Traffic signal network performance measures using high resolution data
Abstract
Traffic signal management has great potential for improvement by leveraging the mature modern communication and software technologies so commonly in use today. Wireless networks, file buffering and data transfer scheduling, Relational Database Management Systems (RDBMS), and Web-Application technologies allow transportation agencies that cover a wide geographic area to monitor their infrastructure effectively and efficiently with limited resources. Performance measures are critical for assessing both communication infrastructure as well as system operation to prioritize maintenance activities. A case study of a 12-signal corridor at State Route 37 in central Indiana presents concepts for (i) how to assess and troubleshoot signal controllers in an active traffic management system using data analytics, (ii) how to adapt new data structuring and storage techniques to improve the flexibility of a pre-existing link-optimizing algorithm for signal re-timing, and (iii) how to evaluate signal re-timing results as a feedback component to agency objectives using large-scale, crowd-sourced vehicular speed information. The impact of the maintenance and operational improvements was shown to reduce median travel time by approximately 30-seconds in the northbound direction and up to two minutes in the southbound direction during the midday period. The concepts presented for this corridor are currently being scaled state-wide.
Degree
M.S.
Advisors
Bullock, Purdue University.
Subject Area
Information Technology|Civil engineering|Transportation planning|Operations research
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