MainStreet translates our ASAP tools to a web application with intuitive visualizations of outputs and provides a clear understanding of analysis.
PersonDelay+ builds upon previous MMLOS methodologies by increasing transparency in the analysis and better informing decision makers and stakeholders of trade-offs.
LOS+ is a quick-response/sketch-planning tool that provides guidance in designing urban streets to better accommodate the four major travel modes.
Ridership+ enhances system-level perspectives of regional travel models with a focus on station-level planning and design strategies, to integrate transit into the community.
MXD+ utilizes research that identifies key relationships between modes of travel and the built environment to more accurately predict vehicle trip generation from MXDs.
Reliability+ transforms data from a variety of transit data sets into versatile transit performance metrics used to inform agencies of segments for improvement along routes.
Using inputs from field surveys, such as number of lanes, posted speed, and average daily traffic volumes, the CrossWalk+ tool guides the selection of crosswalk treatments.
StreetScore+ calculates comfort for people bicycling and walking and allows users to easily compare designs and effectively convey project benefits to stakeholders.
The one-step 3D printing process could reduce the cost of manufacturing and need for extensive assembly work. Explore the potential benefits and drawbacks.
We partnered with Blue Raster to build a new and improved, mobile device friendly Crowdsource+ tool to enable clients to receive public feedback.
We developed an innovative, objective, GIS-based tool known as Active+ for project prioritization within bicycle and pedestrian planning.
Explore our findings from a recent operational simulation analysis of ART for the proposed conventional Bus Rapid Transit (BRT) lanes in San Francisco.
This VMT/GHG calculator estimates the average vehicle-miles of travel from development projects or land use plans based on daily trip generation data.