Office of Operations
21st Century Operations Using 21st Century Technologies

Traffic Analysis Toolbox Volume VI:
Definition, Interpretation, and Calculation of
Traffic Analysis Tools Measures of Effectiveness

1.0 Introduction

Traffic analysis tools play a critical role in prioritizing public investment in strategies employed by transportation professionals to relieve congestion. Traffic analysis tools help practitioners to:

  • Measure the operational performance of transportation facilities;
  • Evaluate various ITS strategies and innovative transportation management concepts;
  • Evaluate alternate designs and operational improvements;
  • Decrease the time and cost for evaluation and design of transportation facilities and systems; and
  • Reduce the risk and disruption to traffic caused by field experimentation.

1.1 Problem Statement

Use of the Highway Capacity Manual (HCM) and traffic simulation tools has become the standard approach for evaluating transportation design alternatives, operational performance, Intelligent Transportation Systems (ITS), and traffic operations strategies. However, the HCM procedures and traffic simulation tools seldom result in identical performance measurements. Moreover, there are no guidelines on interpreting these performance measurements. This leaves decision-makers and transportation professionals with the dilemma of identifying the true performance of the design alternatives and strategies.

1.2 Project Objectives

The goal of this study was to develop information and guidance on which MOEs should be produced, how they should be interpreted, and how they should be defined and calculated in traffic analysis tools. Specific objectives of the study were to:

  1. Gain an understanding of the current use and interpretation, by transportation professionals, of some of the most commonly used MOEs generated by traffic simulation and analytical tools, such as HCM procedures;
  2. Identify how field measurements are processed to estimate the MOEs used in conducting traffic analysis studies;
  3. Provide guidance on how these MOEs are defined and calculated in the tools;
  4. Develop an innovative approach to interpret these MOEs when conducting traffic analysis studies; and
  5. Demonstrate the validity of the approach through a case study of representative tools.

1.3 Report Overview

This report presents innovative approaches for interpreting and presenting traffic simulation and analytical tool MOEs. This report considers alternative MOEs in addition to the Level of Service performance measure prescribed by the HCM. It recommends MOEs that decision-makers could use to interpret results from traffic analysis studies conducted by transportation professionals.

The Executive Summary provides more detail on the contents of this report.

1.4 Report Review Process

A draft of this report was submitted to the FHWA Contracting Officer Technical representative (COTR) and to a panel of volunteer experts in the application of traffic microsimulation to performance measurement for comment.

The volunteer experts were:

Invitee

Affiliation

Type

Scott Aitken

Quadstone

Vendor

John Albeck

Trafficware

Vendor

Jaume Barcelo

Aimsun

Academic/Vendor

Loren Bloomberg

CH2M-HILL

Private

Ken G. Courage

University of Florida

Academic

Mohammed Hadi

Florida International University

Academic

Steve Hague

California Department of Transportation

Government

David Hale

McTrans

Academic/Vendor

Michael Hunter

Georgia Tech University

Academic

Liang Hsia

Florida Department of Transportation

Government

Hani Mahmassani

University of Maryland

Academic/Vendor

Cathy McGhee

Virginia DOT Transportation Research Council

Academic

Arash Mirzaei

North Central Texas Council of Governments

Government

Kiel Ova

PTV-America

Vendor

John Shaw

Wisconsin Department of Transportation

Government

In addition, the report was submitted to the following project team members for review:

Team Member
Organization

John Halkias

Federal Highway Administration

James Colyar

Federal Highway Administration

Grant Zammit

Federal Highway Administration

John Tolle

Federal Highway Administration

James McCarthy

Federal Highway Administration

Vassili Alexiadis

Cambridge Systematics

Vijay Kovvali

Cambridge Systematics

Alexander Skabardonis

University of California, Berkeley

The efforts, advice, and suggestions of the volunteer technical reviewers, the Federal Highway Administration Project Team, and the Consultant Project Team are greatly appreciated. However, it should be noted that the opinions presented in this report are those of the author and not necessarily those of its reviewers. Remaining errors are the responsibility of the author.

1.5 Project Objectives Accomplished

The goal of this study was to develop information and guidance on which MOEs should be produced, how they should be interpreted, and how they should be defined and calculated in traffic analysis tools. Table 5 explains how the specific objectives of this study have been accomplished.

Table 5. Accomplishment of Project Objectives

Objective

How Accomplished

  1. Gain an understanding of the current use and interpretation, by transportation professionals, of some of the most commonly used MOEs generated by traffic simulation and analytical tools, such as HCM procedures.

Chapter 2 provides an overview of current practice. It describes MOEs used in practice and in research. It identifies commonly used tools for computing MOEs.

  1. Identify how field measurements are processed to estimate the MOEs used in conducting traffic analysis studies.

Chapter 3 describes how MOEs are measured in the field.

  1. Provide guidance on how these MOEs are defined and calculated in the tools.

Chapter 4 documents how MOEs are computed by a range of macroscopic and microscopic tools.

  1. Develop an innovative approach to interpret these MOEs when conducting traffic analysis studies.

Chapter 5 presents a recommended approach to defining, calculating, and interpreting MOEs, which were reviewed by a panel of technical experts in Chapter 6, and refined accordingly. The final refined set of MOEs and their interpretation are provided.

  1. Demonstrate the validity of the approach through a case study of representative tools.

Chapter 7 illustrates the application of the MOEs to two case studies taken from vehicle trajectory data developed under the NGSIM program. This chapter illustrates the computation and interpretation of the MOEs. The final set of recommended MOEs and their interpretation based on the results of technical review and the case studies are also provided.