Quantum Fourier transform to estimate drive cycles

Drive cycles in vehicle systems are important determinants for energy consumption, emissions, and safety. Estimating the frequency of the drive cycle quickly is important for the of control applications related to fuel efficiency, emission reduction and improving safety. However, how to efficiently estimate drive cycle frequency remains challenging in existing studies. Quantum computing provides a solution to improve the computational efficiency. This work harnesses the power of quantum computing for transportation systems and vehicles.

We have found that a drive cycle frequency estimation algorithm based on the Quantum Fourier Transform can be calculated faster than using a classical Fourier Transform. The analysis of the drive cycle evaluated on a15 qubit IBM-q quantum computer using current  Quantum Computing Technology are noisy. Our researchers have developed methods to do useful computations with noisy qubits.

We are embarking on an exciting frontier of quantum computing that has significant implications on vehicle dynamics, transportation planning and traffic management. These could help with identifying issues quickly and rapidly determining optimal responses, which could in turn help reduce congestion, emissions and improve safety. To read more about this please go to our published https://www.nature.com/articles/s41598-021-04639-0

For more information

Professor Vinayak Dixit, IAG Chair of Risk in Smart Cities, Director, Research Centre for Integrated Transport Innovation (rCITI), Director TRACSlab@UNSW
Email   v.dixit@unsw.edu.au

Dr Sisi Jian, rCITI visiting Fellow, Lecturer Department of Civil and Environmental Engineering, The Hong Kong University of Science and Technology
Email:   s.jian@unsw.edu.au