Taking a Hybrid (Analog Beamsteering + Digital Signaling) Approach to Automotive Radar to Advance a Myriad of Highly Automated Driving Applications on the Road to Full Autonomy

2021 ◽  
Author(s):  
Maha Achour
Keyword(s):  
Automotive Radar ◽  
Automated Driving ◽  
The Road ◽  
On The Road ◽  
Highly Automated Driving

scholarly journals Behavioral Changes to Repeated Takeovers in Highly Automated Driving: Effects of the Takeover-Request Design and the Nondriving-Related Task Modality

2018 ◽  
Vol 61 (5) ◽  
pp. 839-849 ◽  
Author(s):  
Fabienne Roche ◽  
Anna Somieski ◽  
Stefan Brandenburg
Keyword(s):  
Subjective Experience ◽  
Vehicle Control ◽  
Behavioral Changes ◽  
Behavior Changes ◽  
Automated Driving ◽  
The Road ◽  
Gaze Patterns ◽  
On The Road ◽  
Task Modality ◽  
Highly Automated Driving

Objective: We investigated drivers’ behavior and subjective experience when repeatedly taking over their vehicles’ control depending on the design of the takeover request (TOR) and the modality of the nondriving-related task (NDRT). Background: Previous research has shown that taking over vehicle control after highly automated driving provides several problems for drivers. There is evidence that the TOR design and the NDRT modality may influence takeover behavior and that driver behavior changes with more experience. Method: Forty participants were requested to resume control of their simulated vehicle six times. The TOR design (auditory or visual-auditory) and the NDRT modality (auditory or visual) were varied. Drivers’ takeover behavior, gaze patterns, and subjective workload were recorded and analyzed. Results: Results suggest that drivers change their behavior to the repeated experience of takeover situations. An auditory TOR leads to safer takeover behavior than a visual-auditory TOR. And with an auditory TOR, the takeover behavior improves with experience. Engaging in the visually demanding NDRT leads to fewer gazes on the road than the auditory NDRT. Participants’ fixation duration on the road decreased over the three takeovers with the visually demanding NDRT. Conclusions: The results imply that (a) drivers change their behavior to repeated takeovers, (b) auditory TOR designs might be preferable over visual-auditory TOR designs, and (c) auditory demanding NDRTs allow drivers to focus more on the driving scene. Application: The results of the present study can be used to design TORs and determine allowed NDRTs in highly automated driving.

scholarly journals Analysis of the advancements in real-life performance of highly automated vehicles' with regard to the road traffic safety

2018 ◽  
Vol 231 ◽  
pp. 05003 ◽  
Author(s):  
Arkadiusz Matysiak ◽  
Paula Razin
Keyword(s):  
Traffic Safety ◽  
Large Scale ◽  
Road Traffic ◽  
Real Life ◽  
Automated Vehicles ◽  
Automated Driving ◽  
The Road ◽  
Road Traffic Safety ◽  
On The Road ◽  
The Impact

The article presents the analysis of the performance of the vehicles equipped with automated driving systems (ADS) which were tested in real-life road conditions from 2015 to 2017 in the state of California. It aims at the effort to assess the impact on the road safety the continuous technological advancements in driving automation might have, based on of the first large-scale, real-life test deployments. Vehicle manufacturers and other stakeholders testing the highly automated vehicles in California are obliged to issue yearly reports which provide an insight on the test scale as well as the technology maturity. The so-called 'disengagement reports' highlight the range and number of control takeovers between the ADS and driver, which are made either based on driver's decision or information provided by the vehicle itself. The analysis of these reports allowed to investigate the development made in automated driving technology throughout the years of tests, as well as the direct or indirect influence of the external factors (e.g. various weather conditions) on the ADS performance. The results show that there is still a significant gap in reliability and safety between human drivers and highly automated vehicles which has been yet steadily decreasing due to technology advancements made while driving in the specific infrastructure and traffic conditions of California.

scholarly journals Impact of Automated Truck Platooning on the Performance of Freeway Mixed Traffic Flow

