Advanced vehicle technology: Mapping mental model accuracy and system exposure to driver behavior

2021 ◽  
Vol 65 (1) ◽  
pp. 1072-1076
Author(s):  
Aaron Benson ◽  
Joanne But ◽  
John Gaspar ◽  
Cher Carney ◽  
William J. Horrey
Keyword(s):  
Mental Models ◽  
Mental Model ◽  
Driving Simulator ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driver Education ◽  
The Road ◽  
Vehicle Technology ◽  
Assistance Systems

Advanced driver assistance systems have potential to increase safety and comfort for drivers; however, drivers need to understand the capabilities and limitations of these systems to use them appropriately. This study sought to explore how the quality (accuracy) of drivers’ mental models of adaptive cruise control (ACC) impacted their behavior and interactions while using the system. Seventy-eight participants drove in a high-fidelity driving simulator while operating an ACC system, in normal conditions and while interacting with the system interface. Participants with stronger (more accurate) mental models glanced to the road ahead more often during normal conditions early on compared to drivers were less accurate mental models; however, these differences diminished with increased system exposure. Glance behavior while interacting with the system and time to complete the interactions were less effected by the strength of the participant’s mental model. Results are discussed in the context of driver education and training.

scholarly journals Some Characteristics of Mental Models of Advanced Driver Assistance Systems: A Semi-structured Interviews Approach

2020 ◽  
Vol 64 (1) ◽  
pp. 1313-1317
Author(s):  
Michael A. Nees ◽  
Nithya Sharma ◽  
Karli Herwig
Keyword(s):  
Mental Models ◽  
Future Research ◽  
Negative Consequences ◽  
Cruise Control ◽  
Driver Assistance ◽  
Structured Interviews ◽  
Driver Assistance Systems ◽  
Cognitive Representations ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

People construct mental models—internal cognitive representations—when they interact with dynamic systems. The introduction of automation in vehicles has raised concerns about potential negative consequences of inaccurate mental models, yet characteristics of mental models remain difficult to identify. A descriptive study used semi-structured interviews to explore mental models of advanced driver assistance systems (adaptive cruise control, lane keeping assist, and Level 2 systems). Results exposed shortcomings in drivers’ understandings of the hardware, software, and limitations of these systems and also suggested that mental models will affect behavior while using automation. Further, we found that mental models can be influenced by interface feedback (or lack thereof) and limitations experienced. Some drivers attributed purposeful design to aspects of the systems that likely were chosen idiosyncratically or arbitrarily. Our findings offered potentially useful avenues for future research on mental models of automation and corroborated concerns that inaccurate mental models may be common.

scholarly journals Some Characteristics of Mental Models of Advanced Driver Assistance Systems: A Semi-structured Interviews Approach

2020 ◽  
Author(s):  
Michael Nees ◽  
Nithya Sharma ◽  
Karli Herwig
Keyword(s):  
Mental Models ◽  
Future Research ◽  
Negative Consequences ◽  
Cruise Control ◽  
Driver Assistance ◽  
Structured Interviews ◽  
Driver Assistance Systems ◽  
Cognitive Representations ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

People construct mental models—internal cognitive representations—when they interact with dynamic systems. The introduction of automation in vehicles has raised concerns about potential negative consequences of inaccurate mental models, yet characteristics of mental models remain difficult to identify. A descriptive study used semi-structured interviews to explore mental models of advanced driver assistance systems (adaptive cruise control, lane keeping assist, and Level 2 systems). Results exposed shortcomings in drivers’ understandings of the hardware, software, and limitations of these systems and also suggested that mental models will affect behavior while using automation. Further, we found that mental models can be influenced by interface feedback (or lack thereof) and limitations experienced. Some drivers attributed purposeful design to aspects of the systems that likely were chosen idiosyncratically or arbitrarily. Our findings offered potentially useful avenues for future research on mental models of automation and corroborated concerns that inaccurate mental models may be common.

Visualization of Headlight Illumination for the Virtual Prototyping of Light-Based Driver–Assistance Systems

2016 ◽  
Vol 16 (3) ◽  
Author(s):  
Jan Berssenbrügge ◽  
Ansgar Trächtler ◽  
Christoph Schmidt
Keyword(s):  
Driving Simulator ◽  
Virtual Prototyping ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driving Simulators ◽  
Visualization System ◽  
The Road ◽  
Assistance Systems ◽  
Lighting Systems ◽  
Project Partner

Driving simulators that are capable of simulating a virtual drive at night are increasingly used for the virtual prototyping of light-based driver–assistance systems (DAS). Here, the interplay between driver and assistance system, which enhances the illumination of the road ahead of the vehicle, is investigated. For such investigations, special driving simulators are applied that not only enable a standard driving simulation but also cover the special requirements for the visualization of a driving scenery at night, the simulation of automotive headlights during a virtual drive at night, and the interface to a headlight control module (HCM) that operates the physical headlight prototypes. In this paper, we present the visualization system of the reconfigurable driving simulator from the research project TRAFFIS. We describe the special application focus on the virtual prototyping of a light-based DAS from our project partner Varroc Lighting Systems. The light-based DAS is based on a headlight prototype that combines a glare-free high-beam (GFHB) function and a predictive adaptive frontlighting system (PAFS) for glare-free driving with maximized headlight time.

