Evaluating Signalization and Channelization Selections at Intersections Based on an Entropy Method

Area of Science:

• Transportation Engineering
• Traffic Management Systems
• Environmental Science

Background:

• Direct left turns (DLTs) at intersections contribute to traffic slowdowns, delays, stops, and accidents, particularly on roads without medians.
• Vehicle restriction policies in China, implemented in 56 cities, aim to alleviate traffic congestion and reduce emissions, causing citizen travel inconvenience.
• Optimizing intersection design is crucial for efficient traffic flow and environmental sustainability.

Purpose of the Study:

• To investigate and compare the effectiveness of signalization and channelization strategies for managing direct left turns at intersections.
• To introduce and apply an entropy evaluation method (EEM) for objectively weighting and selecting optimal traffic control solutions.
• To evaluate the impact of different intersection management strategies on traffic volume, CO emissions, and fuel consumption.

Main Methods:

• An entropy evaluation method (EEM) was employed to objectively calculate the weights of six evaluation indexes.
• Six key indexes were considered: number of vehicles, CO emissions, and fuel consumption, in addition to commonly used metrics.
• VISSIM traffic simulation software was utilized to assess the operational performance of intersections under present conditions, channelization, and signalization scenarios.

Main Results:

• The entropy evaluation method (EEM) successfully determined optimal traffic volume combinations for intersections under different management strategies.
• VISSIM simulations demonstrated the effectiveness of both channelization and signalization in mitigating the negative impacts of direct left turns.
• The application of EEM led to significant reductions, ranging from 20% to 70%, across the six evaluated indexes for optimal traffic volume combinations.

Conclusions:

• The entropy evaluation method (EEM) provides a robust and objective approach for selecting appropriate traffic control strategies at intersections.
• Implementing optimized signalization and channelization can substantially improve traffic efficiency and reduce environmental impact.
• The study highlights the potential for significant decreases in traffic congestion, CO emissions, and fuel consumption through informed intersection management.