Official US Government Icon

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you're on a federal government site.

Secure Site Icon

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

The latest general information on the Coronavirus Disease 2019 (COVID-19) is available on Coronavirus.gov. For USDOT specific COVID-19 resources, please visit our page.

Travelers’ Rationality in Anticipatory Online Emergency Response

An innovative project at the North Carolina A&T State University (NC A&T), sponsored by the Center for Advanced Transportation Mobility (CATM), a Tier 1 UTC, is seeking to reduce the time needed for emergency response vehicles (ERVs) to respond to a sequence of emergency service requests while considering the behaviors of travelers stuck in traffic. The Travelers’ Rationality in Anticipatory Online Emergency Response project could improve on decision making related to the allocation of emergency response vehicles (ERVs) by taking real-time information about the behavior of affected travelers into account to anticipate traffic impacts and better manage response resources.

Traditional decisions in response to requests for emergency vehicle resources do not account for traffic flow behavior, nor the rationality (i.e., ability to make wise and sound decisions) of travelers in the transportation network. Existing models have prioritized the fastest response, regardless of the severity of the incidents or potential need for additional emergency resources in a later stage in the incident chain. In this research, an approach from a patent titled “Transportation Infrastructure Location and Redeployment,” issued by the United States Patent and Trademark Office (USSN 16/254,474), has been modified to accommodate online models, consider the availability of emergency vehicle resources in the near future (Figure 1), and minimize the total travel time delay encountered by the users in the transportation network.

Last updated: Thursday, July 9, 2020