Visualization of Headlight Illumination for the Virtual Prototyping of Light-Based Driver Assistance Systems

2015 ◽  
Author(s):  
Jan Berssenbrügge ◽  
Ansgar Trächtler ◽  
Christoph Schmidt
Keyword(s):  
Driving Simulator ◽  
Virtual Prototyping ◽  
Assistance System ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driving Simulators ◽  
Visualization System ◽  
The Road ◽  
Assistance Systems ◽  
Lighting Systems

Driving simulators that are capable of a simulation of a virtual drive at night are increasingly used for the virtual prototyping of light-based driver assistance systems. Here, the interplay between driver and assistance system, which enhances the illumination of the road ahead of the vehicle, is investigated. For such investigations, special driving simulators are applied that enable not only a standard driving simulation but also cover the special requirements for the visualization of a driving scenery at night, the simulation of automotive headlights during a virtual drive at night, and the interface to a headlight control module (HCM) that operates the physical headlight prototypes. In this paper, we present the visualization system of the reconfigurable driving simulator from the research project TRAFFIS. We describe the special application focus on the virtual prototyping of a light-based driver assistance system from our project partner Varroc Lighting Systems. The light-based DAS bases on a headlight prototype that combines a glare-free high beam (GFHB) function and a predictive adaptive frontlighting system (PAFS) for glare-free driving with maximized headlight time.

scholarly journals Advanced Driver Assistant Systems Focused on Pedestrians’ Safety: A User Experience Approach

2021 ◽  
Vol 13 (8) ◽  
pp. 4264
Author(s):  
Matúš Šucha ◽  
Ralf Risser ◽  
Kristýna Honzíčková
Keyword(s):  
Autonomous Vehicles ◽  
Qualitative Data ◽  
Expert Interviews ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistant Systems ◽  
Vehicle Technology ◽  
Assistance Systems ◽  
Technical Solutions ◽  
Near Future

Globally, pedestrians represent 23% of all road deaths. Many solutions to protect pedestrians are proposed; in this paper, we focus on technical solutions of the ADAS–Advanced Driver Assistance Systems–type. Concerning the interaction between drivers and pedestrians, we want to have a closer look at two aspects: how to protect pedestrians with the help of vehicle technology, and how pedestrians–but also car drivers–perceive and accept such technology. The aim of the present study was to analyze and describe the experiences, needs, and preferences of pedestrians–and drivers–in connection with ADAS, or in other words, how ADAS should work in such a way that it would protect pedestrians and make walking more relaxed. Moreover, we interviewed experts in the field in order to check if, in the near future, the needs and preferences of pedestrians and drivers can be met by new generations of ADAS. A combination of different methods, specifically, an original questionnaire, on-the-spot interviewing, and expert interviews, was used to collect data. The qualitative data was analyzed using qualitative text analysis (clustering and categorization). The questionnaire for drivers was answered by a total of 70 respondents, while a total of 60 pedestrians agreed to complete questionnaires concerning pedestrian safety. Expert interviews (five interviews) were conducted by means of personal interviews, approximately one hour in duration. We conclude that systems to protect pedestrians–to avoid collisions of cars with pedestrians–are considered useful by all groups, though with somewhat different implications. With respect to the features of such systems, the considerations are very heterogeneous, and experimentation is needed in order to develop optimal systems, but a decisive argument put forward by some of the experts is that autonomous vehicles will have to be programmed extremely defensively. Given this argument, we conclude that we will need more discussion concerning typical interaction situations in order to find solutions that allow traffic to work both smoothly and safely.

Advanced Driver Assistance Systems (ADAS): Who’s Driving What and What’s Driving Use?

2021 ◽  
Vol 65 (1) ◽  
pp. 1220-1224
Author(s):  
Daniel Palac ◽  
Iiona D. Scully ◽  
Rachel K. Jonas ◽  
John L. Campbell ◽  
Douglas Young ◽  
...  
Keyword(s):  
Group Differences ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driver Safety ◽  
Advanced Driver Assistance Systems ◽  
Additional Group ◽  
Vehicle Technology ◽  
Assistance Systems ◽  
Vehicle Technologies ◽  
Safety Systems

The emergence of vehicle technologies that promote driver safety and convenience calls for investigation of the prevalence of driver assistance systems as well as of their use rates. A consumer driven understanding as to why certain vehicle technology is used remains largely unexplored. We examined drivers’ experience using 13 different advanced driver assistance systems (ADAS) and several reasons that may explain rates of use through a nationally-distributed survey. Our analysis focused on drivers’ levels of understanding and trust with their vehicle’s ADAS as well as drivers’ perceived ease, or difficulty, in using the systems. Respondents’ age and experience with Level 0 or Level 1 technologies revealed additional group differences, suggesting older drivers (55+), and those with only Level 0 systems as using ADAS more often. These data are interpreted using the Driver Behavior Questionnaire framework and offer a snapshot of the pervasiveness of certain driver safety systems.

