Justice, Chandler (Utah State University), Ramsdell, Max (Utah State University), Smith, Stockton (Utah State University), Stott, Nate (Utah State University), Harper, Mario (Utah State University)

Electric Vehicle Charger Reservation Service

Scheduled for presentation during the Regular Session "S05b-Deployment, Modeling, and Optimization in Intelligent Transportation Systems" (WE-EA-T5), Wednesday, November 19, 2025, 14:50−14:50, Surfers Paradise 2

2025 IEEE 28th International Conference on Intelligent Transportation Systems (ITSC), November 18-21, 2025, Gold Coast, Australia

This information is tentative and subject to change. Compiled on October 19, 2025

Abstract

The Electric Vehicle Charger Reservation (EVCR) system provides an intelligent platform for managing electric vehicle (EV) charging through time-aware reservations, price forecasting, and dynamic curtailment. In this work, we analyze real-world usage data following the system’s initial rollout, revealing how user behavior aligns with grid-aware pricing and temporal nudges. Statistical analysis confirms that users, particularly those using DC fast charging (DCFC), respond significantly to time-of-day pricing, concentrating sessions during lower-cost periods while maintaining consistent energy usage per session. The system leverages Open Charge Point Protocol (OCPP) and OpenADR to provide granular control over charger behavior and site-level coordination. At the same time, a random forest regression model predicts 48-hour pricing to optimize user guidance. Since deployment, the platform has maintained a stable base of returning and new users, indicating early success in encouraging economically efficient and grid-conscious charging. These results highlight EVCR’s potential as a scalable solution for load shaping and user engagement in future electrified transportation networks.