Abstract

dvance Driver Assistance Systems designed to enhance safety require a perception module that should be reliable, robust and affordable. We propose a new cooperative fusion method between two exteroceptive sensors for the detection and tracking of obstacles. Focus is cast on the issue of data association of asynchronous measurements from multiple sensors of different nature. This perception and detection module is applied to local perception embedded on a host vehicle (the ego-vehicle) with two types of complementary sensors (laser scanner and mono-camera). The first detection stage is performed by the mono-layer laser scanner which provides a set of clustered impact points. Those clusters are filtered and projected into the image to define targets. Detected vehicles are tracked using an image registration algorithm. A multi-objects association and tracking algorithm based on belief theory is implemented to estimate the dynamic state of the tracks and to monitor appearance and disappearance of obstacles. Our approach does not make any assumption on the type of driving maneuver and is able to address highly non linear dynamic configuration. The method is applied on both real data and in simulated environment for the validation stage.

Abstract

TRA 2018, 7th Transport Research Arena, Vienne, AUTRICHE, 16-/04/2018 - 19/04/2018; 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.

Abstract

dvanced Driver Assistance Systems (ADAS) based on video camera tends to be generalized in today's automotive. However, if most of these systems perform nicely in good weather conditions, they perform very poorly under adverse weather particularly under rain. We present a novel approach that aims at detecting raindrops on a car windshield using only images from an in-vehicle camera. Based on the photometric properties of raindrops, the algorithm relies on image processing technics to highlight raindrops. Its results can be further used for image restoration and vision enhancement and hence it is a valuable tool for ADAS.

Abstract

ITSC 2011 : International IEEE Conference on Intelligent Transportation Systems, WASHINGTON, ETATS-UNIS, 05-/10/2011 - 07/10/2011; This paper presents the implementation of a highly automated driving system on automotive Electronic Control Units (ECUs). It integrates a perception component, which uses the combination of high-level sensors to map the environment, a co-pilot, which finds an optimal trajectory in this environment and a control component, which guides the vehicle on this trajectory. The cooperation between human and automation is managed by the driving Mode Selection and arbitration Unit (MSU) and Human-Machine Interface (HMI) components. The co-pilot and control components have been implemented on AUTOSAR-based ECUs, the other components in the RTMaps environment on a standard PC. It has been first been tested on the simulation tool SiVIC and was then transferred to a physical vehicle on test track.