The National Academies

NCHRP 08-36/Task 141 [Completed]

Evaluation of Walk and Bicycle Demand Modeling Practice
[ NCHRP 08-36 (Research for the AASHTO Standing Committee on Planning) ]

  Project Data
Funds: $100,000
Research Agency: RAND Corporation with RSG
Principal Investigator: Mark Bradley
Effective Date: 5/30/2017
Completion Date: 5/15/2019


Whether to address policy goals or to meet new performance measurement guidelines, states, regions, and cities increasingly need to account for walking and bicycling in planning and investment decisions. As a result, planning tools like regional travel demand models (TDMs)—initially developed to analyze automobile and transit use—must adapt in response to these new needs. In 1993, only two large MPOs (population > 1 million) included walk and/or bicycle travel modes in their TDMs. Today, more than half of large MPOs (and some medium and small agencies) forecast non-motorized travel in one way or another (although fewer distinguish between walking and bicycling). Simultaneously, research efforts to analyze and model walking and bicycling are increasing exponentially. Records on bicycle and pedestrian modeling archived in the Transportation Research Information Database (TRID) have increased from 1 or 2 per year in the early 1990s to more than 20 per year today. Pedestrian and bicyclist data collection is also flourishing. Agencies at all levels are using coordinated volunteer counts, improved household travel surveys, and automated counters to capture more walking and bicycling data. While this proliferation of research, modeling techniques, and data resources is a positive trend, it also poses challenges to public agencies, which have limited resources to connect the latest research and data to their own modeling needs and capabilities.

There is a critical need to evaluate the current state of research and practice in regional pedestrian/ bicycle modeling and share that evaluation with practitioners.  Research output would appear to have outstripped ability to keep up with the state-of-the-art.  Increased volumes of pedestrian and bicyclist data sit without sufficient analytical tools to make use of them.  In addition, different agencies have applied various ad-hoc solutions that depend on their unique decision support needs, data sources, and modeling capabilities, with little consistency. Other agencies, especially medium and small MPOs, lack the technical capacity and funding to undertake model improvements to incorporate walking and bicycling modes in a comprehensive process of demand modeling. A review that links pedestrian and bicycle demand modeling research and practice is necessary to focus research efforts on those areas with the greatest needs, make efficient use of greater access to data resources, and avoid modeling practitioners having to reinvent the wheel. By synthesizing existing research and documenting best practices, this project will provide planners and modelers at state DOTs, MPOs, and consultancies with timely options to consider and will facilitate transfer of successful and innovative techniques that improve how regional TDMs forecast walking and bicycling.

Improving bicycle/pedestrian modeling within TDMs offers a number of immediate advantages for planning agencies. Such efforts increase model sensitivity to non-motorized facilities, land use changes, and the built environment, enabling evaluation of a wider range of planning interventions to meet increasingly urgent needs and performance measurement demands at all levels of planning within states. Models that more accurately predict walking and bicycling activity levels also provide necessary physical activity inputs for health impact assessments and exposure estimates for traffic safety analysis and modeling. These estimates are especially important considering the newly required walking and bicycling safety performance measures for the Highway Safety Improvement Program.


The objective of this research was to synthesize the current landscape of pedestrian and bicycle demand modeling and connect the results to planning needs and practice. To do so, this project undertook the following steps:

1)      Documented, through broad surveys, focused interviews, and literature review, best and common practices for including walking and bicycling in regional travel demand forecasting models;

2)      Evaluated existing gaps between research and practice and needs and capabilities in bicycle/pedestrian demand modeling;

3)      Facilitated transfer of knowledge from research to practice and among practitioners; and

4)      Identified key areas for future research. The results will be presented both in a final report and through dissemination efforts to researchers and practitioners.  

The Final Report is now available.

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