Behavioral/Agent-Based Supply Chain Modeling Research Synthesis and Guide

Chapter 1. INTRODUCTION

PROJECT PURPOSE AND NEED

A handful of public agencies in the United States are in the process of developing—or have already developed—behavioral/agent-based models of supply chain decisions and freight movements. The increase in development of these new models is largely attributable to funding from the Federal Highway Administration (FHWA) Broad Agency Announcement awards and the Strategic Highway Research Program (SHRP2) C20 program, which aims to foster fresh ideas and new approaches to designing and implementing freight demand modeling. The main purpose of this synthesis is to evaluate recent advancements in these behavioral/agent-based models and support the broader application of these methods to forecast future freight flows. This synthesis document is intended for managers of travel demand modeling systems and other technically oriented staff of federal, State, and regional transportation planning agencies who have an interest in behavioral/agent-based modeling of freight flows. Public agencies interested in developing behavioral/agent-based freight models can use this synthesis to assess the feasibility and practicality of developing similar models for their own regions based on the experiences of other agencies.

APPROACH

As part of this synthesis, agent-based supply chain freight models currently in use by the Chicago Metropolitan Agency for Planning (CMAP), Florida Department of Transportation (FDOT), Wisconsin Department of Transportation (WisDOT), Phoenix’s Maricopa Association of Governments (MAG), Oregon Department of Transportation (ODOT), Baltimore Metropolitan Council (BMC), and Metro (Portland, Oregon) were reviewed. Each of the models reviewed are summarized along the following 12 dimensions related to methodology and data.

Methodology

• Determine supply chain modeling needs.
• Determine model structure, component interactions, and segmentation.
• Develop market segmentation (industry, commodity, mode, vehicle type, temporal, activity type).
• Determine modeled performance measures.
• Develop approach to forecasting.
• Understand types of applications and procedures.

Data

• Determine geographic scope.
• Develop data inputs.
• Determine data used for estimating model parameters, model calibration, and model validation.
• Determine data desired, but not found.

Many of the freight models reviewed as part of this synthesis were found to rely on data from publicly available sources such as the Freight Analysis Framework (FAF).¹ The second chapter on common datasets includes descriptions of common data sources used by some of these freight models reviewed as part of this synthesis.

CONTENTS OF THIS REPORT

In addition to the introduction, this synthesis and guide includes four additional chapters:

1. Chapter 1 provides an introduction and overview of this synthesis and guide.
2. Chapter 2 describes modeling needs, concepts, terminology, and common modeling approaches used in behavioral supply chain models.
3. Chapter 3 describes the data required to support a behavioral supply chain model. This chapter also describes the common datasets used in behavioral/agent-based supply chain models.
4. Chapter 4 includes a comprehensive model review that was developed after reviewing model documentation and contacting State departments of transportation (DOTs) and metropolitan planning organizations (MPOs) that have implemented, or are in the process of implementing, behavioral/agent-based supply chain models.
5. Chapter 5 describes how State DOTs and MPOs can assess and prepare for supply chain model readiness.
6. Chapter 6 describes freight performance measures used by public and private sector.
7. Chapter 7 describes public and private sector data sharing and issues. This chapter also discusses the success that some public agencies have had in finding collaboration opportunities to obtain or use freight model data.

Chapters 2 and 3 include discussion of common data sources that support the development of a behavioral supply chain model along with common modeling approaches.

Chapter 4, the comprehensive model review, uses information collected from seven public agencies. The project team used this information to develop this synthesis of best practices and lessons learned, as communicated by each agency. This chapter is based on the findings of the state-of-the-art model review. The models are presented in the order of the development date with the earliest developed model, described first.

Chapter 5 helps agencies assess whether a behavioral or agent-based supply chain modeling approach is right for their needs and discusses considerations when planning for model development. Chapter 6 discusses public and private sector’s freight performance measures. In addition, Chapter 7 describes data sharing issues and arrangements between public and private sectors.