Next-Generation Neural Processing for Autonomous Vehicles

Authors

  • Drew Hernandez
  • Pat Lewis
  • Casey King

Keywords:

autonomous vehicles, neural processing, real-time data, vehicle safety, navigation

Abstract

This study delves into the development of next-generation neural processing units (NPUs) designed to enhance the capabilities of autonomous vehicles. By focusing on real-time data processing and decision-making, the research evaluates the impact of NPUs on vehicle safety, navigation accuracy, and energy efficiency. Through simulation and field testing, the article demonstrates how NPUs enable autonomous systems to operate effectively in complex environments. The findings offer insights into the technological advancements necessary for the widespread adoption of autonomous driving solutions, contributing to the ongoing evolution of intelligent transportation systems.

Author Biographies

Drew Hernandez

PhD in Electrical Engineering
Stanford University
450 Serra Mall, Stanford, CA 94305, USA

Pat Lewis

PhD in Automotive Engineering
RWTH Aachen University
Templergraben 55, 52062 Aachen, Germany

Casey King

PhD in Computer Science
National Aviation University
Liubomyra Huzara Ave, 1, Kyiv, 03058, Ukraine

References

Darvishy, A., & Hutter, H. P. (2013). Comparison of the effectiveness of different accessibility plugins based on important accessibility criteria. In Universal Access in Human-Computer Interaction. Applications and Services for Quality of Life: 7th International Conference, UAHCI 2013, Held as Part of HCI International 2013, Las Vegas, NV, USA, July 21-26, 2013, Proceedings, Part III 7 (pp. 305-310). Springer Berlin Heidelberg.

Munteanu, E., Guggiana, V., Darvishi, A., Schauer, H., Rauterberg, G. W. M., & Motavalli, M. (1995). Physical modelling of environmental sounds. In Proceedings of the 2nd international conference on acoustic and musical research, CIARM'95 (pp. 107-112). Universita di Ferrara.

Rauterberg, G. W. M., Motavalli, M., Darvishi, A., & Schauer, H. (1994). Automatic sound generation for spherical objects hitting straight beams based on physical models. In Educational multimedia and hypermedia, 1994: proceedings of ED-MEDIA 94, World Conference on Educational Multimedia and Hypermedia, Vancouver, BC, Canada, June 25-30, 1994 (pp. 468-473). Association for the Advancement of Computing in Education.

Satyanarayana, D., & Elmirghani, J. M. (2010, December). An energy efficient network architecture for infrastructured wireless networks. In 2010 IEEE Global Telecommunications Conference GLOBECOM 2010 (pp. 1-6). IEEE.

Satyanarayana, D., & Elmirghani, J. M. (2009, September). A voronoi based energy efficient architecture for wireless networks. In 2009 Third International Conference on Next Generation Mobile Applications, Services and Technologies (pp. 377-382). IEEE.

Satyanarayana, D., & Alasmi, A. S. (2022, October). Detection and mitigation of DDOS based attacks using machine learning algorithm. In 2022 International Conference on Cyber Resilience (ICCR) (pp. 1-5). IEEE.

Satyanarayana, D., Chattopadhyay, S., & Sasidhar, J. (2004, January). Low power combinational circuit synthesis targeting multiplexer based FPGAs. In 17th International Conference on VLSI Design. Proceedings. (pp. 79-84). IEEE.

Rahimov, E. R. (2010). BASE PRINCIPAL OF MANAGING OF NETWORK SOFTWARE SECURITY BY VULNERABILITIES DETERMINATION MODEL. Computer Sciences and Telecommunications, (5), 70-74.

Published

2023-09-04

Issue

Section

Articles