Efficient Neural Network Implementations on Parallel Embedded Platforms Applied to Real-Time Torque-Vectoring Optimization Using Predictions for Multi-Motor Electric Vehicles

The combination of machine learning and heterogeneous embedded platforms enables new potential for developing sophisticated control concepts which are applicable to the field of vehicle dynamics and ADAS. This interdisciplinary work provides enabler solutions -ultimately implementing fast predictions using neural networks (NNs) on field programmable gate arrays (FPGAs) and graphical processing units (GPUs)- while applying them to a challenging application: Torque Vectoring on a multi-electric-motor vehicle for enhanced vehicle dynamics. The foundation motivating this work is provided by discussing multiple domains of the technological context as well as the constraints related to the automotive field, which contrast with the attractiveness of exploiting the capabilities of new embedded platforms to apply advanced control algorithms for complex control problems. In this particular case we target enhanced vehicle dynamics on a multi-motor electric vehicle benefiting from the greater degrees of freedom and controllability offered by such powertrains. Considering the constraints of the application and the implications of the selected multivariable optimization challenge, we propose a NN to provide batch predictions for real-time optimization. This leads to the major contribution of this work: efficient NN implementations on two intrinsically parallel embedded platforms, a GPU and a FPGA, following an analysis of theoretical and practical implications of their different operating paradigms, in order to efficiently harness their computing potential while gaining insight into their peculiarities. The achieved results exceed the expectations and additionally provide a representative illustration of the strengths and weaknesses of each kind of platform. Consequently, having shown the applicability of the proposed solutions, this work contributes valuable enablers also for further developments following similar fundamental principles.Some of the results presented in this work are related to activities within the 3Ccar project, which has received funding from ECSEL Joint Undertaking under grant agreement No. 662192. This Joint Undertaking received support from the European Union’s Horizon 2020 research and innovation programme and Germany, Austria, Czech Republic, Romania, Belgium, United Kingdom, France, Netherlands, Latvia, Finland, Spain, Italy, Lithuania. This work was also partly supported by the project ENABLES3, which received funding from ECSEL Joint Undertaking under grant agreement No. 692455-2

Platoon Merging Approach Based on Hybrid Trajectory Planning and CACC Strategies

Currently, the increase of transport demands along with the limited capacity of the road network have increased traffic congestion in urban and highway scenarios. Technologies such as Cooperative Adaptive Cruise Control (CACC) emerge as efficient solutions. However, a higher level of cooperation among multiple vehicle platoons is needed to improve, effectively, the traffic flow. In this paper, a global solution to merge two platoons is presented. This approach combines: (i) a longitudinal controller based on a feed-back/feed-forward architecture focusing on providing CACC capacities and (ii) hybrid trajectory planning to merge platooning on straight paths. Experiments were performed using Tecnalia’s previous basis. These are the AUDRIC modular architecture for automated driving and the highly reliable simulation environment DYNACAR. A simulation test case was conducted using five vehicles, two of them executing the merging and three opening the gap to the upcoming vehicles. The results showed the good performance of both domains, longitudinal and lateral, merging multiple vehicles while ensuring safety and comfort and without propagating speed changes.This research was supported by the European Project SHOW from the Horizon 2020 program under Grant Agreement No. 875530

Arbitration for balancing control between the driver and ADAS systems in an automated vehicle: Survey and approach

International audience— Automated functions for real scenarios have been increasing in last years in the automotive industry. Many research contributions have been done in this field. However, other problems have come to the drivers: When should they (the drivers or the new automated systems) be able to take control of the vehicle? This question has not a simple answer; it de-pends on different conditions, such as: the environment, driver condition, vehicle capabilities, fault tolerance, among others. For this reason, in this work we will analyze the acceptability to the ADAS functions available in the market, and its relation with the different control actions. In this paper a survey on arbitration and control solutions in ADAS is presented. It will allow to create the basis for future development of a generic ADAS control (the lateral and longitudinal behavior), based on the integration of the application request, the driver behavior and driving conditions in the framework of the DESERVE project (DEvelopment platform for Safe and Efficient dRiVE 1 , a ARTEMIS project 2012-2105). The main aim of this work is to allow the development of a new generation of ADAS solutions where the control could be effectively shared between the vehicle and the driver. Different solutions of shared control have been analyzed. A first approach is proposed, based on the presented solutions

Step and curb detection for autonomous vehicles with an algebraic derivative-based approach applied on laser rangefinder data

International audiencePersonal Mobility Vehicles (PMV) is is an important part of the Intelligent Transportation System (ITS) domain. These new transport systems have been designed for urban traffic areas, pedestrian streets, green zones and private parks. In these areas, steps and curbs make the movement of disable or mobility reduced people with PMV, and with standard chair wheels difficult. In this paper, we present a step and curb detection system based on laser sensors. This system is dedicated to vehicles able to cross over steps, for transportation systems, as well as for mobile robots. The system is based on the study of the first derivative of the altitude and highlights the use of a new algebraic derivative method adapted to laser sensor data. The system has been tested on several real scenarios. It provides the distance, altitude and orientation of the steps in front of the vehicle and offers a high level of precision, even with small steps and challenging scenarios such as stairs

Cooperative controllers for highways based on human experience

The AUTOPIA program has been working on the development of intelligent autonomous vehicles for the last 10 years. Its latest advances have focused on the development of cooperative manœuvres based on communications involving several vehicles. However, so far, these manœuvres have been tested only on private tracks that emulate urban environments. The first experiments with autonomous vehicles on real highways, in the framework of the grand cooperative driving challenge (GCDC) where several vehicles had to cooperate in order to perform cooperative adaptive cruise control (CACC), are described. In this context, the main challenge was to translate, through fuzzy controllers, human driver experience to these scenarios. This communication describes the experiences deriving from this competition, specifically that concerning the controller and the system implemented in a Citröen C3

