Impacts on Driver Perceptions in Initial Exposure to ADAS Technologies

Author(s):  
Ashley B. Nylen ◽  
Michelle L. Reyes ◽  
Cheryl A. Roe ◽  
Daniel V. McGehee

Advanced driver assistance systems (ADAS) offer great promise in improving the safety of our roadways. Although ADAS have rapidly entered the U.S. passenger vehicle market, little is known about driver understanding and attitudes toward ADAS, especially the impact of their initial exposure to the technologies. Whereas some ADAS may be easy to learn and use, others are more complex and have limitations that may not be obvious to the driver. The Technology Demonstration Study was conducted to evaluate how the ways in which drivers learn about ADAS affect their knowledge and perceptions of the technology. Two base learning methods were utilized for the study, both of which are traditional forms of learning for the average driver: reading the owner’s manual and making observations inside the vehicle. From these base learning methods, four learning protocols were developed, two of which included both methods. This paper investigates how drivers’ perceptions of usefulness, apprehension, and trust with regard to ADAS functionality were affected by initial exposure to the technology. Participants who observed ADAS during a demonstration drive had more positive perceptions relative to those who only read about them, particularly for ADAS that provide vehicle control.

Author(s):  
Vanessa Nasr ◽  
David Wozniak ◽  
Farzaneh Shahini ◽  
Maryam Zahabi

Motor vehicle crashes are one of the leading causes of injuries and deaths for police officers. Advanced driver-assistance systems (ADAS) are driving control systems that have been found to improve civilian drivers’ safety; however, the impact of ADAS on police officers’ driving safety has yet to be investigated thoroughly. Disparities between driver states and tasks performed while driving between police and civilian drivers necessitate this distinction. This study identified the types of ADAS used in police vehicles, their impact on officers’ safety, and proposed potential future ADAS features to be implemented in police vehicles. A systematic literature review was conducted using Google Scholar, Compendex, Web of Science, Transport Research International Documentation (TRID), and Google Patents databases to identify the most prevalent police vehicles used in the U.S., available ADAS features in those vehicles, and the impact of ADAS on officers’ safety. A list of recommended ADAS features was developed based on the review of literature, authors’ knowledge and experience in the field, and the findings of an online survey with 73 police officers. Results indicated the addition of multiple ADAS features including the front vehicle detection system, intersection collision avoidance, evasive steering systems, left turn assist, traffic sign detection system, traffic jam assist, two lane and lane-ending detection, wrong-way alert, and autonomous highway driving features have the potential to improve officer safety and performance while driving. However, there was a void of studies focused on ADAS effects on police driving safety which needs to be addressed in future investigations.


2021 ◽  
Vol 15 ◽  
Author(s):  
Francesco Rundo ◽  
Sabrina Conoci ◽  
Concetto Spampinato ◽  
Roberto Leotta ◽  
Francesca Trenta ◽  
...  

In recent years, the automotive field has been changed by the accelerated rise of new technologies. Specifically, autonomous driving has revolutionized the car manufacturer's approach to design the advanced systems compliant to vehicle environments. As a result, there is a growing demand for the development of intelligent technology in order to make modern vehicles safer and smarter. The impact of such technologies has led to the development of the so-called Advanced Driver Assistance Systems (ADAS), suitable to maintain control of the vehicle in order to avoid potentially dangerous situations while driving. Several studies confirmed that an inadequate driver's physiological condition could compromise the ability to drive safely. For this reason, assessing the car driver's physiological status has become one of the primary targets of the automotive research and development. Although a large number of efforts has been made by researchers to design safety-assessment applications based on the detection of physiological signals, embedding them into a car environment represents a challenging task. These mentioned implications triggered the development of this study in which we proposed an innovative pipeline, that through a combined less invasive Neuro-Visual approach, is able to reconstruct the car driver's physiological status. Specifically, the proposed contribution refers to the sampling and processing of the driver PhotoPlethysmoGraphic (PPG) signal. A parallel enhanced low frame-rate motion magnification algorithm is used to reconstruct such features of the driver's PhotoPlethysmoGraphic (PPG) data when that signal is no longer available from the native embedded sensor platform. A parallel monitoring of the driver's blood pressure levels from the PPG signal as well as the driver's eyes dynamics completes the reconstruction of the driver's physiological status. The proposed pipeline has been tested in one of the major investigated automotive scenarios i.e., the detection and monitoring of pedestrians while driving (pedestrian tracking). The collected performance results confirmed the effectiveness of the proposed approach.


Author(s):  
Tobias Lorenz ◽  
Klaus Jaschke ◽  
Frank Köster

The development and evaluation of human centered driver assistance systems is one major research focus within the automotive domain of the Institute of Transportation Systems (TS) at the German Aerospace Center (DLR). To investigate the impact of new driver assistance systems on driver behavior different research facilities from simulations to real car environments are used. One research facility at TS is the dynamic driving simulator with a hexapod structure. Using dynamic driving simulators to reproduce real car motion is a major challenge as the workspace is limited. Within this paper a method of state adaption is presented. This method enables a discrete switching of high-pass filter corner frequencies within one single simulation time step. Thereby discontinuities of the filter output signal as well as in the derivatives of the output signal are avoidable. Thus, it is possible to adapt corner frequencies of high-pass filters of a Motion Cueing Algorithm (MCA), according to the current driving situation. The paper starts with a description of the MCA currently used for the motion rendering at TS. Afterward the state adaption method is described including the challenges for adapting this method to the current MCA structure. In the end of the new structure for the time-variant MCA as well as the boundary conditions for corner frequency switching and the test results of the new time-variant approach using the state adaption method are outlined.


2021 ◽  
Vol 13 (8) ◽  
pp. 4264
Author(s):  
Matúš Šucha ◽  
Ralf Risser ◽  
Kristýna Honzíčková

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.


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