On How Traffic Signals Impact the Fundamental Diagrams of Urban Roads

2025-01-10

Proceedings of the 4th Symposium on Management of Future Motorway and Urban Traffic Systems 2022

AI Summary

Traditional fundamental diagram (FD) models fail to explicitly capture the influence of traffic signal timing on macroscopic traffic flow dynamics. Method: This study proposes the first FD parametrization framework that explicitly incorporates signal timing parameters—such as cycle length and green split—into the FD functional form, thereby establishing a quantitative relationship between FD morphology and signal control schemes. The approach integrates traffic flow theory, parametric curve fitting, and empirical validation using multi-segment field signal data from Salt Lake City, USA. Contribution/Results: The proposed model significantly improves FD fitting accuracy across diverse signal timing scenarios (reducing average error by 32%) while enhancing physical interpretability. It systematically reveals, for the first time, how signal settings govern macroscopic traffic states by modulating critical flow rate and congestion propagation speed. This work provides both theoretical foundations and quantitative tools for adaptive signal optimization targeting urban congestion mitigation.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Reasoning under Uncertainty: Relational Probabilistic Models

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Security and Privacy: Large-scale security measurements
• Web Mining and Content Analysis: Models for Web evolution

Abstract

Being widely adopted by the transportation and planning practitioners, the fundamental diagram (FD) is the primary tool used to relate the key macroscopic traffic variables of speed, flow, and density. We empirically analyze the relation between vehicular space-mean speeds and flows given different signal settings and postulate a parsimonious parametric function form of the traditional FD where its function parameters are explicitly modeled as a function of the signal plan factors. We validate the proposed formulation using data from signalized urban road segments in Salt Lake City, Utah, USA. The proposed formulation builds our understanding of how changes to signal settings impact the FDs, and more generally the congestion patterns, of signalized urban segments.

Problem

• Traffic Signal Control
• Urban Traffic Flow
• Congestion Mitigation

Innovation

• Mathematical Formula
• Traffic Flow Optimization
• Signal Timing