Third-Party Vehicle Data Collection for Advanced Driver Assistance Systems Analysis

2021 ◽  
pp. 036119812110391
Author(s):  
Kathleen Berman ◽  
Keith Campbell ◽  
Valerie Gawron ◽  
Jeffrey Long ◽  
Samir Yuha
Keyword(s):  
Can Bus ◽  
Third Party ◽  
Steering Wheel ◽  
Gps Data ◽  
Area Network ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Assistance Systems

Logs of vehicle controller area network (CAN) bus traffic supplemented by accelerometer and GPS data can provide valuable information about the use and operation of advanced driver assistance systems (ADAS) to the broader safety research community. Although CAN bus message codes are often manufacturer-specific, third-party libraries provide partial decoding of messages from many vehicle models, which can be augmented by reverse-engineering additional signals. This study explored the value of CAN bus, accelerometer, and GPS data that were logged on a variety of light vehicle models with an emphasis on availability of lane keep assist/lane departure warning, and adaptive cruise control. This study demonstrated that in-vehicle ADAS variables such as system on/off status and whether the system is actively controlling the vehicle could be determined on a variety of vehicle types. Associated control variables such as steering wheel angle, gas pedal state, and brake pedal state could also be determined from most vehicles tested. CAN messages, together with roadway features identified via GPS location, can provide a richer understanding of ADAS efficacy. Comparisons of message structure between models may also inform standardization efforts for electronic data recorders and telematics.

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.

Instrumented Steering Wheel: Accurate Experimental Characterisation of the Forces Exerted by the Driver Hands for Future Advanced Driver Assistance Systems

2018 ◽  
Author(s):  
Francesco Comolli ◽  
Federico M. Ballo ◽  
Massimiliano Gobbi ◽  
Gianpiero Mastinu
Keyword(s):  
Steering Wheel ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Advanced Driver Assistance Systems ◽  
Plate Test ◽  
Driving Behaviors ◽  
Load Cells ◽  
Assistance Systems ◽  
Lateral Disturbance ◽  
Experimental Characterisation

The interaction between driver and vehicle is analyzed in the paper. The driver acts on the steering wheel to modify the trajectory and to control the vehicle during panic situations. The knowledge of the forces exerted by the driver at the steering wheel is useful for a better understanding of the driver steering action. The final aim is to inspire the development of haptic steering wheels for better tuning of Advanced Driver Assistance Systems (ADAS). An instrumented steering wheel has been used, which includes two six axis load cells to measure the forces and the moments exerted by the driver hands and six sensors used to measure the grip strength. Two maneuvers have been considered, a moderate speed turn and a kick plate test which simulates a panic situation with an impulsive lateral disturbance. For both of the two considered situations, some common driving behaviors have been highlighted and analyzed. The preliminary results encourage the development of haptic instrumented steering wheels, able to improve ADAS. Actually it seems possible to infer the driver steering purpose before the steering wheel is actually rotated.

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.

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.

scholarly journals Is a flick-through enough? A content analysis of Advanced Driver Assistance Systems (ADAS) user manuals

PLoS ONE ◽  
2021 ◽  
Vol 16 (6) ◽  
pp. e0252688
Author(s):  
Oscar Oviedo-Trespalacios ◽  
Jennifer Tichon ◽  
Oliver Briant
Keyword(s):  
Content Analysis ◽  
Blind Spot ◽  
Cruise Control ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Regulatory Oversight ◽  
Advanced Driver Assistance Systems ◽  
Research Gap ◽  
Assistance Systems ◽  
Education Needs

Advanced Driver Assistance Systems (ADAS) are being developed and installed in increasing numbers. Some of the most popular ADAS include blind spot monitoring and cruise control which are fitted in the majority of new vehicles sold in high-income countries. With more drivers having access to these technologies, it is imperative to develop policy and strategies to guarantee the safe uptake of ADAS. One key issue is that ADAS education has been primarily centred on the user manual which are not widely utilised. Moreover, it is unclear if user manuals are an adequate source of education in terms of content and readability. To address this research gap, a content analysis was used to assess the differences in ADAS-related content and readability among the manuals of the highest selling vehicles in Australia. The qualitative findings showed that there are seven themes in the user manuals: differences between driving with and without ADAS, familiarisation requirements, operational limits of the ADAS, potential ADAS errors, behaviour adaptation warnings, confusion warnings, and malfunction warnings. The quantitative analysis found that some of the manuals require several years of education above the recommended for a universal audience (>8 years) to be understood. Additionally, there is a notable number of text diversions and infographics which could make comprehension of the user manual difficult. This investigation shows that there is a lack of standardisation of ADAS user manuals (in both content and delivery of information) which requires regulatory oversight. Driver ADAS education needs to be prioritised by policymakers and practitioners as smart technology continues to increase across the transport system. It seems that current strategies based on user manuals are insufficient to achieve successful adoption and safe use of these technologies.

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