Different Types, Different Speeds – The Effect of Interaction Partners and Encountering Speeds at Intersections on Drivers’ Gap Acceptance as an Implicit Communication Signal in Automated Driving

Author(s):  
Ann-Christin Hensch ◽  
Matthias Beggiato ◽  
Maike X. Schömann ◽  
Josef F. Krems
Author(s):  
Manuel Dietrich

AbstractAutomated vehicles (AVs) are expected to operate on public roads, together with non-automated vehicles and other road users such as pedestrians or bicycles. Recent ethical reports and guidelines raise worries that AVs will introduce injustice or reinforce existing social inequalities in road traffic. One major injustice concern in today’s traffic is that different types of road users are exposed differently to risks of corporal harm. In the first part of the paper, we discuss the responsibility of AV developers to address existing injustice concerns regarding risk exposure as well as approaches on how to fulfill the responsibility for a fairer distribution of risk. In contrast to popular approaches on the ethics of risk distribution in unavoidable accident cases, we focus on low and moderate risk situations, referred to as routine driving. For routine driving, the obligation to distribute risks fairly must be discussed in the context of risk-taking and risk-acceptance, balancing safety objectives of occupants and other road users with driving utility. In the second part of the paper, we present a typical architecture for decentralized automated driving which contains a dedicated module for real-time risk estimation and management. We examine how risk estimation modules can be adjusted and parameterized to redress some inequalities.


2020 ◽  
Author(s):  
Yee Mun Lee ◽  
Ruth Madigan ◽  
Chinebuli Uzondu ◽  
Jorge Garcia ◽  
Richard Romano ◽  
...  

In current urban traffic, pedestrians attempting to cross the road at un-signalised locations are thought to mostly use implicit communication, such as deceleration cues, to interpret a vehicle’s intention to yield. There is less reliance on explicit driver- or vehicle-based messages, such as hand/head movements, or flashing lights/beeping horns. With the impending deployment of Automated Vehicles (AV), especially those at SAE Level 4 and 5, where the driver is no longer in control of the vehicle, there has been a surge in interest in the value of new forms of communication for AVs, for example, via different types of external Human Machine Interfaces (eHMIs). However, there is still much to be understood about how quickly a novel eHMI affects pedestrian crossing decisions, and whether it provides any additional aid, above and beyond implicit/kinematic information from the vehicle. The aim of this between-participant study, funded by the H2020 interACT project, was to investigate how the combination of kinematic information from a vehicle (e.g. Speed and Deceleration), and eHMI designs, play a role in assisting the crossing decision of pedestrians in a cave-based pedestrian simulator. Using an existing, well-recognised, message for yielding (Flashing Headlights - FH) as a benchmark, this study also investigated how quickly a novel eHMI (Slow Pulsing Light Band – SPLB) was learned. To investigate the effect of eHMI visibility on crossing decisions, the distance at which each eHMI was perceivable was also measured. Results showed that, compared to SPLB, the FH led to earlier crossings during vehicle deceleration, especially at lower approaching speeds, and smaller time gaps. However, although FH was visible earlier than SPLB, this visibility does not appear to be the only reason for earlier crossings, with message familiarity thought to play a role. Participants were found to learn the meaning conveyed by FH relatively quickly, crossing around 1 second earlier in its presence (compared to the no eHMI condition), across the three blocks of trials. On the other hand, it took participants at least one block of 12 trials for the new SPLB signal to affect crossing, which only accelerated crossing initiations by around 200ms, compared to the no eHMI condition. The role of comprehension, long-term exposure, and familiarity of novel messages in this context is therefore important, if AVs are to provide safe, trustworthy communication messages, which will enhance traffic flow and efficiency.