ADVANCED HIGH FREQUENCY LTCC MATERIALS FOR APPLICATIONS BEYOND 60 GHZ

2012 ◽  
Vol 2012 (CICMT) ◽  
pp. 000077-000081
Author(s):  
Sebastian Brunner ◽  
Manfred Stadler ◽  
Xin Wang ◽  
Frank Bauer ◽  
Klaus Aichholzer
Keyword(s):  
60 Ghz ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Automotive Safety ◽  
Radar Sensors ◽  
Collision Mitigation ◽  
Assistance Systems ◽  
5 Ghz ◽  
Safety Systems

In this paper we will present an application of advanced Low Temperature Cofired Ceramic (LTCC) technology beyond 60 GHz. Therefore a RF frontend for 76–81 GHz radar frequency was built. LTCC is a well established technology for applications for consumer handheld units <5 GHz but will provide solutions for applications for high frequencies in the range of 60 GHz and beyond. Radar sensors operating in the 76-81 GHz range are considered key for Advanced Driver Assistance Systems (ADAS) like Adaptive Cruise Control (ACC), Collision Mitigation and Avoidance Systems (CMS) or Lane Change Assist (LCA). These applications are the next wave in automotive safety systems and have thus generated increased interest in lower-cost solutions especially for the mm-wave frontend section.

scholarly journals Examining Senior Drivers’ Attitudes Toward Advanced Driver Assistance Systems After Naturalistic Exposure

2020 ◽  
Vol 4 (3) ◽  
Author(s):  
Dan Liang ◽  
Nathan Lau ◽  
Stephanie A Baker ◽  
Jonathan F Antin
Keyword(s):  
Focus Group ◽  
User Interfaces ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Perceived Safety ◽  
Age Related ◽  
Assistance Systems ◽  
Senior Drivers

Abstract Background and Objectives The increasing number of senior drivers may introduce new road risks due to age-related declines in physical and cognitive abilities. Advanced driver assistance systems (ADAS) have been proposed as solutions to minimize age-related declines, thereby increasing both senior safety and mobility. This study examined factors that influence seniors’ attitudes toward adopting ADAS after significant exposure to the technology in naturalistic settings. Research Design and Methods This study recruited 18 senior drivers aged 70–79 to drive vehicles equipped with ADAS for 6 weeks in their own environments. Afterward, each participant was enrolled in 1 of the 3 focus group sessions to discuss their changes in attitude toward ADAS based on their driving experiences. We applied structural topic modeling (STM) on the focus group transcripts to reveal key topics deemed important to seniors. Results STM revealed 5 topics of importance for seniors. In order of prevalence, these were (i) safety, (ii) confidence concerning ADAS, (iii) ADAS functionality, (iv) user interface/usability, and (v) non-ADAS–related features. Based on topics and associated keywords, seniors perceived safety improvement with ADAS but expressed concerns about its limitations in coping with adverse driving conditions. Experience and training were suggested for improving seniors’ confidence in ADAS. Blind spot alert and adaptive cruise control received the most discussion regarding perceived safety and comfort. Discussion and Implications This study indicated that promoting road safety for senior drivers through ADAS is feasible. Acceptance and appropriate use of ADAS may be supported through intuitive and senior-friendly user interfaces, in-depth training programs, and owner’s manuals specifically designed and tested for senior drivers.

scholarly journals Probabilistic Approach for Validation of Advanced Driver Assistance Systems

2005 ◽  
Vol 1910 (1) ◽  
pp. 20-28
Author(s):  
O. J. Gietelink ◽  
B. De Schutter ◽  
M. Verhaegen
Keyword(s):  
Randomized Algorithms ◽  
Methodological Approach ◽  
Probabilistic Approach ◽  
Performance Criteria ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

This paper presents a methodological approach for validation of advanced driver assistance systems. The methodology relies on the use of randomized algorithms that are more efficient than conventional validation that uses simulations and field tests, especially with increasing complexity of the system. The methodology first specifies the perturbation space and performance criteria. Then, a minimum number of samples and a relevant sampling space are selected. Next, an iterative randomized simulation is executed; then the simulation model is validated with the use of hardware tests to increase the reliability of the estimated performance. The proof of concept is illustrated with some examples of a case study involving an adaptive cruise control system. The case study points out some characteristic properties of randomized algorithms with respect to the necessary sample complexity and sensitivity to model uncertainty. Solutions for these issues are proposed as are corresponding recommendations for research.

Sign in / Sign up

Export Citation Format

Share Document