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Navigating MARRVEL, a Web-Based Tool that Integrates Human Genomics and Model Organism Genetics Information

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Integrated optimization of spatiotemporal resources at the intersection for delay minimization using genetic

Zhen Yang¹, Lan Wu¹, Gen Li¹

¹College of Automobile and Traffic Engineering, Nanjing Forestry University, Nanjing, China.

|January 23, 2026

Summary

This summary is machine-generated.

This study introduces integrated optimization of spatiotemporal resources at the intersection (IOSTRI) for traffic signal control. The developed model and genetic algorithm efficiently minimize traffic delays, adapting to various flow patterns for real-time control.

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Area of Science:

Traffic Engineering
Operations Research
Computer Science

Background:

Integrated optimization of spatiotemporal resources at the intersection (IOSTRI) is vital for efficient traffic signal control.
Current methods often optimize lane allocation and signal control separately, limiting overall performance.

Purpose of the Study:

To develop a unified framework for optimizing both lane allocation and signal control plans simultaneously.
To minimize traffic delays through an integrated approach to spatiotemporal resource management at intersections.

Main Methods:

Formulation of the IOSTRI problem as a binary mixed-integer nonlinear program (BMINLP) model.
Development of a tailored genetic algorithm with specialized modules for lane and signal plan conversion, flow, and delay calculation.
Incorporation of shared lane utilization and lane adjustments within the optimization model.

Main Results:

The proposed BMINLP model and genetic algorithm effectively address the IOSTRI problem.
The approach demonstrates adaptability to diverse traffic flow distributions.
High-quality solutions for traffic delay minimization were achieved within 40-55 seconds.

Conclusions:

The integrated optimization framework significantly improves upon previous traffic signal control methods.
The developed model and algorithm satisfy the demands for real-time adaptive control of single intersections.