Dynamic Lane Reversal Strategy in Intelligent Transportation Systems in Smart Cities.

Area of Science:

• Intelligent Transportation Systems (ITSs)
• Traffic Engineering
• Urban Planning

Background:

• Advanced traveler information systems are crucial components of ITSs.
• Existing route guidance strategies primarily focus on vehicle navigation, not infrastructure control.
• Tidal traffic patterns present significant challenges for urban road networks.

Purpose of the Study:

• To propose a novel dynamic lane reversal strategy (DLRS) for managing tidal traffic.
• To develop a congestion-aware approach for controlling reversible lanes.
• To enhance the adaptability of transportation infrastructure to fluctuating traffic demands.

Main Methods:

• A dynamic lane reversal strategy (DLRS) was developed, utilizing congestion cluster density.
• The strategy employs specific density thresholds (0.37 for reversal, 0.22 for return) to control lane direction.
• Simulations were conducted to evaluate the DLRS performance under tidal traffic conditions.

Main Results:

• The proposed DLRS demonstrates effective control over reversible lanes based on real-time traffic density.
• The strategy shows superior adaptability in managing the fluctuations characteristic of tidal traffic.
• Simulation results confirm the efficacy of the DLRS in mitigating congestion.

Conclusions:

• The DLRS offers a viable infrastructure-based solution for addressing tidal traffic congestion.
• Dynamic lane control based on congestion density improves traffic flow efficiency.
• This strategy represents an advancement in intelligent transportation systems for urban mobility.