Traffic Optimization for Unmanned Vehicles Using Quantum Computing

Seminar

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Date

10 Nov 2023
Organiser

Department of Aeronautical and Aviation Engineering
Time

10:00 - 11:00
Venue

TU103 Map

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Summary

Abstract

Quantum computing is potentially capable of providing exponential acceleration in solving optimization problems. Traffic control for unmanned vehicles can be seen as an optimization problem, which aims to plan the optimal route for each individual vehicle under its own conditions such as speed and endurance, meanwhile letting the whole system to achieve the goal with e.g. minimal total energy consumption. In this seminar we will walk through the basic principles of quantum computation, explore the advantages and obstacles in solving traffic optimization problems using a quantum computer. Implementations, simulator and resources for available quantum computers are also introduced.

Speaker

Dr Kai Yan received his BEng, MSc and PhD degrees in Information Science & Technology from The University of Tokyo, Japan, in 2008, 2010, and 2013 respectively. Dr Yan joined the National Institute of Informatics (Tokyo, Japan) in 2008 where he co-invented and engaged in theoretical research of the coherent Ising machine, one of quantum computing systems that natively implements NP-complete problems. In 2013, he worked in Ginzton lab., Stanford University (CA, US) as a visiting scholar where he participated in the physical implementation of the coherent Ising machine with a laser network. He is the founder and CEO of LabRomance Inc. and director of Drone Autopilot Lab Co., Ltd. (Tokyo Japan). His life-time research work is to develop efficient algorithms for solving NP-complete problems on both quantum and classical systems, meanwhile he is leading the development of OpenKAI, an open source control framework for unmanned vehicles that has been incorporated in more than 100 industry customers worldwide.