BCA4ABM : A Benefit-Cost Analysis Tool Optimized For Activity-Based Models
Corresponding Author: Mark Bradley, RSG
Presented By: Mark Bradley, RSG
Activity-based models provide outputs that can enhanced benefit-cost analysis in a number of different ways. Traditional benefit-cost methods use the "rule of a half" approach to measure the benefits of changes in travel costs and times in a way that accounts for generated or suppressed demand.
Output from activity-based models can be used to enhance benefit measures in a number of ways. The benefit can be segmented along any household and person characteristics that are available for the synthetic population records. Also, the model "logsums" can be used to capture benefits beyond changes in travel times and costs, including those related to the inherent attractiveness of different travel modes and destinations.
The paper describes a tool that was programmed in Python to be easily configurable to use with outputs from different activity-based model systems and for testing different types of benefit calculations and population benefit segmentations. In addition to calculating tour- and trip-related benefits from the AB model outputs, the tool can perform matrix-based benefit calculations for other travel markets (e.g. commercial vehicles, visitor trips and external trips), as well as link-based benefit calculations for outputs such as accident-related costs.
The paper describes how the BCA4ABM tool was applied for the Tampa region AB model, which uses the DaySim AB model platform and the Cube network software, as well as for the San Diego region AB model, which uses the CT-RAMP AB model platform and the TransCAD network software. Logsum-based benefit measures are compared against more traditional "rule-of-a-half" based measures for both infrastructure change and land use change scenarios.
The paper recommends how the tool can best be used in practice, as well as potential areas for further development.