Traffic signal optimization on a square lattice with quantum annealing

Area of Science:

• Computational Science
• Traffic Engineering
• Quantum Computing

Background:

• Intelligent transportation systems (ITS) in urban areas face computational challenges managing large-scale traffic.
• Existing traffic management architectures struggle with heavy computational loads.

Purpose of the Study:

• To develop a novel global traffic signal control method using quantum annealing.
• To optimize traffic flow and minimize imbalance in urban networks.

Main Methods:

• Formulated traffic signal optimization as a problem minimizing traffic flow imbalance.
• Reformulated the problem as an Ising Hamiltonian for quantum annealers (D-Wave).
• Compared quantum annealing with conventional local control and simulated annealing.

Main Results:

• The global quantum control method significantly suppressed traffic imbalance in a 50x50 city simulation.
• Quantum annealing solutions were superior to simulated annealing.
• Analytical proof and numerical experiments confirmed method convergence.

Conclusions:

• Quantum annealing offers a superior approach for global traffic signal control in intelligent transportation systems.
• This method effectively manages large-scale traffic and reduces computational load.
• The findings pave the way for more efficient urban traffic management solutions.