The OpenTripPlanner (OTP) project was launched in 2009 as an open source, community-driven effort to produce an advanced multimodal trip itinerary planning platform. The project has since attracted a thriving community of users and developers, with live deployments now found in eight countries.

Since its inception, OTP has primarily been focused on supporting the deployment of conventional rider-facing web-based trip planning services, similar to proprietary (though generally single-mode) offerings provided by many transit agencies and third-party providers such as Google. With OTPs unique position as a fully multimodal, open source platform, this application serves an important audience for the software and will continue to be a primary focus going forward.

There is also increasing interest in applications of OTP that go beyond the original objective of rider-oriented, point-to-point itinerary planning. In particular, there is a growing focus on data-driven decision making in the transportation policy arena, accompanied by an increasing demand for robust, adaptable software tools that can support this activity. We believe that the core functions of transit system modeling and routing logic developed for the existing OTP project can be leveraged to support a wide range of analytical tools as well.

To that end, OpenPlans has begun the process of developing a long-range road map for an Analyst Extension to OpenTripPlanner. The extension is envisioned as a companion to the core OTP project, developed as a freestanding codebase but with linkages to the relevant components of the existing project. Like the core OTP project, the Analytics Extension is fully open source with a community-based approach to project development. Both OTP and the Analyst Extension are envisioned as eventual components of a comprehensive suite of open source transportation data management and analysis tools.

The road map being developed identifies a number of specific policy questions that could be addressed, and several are discussed in more detail below:

Location-Based Accessibility: This function would measure multimodal accessibility to or from specific locations in the transportation network. Two primary modes of operation are envisioned: origin-based (i.e., what can be reached starting from a given point of origin?) and destination-based (i.e., who can reach a given destination point?). Outputs will include polygonal geometries (isochrones) indicating accessible areas as determined by specific time limits or other parameters. If additional demographic data is supplied, the software can also produce summaries of population, jobs, etc. contained within the isochrone regions.

Systemwide Level of Service Analysis: This function would assess overall level of service provided for one or more modes on systemwide basis. Level of service can be defined in different ways for various modes -- for instance, average frequency/headways for transit, density of intersections for walkability, etc. The tool could produce raster based heat maps showing level of service across a specified area, and given additional geospatial data could also produce a correlation/regression analysis mapping level of service to other analysis inputs (e.g. housing prices).

Aggregate Search Analysis: This function involves batch execution of a potentially large set of user searches to answer various questions about how demand for service (represented by the collective searches) relates to supply (represented by the base transit network). The search datasets can be drawn from variety of sources, including regional origin/destination surveys and archived OTP user searches. Specific questions that could be addressed include measures of system effectiveness (e.g. what percentage of searched trips can be completed?) and measures identifying latent demand for multimodal infrastructure (e.g. which areas/corridors are most underserved by existing transit/bicycle/pedestrian facilities, and to what degree?).

System Modification Impact Analysis: This feature would allow for comparison of before and after snapshots of a transportation network, producing system-level statistics describing the impact of modifications to the network. The tool could be used in variety of analysis contexts, such as assessing and quantifying the negative impacts of transit service reductions (e.g. how many riders can no longer complete their trips after a given route or routes are cut?), or predicting the positive impact of proposed system expansions.