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This page is part of the Category Project-level traffic Forecasting.


Project-level traffic forecasting is a specialized set of techniques to better make forecasts over short time horizons, typically by using ground data along with other methodologies. Project-level traffic forecasting became well established with the publication of NCHRP Report 255, which was itself updated by NCHRP Report 765. The "Hawaii Guidelines" are a rewritten version of much of the material in NCHRP Report 765, and these guidelines form the basis for this article.

The Practice of Project-Level Travel Forecasting


Forecasting process

National guidelines

Quality assurance and validation standards

Choice of techniques

Errors and variability in volume data

Half-lane rule and extensions

Limited role of judgment

Scenario/sensitivity testing

Reporting of reasonable bounds on forecast values

Documentation standards

Interfacing with Models Developed by Partner Agencies

Standard Models

Ideal Travel Model Standard Best Practical Experience Model Standard Acceptable Practical Experience Model Standard Discussion of Travel Delay in Acceptable Models

Direct Use of Travel Model Outputs

Interpolation between Forecast Years Pivoting with Select Link Analysis for Small Developments

Refinement Methods

OD Table Refinements Temporal Refinements and Directional Split Refinements Vehicle Mix Refinements Turning Movement Refinements Screenline Refinements Speed and Travel Time Refinements

Special Reporting Requirements


Measures of Effectiveness and Performance Measures

Refinement for Evaluation

Refining Vehicle Class Forecasts for Evaluation Refining Speeds for Evaluation

Traffic Microsimulation

Land Use Models

Special Reporting Requirements

Custom Project-Level Models

Techniques for Increasing Spatial Resolution

Windowing with OD Table Estimation from Traffic Counts Working with Vehicle Re-identification Data Subarea Focusing

Blended Models

Hybrid Models Multi-resolution Models

Improving Temporal Detail

Temporal Resolution Traffic Dynamics

Guidelines for Specific Project Types

Bypasses of Regional Scope Bypasses of Local Scope

Special Reporting Requirements

Conventional Post-Processing

Highway Noise Analysis Safety Analysis User Benefits Pavement Design Air Quality, GHG Emissions and Energy Consumption

Time Series Methods

Linear Regression Techniques

Trend Models Linear Models with Explanatory Variables Smoothing

Box-Jenkins/ARIMA Methods

Autoregressive (AR) Models Autoregressive with Explanatory Variables (ARX or SAR) Models Box-Cox Transformations

Time Series Examples

Example 1: 2-Lane Rural Highway Site (Island of Maui) Example 2: 6-Lane Freeway Site (Island of Oahu) Example 3: An Autoregression Model with Box-Cox Transformation

Special Reporting Requirements

Case Studies