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Traffic light optimization using non-dominated sorting genetic algorithm (NSGA2).

Samara Soares Leal1, Paulo Eduardo M de Almeida2

  • 1University Center of Belo Horizonte - UniBH, Av. Professor Mário Werneck, 1685, Buritis, Belo Horizonte, MG, 30575-180, Brazil. samara.leal@unibh.br.

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This study introduces a new real-time traffic signal control method, Active Control of Traffic Signals (ACTS), which significantly reduces vehicle delays and traffic congestion in urban areas.

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Area of Science:

  • Urban planning and intelligent transportation systems
  • Computational intelligence applications in traffic management
  • Optimization algorithms for real-world problems

Background:

  • Traffic congestion negatively impacts urban society, environment, and economy.
  • Existing computational intelligence (CI) strategies for traffic control often lack real-time adaptation and multi-objective optimization.
  • Many CI models rely heavily on simulation, hindering practical deployment.

Purpose of the Study:

  • To present a novel real-time traffic signal optimization method for interconnected intersections.
  • To address limitations in current traffic control strategies by incorporating dynamic vehicle demand and multiple objectives.
  • To evaluate the proposed method's effectiveness using real-world traffic data.

Main Methods:

  • Development of the Active Control of Traffic Signals (ACTS) method.
  • Integration of ACTS with the Non-Dominated Sorting Genetic Algorithm for multi-objective optimization (minimizing average delay and vehicle stops).
  • Validation using a real vehicle demand dataset from Belo Horizonte (BHTrans) within the AIMSUN traffic simulator.

Main Results:

  • The ACTS method demonstrated a significant reduction in average vehicle delay, nearly halving it compared to the existing BHTrans traffic control plan.
  • The optimization process effectively balanced multiple objectives, including minimizing delays and vehicle stops.
  • Simulation results indicate substantial improvements in traffic flow and congestion reduction.

Conclusions:

  • The ACTS method offers a practical and effective solution for real-time traffic signal optimization in urban networks.
  • This approach has the potential to significantly alleviate traffic congestion, leading to faster travel times and improved urban mobility.
  • The study highlights the importance of real-time, multi-objective optimization for intelligent traffic management systems.