Date of Award

12-2018

Document Type

Thesis

Degree Name

Master of Science (MS)

Department

Mechanical and Civil Engineering

First Advisor

Aldo Fabregas Ariza

Second Advisor

Luis Daniel Otero

Third Advisor

Troy Nguyen

Fourth Advisor

Ashok Pandit

Abstract

The goal of transportation management is to ensure the mobility of people and goods, in a reliable and efficient manner. Operation and maintenance of transportation infrastructure is key to accomplish their objectives. Intelligent Transportation Systems (ITS) applications rely on massive detection networks that collectively demand significant maintenance resources. Resource constraints force transportation agencies to look for innovative ways to optimize their operational and maintenance costs while serving their users at intended performance levels. The system inputs come from vehicle detection system (VDS), acting as field data collection devices, enabling traffic monitoring and management through response to specific conditions. This research uses a Six Sigma methodology i.e. DMAIC process to perform cause and effect analysis to determine reasons for VDS accuracy degradation and potential root causes. Then CUSUM charts are used to monitor and control the system variability. At last six pack capability report enables to monitor and control the critical components of the system. Research also performs an analysis of techniques used for monitoring accuracy to derive traffic detection sensor requirements for components and subsystems based on application-specific needs. The goal of the approach is to obtain stakeholders view of an acceptable performance based on the top-level functionality for a given ITS application. Suggest improvements on maintenance practices, and cost savings

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