Coordinated Transit Response Planning and Operations Support Tools for Mitigating Impacts of All-Hazard Emergency Events

This report summarizes current computer simulation capabilities and the availability of near-real-time data sources allowing for a novel approach of analyzing and determining optimized responses during disruptions of complex multi-agency transit system. The authors integrated a number of technologies and data sources to detect disruptive transit system performance issues, analyze the impact on overall system-wide performance, and statistically apply the likely traveler choices and responses. The analysis of unaffected transit resources and the provision of temporary resources are then analyzed and optimized to minimize overall impact of the initiating event

A stated-preference intercept survey of transit-rider response to service disruptions

A web-based intercept survey was designed and implemented in order to capture the response of transit riders in the Chicago metropolitan area to a variety of service disruptions. Current transit riders were intercepted in the field from November 2017 through January 2018, according to a sampling plan based on local ridership information, in order to gain a representative sample for analysis. Each participant completed a questionnaire regarding the intercepted trip, along with demographic and travel experience information. The survey included a series of stated-preference responses where the current trip is randomly disrupted and alternative travel modes are proposed with service characteristics randomly altered from a baseline scenario. This was designed to understand individual trade-offs between various mode alternatives and travel plan modification strategies under a variety of scenarios. Altogether, 659 transit riders gave responses to 2626 different disruption scenarios. In general, a plurality of riders (49%) choose to continue using transit, either waiting for service restoration or using agency-provided shuttle service, although at a decreasing rate as the travel delay increases. Fewer riders, approximately 15%, choose to alter their activity patterns altogether, while 26% would alter their travel to use either a taxi or an alternative transportation network company (TNC). Having a more detailed understanding of the behavior of riders under various disruption scenarios should allow transit agencies to better prepare for service recovery and restoration after and during local disruptions