Quantifying Multimodal Metrics of Performance on Arterial Corridors Using ITS Data

Abstract

Recent advances in intelligent transportation systems (ITS) and emerging probe-based mobility data sources present new opportunities for effective analysis and improvement of corridor performance. While prior research efforts have looked at the use of specific data sources to address one mode at a time, challenges exist in combining a variety of data sources, each with varying quality and resolution, to understand and improve upon performance of all motorized and non-motorized modes in a unified way. This paper provides an overview of the data types often available to decision-makers and proposes a data model to facilitate the analysis of multimodal data on arterial corridors, including the metadata required to support automated workflows. Two types of metrics are implemented: travel time reliability calculated using probe-based data and transit performance based on automated passenger count data. Our results illustrate the challenges and appropriate interpretations involved in quantifying arterial corridor performance.

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