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Graphics and Human Computer Interfaces Commons™
Open Access. Powered by Scholars. Published by Universities.®
- Keyword
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- Advanced driver assistance system (1)
- Automated (1)
- Connected (1)
- Data cleaning (1)
- Data models (1)
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- Data sharing (1)
- Driver behavior (1)
- Georgia Institute of Technology (1)
- Machine learning (1)
- Neural networks (1)
- P.D. Quick (1)
- Physiology (1)
- Psychology (1)
- Siggraph '95 (1)
- Simulator (1)
- The Vivid Group and Multigen Inc. (1)
- University of North Carolina Chapel Hill (1)
- Virtual I/O (1)
- Virtual Reality (1)
- Warning (1)
- Publication
- Publication Type
Articles 1 - 3 of 3
Full-Text Articles in Graphics and Human Computer Interfaces
Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla
Drivers’ Response To Scenarios When Driving Connected And Automated Vehicles Compared To Vehicles With And Without Driver Assist Technology, Srinivas S. Pulugurtha, Raghuveer Gouribhatla
Mineta Transportation Institute
Traffic related crashes cause more than 38,000 fatalities every year in the United States. They are the leading cause of death among drivers up to 54 years in age and incur $871 million in losses each year. Driver errors contribute to about 94% of these crashes. In response, automotive companies have been developing vehicles with advanced driver assistance systems (ADAS) that aid in various driving tasks. These features are aimed at enhancing safety by either warning drivers of a potential hazard or picking up certain driving maneuvers like maintaining the lane. These features are already part of vehicles with Driver …
Taming The Data In The Internet Of Vehicles, Shahab Tayeb
Taming The Data In The Internet Of Vehicles, Shahab Tayeb
Mineta Transportation Institute
As an emerging field, the Internet of Vehicles (IoV) has a myriad of security vulnerabilities that must be addressed to protect system integrity. To stay ahead of novel attacks, cybersecurity professionals are developing new software and systems using machine learning techniques. Neural network architectures improve such systems, including Intrusion Detection System (IDSs), by implementing anomaly detection, which differentiates benign data packets from malicious ones. For an IDS to best predict anomalies, the model is trained on data that is typically pre-processed through normalization and feature selection/reduction. These pre-processing techniques play an important role in training a neural network to optimize …
Vrware Beware: Vr At Siggraph, P.D. Quick
Vrware Beware: Vr At Siggraph, P.D. Quick
SWITCH
The article uses the author’s experiences from the event of Siggraph ‘95 to comment on upcoming products using virtual or augmented reality. The article includes further discussion on the products’ effects on the psychology and physiology of consumers. Some examples include the “i-Glasses” from Virtual I/O, the “Smart Model” from Multigen, as well as the nanomanipulator created by University of North Carolina Chapel Hill Department of Computer Science, and the Phobia Project developed by the Georgia Tech Graphics Visualization and Usability Center. The article also covers not only the products of this event, but also the courses, panels, papers, and …