Advanced Driver Assistance Systems

Tato bakalářská práce popisuje funkce pokročilých asistenčních systémů řidiče. Tyto systémy slouží ke zvýšení bezpečnosti všech účastníků silničního provozu. Práce se věnuje rozdělení asistenčních systémů, popisu snímačů, které tyto systémy využívají, ale hlavní část práce se zabývá popisem jednotlivých asistenčních systémů. V závěru této práce je také zahrnutí asistenčních systémů v legislativě a krátký pohled do budoucnosti těchto technologií.This Bachelor´s thesis describes functions of advanced driver assistance systems. These systems are used to increase safety of road users. The thesis deals with distribution of assistance systems, description of sensors that are used by these systems, but the main part describes the assistance systems itself. In the conclusion part of this thesis is the inclusion of driver assistance systems in the legislation and a brief look into the future of these technologies.

Introducing Advanced Driver Assistance Systems

The introduction of Advanced Driver Assistance Systems (ADAS) in road traffic induces many complex questions. One of them is whether or not present legislation frameworks are able to accommodate a smooth development and market implementation of ADAS. This is strongly related to the aspect of traffic safety. The various aspects related to this issue are categorised based on an exploration of the functionality and possible failure of ADAS. Next, some problem categories are more in-depth elaborated. In particular attention is paid to the need for establishing safety requirements to the design and marketing of ADAS as well as the issue of liability regulation. It is concluded that decision making on safety requirements mainly takes place at an international level. However, so far hardly any requirements regarding ADAS have been laid down in compulsory rules yet. It is further concluded that current legal frameworks in both the fields of vehicle safety standards and liability provide for (some) flexibility towards technical developments regarding ADAS, i.e. these frameworks do not contain many ‘hard rules’ obstructing the introduction of ADAS. Concerning the safety regulation of ADAS it is argued that the speed of technological developments and the innovative and specific nature of ADAS technology generate various tensions. These tensions should have consequences for the weight that is put on public and private intervention mechanisms and the relation between preventive safety standards and reactive regimes such as product liability and post-market controls

Editorial Advanced Driver Assistance Systems

The application of Intelligent Transportation Systems (ITS), in particular Advanced Driver Assistance Systems (ADAS), is expected to improve the performance of road transportation significantly. Public policy makers, among others, are therefore increasingly interested in the implementation of these systems. Available knowledge on various implementation issues is growing, but still limited. This is due to the complex interactions between technological re- quirements, market introduction, impacts on driver behaviour and traffic performance and policy priorities. This article provides a framework for ADAS implementation, reviews recent developments in this field and introduces the contributions to this special issue

Metrology Impact of Advanced Driver Assistance Systems

open1noMetrological applications to road environment are usually focused on the characterization of the road, considering as mea- surands several characteristics related to the road as a whole or the performances of single components, like the road surface, lighting systems, active and/or passive signaling and obviously vehicles equipment. In current standards approach, driving on the road means to navigate ”visually” (for a human being driver), the characterizations are mostly photometric performances oriented for given reference conditions and reference observer (photomet- ric observer observing the road from assigned points of view, with given spectral sensitivity). But considering the present and fu- ture technological trends and knowledge on visual performances, characterizations based on only photometric quantities in refer- ence conditions as described in the current standards would be not fully suitable, even for human driver visual needs. Nowadays research on components and systems for ad- vanced driver assistance are evolving, following different paths toward different solutions: it is not possible, nor useful to define strict constraints as it has been done previously for road appli- cations measurements. The paper presents the current situation of metrological characterization of road environment and com- ponents, on laboratory and on site using mobile high efficiency laboratories, and suggests to use ADAS (Advanced Driver Assis- tance System) for diffuse mapping of road characteristics for a better understanding of the road environment and maintenance. The suggestion has the additional advantage of minimizing mea- surement costs, but for its full applicability, the reliability and metrological performances of installed devices and of the mea- surements performed by ADAS are a priority.openIacomussiIacomussi, Paol

VEHIL - HIL testing of advanced driver assistance systems

A new Hardware-in-the-Loop method for the design of Advanced Driver Assistance (ADA) systems for road vehicles is presented. This method, called VEHIL, aims to support the development and verification of ADA systems, increasing the level of reproducibility, effectiveness and safety of the testing process. To this end, a test vehicle, positioned on a roller bench, is placed in a simulated traffic environment. A selection of simulated traffic participants is represented by wheeled mobile robots in order to provide the test vehicle’s environment sensor input. VEHIL is positioned in the development methodology as commonly used by OEM’s and 1st Tier suppliers and the added value of VEHIL is illustrated by means of three test cases regarding sensor mapping, ACC and collision mitigation

Visual Saliency Detection in Advanced Driver Assistance Systems

Visual Saliency refers to the innate human mechanism of focusing on and extracting important features from the observed environment. Recently, there has been a notable surge of interest in the field of automotive research regarding the estimation of visual saliency. While operating a vehicle, drivers naturally direct their attention towards specific objects, employing brain-driven saliency mechanisms that prioritize certain elements over others. In this investigation, we present an intelligent system that combines a drowsiness detection system for drivers with a scene comprehension pipeline based on saliency. To achieve this, we have implemented a specialized 3D deep network for semantic segmentation, which has been pretrained and tailored for processing the frames captured by an automotive-grade external camera. The proposed pipeline was hosted on an embedded platform utilizing the STA1295 core, featuring ARM A7 dual-cores, and embeds an hardware accelerator. Additionally, we employ an innovative biosensor embedded on the car steering wheel to monitor the driver drowsiness, gathering the PhotoPlethysmoGraphy (PPG) signal of the driver. A dedicated 1D temporal deep convolutional network has been devised to classify the collected PPG time-series, enabling us to assess the driver level of attentiveness. Ultimately, we compare the determined attention level of the driver with the corresponding saliency-based scene classification to evaluate the overall safety level. The efficacy of the proposed pipeline has been validated through extensive experimental results