scholarly journals A decision-making architecture for automated driving without detailed prior maps

Author(s):  
Antonio Artunedo ◽  
Jorge Godoy ◽  
Jorge Villagra
Author(s):  
Lucero Rodriguez Rodriguez ◽  
Carlos Bustamante Orellana ◽  
Jayci Landfair ◽  
Corey Magaldino ◽  
Mustafa Demir ◽  
...  

As technological advancements and lowered costs make self-driving cars available to more people, it becomes important to understand the dynamics of human-automation interactions for safety and efficacy. We used a dynamical approach to examine data from a previous study on simulated driving with an automated driving assistant. To maximize effect size in this preliminary study, we focused the current analysis on the two lowest and two highest-performing participants. Our visual comparisons were the utilization of the automated system and the impact of perturbations. Low-performing participants toggled and maintained reliance either on automation or themselves for longer periods of time. Decision making of high-performing participants was using the automation briefly and consistently throughout the driving task. Participants who displayed an early understanding of automation capabilities opted for tactical use. Further exploration of individual differences and automation usage styles will help to understand the optimal human-automation-team dynamic and increase safety and efficacy.


2021 ◽  
Author(s):  
William N. Caballero ◽  
Roi Naveiro ◽  
David Ríos Insua

Whereas automated driving technology has made tremendous gains in the last decade, significant questions remain regarding its integration into society. Given its revolutionary nature, the use of automated driving systems (ADSs) is accompanied by myriad novel quandaries relating to both operational and ethical concerns that are relevant to numerous stakeholders (e.g., governments, manufacturers, and passengers). When considering any such problem, the ADS’s decision-making calculus is always a central component. This is true for concerns about public perception and trust to others regarding explainability and legal certainty. Therefore, in this manuscript, we set forth a general decision-analytic framework tailorable to multitudinous stakeholders. More specifically, we develop and validate a generic tree of ADS management objectives, explore potential attributes for their measurement, and provide multiattribute utility functions for implementation. Given the contention surrounding numerous ethical concerns in ADS operations, we explore how each of the aforementioned components can be tailored in accordance with the stakeholder’s desired ethical perspective. A simulation environment is developed upon which our framework is tested. Within this environment we illustrate how our approach can be leveraged by stakeholders to make strategic trade-offs regarding ADS behavior and to inform policymaking efforts. In so doing, our framework is demonstrated as a practical, tractable, and transparent means of modeling ADS decision making.


Author(s):  
Christian Lienke ◽  
Manuel Schmidt ◽  
Christian Wissing ◽  
Martin Keller ◽  
Carlo Manna ◽  
...  

Electronics ◽  
2018 ◽  
Vol 7 (10) ◽  
pp. 228 ◽  
Author(s):  
Felipe Jiménez ◽  
José Naranjo ◽  
Sofía Sánchez ◽  
Francisco Serradilla ◽  
Elisa Pérez ◽  
...  

Road vehicles include more and more assistance systems that perform tasks to facilitate driving and make it safer and more efficient. However, the automated vehicles currently on the market do not exceed SAE level 2 and only in some cases reach level 3. Nevertheless, the qualitative and technological leap needed to reach level 4 is significant and numerous uncertainties remain. In this sense, a greater knowledge of the environment is needed for better decision making and the role of the driver changes substantially. This paper proposes the combination of cooperative systems with automated driving to offer a wider range of information to the vehicle than on-board sensors currently provide. This includes the actual deployment of a cooperative corridor on a highway. It also takes into account that in some circumstances or scenarios, pre-set or detected by on-board sensors or previous communications, the vehicle must hand back control to the driver, who may have been performing other tasks completely unrelated to supervising the driving. It is thus necessary to assess the driver’s condition as regards retaking control and to provide assistance for a safe transition.


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