Affiliation:
1. School of Optoelectronic Science and Engineering & Collaborative Innovation Center of Suzhou Nano Science and Technology, Soochow University, Suzhou 215006, China
2. Key Lab of Advanced Optical Manufacturing Technologies of Jiangsu Province & Key Lab of Modern Optical Technologies of Education Ministry of China, Soochow University, Suzhou 215006, China
Abstract
As the next generation of in-vehicle intelligent platforms, the augmented reality heads-up display (AR-HUD) has a huge information interaction capacity, can provide drivers with auxiliary driving information, avoid the distractions caused by the lower head during the driving process, and greatly improve driving safety. However, AR-HUD systems still face great challenges in the realization of multi-plane full-color display, and they cannot truly achieve the integration of virtual information and real road conditions. To overcome these problems, many new devices and materials have been applied to AR-HUDs, and many novel systems have been developed. This study first reviews some key metrics of HUDs, investigates the structures of various picture generation units (PGUs), and finally focuses on the development status of AR-HUDs, analyzes the advantages and disadvantages of existing technologies, and points out the future research directions for AR-HUDs.
Funder
National Key Research and Development Program of China
Natural Science Foundation of China
Jiangsu Provincial Key Research and Development Program
Leading Technology of Jiangsu Basic Research Plan
Priority Academic Program Development (PAPD) of Jiangsu Higher Education Institutions
Reference110 articles.
1. (2020, January 01). Available online: https://www.who.int/data/gho/data/themes/mortality-and-global-health-estimates/global-health-estimates-leading-causes-of-dalys.
2. (2019, January 01). Available online: https://www.who.int/news-room/fact-sheets/detail/road-traffic-injuries.
3. Kuhnert, F., Sturmer, C., and Koster, A. (2018). Five Trends Transforming the Automotive Industry, Pricewaterhouse Coopers GmbH.
4. Multi-Sensor Fusion in Automated Driving: A Survey;Wang;IEEE Access,2020
5. Klauer, S.G., Dingus, T.A., and Le, T.V. (2006). The Impact of Driver Inattention on Near-Crash/Crash Risk: An Analysis Using the 100-Car Naturalistic Driving Study Data.