scholarly journals Co-DAS: Development and Evaluation of Co-Driver Assistance System Concepts to Reduce Passenger Discomfort

2021 ◽  
Author(s):  
Sandra Ittner ◽  
Dominik Muehlbacher ◽  
Mark Vollrath ◽  
Thomas H. Weisswange
Keyword(s):  
Cognitive Processes ◽  
Driver Assistance System ◽  
Missing Information ◽  
Driver Assistance ◽  
Driving Experience ◽  
Car Following ◽  
The Everyday ◽  
Assistant Systems ◽  
Assistance Systems

The front seat passenger is often neglected when developing support systems for cars. There exist few examples of systems that provide information or interaction possibilities specifically to those passengers. Previous research indicated that the passive role of the passenger can frequently lead to a feeling of discomfort, potentially caused by missing information and missing control with respect to the driving situation. This paper proposes a variety of prototypical passenger assistance systems that target different aspects of the cognitive processes which could cause the feeling of discomfort. In a simulator study with N = 40 participants, these systems were investigated with respect to their influence on measures of discomfort. Participants experienced different car following and braking scenarios on the highway with different time headways, with and without one of the passenger assistance systems. Based on the subjective measures, three systems were identified as particularly useful in reducing discomfort. For the best of these proposals, more than 63 % of the passengers confirmed the usefulness of the approach and reported an interest in using it in their vehicle. This demonstrates significant opportunities to improve the everyday driving experience beyond classical assistant systems by explicitly taking into account the needs of the passengers.

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.

scholarly journals THE USE OF VEHICLE DATA IN ADAS DEVELOPMENT, VERIFICATION AND FOLLOW-UP ON THE SYSTEM

2020 ◽  
Vol 1 ◽  
pp. 2551-2560
Author(s):  
J. Orlovska ◽  
C. Wickman ◽  
R. Soderberg
Keyword(s):  
Data Driven ◽  
Context Aware ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Volvo Cars ◽  
Vehicle Data ◽  
Assistance Systems ◽  
High Level

AbstractAdvanced Driver Assistance Systems (ADAS) require a high level of interaction between the driver and the system, depending on driving context at a particular moment. Context-aware ADAS evaluation based on vehicle data is the most prominent way to assess the complexity of ADAS interactions. In this study, we conducted interviews with the ADAS development team at Volvo Cars to understand the role of vehicle data in the ADAS development and evaluation. The interviews’ analysis reveals strategies for improvement of current practices for vehicle data-driven ADAS evaluation.

scholarly journals Toward Intelligent Human Machine Interactions

2017 ◽  
Vol 139 (06) ◽  
pp. S4-S8 ◽  
Author(s):  
Yingzi Lin
Keyword(s):  
Control Strategy ◽  
Driver Assistance System ◽  
Effective Means ◽  
Rehabilitation Robotics ◽  
Driver Assistance ◽  
Human Errors ◽  
Important Method ◽  
Warning Message ◽  
Powerful Research Tool ◽  
Assistance Systems

This article discusses the concept of human assistance systems (HAS) and research works to design the interface of HAS. It also focuses on the issue of how humans and HAS collaborate with each other during such interactions. HAS are expected to detect and compensate for human errors. In a case that a machine is a part of the team to complete an operation, it is highly desired that HAS collaborate with humans effectively. Advances on HAS have been made within application areas including vehicle driving, pilot–flight interfaces, healthcare and rehabilitation, robotics, etc. One important method for studying driver assistance system (DAS) is the availability of a powerful research tool, as the simulator is an effective means to generate real-world traffic scenarios without putting drivers in any real danger. A control strategy for HAS been investigated, especially for DAS. The goal is to provide a warning message and/or intervention to the driver if necessary to avoid hitting objects on road while not frustrating the user.

scholarly journals Can ADAS Distract Driver’s Attention? An RGB-D Camera and Deep Learning-Based Analysis

2021 ◽  
Vol 11 (24) ◽  
pp. 11587
Author(s):  
Luca Ulrich ◽  
Francesca Nonis ◽  
Enrico Vezzetti ◽  
Sandro Moos ◽  
Giandomenico Caruso ◽  
...  
Keyword(s):  
Deep Learning ◽  
Expression Recognition ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Driving Experience ◽  
Vehicle Accidents ◽  
Non Invasive ◽  
Driver Inattention ◽  
Assistance Systems ◽  
Invasive Techniques

Driver inattention is the primary cause of vehicle accidents; hence, manufacturers have introduced systems to support the driver and improve safety; nonetheless, advanced driver assistance systems (ADAS) must be properly designed not to become a potential source of distraction for the driver due to the provided feedback. In the present study, an experiment involving auditory and haptic ADAS has been conducted involving 11 participants, whose attention has been monitored during their driving experience. An RGB-D camera has been used to acquire the drivers’ face data. Subsequently, these images have been analyzed using a deep learning-based approach, i.e., a convolutional neural network (CNN) specifically trained to perform facial expression recognition (FER). Analyses to assess possible relationships between these results and both ADAS activations and event occurrences, i.e., accidents, have been carried out. A correlation between attention and accidents emerged, whilst facial expressions and ADAS activations resulted to be not correlated, thus no evidence that the designed ADAS are a possible source of distraction has been found. In addition to the experimental results, the proposed approach has proved to be an effective tool to monitor the driver through the usage of non-invasive techniques.

scholarly journals The Driving Lesson as a Socio-Technical Situation. A Case Study on the Interaction between Learner Driver, Driving Instructor, and the Motor Car

2021 ◽  
Vol 17 (2) ◽  
pp. 6-21
Author(s):  
Alexander Schmidl
Keyword(s):  
Detailed Analysis ◽  
Human Body ◽  
Technical Information ◽  
Theoretical Background ◽  
The Body ◽  
Driver Assistance ◽  
Driver Assistance Systems ◽  
Assistance Systems

A micro-sociological examination of the driving lesson raises the following question: How is the interaction between learner driver and driving instructor structured in this technical setting, and what meaning can be ascribed in this threefold constellation to the vehicle with its various technical elements? This case study examines the orientation patterns which exist between the learner driver, the driving instructor, and the car, which together constitute a socio-technical triangle, and what actions the learner driver needs to learn to enable them to drive the car safely. The theoretical background to the study is provided by interactionist theories, which have been broadened to include a greater sensitivity for the body and technology, and a sociological reading of postphenomenology. Using a method based on this theoretical background and informed by workplace studies, this study observed and made audiovisual recordings of driving lessons. This approach made it possible to undertake a detailed analysis of the situations, reveal how the human body interacts with technology, and how a person’s attention responds to technical information. In these situations, the driving instructor takes on the role of the translator by mediating between various situational definitions—one’s own, that of the inexperienced learner driver, other motorists, and the driver assistance systems in the car. The driving instructor represents the driving school as an institution that is responsible for creating an intersubjectively arranged understanding of how to deal with technology and socio-technical situations.

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