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Seolyoung Lee ◽  
Cheol Oh ◽  
Gunwoo Lee
Keyword(s):  
Traffic Flow ◽  
Energy Savings ◽  
Automated Driving ◽  
Average Speed ◽  
The Road ◽  
Mobility Performance ◽  
Vehicle Platooning ◽  
Negative Effect ◽  
The Difference ◽  
On The Road

Vehicle platooning service through wireless communication and automated driving technology has become a reality. Vehicle platooning means that several vehicles travel like a train on the road with a minimum safety distance, which leads to the enhancement of safety, mobility, and energy savings. This study proposed a framework for exploring traffic mobility and safety performance due to the market penetration rate (MPR) of truck platoons based on microscopic traffic simulations. A platoon formation algorithm was developed and run on the VISSIM platform to simulate automated truck maneuvering. As a result of the mobility analysis, it was found that the difference in network mobility performance was not significant up to MPR 80%. Regarding the mobility performance of the truck-designated lane, it was found that the average speed was lower than in other lanes. In the truck-designated lane of the on-ramp section, the average speed was identified to be approximately 33% lower. From the viewpoint of network safety, increasing the MPR of the truck platoon has a positive effect on longitudinal safety but has a negative effect on lateral safety. The safety analysis of the truck-designated lane indicated that the speed difference by lane of MPR 100% is 2.5 times higher than that of MPR 0%. This study is meaningful in that it explores traffic flow performance on mobility and safety in the process of platoon formation. The outcomes of this study are expected to be utilized as fundamentals to support the novel traffic operation strategy in platooning environments.

scholarly journals Displays for Productive Non-Driving Related Tasks: Visual Behavior and Its Impact in Conditionally Automated Driving

2021 ◽  
Vol 5 (4) ◽  
pp. 21
Author(s):  
Clemens Schartmüller ◽  
Klemens Weigl ◽  
Andreas Löcken ◽  
Philipp Wintersberger ◽  
Marco Steinhauser ◽  
...  
Keyword(s):  
Driving Simulator ◽  
Reaction Times ◽  
Driving Performance ◽  
Automated Driving ◽  
Auditory Condition ◽  
Safety Critical ◽  
The Road ◽  
Within Subjects ◽  
On The Road ◽  
Vehicle Automation

(1) Background: Primary driving tasks are increasingly being handled by vehicle automation so that support for non-driving related tasks (NDRTs) is becoming more and more important. In SAE L3 automation, vehicles can require the driver-passenger to take over driving controls, though. Interfaces for NDRTs must therefore guarantee safe operation and should also support productive work. (2) Method: We conducted a within-subjects driving simulator study (N=53) comparing Heads-Up Displays (HUDs) and Auditory Speech Displays (ASDs) for productive NDRT engagement. In this article, we assess the NDRT displays’ effectiveness by evaluating eye-tracking measures and setting them into relation to workload measures, self-ratings, and NDRT/take-over performance. (3) Results: Our data highlights substantially higher gaze dispersion but more extensive glances on the road center in the auditory condition than the HUD condition during automated driving. We further observed potentially safety-critical glance deviations from the road during take-overs after a HUD was used. These differences are reflected in self-ratings, workload indicators and take-over reaction times, but not in driving performance. (4) Conclusion: NDRT interfaces can influence visual attention even beyond their usage during automated driving. In particular, the HUD has resulted in safety-critical glances during manual driving after take-overs. We found this impacted workload and productivity but not driving performance.

scholarly journals How the Initial Level of Trust in Automated Driving Impacts Drivers’ Behaviour and Early Trust Construction

2021 ◽  
Author(s):  
J. B. Manchon ◽  
Mercedes Bueno ◽  
Jordan Navarro
Keyword(s):  
Driving Simulator ◽  
Initial Level ◽  
Environment Monitoring ◽  
Automated Driving ◽  
The Road ◽  
Trust In Automation ◽  
Gaze Behaviour ◽  
Simulator Study ◽  
The Impact ◽  
Highly Automated Driving

