Paper Info
Title
Guest Editorial Multifaceted Driver-Vehicle Systems: Toward More Effective Driving Simulations, Reliable Driver Modeling, And Increased Trust And Safety
Abstract
The papers in this special section focus on multifaceted driver-vehicle systems. The current panorama of driver–vehicle systems is rapidly evolving, as the path toward autonomous vehicles is being paved. Many design decisions are yet to be made, and evolving legislative policies will play a significant role in the scientific research, which needs to be addressed. For example, there are countries that are considering a “step change” from fully human- driven to fully automated vehicles, while others are designing a period of coexistence of the two driving modes. Clearly, either of these approaches will require deep study of the interactions that will develop between drivers and vehicles. Related to this, for the first time in history, automated systems will primarily control vehicles and drivers may become passive “spectators” to vehicle control. However, it is also reasonable to expect that humans will be asked to intervene in dubious and/or dangerous situations that are not manageable by automation alone. Such interventions may also be used as bases for “robotic drivers” to learn human-based reasoning and ethics in vehicle control. Some researchers have already started to ask for how long will “former” drivers be able to offer prompt and wise reactions to off-nominal events, as their capabilities will decline with automation dependence and loss of practice. It is easy to foresee that the next decade will be crucial for scientific research in this field. Scientists will be asked to provide prompt and reliable responses to whatever final human–automation interaction scenario will develop for driving activities. To address this need, human–machine systems competencies will be of the utmost importance. In the context outlined above, and in preparation for autonomous vehicles driving around the world, some of the issues that need to be tackled include design of more accurate and reliable driving simulation models for coexistence tests, in which autonomous vehicles are simulated together with humandriven ones. Such technology is needed to reproduce interaction schemes that will develop on roadways and replicate the specific cues to which drivers may be exposed for the assessment of consequent behaviors. These tools are expected to provide more efficient methods for estimating different aspects of driver behaviors.
Year
DOI
Venue
2018
10.1109/THMS.2017.2784018
IEEE TRANSACTIONS ON HUMAN-MACHINE SYSTEMS
Field
DocType
Volume
Legislature,Competence (human resources),Computer science,Human factors and ergonomics,Automation,Risk analysis (engineering),Artificial intelligence,Driving simulation,Vehicle control,Vehicle safety,Machine learning,Scientific method
Journal
48
Issue
ISSN
Citations 
1
2168-2291
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Mara Tanelli128738.24
Rafael Toledo-Moreo232731.58
Laura M. Stanley302.70