A Novel Control-Oriented Cell Transmission Model Including Service Stations on Highways

Cenedese, Carlo; Cucuzzella, Michele; Ferrara, Antonella; Lygeros, John · 2022 · OpenAlex-citations

DOI: 10.1109/cdc51059.2022.9993229

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Summary

This paper introduces the Cell Transmission Model with service station (CTM-s), a novel macroscopic traffic model designed to describe how highway traffic evolution is affected by the presence of service stations. The research is motivated by the need for efficient, low-cost traffic demand management strategies to address rising congestion costs and environmental impacts, such as increased CO2 emissions. While classical solutions involve infrastructure expansion, the authors propose using mathematical models to design control strategies that leverage existing infrastructure, such as service stations, to alleviate congestion. The CTM-s enhances the classical Cell Transmission Model (CTM) by explicitly modeling the dynamics of vehicles stopping at service stations for refueling, charging, or ancillary services before merging back into the main traffic stream. The methodology involves modeling a highway stretch as a chain of consecutive cells, incorporating on-ramps, off-ramps, and multi-purpose service stations located between specific entry and exit cells. The model tracks traffic density, flow rates, and split ratios for vehicles entering and exiting the main stream. Crucially, it accounts for the time vehicles spend at service stations and the potential for queuing if the merging flow exceeds the receiving cell’s supply capacity. The dynamics are governed by equations that calculate demand and supply for both the main stream and service station exits, handling both free-flow and congested scenarios through priority-based allocation rules. The model supports complex configurations, including multiple stations with different average stopping times and shared entry/exit points. The study validates the CTM-s through numerical simulations, assessing the impact of service stations on traffic evolution. The results demonstrate that the presence of service stations can have a beneficial effect on highway traffic congestion, particularly during relatively short congested periods. By allowing vehicles to temporarily exit the main stream, service stations act as buffers that reduce immediate pressure on the highway, effectively smoothing traffic flow. The simulations confirm that the model accurately captures these dynamics and can be used to evaluate interventions such as monetary incentives or physical constraints that influence driver behavior. The significance of this work lies in providing a flexible, control-oriented tool for active traffic demand management. The CTM-s enables policymakers and researchers to simulate and optimize strategies that utilize service stations to mitigate congestion without requiring new infrastructure. This approach aligns with broader trends in smart mobility, such as "valley filling" in smart grids, by incentivizing positive driver behaviors. The model’s ability to handle multiple service types and complex highway configurations makes it a valuable asset for designing efficient, sustainable traffic management systems.

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• traffic density