Automated Driving and Driver Assistance Systems

2019 ◽  
Author(s):  
Tom Denton
Keyword(s):  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Assistance Systems

scholarly journals Auditory interfaces in automated driving: an international survey

2015 ◽  
Author(s):  
Pavlo Bazilinskyy ◽  
Joost C. F. De Winter
Keyword(s):  
Warning System ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Sound System ◽  
Collision Warning ◽  
English Speaking ◽  
Assistance Systems ◽  
Forward Collision Warning ◽  
Auditory Interfaces

This study investigated peoples’ opinion on auditory interfaces in contemporary cars and their willingness to be exposed to auditory feedback in automated driving. We used an Internet-based survey to collect 1,205 responses from 91 countries. The participants stated their attitudes towards two existing auditory driver assistance systems, a parking assistant (PA) and forward collision warning system (FCWS), as well as towards a futuristic augmented sound system (FS) proposed for fully automated driving. The respondents were positive towards the PA and FCWS, and rated their willingness to have these systems as 3.87 and 3.77, respectively (1 = disagree strongly, 5 = agree strongly). The respondents tolerated the FS. The results showed that a female voice is the most preferred feedback mode for the support of takeover requests in highly automated driving, regardless of whether the respondents’ country is English speaking or not. The present results could be useful for designers of automated vehicles and other stakeholders.

Adaptive intervention logic for automated driving systems based on injury risk minimization

2020 ◽  
Vol 234 (13) ◽  
pp. 2975-2987
Author(s):  
Dario Vangi ◽  
Antonio Virga ◽  
Michelangelo-Santo Gulino
Keyword(s):  
Injury Risk ◽  
Simulation Software ◽  
Motor Vehicles ◽  
Adaptive Logic ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Adaptive Intervention ◽  
Assistance Systems

Performance improvement of advanced driver assistance systems yields two major benefits: increasingly rapid progress towards autonomous driving and a simultaneous advance in vehicle safety. Integration of multiple advanced driver assistance systems leads to the so-called automated driving system, which can intervene jointly on braking and steering to avert impending crashes. Nevertheless, obstacles such as stationary vehicles and buildings can interpose between the opponent vehicles and the working field of advanced driver assistance systems’ sensors, potentially resulting in an inevitable collision state. Currently available devices cannot properly handle an inevitable collision state, because its occurrence is not subject to evaluations by the system. In the present work, criteria for intervention on braking and steering are introduced, based on the vehicle occupants’ injury risk. The system must monitor the surrounding and act on the degrees of freedom adapting to the evolution of the scenario, following an adaptive logic. The model-in-the-loop, software-in-the-loop and hardware-in-the-loop for such adaptive intervention are first introduced. To highlight the potential benefits offered by the adaptive advanced driver assistance systems, simulation software has been developed. The adaptive logic has been tested in correspondence of three inevitable collision state conditions between two motor vehicles: at each instant, the adaptive logic attitude of creating impact configurations associated with minimum injury risk is ultimately demonstrated.

scholarly journals Checklist for Expert Evaluation of HMIs of Automated Vehicles—Discussions on Its Value and Adaptions of the Method within an Expert Workshop

Information ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 233 ◽  
Author(s):  
Nadja Schömig ◽  
Katharina Wiedemann ◽  
Sebastian Hergeth ◽  
Yannick Forster ◽  
Jeffrey Muttart ◽  
...  
Keyword(s):  
Evaluation Methods ◽  
Assessment Method ◽  
Evaluation Methodology ◽  
Santa Fe ◽  
Driver Assistance ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Hands On ◽  
Assistance Systems

Within a workshop on evaluation methods for automated vehicles (AVs) at the Driving Assessment 2019 symposium in Santa Fe; New Mexico, a heuristic evaluation methodology that aims at supporting the development of human–machine interfaces (HMIs) for AVs was presented. The goal of the workshop was to bring together members of the human factors community to discuss the method and to further promote the development of HMI guidelines and assessment methods for the design of HMIs of automated driving systems (ADSs). The workshop included hands-on experience of rented series production partially automated vehicles, the application of the heuristic assessment method using a checklist, and intensive discussions about possible revisions of the checklist and the method itself. The aim of the paper is to summarize the results of the workshop, which will be used to further improve the checklist method and make the process available to the scientific community. The participants all had previous experience in HMI design of driver assistance systems, as well as development and evaluation methods. They brought valuable ideas into the discussion with regard to the overall value of the tool against the background of the intended application, concrete improvements of the checklist (e.g., categorization of items; checklist items that are currently perceived as missing or redundant in the checklist), when in the design process the tool should be applied, and improvements for the usability of the checklist.

Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS

2021 ◽  
Keyword(s):  
Autonomous Driving ◽  
Full Potential ◽  
Driver Assistance ◽  
Automated Driving ◽  
High Definition ◽  
Driver Assistance Systems ◽  
Resource Needs ◽  
Mapping Technology ◽  
Assistance Systems ◽  
Multiple Challenges

Current advanced driver-assistance systems (ADAS) and automated driving systems (ADS) rely on high-definition (HD) maps to enable a range of features and functions. These maps can be viewed as an additional sensor from an ADAS or ADS perspective as they impact overall system confidence, reduce system computational resource needs, help improve comfort and convenience, and ultimately contribute to system safety. However, HD mapping technology presents multiple challenges to the automotive industry. Unsettled Issues on HD Mapping Technology for Autonomous Driving and ADAS identifies the current unsettled issues that need to be addressed to reach the full potential of HD maps for ADAS and ADS technology and suggests some possible solutions for initial map creation, map change detection and updates, and map safety levels.

scholarly journals Camera-Based Lane Detection—Can Yellow Road Markings Facilitate Automated Driving in Snow?

Vehicles ◽  
2021 ◽  
Vol 3 (4) ◽  
pp. 661-690
Author(s):  
Ane Dalsnes Storsæter ◽  
Kelly Pitera ◽  
Edward McCormack
Keyword(s):  
Lane Detection ◽  
Color Spaces ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Visual Contrast ◽  
Infrastructure Design ◽  
Assistance Systems ◽  
Cost Efficient ◽  
Road Marking

Road markings are beneficial to human drivers, advanced driver assistance systems (ADAS), and automated driving systems (ADS); on the contrary, snow coverage on roads poses a challenge to all three of these groups with respect to lane detection, as white road markings are difficult to distinguish from snow. Indeed, yellow road markings provide a visual contrast to snow that can increase a human drivers’ visibility. Yet, in spite of this fact, yellow road markings are becoming increasingly rare in Europe due to the high costs of painting and maintaining two road marking colors. More importantly, in conjunction with our increased reliance on automated driving, the question of whether yellow road markings are of value to automatic lane detection functions arises. To answer this question, images from snowy conditions are assessed to see how different representations of colors in images (color spaces) affect the visibility levels of white and yellow road markings. The results presented in this paper suggest that yellow markings provide a certain number of benefits for automated driving, offering recommendations as to what the most appropriate color spaces are for detecting lanes in snowy conditions. To obtain the safest and most cost-efficient roads in the future, both human and automated drivers’ actions must be considered. Road authorities and car manufacturers also have a shared interest in discovering how road infrastructure design, including road marking, can be adapted to support automated driving.

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