Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment

Area of Science:

• Transportation Engineering
• Environmental Science
• Computer Science

Background:

• Connected vehicles offer potential for traffic management improvements.
• Existing methods lack focus on fuel consumption and emissions across signalized intersections.
• Optimization of traffic signals and vehicle speeds is crucial for sustainable transportation.

Purpose of the Study:

• To develop a novel technique for optimizing traffic signals and vehicle speeds.
• To address fuel consumption and pollutant emissions in connected vehicle networks.
• To enhance overall transportation network efficiency and environmental performance.

Main Methods:

• Development of an integrated optimization technique for traffic signals and vehicle speeds.
• Simulation-based analysis of the proposed method's effectiveness.
• Evaluation of impacts on vehicle delay, stops, fuel consumption, and CO2 emissions.

Main Results:

• The proposed method significantly alleviates vehicle delay and reduces the number of stops.
• Demonstrated substantial reductions in fuel consumption and CO2 emissions.
• Effectiveness is particularly pronounced under moderate traffic density conditions.

Conclusions:

• The novel technique effectively optimizes traffic signals and vehicle speeds for connected vehicles.
• Significant environmental benefits, including reduced fuel use and emissions, are achievable.
• The method shows versatility and positive impact across various traffic conditions, especially moderate density.