Author(s):  
Kira Coder Gylling ◽  
Åke Brännström

Evolution of cooperation has traditionally been studied by assuming that individuals adopt either of two pure strategies, to cooperate or defect. Recent work have considered continuous cooperative investments, turning full cooperation and full defection into two opposing ends of a spectrum and sometimes allowing for the emergence of the traditionally-studied pure strategies through evolutionary diversification. These studies have typically assumed a well-mixed population in which individuals are encountered with equal probability, Here, we allow for the possibility of assortative interactions by assuming that, with specified probabilities, an individual interacts with one or more other individuals of the same strategy. A closely related assumption has previously been made in evolutionary game theory and has been interpreted in terms of relatedness. We systematically study the effect of relatedness and find, among other conclusions, that the scope for evolutionary branching is reduced by either higher average degree of, or higher uncertainty in, relatedness with interaction partners. We also determine how different types of non-linear dependencies of benefits and costs constrain the types of evolutionary outcomes that can occur. While our results overall corroborate the conclusions of earlier studies, that higher relatedness promotes the evolution of cooperation, our investigation gives a comprehensive picture of how relatedness affects the evolution of cooperation with continuous investments.


Author(s):  
William J. Horrey ◽  
John D. Lee

Objective The aim of this special issue is to bring together the latest research related to driver interaction with various types of vehicle automation. Background Vehicle technology has undergone significant progress over the past decade, bringing new support features that can assist the driver and take on more and more of the driving responsibilities. Method This issue is comprised of eight articles from international research teams, focusing on different types of automation and different user populations, including driver support features through to highly automated driving systems. Results The papers comprising this special issue are clustered into three categories: (a) experimental studies of driver interactions with advanced vehicle technologies; (b) analysis of existing data sources; and (c) emerging human factors issues. Studies of currently available and pending systems highlight some of the human factors challenges associated with the driver–system interaction that are likely to become more prominent in the near future. Moreover, studies of more nascent concepts (i.e., those that are still a long way from production vehicles) underscore many attitudes, perceptions, and concerns that will need to be considered as these technologies progress. Conclusions Collectively, the papers comprising this special issue help fill some gaps in our knowledge. More importantly, they continue to help us identify and articulate some of the important and potential human factors barriers, design considerations, and research needs as these technologies become more ubiquitous.


Author(s):  
Anna Feldhütter ◽  
Christian Gold ◽  
Adrian Hüger ◽  
Klaus Bengler

Highly automated vehicles (HAV), which could help to enhance road safety and efficiency, are very likely to enter the market within the next decades. To have an impact, these systems need to be purchased, which is a matter of trust and acceptance. These factors are dependent on the level of information that one has about such systems. One important source of information is various media, such as newspapers, magazines and videos, in which highly automated driving (HAD) is currently a frequent topic of discussion. To evaluate the influence of media on the perception of HAD, 31 participants were presented with three different types of media addressing HAD in a neutral manner. Afterwards, the participants experienced HAD in the driving simulator. In between these steps, the participants completed questionnaires assessing comfort, trust in automation, increase in safety, intention to use and other factors in order to analyze the effect of the media and the driving simulation experience. Results indicate that the perception of some aspects of HAD were affected by the media presented, while experiencing HAD in the driving simulator generally did not have an effect on the attitude of the participants. Other aspects, such as trust, were not affected by either media or experience. In addition, gender-related differences in the perception of HAD were found.


Author(s):  
Alisha Parveen ◽  
Rajesh Kumar ◽  
Ravi Tandon ◽  
Sukant Khurana ◽  
Chandan Goswami ◽  
...  

