01710391

Component

Over the past decade, relocation mode choice has been studied in an effort to improve disaster management and planning, focusing on traditional modes such as personal automobiles, carpooling, and transit. Recently, however, on-demand rideshare, or ridesourcing, has entered the scene most notably through transportation network companies, such as Uber and Lyft, as a new transportation option with important implications for collaborative disaster response and recovery. This work investigates the possible role of ridesourcing in small-scale transportation emergencies as a supplemental relocation tool. The research involves a case study deployed in New York City, Los Angeles, and Chicago containing 185 responses. A choice model is developed using data from the internet-based stated preference survey. The results reveal that on-demand ridesourcing is a desired mode choice during some emergency scenarios, depending on the region, socioeconomic factors, and context of the scenario. This pilot study suggests that on-demand ridesourcing has potential as an innovative resource for adaptive and collaborative disaster response. Marginal effects provide evidence that the demographic factors (in particular, age and income) appear to be the most impactful for relocation mode selection. Among the contextual factors, event severity and familiarity of location have the strongest effects. These findings may aid in the design of tailored emergency communication strategies for specific audiences and desired outcomes. Additionally, improved awareness and anticipation of the use of ridesourcing for no-notice transportation events could support the implementation of preparative measures and guided policy-making for emergency relocation to enhance the resilience of urban areas to unforeseen disturbances.

Alternate title: On-Demand Rideshare for Emergency Relocation: An Exploratory Analysis of Context and Emotionality

19-05418

English

21p

2019

Transportation Research Board 98th Annual Meeting

Digital/other

Figures; References; Tables

Case studies; Choice models; Demand responsive transportation; Emergency transportation; Evacuation; Mode choice; Ridesharing; Ridesourcing; Stated preferences

Chicago (Illinois); Los Angeles (California); New York (New York)

Highways; Planning and Forecasting; Security and Emergencies

Transportation Research Board Annual Meeting 2019 Paper #19-05418

TRIS, TRB, ATRI

Jun 27 2019 2:36PM

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• Review of Rigid Airfield Pavement Cracking Failure Models
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