A new model-free design for vehicle control and its validation through an advanced simulation platform

A new model-free setting and the corresponding "intelligent" P and PD controllers are employed for the longitudinal and lateral motions of a vehicle. This new approach has been developed and used in order to ensure simultaneously a best profile tracking for the longitudinal and lateral behaviors. The longitudinal speed and the derivative of the lateral deviation, on one hand, the driving/braking torque and the steering angle, on the other hand, are respectively the output and the input variables. Let us emphasize that a "good" mathematical modeling, which is quite difficult, if not impossible to obtain, is not needed for such a design. An important part of this publication is focused on the presentation of simulation results with actual and virtual data. The actual data, used in Matlab as reference trajectories, have been obtained from a properly instrumented car (Peugeot 406). Other virtual sets of data have been generated through the interconnected platform SiVIC/RTMaps. It is a dedicated virtual simulation platform for prototyping and validation of advanced driving assistance systems. Keywords- Longitudinal and lateral vehicle control, model-free control, intelligent P controller (i-P controller), algebraic estimation, ADAS (Advanced Driving Assistance Systems).Comment: in 14th European Control Conference, Jul 2015, Linz, Austria. 201

Intelligent Vehicle embedded sensors fault detection and identification using analytical redundancy and non-linear transformations

This work proposes a fault detection architecture for a vehicle embedded sensors, allowing to deal with both system non-linearity and environmental disturbances and degradations. The proposed method use measurements analytical redundancy and a non-linear transformation to generate the residual value allowing the fault detection. A strategy dedicated to the optimization of the detection parameters choice is also develope

Topology Control in VANET and Capacity Estimation

International audienceSome safety applications using VANET exchange a large amount of data, and consequently require an important network capacity. In this paper, we focus on extended perception map applications, that use information from local and distant sensors to offer driving assistance (autonomous driving, collision warning, etc). Extended perception requires a high bandwidth that might not be available in practice in classical IEEE 802.11p ad hoc networks. Therefore, we propose an adaptive power control algorithm optimized for this particular application. We show through an analytical model and a large set of simulations that the network capacity is then significantly increased

A new clustering structure for VANET

The Vehicular Ad-Hoc Network (VANET) paradigm offers the opportunity of extending Intelligent Transport System (ITS) by supporting its applications through vehicle-to-vehicle communications, notably in the areas where the infrastructure is inexistent, in failure, or overloaded. However, the complexity induced by ad hoc network management raises many challenges that have to be solved such as the sharing of bandwidth resources, the limitations on the duration of the connections between the vehicles, and the application-specific quality of service (QoS) requirements. Recently, the Chain-Branch-Leaf clustering scheme (CBL) has been proposed for vehicle-to-vehicle ad hoc routing that combines the information of road configuration, vehicle mobility, and link quality in order to build an efficient clustering connecting the entire VANET through a flexible backbone. This work presents a comparative study between the native Multipoint relaying clustering used in the Optimized Link State Routing (OLSR) and CBL scheme. The results show that CBL reduces significantly the routing traffic overhead compared to native OLSR, thus freeing up more bandwidth for ITS applications and reducing the IP delays for peer-to-peer applications

Construction de l'environnement dynamique autour d'un véhicule automobile dans un milieu autoroutier pour le projet CASSICE

Dans cet article, nous présentons un algorithme de cartographie de l'environnement dynamique autour d'un véhicule instrumenté (STRADA). Il s'appuie sur deux outils mathématiques pour gérer l'imprécision et l'incertitude qui caractérisent la présence et la position d'un véhicule : le filtrage de Kalman pour l'estimation et la prédiction, et la théorie de la croyance pour l'association et le suivi multi-objet. Nous pouvons ainsi quantifier l'imprécision et la certitude d'un résultat à chaque étape du traitement de l'information. Cette étude entre de le cadre du projet CASSICE et plus généralement dans le développement de système d'aide à la conduite automobile

Obstacle Detection Based on Fusion Between Stereovision and 2D Laser Scanner

International audienceObstacle detection is an essential task for mobile robots. This subject has been investigated for many years by researchers and a lot of obstacle detection systems have been proposed so far. Yet designing an accurate and totally robust and reliable system remains a challenging task, above all in outdoor environments. Thus, the purpose of this chapter is to present new techniques and tools to design an accurate, robust and reliable obstacle detection system in outdoor environments based on a minimal number of sensors. So far, experiments and assessments of already developed systems show that using a single sensor is not enough to meet the requirements: at least two complementary sensors are needed. In this chapter a stereovision sensor and a 2D laser scanner are considered

A new approach for robust road marking detection and tracking applied to multi-lane estimation

International audienceIn this paper, an original and inovative algorithm for multi-lane detection and estimation is proposed. Based on a three-step process, (1) road primitives extraction, (2) road markings detection and tracking, (3) lanes detection and estimation. This algorithm combines several advantages at each processing level and is quite robust to the extraction method and more specifically to the choice of the extraction threshold. The detection step is so efficient, by using robust poly-fitting based on the point intensity of extracted points, that correction step is almost not necessary anymore. This approach has been used in several project in real condition and its performances have been evaluated with the sensor data generated from SiVIC platform. This validation stage has been done with more than 2500 simulated and realistic images. . Results are very encouraging : more than 95% of marking lines are detected for less than 2% of false alarm, with 3 cm accuracy at a range of 60 m

Development of Full Speed Range ACC with SiVIC, a virtual platform for ADAS Prototyping, test and evaluation

LIVIC-IFSTTAR develops driving assistance services in order to improve the driving safety. These systems are tested on several real prototypes equipped with sensors and perception, decision and control modules. But tests on real prototypes are not always available, effectively some hardware architectures could be too expensive to implement, scenario may lead to hazardous situations. Moreover, lots of reasons could lead to the inability to obtain both sensors and ground truth data for ADAS evaluation. However, safety applications must be tested in order to guaranty their reliability. For this task, simulation appears as a good alternative to the real prototyping and testing stages. In this context, the simulation must provide the same opportunities as reality, by providing all the necessary data to develop and to prototype different types of ADAS based on local or extended environment perception. The sensor data provided by simulation must be as noised and imperfect as those obtained with real sensors. To address this issue, the SiVIC platform has been developed; it provides a virtual road environment including realistic dynamic models of mobile entities (vehicles), realistic sensors, and sensors for ground truth. To test real embedded applications, an interconnection has been developed between SiVIC and third party applications (ie. RTMaps). In this way, the prototyped application can be directly embedded in real prototypes in order to test it in real conditions. A Full Speed Range ACC application is presented in this paper to illustrate the capabilities and the functionalities of this virtual platform