scholarly journals Traded Control Architecture for Automated Vehicles Enabled by the Scene Complexity Estimation

Author(s):  
Juan Medina-Lee ◽  
Jorge Villagra ◽  
Antonio Artuñedo
Author(s):  
Jorge Villagrá ◽  
Vicente Milanés ◽  
Joshué Pérez ◽  
Jorge Godoy ◽  
Enrique Onieva ◽  
...  

2018 ◽  
Author(s):  
Timo Liljamo ◽  
Heikki Liimatainen ◽  
Markus Pöllänen
Keyword(s):  

1995 ◽  
Vol 34 (05) ◽  
pp. 475-488
Author(s):  
B. Seroussi ◽  
J. F. Boisvieux ◽  
V. Morice

Abstract:The monitoring and treatment of patients in a care unit is a complex task in which even the most experienced clinicians can make errors. A hemato-oncology department in which patients undergo chemotherapy asked for a computerized system able to provide intelligent and continuous support in this task. One issue in building such a system is the definition of a control architecture able to manage, in real time, a treatment plan containing prescriptions and protocols in which temporal constraints are expressed in various ways, that is, which supervises the treatment, including controlling the timely execution of prescriptions and suggesting modifications to the plan according to the patient’s evolving condition. The system to solve these issues, called SEPIA, has to manage the dynamic, processes involved in patient care. Its role is to generate, in real time, commands for the patient’s care (execution of tests, administration of drugs) from a plan, and to monitor the patient’s state so that it may propose actions updating the plan. The necessity of an explicit time representation is shown. We propose using a linear time structure towards the past, with precise and absolute dates, open towards the future, and with imprecise and relative dates. Temporal relative scales are introduced to facilitate knowledge representation and access.


2017 ◽  
Vol 86 ◽  
pp. 361-411
Author(s):  
Jewoo Lee ◽  
Soon-Koo MYOUNG

1998 ◽  
Author(s):  
Mark A. Murphy ◽  
Robert L. Williams ◽  
III

Author(s):  
Bryant Walker Smith

This chapter highlights key ethical issues in the use of artificial intelligence in transport by using automated driving as an example. These issues include the tension between technological solutions and policy solutions; the consequences of safety expectations; the complex choice between human authority and computer authority; and power dynamics among individuals, governments, and companies. In 2017 and 2018, the U.S. Congress considered automated driving legislation that was generally supported by many of the larger automated-driving developers. However, this automated-driving legislation failed to pass because of a lack of trust in technologies and institutions. Trustworthiness is much more of an ethical question. Automated vehicles will not be driven by individuals or even by computers; they will be driven by companies acting through their human and machine agents. An essential issue for this field—and for artificial intelligence generally—is how the companies that develop and deploy these technologies should earn people’s trust.


1999 ◽  
Vol 7 (4) ◽  
pp. 391-404 ◽  
Author(s):  
TONG FANG ◽  
MOHSEN A. JAFARI ◽  
AHMAD SAFARI ◽  
STEPHEN C. DANFORTH

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