scholarly journals An Interacting Multiple Model Approach for Target Intent Estimation at Urban Intersection for Application to Automated Driving Vehicle

2020 ◽  
Vol 10 (6) ◽  
pp. 2138 ◽  
Author(s):  
Donghoon Shin ◽  
Subin Yi ◽  
Kang-moon Park ◽  
Manbok Park
Keyword(s):  
Traffic Accidents ◽  
Estimation Algorithm ◽  
Driver Model ◽  
Interacting Multiple Model ◽  
Multiple Model ◽  
Driver Assistance ◽  
Automated Driving ◽  
Driver Assistance Systems ◽  
Assistance Systems ◽  
Model Approach

Research shows that urban intersections are a hotspot for traffic accidents which cause major human injuries. Predicting turning, passing, and stop maneuvers against surrounding vehicles is considered to be fundamental for advanced driver assistance systems (ADAS), or automated driving systems in urban intersections. In order to estimate the target intent in such situations, an interacting multiple model (IMM)-based intersection-target-intent estimation algorithm is proposed. A driver model is developed to represent the driver’s maneuvering on the intersection using an IMM-based target intent classification algorithm. The performance of the intersection-target-intent estimation algorithm is examined through simulation studies. It is demonstrated that the intention of a target vehicle is successfully predicted based on observations at an individual intersection by proposed algorithms.

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.

scholarly journals Driver perceptions of advanced driver assistance systems: A case study

F1000Research ◽  
2021 ◽  
Vol 10 ◽  
pp. 1122
Author(s):  
Siti Fatimah Abdul Razak ◽  
Sumendra Yogarayan ◽  
Afizan Azman ◽  
Mohd Fikri Azli Abdullah ◽  
Anang Hudaya Muhamad Amin ◽  
...  
Keyword(s):  
Technology Use ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems ◽  
Convenience Sampling ◽  
Safety Applications

Background: Automobile manufacturers need to have an insight and understand how consumers, specifically drivers, respond to the advanced driver assistance systems (ADAS) technology in their manufactured vehicles. This study reveals drivers’ perceptions of Malaysia’s advanced driver assistance systems, which is currently lacking in the literature. So far, other studies have focused on countries that are unlike Malaysia’s multi-culture environment. Methods: A survey was designed and distributed using convenience sampling to obtain responses from licensed drivers. Questions included demographic and driving questions, the perceptions of benefits and obstacles relevant to ADAS use, vehicle decision-making, and technology use. Data were collected from 818 respondents who were licensed drivers in Malaysia. Results were then analysed using statistical approaches. Results: The findings indicated that 76.8% of drivers have a positive attitude towards ADAS technology, particularly safety applications when they are available. Regardless of the accuracy of these systems, acceptance of the technology may shift upon viewing or hearing messages of possible problems with ADAS. Conclusions: It can be concluded that the safety advantages of ADAS technology are less valued by drivers who do not have experience of road traffic accidents. Furthermore, acceptance of the technology could be undermined by assuming that the safety applications could be compromised.

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