification is made using The SAL model checker. Validation by simulation is made using an internal tool called Vivus.

Vehicle platoon approaches found in literature deal generally with column formations adapted to urban or highway transportation systems. This paper presents an approach in which each platoon vehicle follows a virtual vehicle, in order to cope with issues such as different platoon geometries. Those different types of formations can be encountered in a wide range of field such as the military or agriculture. A platoon formation is composed of a vehicle which assumes the platoon leader role (generally human driven) and other vehicles which play the follower role. A follower vehicle assigns a local leader role to one of the vehicles it perceives. The approach presented here bases on a predefined translation of position, by a follower vehicle, calculated from the perceived position of its local leader vehicle. This translation depends on the desired platoon geometry, expressed in terms of a predefined longitudinal and lateral distance of a follower vehicle relatively to its local leader position. Each vehicle is implemented as an agent which makes decisions depending only on its own perception.

This paper presents a reactive multi-agent system for echelon platoon organization. Platoon systems are sets of vehicles that move together while keeping a predefined geometrical configuration without any material coupling. Each vehicle represents an autonomous agent that behaves based only on its own perceptions. The distributed platoon organization problem consists in defining the algorithms to be executed by each vehicle's embedded software, in order to maintain the desired platoon configuration during displacements. Platoon systems found in literature deal generally with column formations adapted to urban or highway transportation systems. Other formations such as line, echelon,... can be encountered in fields like agriculture and the military. In this paper, we focus on the platoon echelon formation. An approach based on a virtual vehicle-to-vehicle interaction model composed of two springs is proposed. Those virtual springs attach a platoon's vehicle to its local leader, another platoon's vehicle. In this work, five different spring's attachment points are evaluated, to compare them and conclude about the more suitable one, depending on platoon's trajectory. Eventually, from the evaluation results, it can be conceived to make attachment points evolve during platoon operation.

This paper presents a reactive multi agent approach to the platoon control problem for the linear configuration. Platoon is a train of vehicles composed of a head vehicle and a variable number of followers. Vehicle-to vehicle coupling is virtual. Each follower vehicle controls its movement by interacting only with the preceding one. To this end, platoon control was designed as a reactive multi agent system where each follower vehicle is an agent. Each agent behavior is specified by a physics inspired interaction model, which allows to compute vehicle speed and direction from a single perception: the distance to the preceding vehicle. We present the physics inspired interaction model together with a safety verification case study and simulations results.