Dynamic Trajectory Generation Using Continuous-Curvature Algorithms for Door to Door Assistance Vehicles

International audienceIn this paper, an algorithm for dynamic path generation in urban environments is presented, taking into account structural and sudden changes in straight and bend segments (e.g. roundabouts and intersections). The results present some improvements in path generation (previously hand plotted) considering parametric equations and continuous-curvature algorithms, which guarantees a comfortable lateral acceleration. This work is focused on smooth and safe path generation using road and obstacle detection information. Finally, some simulation results show a good performance of the algorithm using different ranges of urban curves. The main contribution is an Intelligent Trajectory Generator, which considers infrastructure and vehicle information. This method is recently used in the framework of the project CityMobil2, for urban autonomous guidance of Cybercars

On-board Intelligence for the Furbot: a new Concept for Urban Freight Transport

International audienceThe Furbot project proposes to develop a new concept for urban freight transport. The novelty of the concept is twofold. A new architecture of light-duty, full-electrical vehicle is proposed. A great effort is devoted to energy management: new power train layout integrated in the chassis; new battery and energy management system; regenerative braking… But if attention is given to energy management for one vehicle, the Furbot concept consists in having a fleet of several vehicles offering a new sustainable and very adaptable (evolvable) urban freight transport system. In this article, we focus on the intelligent on-board unit. It has mainly two functions. First, it offers assistance to the driver: emergency braking, obstacle avoidance, parking assistance, itinerary assistance or adaptive speed control. Second, it proposes automation abilities for the loading/unloading of the payload. Regarding the multi-sensorial perception system, an intelligent human-machine interface is also conceived in order to let the driver choose between the driving modes (fully manual, assisted, automated loading), in order to provide him general information (map, mission, fleet state...) and warn him about safety issues, power caution and vehicle diagnosis.Le projet Furbot propose de développer un nouveau concept de transport de fret. La nouveauté du concept est double. Tout d'abord, un nouveau type de véhicule est proposé : léger et complètement électrique. Un grand effort est consacré à la gestion de l'énergie : nouveau système de propulsion intégré dans le châssis, batterie innovante et système de gestion de l'énergie intelligent; etc. Mais si une attention particulière est dédiée à la gestion de l'énergie pour un véhicule, le concept Furbot consiste à avoir une flotte de plusieurs véhicules qui constitue un nouveau système de transport de marchandises durable et très adapté au milieu urbain. Dans cet article, nous nous concentrons sur l'intelligence embarquée à bord du véhicule. Il a principalement deux fonctions. Tout d'abord, il offre une assistance au conducteur : freinage d'urgence, évitement d'obstacles, aide au stationnement, assistance pour le choix d'itinéraire ou de contrôle de vitesse adaptatif. Deuxièmement, il propose le chargement / déchargement de la charge utile (boîte de marchandise) en mode complètement automatique. Fort de ces innovations technologiques, une interface homme-machine intelligente est également conçu pou

Novel Fuzzy Torque Vectoring Controller for Electric Vehicles with per-wheel Motors

[Resumen] The continuous innovation on the electric vehicle area has led to the use of multi-motor powertrain topologies. These powertrains imply new degrees of freedom and better controllability, thus enabling elaborate control solutions for enhanced vehicle dynamics. This allows not only to achieve better vehicle stability, but also greater performance and responsiveness, leading to safer and more satisfying vehicle handling. This work presents a Fuzzy Torque Vectoring Controller for a rear-wheel drive car with independent motors per wheel. The developed design has been validated in a high fidelity vehicle dynamics simulation platform demonstrating its capability to enhance not only curve performance, but also stability

Controladores borrosos para la dirección de vehículos autónomos en maniobras dentro de entornos urbanos

National audienceHasta la fecha, los sistemas de ayuda a la conducción desarrollados en el sector de la automoción se centran especialmente en el control de velocidad del vehículo. Sin embargo, sistemas que involucren el control (ya sea parcial o total) sobre la dirección del vehículo se encuentran todavía en fase experimental. Este trabajo está centrado en el diseño, desarrollo e implementación de un sistema de control lateral en cascada para vehículos autónomos reales, basado en controladores borrosos de alto nivel para maniobras en circuitos urbanos. Diferentes experimentos se han llevado a cabo en curvas de distinto radio y a diferentes velocidades (dentro de entornos urbanos), además, se han implementado dos nuevas maniobras: la marcha atrás y conducción en rotondas, mostrando un buen funcionamiento

Fuzzy logic techniques for Cybercars: a control and decision approach.

National audienceIn the context of Intelligent Transportation Systems (ITS) one of the aims is to reach autonomous vehicle capabilities based on human driver experiences in different situations. This problem can be treated from two points of view: by tracking a reference (curve lines -lateral control- or speed -longitudinal control-) and by the decision approach (in specific or dangerous situations). In this paper, fuzzy logic techniques have been implemented in real time control tools to translate human knowledge to driverless control processes, considering risk/warning situation. A comparison with previous works (based in classic control laws) for driving, was carried out in urban areas. Moreover, a new approach to give the driver, a reference speed when the vehicle is arriving to a traffic light intersection was developed. Some simulations show that fuzzy logic techniques are promising in the development of ITS applications