Optimization of signalized network configurations using the Lane-based method.

Area of Science:

• Traffic Engineering
• Transportation Science
• Operations Research

Background:

• Lane markings guide vehicle movements at signalized intersections, influencing traffic flow and connectivity.
• Current traffic signal coordination often relies on fixed lane markings, limiting network optimization potential.

Purpose of the Study:

• To develop an optimization framework for lane markings and traffic signal settings to maximize green bandwidths.
• To enhance traffic signal coordination and improve overall network performance in urban traffic systems.

Main Methods:

• Relaxing fixed lane markings into binary variables for optimization.
• Formulating the problem as a binary-mixed-integer-linear-program solved with branch-and-bound techniques.
• Linearizing non-linear delay functions and using bandwidth maximization instead of total delay minimization.

Main Results:

• Optimized lane markings and signal coordination significantly improve network link configurations.
• The proposed methodology demonstrates enhanced overall network performance compared to previous studies.
• Numerical results from a four-intersection network validate the effectiveness of the approach.

Conclusions:

• Dynamic optimization of lane markings, integrated with traffic signal coordination, offers substantial improvements in traffic flow.
• The developed binary-mixed-integer-linear-program provides an effective tool for designing efficient signalized road networks.
• This research contributes to advancing intelligent transportation systems through optimized traffic management strategies.