Traffic Network Travel Time by Nithin Gopidi

Nithin completed his thesis in May 2016.  She developed methods for constructing speed and travel time distributions from hundreds of thousands of GPS routes gathered by emergency response vehicles.

Complete Thesis

Gopidi, N. R. (2016).  Emergency Response Vehicle Travel Time Analysis (Masters Thesis).  The University of Texas at Austin.

Abstract

Fire departments, ambulance services and police departments often worry if they are providing prompt response times in case of an emergency. To be effective, emergency response vehicles (ERV) have to be on the scene within a certain time of the initial emergency call. Emergency response vehicles are exempt from many traffic regulations like speed limit, crossing red signal and moreover other vehicles are expected to yield for ERV. Hence the response time analysis of ERV is very different from the regular traffic study. Advancements in the field of traffic signal control technology brought into picture new traffic signal control devices (TCDs). These TCDs automatically detect arrival of an ERV to turn traffic signal green for the ERV to go through. Unfortunately, high installation costs limit the number of TCDs that can be deployed. The key goal of this article is to identify potential intersections in a traffic system for the installation of a TCDs.

We propose a method of using Global Positioning System (GPS) data from ERVs to identify slow spots in the traffic system. We extend existing map matching methods, whose main goal to recreate the vehicle path from GPS data, to be able to derive travel time and speed distributions for ERVs in a traffic system. We fpresent results of our algorithms on 2 years of ERV GPS data from Austin Fire Department. The analysis allows us to identify important intersections in Austin for the installation of TCDs. The results and methodology we introduce can be used to significantly improve response times, while meeting budget restrictions.


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