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Augmented Reality Projection for Driver Assistance in Autonomous Vehicles
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 14, 2020 by SAE International in United States
This content contains downloadable datasetsAnnotation ability available
Augmented Reality (AR), which involves the integration of digital information with our physical environment in real-time, has been steadily growing over the past few years, finding its way into multiple areas of our lives. Augmented Reality (AR) in automotive vehicles has contributed to revolutionizing the way passengers and drivers access information, acquire knowledge and integrate into the physical spaces and destinations visited. The studies produced concerning this field are still limited, particularly in the perception of how users adopt technology and what use they make of it. On the other hand, even more limited are the studies that consider the role of stakeholders in the implementation of AR technology. In this paper, we discuss and propose solutions for following ADAS applications using projection unit mounted on board projecting on the windshield.
- 5G in your route (signal strength - android applications on HU to detect the signal strength and display it on projection unit)). 5G connectivity help to realize the future of connected cars through higher speeds (up to 10 Gbps), better coverage (capacity expansion by a factor of 1,000) and improved reliability (by leveraging ultra-wide bandwidth and throughput).Connectivity and QoS is always a concern for a moving vehicle
- Fuel/charging stations in your route
- Hazardous road conditions
- Emergency service in your route. Emergency situations can arise in any conditions and lead to various consequences. In this regard, the problem of creating emergency systems is very wide and covers completely different aspects and areas.
- Smart destinations
CitationChandupatla, S., Yerram, N., and Achuthan, B., "Augmented Reality Projection for Driver Assistance in Autonomous Vehicles," SAE Technical Paper 2020-01-1035, 2020, https://doi.org/10.4271/2020-01-1035.
Data Sets - Support Documents
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