This paper describes the findings of an independent peer review of the modeling tools used by the Volpe National Transportation Systems Center to forecast national vehicle miles traveled (VMT) over the next 30 years. Overall, the VMT forecasting models, which use autoregressive distributed lag models for light-duty vehicle, single-unit truck, and combination truck VMT, work well to estimate travel demand. All model estimations were reviewed, and all models perform well against several validation and testing techniques. The study team was supported by an expert panel selected from academia, government, and industry with experience in econometric methods, transportation and economic data, and modeling methods. The panel reviewed model documentation as well as the report assessing the VMT forecasting models and provided insight into alternative model research. The paper is an effort to synthesize the approaches and the validation methods used. A complementary literature search was also conducted to test the validity and comparability of several estimated variable coefficients. The paper concludes by summarizing the key findings and making recommendations on future model improvements.

本文描述了对 Volpe 国家交通系统中心用于预测未来 30 年全国车辆行驶里程 (VMT) 的建模工具的独立同行评审的结果。总体而言，使用自回归分布式滞后模型的 VMT 预测模型适用于轻型车辆、单体卡车和组合卡车 VMT，可以很好地估计出行需求。审查了所有模型估计，并且所有模型在多种验证和测试技术下都表现良好。该研究团队得到了一个从学术界、政府和行业中选出的专家小组的支持，该小组在计量经济学方法、运输和经济数据以及建模方法方面具有丰富的经验。该小组审查了模型文档以及评估 VMT 预测模型的报告，并提供了对替代模型研究的见解。该论文旨在综合所使用的方法和验证方法。还进行了补充文献检索，以测试几个估计变量系数的有效性和可比性。本文最后总结了主要发现并对未来的模型改进提出了建议。