Urban traffic Eco-Driving: A macroscopic steady-state analysis

De Nunzio, Giovanni; de Wit, Carlos Canudas; Moulin, Philippe · 2014 · OpenAlex-citations

DOI: 10.1109/ecc.2014.6862403

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Summary

This paper addresses the problem of optimizing energy efficiency in urban traffic networks through "Eco-Driving" strategies, specifically focusing on macroscopic steady-state analysis. The research is motivated by the need to reduce pollution and congestion in urban environments, where traffic signals create complex flow dynamics. The authors aim to identify optimal traffic operation points that balance global energy consumption with travel time and infrastructure utilization, using variable speed limits as the primary control mechanism. The study employs a modified Variable Length Model (VLM), a macroscopic traffic model adapted from highway applications to urban settings. Unlike traditional Cell Transmission Models that require fine discretization, the VLM represents a road section with only two cells: an upstream free-flow cell and a downstream congested cell, separated by a moving congestion front. To handle the periodic nature of traffic lights, the authors apply averaging theory to the model, transforming the binary switching behavior of signals into continuous average boundary flows. This simplification allows for steady-state analysis without simulating oscillatory congestion dynamics. The paper defines specific performance metrics adapted to this model: Instantaneous Travel Time (ITT), Total Travel Time (TTT), Total Travel Distance (TTD), and a macroscopic energy consumption functional. The energy model assumes electric vehicles and accounts for energy used during constant-speed travel in free and congested cells, as well as energy consumed during acceleration/deceleration at cell interfaces. The results present a steady-state analysis of the system’s equilibrium points reachable via variable speed limits. The authors demonstrate that by adjusting the maximum allowed speed in the free cell, the system can reach various equilibrium states characterized by different densities and congestion lengths. The study identifies efficient operation points as a trade-off between minimizing energy consumption and travel time while maximizing infrastructure utilization (TTD). The analysis reveals that reducing speed limits does not always reduce total travel time if inflow remains constant, as it may merely redistribute vehicles within the section. However, specific speed limits can significantly lower energy consumption by smoothing velocity transitions and optimizing the balance between free-flow and congested states. The significance of this work lies in providing a simplified yet accurate macroscopic framework for analyzing and controlling urban traffic energy efficiency. By reducing the complexity of traffic modeling to a two-cell averaged system, the approach facilitates the design of control policies that can be implemented via intelligent transportation systems, such as variable speed limit signs. The findings suggest that coordinated speed management can effectively minimize collective energy consumption while maintaining acceptable traffic flow metrics, offering a practical tool for urban traffic control strategies aimed at sustainability.

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• eco driving