Dead Reckoning in Emergency Vehicle Preemption System Using Deep Output Kernel Learning and Extended Kalman Filter-Reference-Cited by-同舟云学术

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Dead Reckoning in Emergency Vehicle Preemption System Using Deep Output Kernel Learning and Extended Kalman Filter

Published:2024-02-15 Issue: Volume: Page:1-18
ISSN:0377-2063
Container-title:IETE Journal of Research
language:en
Short-container-title:IETE Journal of Research

Author:

Rosayyan Prakash¹^ORCID,Paul Jasmine²,Subramaniam Senthilkumar³,Ganesan SaravanaIlango³

Affiliation:

1. Intelligent Transportation and Networking Section of C-DAC Thiruvananthapuram, Thiruvananthapuram, India

2. Department of Computer Science and Engineering, St. Thomas Institute for Science and Technology, Thiruvananthapuram, India

3. Department of Electrical and Electronics Engineering, National Institute of Technology, Tiruchirappalli, India

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/03772063.2024.2315207

Reference43 articles.

1. J. F. Paniati and M. Amoni. “Traffic signal preemption for emergency vehicles ” in RITA. US Development of Transportation Research and Innovative Technology Administration Jan. 2006.

2. A Strategy for Emergency Vehicle Preemption and Route Selection

3. An efficient dynamic traffic light scheduling algorithm considering emergency vehicles for intelligent transportation systems;Younes M. B.;Wirel. Netw.,2018

4. Multi-agent preemptive longest queue first system to manage the crossing of emergency vehicles at interrupted intersections;Louati A.;Eur. Transp. Res. Rev.,2018

5. Density based traffic control for smart ambulance system;Umakant V.;Int. Res. J. Eng. Technol.,2018

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