Effect of Driving Contexts on Driver Acceptance of Advanced Driver Assistance Systems

2017 ◽  
Vol 61 (1) ◽  
pp. 1944-1948 ◽  
Author(s):  
Md Mahmudur Rahman ◽  
Lesley Strawderman ◽  
Daniel W. Carruth
Keyword(s):  
Online Survey ◽  
Time Pressure ◽  
Time Of Day ◽  
Transportation Safety ◽  
Intention To Use ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems ◽  
Driver Acceptance

Advanced Driver Assistance Systems (ADASs) has been developed to enhance driver performance and comfort and improve transportation safety. The potential benefits of these technologies include: reduction in the number of crashes, enhanced vehicle control for drivers, reduced environmental impact, etc. However, for these technologies to achieve their potential, drivers must accept them and use them appropriately in traffic. This study investigated the effect of driving contexts on driver acceptance, more specifically, on the intention to use such technologies. Three contextual factors were considered: drivers’ fatigue level, time pressure, and time of day. Data collection was done using an online survey approach ( n = 386). Results found that fatigue and time pressure significantly affect drivers’ intention to use an ADAS. Results showed that drivers have increased intention to use an ADAS when they are fatigued or when there is no time pressure, as compared to a general driving condition.

Exploring User Understanding of Advanced Driver Assistance Systems Iconography Using Novel Survey Methods

2021 ◽  
pp. 036119812110513
Author(s):  
Steven Landry ◽  
Bobbie Seppelt ◽  
Luca Russo ◽  
Martin Krampell
Keyword(s):  
Online Survey ◽  
Evaluation Method ◽  
Survey Methods ◽  
Functional Requirements ◽  
Visual Displays ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

As advanced driver assistance systems (ADAS) increase in functionality, so do the functional requirements of their visual displays to communicate status and settings. Drivers who misinterpret in-vehicle displays may be more likely to misuse or avoid using ADAS, negating the potential safety benefits. A novel evaluation method is proposed and applied to the (at the time of surveying) latest Volvo instrument cluster. An online survey was completed by 838 Volvo car owners with varying levels of familiarity with adaptive cruise control and pilot assist. Results suggest that the concepts of a system being “available but not on” or “on but not actively providing support” can be difficult for novice users to recognize, resulting in a mode or state confusion. However, more experienced users were less likely to make these types of errors. The assessment method of providing users with partially masked images shows promise as a useful tool for evaluating comprehension of ADAS in-vehicle visual displays.

Advanced driver assistance systems: Using multimodal redundant warnings to enhance road safety

2017 ◽  
Vol 58 ◽  
pp. 238-244 ◽  
Author(s):  
Francesco Biondi ◽  
David L. Strayer ◽  
Riccardo Rossi ◽  
Massimiliano Gastaldi ◽  
Claudio Mulatti
Keyword(s):  
Road Safety ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

MỘT PHƯƠNG PHÁP PHÁT HIỆN ĐIỂM MÙ VỚI ĐỘ TIN CẬY CAO VÀ THỜI GIAN THỰC CHO CÁC HỆ THỐNG HỖ TRỢ LÁI XE THÔNG MINH

2020 ◽  
pp. 47-58
Author(s):  
Sơn
Keyword(s):  
Region Of Interest ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

Các hệ thống hỗ trợ lái xe tiên tiến (Advanced Driver Assistance Systems: ADAS) đóng một vai trò quan trọng trong hệ thống an toàn chủ động chỉ có camera và các phương tiện tự động thông minh. Đối với các ứng dụng này, các yêu cầu về hiệu suất phát hiện đáng tin cậy và thời gian thực là các yếu tố cấp thiết. Bài báo này đề xuất giải pháp tối ưu tốc độ phát hiện ô tô và giảm các cảnh báo lỗi cho các hệ thống phát hiện điểm mù. Theo đó, trước tiên chúng tôi đề xuất bộ phân tầng Cascade – AdaBoost cùng với tập dữ liệu mẫu và thuật toán đào tạo của chúng tôi. Ngoài ra, để cải thiện tốc độ phát hiện, một kĩ thuật lựa chọn vùng quan tâm (Region of Interest: ROI) cũng được sử dụng để tránh trích xuất các vùng có khả năng tạo ra các cảnh báo lỗi như là bầu trời hoặc các vùng không phù hợp với phối cảnh. Phương pháp đề xuất đã tăng tốc độ phát hiện lên ít nhất 1,9 lần và giảm cảnh báo lỗi 2,24 lần so với phương pháp truyền thống ở các ảnh có độ phân giải cao (720 x 480) với tỷ lệ phát hiện đạt 99,4% và tỷ lệ cảnh báo lỗi nhỏ là 4,08%. Phương pháp đề xuất này có thể được ứng dụng cho các xe tự hành thông minh thời gian thực.

Gradient Reversal Domain Adaptation Pipeline in Advanced Driver Assistance Systems

2021 ◽  
Author(s):  
Francesco Rundo ◽  
Roberto Leotta ◽  
Sebastiano Battiato ◽  
Concetto Spampinato ◽  
Sabrina Conoci
Keyword(s):  
Domain Adaptation ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

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.

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