Modeling Energy Consumption Impact of Autonomous Vehicles at Pedestrian Crossings Considering Pedestrian-Aware Speed Adaptation

Szigeti, Szilárd and Pauer, Gábor and Földes, Dávid (2026) Modeling Energy Consumption Impact of Autonomous Vehicles at Pedestrian Crossings Considering Pedestrian-Aware Speed Adaptation. IEEE ACCESS, 14. pp. 77439-77453. ISSN 2169-3536

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Abstract

Pedestrian crossings are critical locations in urban traffic networks where frequent deceleration and acceleration strongly influence vehicle energy consumption. The increasing presence of autonomous vehicles creates new opportunities to optimize vehicle approach behavior in such environments; however, the combined effects of automation level and vehicle propulsion technology remain insufficiently explored. This study presents a microsimulation-based framework developed in Vissim traffic simulation software to evaluate energy consumption at unsignalized pedestrian crossings under mixed traffic conditions, considering both internal combustion engine and electric vehicles. The framework integrates pedestrian movement, vehicle dynamics, and a pedestrian-aware speed-adaptation logic implemented via an external scripting interface. Human-driven vehicles are represented using multiple driving behavior profiles, while autonomous vehicles dynamically adjust their speed based on pedestrian position and detection range. Energy consumption is calculated using physics-based formulations, enabling a consistent comparison across propulsion types. A comprehensive set of scenarios was analyzed by varying autonomous vehicle penetration rates and pedestrian detection capabilities. Results indicate that increasing automation reduces energy consumption by approximately 3–7% at low to medium penetration levels and by about 12% under fully autonomous traffic conditions. These improvements are primarily driven by smoother speed adaptation and reduced abrupt deceleration, while statistical analysis confirms that autonomous vehicle penetration is the dominant influencing factor. Similar relative reductions are observed for both propulsion types, with differences remaining within approximately one percentage point across the analyzed scenarios. Overall, the findings demonstrate that pedestrian-aware autonomous driving can significantly improve energy efficiency at pedestrian crossings.

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