Trust in Automation is known to influence human-automation interaction and user behaviour. In the Automated Driving (AD) context, studies showed the impact of drivers’ Trust in Automated Driving (TiAD), and linked it with, e.g., difference in environment monitoring or driver’s behaviour. This study investigated the influence of driver’s initial level of TiAD on driver’s behaviour and early trust construction during Highly Automated Driving (HAD). Forty drivers participated in a driving simulator study. Based on a trust questionnaire, participants were divided in two groups according to their initial level of TiAD: high (Trustful) vs. low (Distrustful). Declared level of trust, gaze behaviour and Non-Driving-Related Activities (NDRA) engagement were compared between the two groups over time. Results showed that Trustful drivers engaged more in NDRA and spent less time monitoring the road compared to Distrustful drivers. However, an increase in trust was observed in both groups. These results suggest that initial level of TiAD impact drivers’ behaviour and further trust evolution.

scholarly journals A Survey to Understand Emotional Situations on the Road and What They Mean for Affective Automotive UIs

2018 ◽  
Vol 2 (4) ◽  
pp. 75 ◽  
Author(s):  
Michael Braun ◽  
Bastian Pfleging ◽  
Florian Alt
Keyword(s):  
Positive Emotions ◽  
Online Survey ◽  
Life Experiences ◽  
Negative Emotion ◽  
Real Life ◽  
Automated Driving ◽  
Negative Experiences ◽  
The Road ◽  
On The Road ◽  
Traffic Behavior

In this paper, we present the results of an online survey (N = 170) on emotional situations on the road. In particular, we asked potential early adopters to remember a situation where they felt either an intense positive or negative emotion while driving. Our research is motivated by imminent disruptions in the automotive sector due to automated driving and the accompanying switch to selling driving experiences over horsepower. This creates a need to focus on the driver’s emotion when designing in-car interfaces. As a result of our research, we present a set of propositions for affective car interfaces based on real-life experiences. With our work we aim to support the design of affective car interfaces and give designers a foundation to build upon. We find respondents often connect positive emotions with enjoying their independence, while negative experiences are associated mostly with traffic behavior. Participants who experienced negative situations wished for better information management and a higher degree of automation. Drivers with positive emotions generally wanted to experience the situation more genuinely, for example, by switching to a “back-to-basic” mode. We explore these statements and discuss recommendations for the design of affective interfaces in future cars.

scholarly journals Repeated Usage of an L3 Motorway Chauffeur: Change of Evaluation and Usage

Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 114 ◽  
Author(s):  
Barbara Metz ◽  
Johanna Wörle ◽  
Michael Hanig ◽  
Marcus Schmitt ◽  
Aaron Lutz
Keyword(s):  
Driving Simulator ◽  
Automated Driving ◽  
Driving Function ◽  
Behavioural Adaptation ◽  
The Road ◽  
Driving Time ◽  
Level 3 ◽  
Simulator Study ◽  
First Contact ◽  
Highly Automated Driving

Most studies on users’ perception of highly automated driving functions are focused on first contact/single usage. Nevertheless, it is expected that with repeated usage, acceptance and usage of automated driving functions might change this perception (behavioural adaptation). Changes can occur in drivers’ evaluation, in function usage and in drivers’ reactions to take-over situations. In a driving simulator study, N = 30 drivers used a level 3 (L3) automated driving function for motorways during six experimental sessions. They were free to activate/deactivate that system as they liked and to spend driving time on self-chosen side tasks. Results already show an increase of experienced trust and safety, together with an increase of time spent on side tasks between the first and fourth sessions. Furthermore, attention directed to the road decreases with growing experience with the system. The results are discussed with regard to the theory of behavioural adaptation. Results indicate that the adaptation of acceptance and usage of the highly automated driving function occurs rather quickly. At the same time, no behavioural adaptation for the reaction to take-over situations could be found.

