Department of Computer Science at UH

University of Houston

Department of Computer Science

In Partial Fulfillment of the Requirements for the Degree of
Master of Science

Daxiao Liu

Will defend his thesis

An Energy-Saving Approach For Real-Time Highway Traffic Estimation Using GPS-Enabled Smartphones


This paper presents a microscopic traffic estimation algorithm for smartphones by employing their built-in probes (such as GPS and acceleration sensors) to increase the accuracy of estimating the real-time traffic condition without significantly increasing these smart phones' energy consumption. In this approach, real-time traffic data is collected through cooperating smartphone users traveling on urban roads. A new reporting algorithm is provided on smartphone users' side to minimize smartphone probes' connection with the server. Based on these probes' data, real- time traffic condition is estimated on the server side, by applying the Kalman-Filtering (KF) algorithm. Also the real-time traffic level of service (LOS) is estimated on urban roads. A smartphone app is also developed to work as one sample GPS probe together with different simulation-based traffic scenario. Simulation result shows that the proposed algorithm requires less energy usage that existing methods without sacrificing the accuracy of the real-time traffic estimation.


Date: Thursday, November 20, 2014
Time: 2:45 PM
Place: PGH 550

Faculty, students, and the general public are invited.
Advisor: Prof. Albert M.K. Cheng