Dynamic green split optimization in intersection signal design for urban street network
In the past few decades, auto travel demand in the United States has significantly increased, but roadway capacity unfortunately has not expanded as quickly, which has led to severe levels of highway traffic congestion in many areas. In theory, the problem of congestion addressed through demand management and roadway expansion. However, system expansion in urban areas is difficult due to the extremely high cost of land; therefore, maximizing the existing capacity therefore often is considered the most realistic option. In urban areas, most of the traffic congestion and delays typically occur at signalized intersections. This thesis aims to prove the hypothesis that it is possible to increase capacity by establishing traffic signal timing plans that are more effective than existing plans. A new methodology is introduced in this thesis for dynamic green split optimization as a part of intersection signal-timing design to achieve maximized reduction in overall delay at all the intersections within an urban street network. The measurement of effectiveness in this new method is reduction in the average delay per vehicle per signal cycle. This thesis used data from 143 signalized intersections and 334 street segments in the Chicago Loop area street network to demonstrate the proposed methodology. The results suggest that it is possible to reduce delay by approximately 35% through the optimization of signal green splits for the four-hour AM and four-hour PM peak periods of a typical day
Labi, Purdue University.
Civil engineering|Transportation planning|Urban planning
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