An Advanced Microscopic Energy Consumption Model for Automated Vehicle:Development, Calibration, Verification

TL;DR

This paper introduces the AA-Micro model, a new energy consumption model for automated vehicles with ACC, calibrated with empirical data, showing high accuracy and reliability for ACC systems but less so for human-driven vehicles.

Contribution

The paper develops and validates a novel energy consumption model specifically for ACC-equipped automated vehicles, improving prediction accuracy over traditional models.

Findings

AA-Micro achieves 90% accuracy in predicting ACC energy consumption.

The model shows strong consistency and reliability for ACC vehicles.

Significant discrepancies exist when applying the model to human-driven vehicle data.

Abstract

The automated vehicle (AV) equipped with the Adaptive Cruise Control (ACC) system is expected to reduce the fuel consumption for the intelligent transportation system. This paper presents the Advanced ACC-Micro (AA-Micro) model, a new energy consumption model based on micro trajectory data, calibrated and verified by empirical data. Utilizing a commercial AV equipped with the ACC system as the test platform, experiments were conducted at the Columbus 151 Speedway, capturing data from multiple ACC and Human-Driven (HV) test runs. The calibrated AA-Micro model integrates features from traditional energy consumption models and demonstrates superior goodness of fit, achieving an impressive 90% accuracy in predicting ACC system energy consumption without overfitting. A comprehensive statistical evaluation of the AA-Micro model's applicability and adaptability in predicting energy consumption and vehicle trajectories indicated strong model consistency and reliability for ACC vehicles, evidenced by minimal variance in RMSE values and uniform RSS distributions. Conversely, significant discrepancies were observed when applying the model to HV data, underscoring the necessity for specialized models to accurately predict energy consumption for HV and ACC systems, potentially due to their distinct energy consumption characteristics.