Abstract

International audience; — This paper presents a real-time motion planning scheme for urban autonomous driving that will be deployed as a basis for cooperative maneuvers defined in the European project AutoNet2030. We use a path-velocity decomposition approach to separate the motion planning problem into a path planning problem and a velocity planning problem. The path planner first generates a collision-free piecewise linear path and then uses quintic Bézier curves to smooth the path with C 2 continuity. A derive-free optimization technique Subplex is used to further smooth the curvature of the path in a best-effort basis. The velocity planner generates an optimal velocity profile along the reference path using Model Predictive Control (MPC), taking into account user preferences and cooperative maneuver requirements. Simulation results are presented to validate the approach, with special focus on the flexibility, cooperative-awareness and efficiency of the algorithms.

Abstract

International audience; Predicting other traffic participants trajectories is a crucial task for an autonomous vehicle, in order to avoid collisions on its planned trajectory. It is also necessary for many Advanced Driver Assistance Systems, where the ego-vehicle's trajectory has to be predicted too. Even if trajectory prediction is not a deterministic task, it is possible to point out the most likely trajectory. This paper presents a new trajectory prediction method which combines a trajectory prediction based on Constant Yaw Rate and Acceleration motion model and a trajectory prediction based on maneuver recognition. It takes benefit on the accuracy of both predictions respectively a short-term and long-term. The defined Maneuver Recognition Module selects the current maneuver from a predefined set by comparing the center lines of the road's lanes to a local curvilinear model of the path of the vehicle. The overall approach was tested on prerecorded human real driving data and results show that the Maneuver Recognition Module has a high success rate and that the final trajectory prediction has a better accuracy.

Abstract

International audience; Air Traffic has evolved over the years with current commercial fleet expected to double in the near future, increasing airspace congestion. Jet fuel prices volatility, market competition and drones integrating the same airspace require a modernization of the Air Transportation System. In this context, Airbus proposes modern avionics and cockpit designs to fulfil these requirements. Flight Management System (FMS), in-service since the early 1980s, is one of these candidate avionic systems to be revisited. During high workload flight phases as descent and approach are, best-in-class FMSs compute a fixed vertical reference trajectory based on a lateral flight plan and applicable procedures. Then, flight guidance is responsible for tactical replanning so that deviations are absorbed. FMS reference profile is constructed through a series of hypotheses, which could be enhanced by taking into account other factors such as aircraft optimal energy repartition, ATC restrictions, surrounding traffic, wind errors and mass biases. This paper proposes and compares two methodologies based on a modified version of A* algorithm that solves the Optimal Control Problem in the vertical plane. Fixed and variable speed aircraft trajectories are compared in order to quantify the benefits with respect to current FMS design. The problem is formulated through a relaxed point-mass model with a real performance database for a modern commercial aircraft. It accounts for flight constraints as well as aircraft dynamics for trajectory generation. Fuel consumption is optimized without excessively penalizing flight time. These trajectories are compared with those generated by Airbus FMS simulator. Results show that, for modern arrival procedures such as those defined for Continuous Descent Operations, aircraft energy management (potential and kinetic) is enhanced, producing continuously idle trajectories that consume up to 30 % less fuel than current operations, as obtained for this particular procedure. In that case, flight time would be stretched by few minutes yielding to 15% extra time, whose trade-off still seems interesting from the airline perspective.

Abstract

International audience; Regulations from the ICAO use the term Well Clear without defining it. Now, this definition is needed to design air traffic Detect And Avoid systems. A definition is currently discussed at the ICAO level, with work on the associated Remain Well Clear (RWC) function underway at standardisation bodies level (RTCA, EUROCAE). But many members of the communities impacted by these works are not well aware of their state. To adress this lack of awareness, this paper provides three contributions. First, it derives from ICAO texts the components of a RWC function: boundaries, alerts and guidances. These are linked to essential elements required to define the Well Clear term: a start and end, the actors involved, and the expected actions. Second, it summarizes the current regulatory efforts in RTCA, EUROCAE and ICAO regarding the Well Clear and Remain Well Clear notions. Third, it proposes discussion topics to move forward. From a DAA perspective, the notion of Well Clear is key to unlock RPAS full integration, i.e. operation in all classes of airspaces. Though existing works make good progress, the ressources engaged on this topic seem insufficient when compared with the complexity and importance of the task at hand.

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International audience; In this article, we discuss about the benefit of IoT for people with disabilities, particularly for visually impaired and blind people mobility. We propose a simple prototype using OpenStreetMap data combined to physical environment data measured from sensors connected to a Arduino board through Speech recognition.

Abstract

International audience; In this paper we develop a boundary state feedback control law for a cascaded traffic flow network system: one incoming and one outgoing road connected by a junction. The macroscopic traffic dynamics on each road segment are governed by Aw-Rascle-Zhang (ARZ) model, consisting of second-order nonlinear partial differential equations (PDEs) for traffic density and velocity. Different equilibrium road conditions are considered for the two segments. For stabilization of stop-and-go traffic congestion on the two roads, we consider a ramp metering located at the connecting junction. The traffic flow rate entering from the on-ramp to the mainline junction is actuated. The objective is to simultaneously stabilize the upstream and downstream traffic to given spatially-uniform constant steady states. We design a full state feedback control law for this under-actuated network of two systems of two hetero-directional linear first-order hyperbolic PDEs interconnected through the junction boundary. Exponential Convergence to steady states in L 2 sense is validated by a numerical simulation.

Abstract

This paper presents a 'CPN/B method' based process for railway systems safety analysis. Achieving interoperability through the European Rail Traffic Management System (ERTMS/ETCS) is facing difficulties in railway safety assessment due to the interaction of national and European operating specifications. These specifications have been modeled using several formalisms, which makes it is extremely hard to preserve all requirements when switching between different formalisms. However, this problem, crucial for efficient progress in railway safety research, has received very little attention in the literature. In this respect, the purpose of this contribution is to provide a methodology to demonstrate safety in railway systems by converting CPN models, widely used in modeling, into B abstract machines. It aims at enabling a stronger combination of formal design techniques and analysis tools able to cope with the real complexity of systems and automatically prove that safety properties are unambiguous, consistent and not contradictory, considering an industrial railway context. Document type: Article