scholarly journals Autonomous Driving – How to Apply Safety Principles

Dependability ◽  
2019 ◽  
Vol 19 (3) ◽  
pp. 21-33
Author(s):  
H. Schӓbe
Keyword(s):  
Autonomous Driving ◽  
Automated Driving ◽  
Safety Standards ◽  
The Road ◽  
Safe Life ◽  
Level Of Automation ◽  
Human Driver ◽  
On The Road ◽  
Fail Safe ◽  
Automatic Systems

We discuss safety principles of autonomous driving road vehicles. First, we provide a comparison between principles and experience of autonomous or automatic systems on rails and on the road. An automatic metro operates in a controlled and well-defined environment, passengers and third persons are separated from driving trains by fences, tunnels, etc. A road vehicle operates in a much more complex environment. Further, we discuss safety principles. The application of safety principles (e.g. fail-safe or safe-life) is used to design and implement a safe system that eventually fulfils the requirements of the functional safety standards. The different responsibility of human driver and technical driving system in different automation levels for autonomous driving vehicles require the application of safety principles. We consider, which safety principles have to be applied using general safety principles and analysing the relevant SAE level based on the experience from projects for the five levels of automated driving as defined by the SAE. Depending on the level of automation, the technical systems are implemented as fail-silent, fails-safe or as safe-life.

scholarly journals Study on the Road Friction Database for Automated Driving: Fundamental Consideration of the Measuring Device for the Road Friction Database

2021 ◽  
Vol 12 (1) ◽  
pp. 18
Author(s):  
Ichiro Kageyama ◽  
Yukiyo Kuriyagawa ◽  
Tetsunori Haraguchi ◽  
Tetsuya Kaneko ◽  
Motohiro Asai ◽  
...  
Keyword(s):  
Friction Coefficient ◽  
Traffic Safety ◽  
Surface Condition ◽  
Automated Driving ◽  
Friction Coefficients ◽  
Measuring Device ◽  
Friction Characteristics ◽  
The Road ◽  
Road Friction ◽  
On The Road

This study deals with the possibility of construction of a database on the braking friction coefficient for actual roads from the viewpoint of traffic safety, especially for automated driving, such as level 4 or higher. At these levels of automated driving, the controller needs to control the vehicle. However, the road surface condition, especially the road friction coefficient on wet roads and snowy or icy roads, changes greatly, and in some cases, changes by almost one order. Therefore, it is necessary for the controller to constantly collect environment information, such as the road friction coefficients, and prepare for emergencies, such as obstacle avoidance. However, at present, the measurement of the road friction coefficients is not systemically performed, and a method for accurately measuring has not been established. In order to improve this situation, this study examines a method for continuous measurement of the road friction characteristics, such as the μ-s characteristics. It is shown that the μ-s characteristics are continuously measured using the MF generally used in tire engineering, and the friction characteristics identified from the results are sufficiently satisfactory.

scholarly journals Underload on the Road: Measuring Vigilance Decrements During Partially Automated Driving

2021 ◽  
Vol 12 ◽  
Author(s):  
Thomas McWilliams ◽  
Nathan Ward
Keyword(s):  
Cognitive Demand ◽  
Future Research ◽  
Automated Vehicles ◽  
Automated Driving ◽  
Automated Vehicle ◽  
The Road ◽  
Critical Situation ◽  
Vehicle Technology ◽  
On The Road

Partially automated vehicle technology is increasingly common on-road. While this technology can provide safety benefits to drivers, it also introduces new concerns about driver attention. In particular, during partially automated driving (PAD), drivers are expected to stay vigilant so they can readily respond to important events in their environment. However, using partially automated vehicles on the highway places drivers in monotonous situations and requires them to do very little. This can place the driver in a state of cognitive underload in which they experience a very small amount of cognitive demand. In this situation, drivers can exhibit vigilance decrements which impact their ability to respond to on-road threats. This is of particular concern in situations when the partially automated vehicle fails to respond to a potentially critical situation and leaves all responsibility to safely navigate to the driver. This paper reviews situations that lead to vigilance decrements and characterizes the different methodologies of measuring driver vigilance during PAD, highlighting their advantages and limitations. Based on our reading of the literature, we summarize several factors future research on vigilance decrements in PAD should consider.

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