Heat shock protein 47kDa (HSP47) serves as a client-specific chaperone, essential for collagen biosynthesis and its folding and structural assembly. To date, there is no comprehensive study on mutational hotspots and protein network for human HSP47. Using five different human mutational databases, we deduced a comprehensive list of human HSP47 mutations and we found 24 67, 50, 43 and 2 deleterious mutations from the 1000 genomes data, gnomAD, COSMICv86, cBioPortal, and CanVar. We identified thirteen top-ranked missense mutations of HSP47 with the stringent cut-off of CADD score (>25) and Grantham score (≥151) as Ser76Trp, Arg103Cys, Arg116Cys, Ser159Phe, Arg167Cys, Arg280Cys, Trp293Cys, Gly323Trp, Arg339Cys, Arg373Cys, Arg377Cys, Ser399Phe, and Arg405Cys with the arginine-cysteine change as the predominant mutation. We also found that HSP47 is up-regulated and down-regulated in 11 and 4 of cancers types. Upon constructing protein interactome map of human HSP47, we found that a set of molecular chaperones is interaction partners of HSP47, which included two copies each of CREB binding proteins, HSP27, HSP40, HSP70, HSP90, ubiquitin proteins and one copy each of cartilage associated protein (CRTAP), HSPH1, HSBP1, FK506-binding protein B (FKBP), kruppel-like factor (KLF13), peptidyl-prolyl isomerase PIPB and Prolyl 4-hydroxylase beta subunit (P4HB). This suggested a cocktail of different chaperones interact with HSP47. These findings will assist in the evaluation of roles of HSP47 in human disease including different types of cancers.


2018 ◽  
Vol 66 (2) ◽  
pp. 119-131 ◽  
Author(s):  
Julian Eggert

AbstractVehicles will be equipped with sensors and functions for highly automated driving in the foreseeable future. A big topic of research on the way to this goal is how to convey to these vehicles an understanding of the driving situations that is comparable to that of humans. For safe driving, this requires predicting how a scene will evolve and anticipating how dangerous it will potentially be. Risk estimation is a central ingredient in this process. In this paper, we describe how risk modeling frameworks help in managing the complexity of the driving task. We approach risk from the perspective of rare probabilistic events in environments where predictions might be inherently uncertain, and explain how this leads to a survival-based formulation which allows to model different types of risks encountered in driving situations within a single unified concept. In addition, we show how the framework can be used for driving behavior evaluation and risk-avoiding trajectory planning.


Information ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 61 ◽  
Author(s):  
Klaus Bengler ◽  
Michael Rettenmaier ◽  
Nicole Fritz ◽  
Alexander Feierle

During automated driving, there is a need for interaction between the automated vehicle (AV) and the passengers inside the vehicle and between the AV and the surrounding road users outside of the car. For this purpose, different types of human machine interfaces (HMIs) are implemented. This paper introduces an HMI framework and describes the different HMI types and the factors influencing their selection and content. The relationship between these HMI types and their influencing factors is also presented in the framework. Moreover, the interrelations of the HMI types are analyzed. Furthermore, we describe how the framework can be used in academia and industry to coordinate research and development activities. With the help of the HMI framework, we identify research gaps in the field of HMI for automated driving to be explored in the future.


2015 ◽  
Vol 27 (3) ◽  
pp. 227-235 ◽  
Author(s):  
Jinxing Shen ◽  
Wenquan Li ◽  
Feng Qiu ◽  
Shukang Zheng

This paper is aimed at investigating the influence of different types of traffic flows on the capacity of freeway merge areas. Based on the classical gap-acceptance model, two calculating models were established specifically considering randomly arriving vehicles and individual difference in driving behaviours. Monte-Carlo simulation was implemented to reproduce the maximum traffic volume on the designed freeway merge area under different situations. The results demonstrated that the proposed calculating models have better performance than the conventional gap-acceptance theory on accurately predicting the capacity of freeway merge areas. The findings of research could be helpful to improve the microscopic traffic flow simulation model from a more practical perspective and support the designing of freeway merge areas as well.


2019 ◽  
Vol 3 (2) ◽  
pp. 25-30
Author(s):  
Emanuel S. H. Qas Marrogy

The identification of different types of modulation for any intercepted communication signal out of the vast hierarchy of possible modulation types is a key fundamental before advising a suitable type of demodulator, where this process is usually a manual option. This technique is extremely important for the purposes of communication intelligence. In this paper, a proposed methodology is suggested, validated, and tested (through computer simulations) for the automatic identification of the modulation type (analog and digital) of the intercepted communication signals. The methodology is based on the zero-based representation of signals and utilization of new algorithms for such identification.


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