Developing a model for the utilisation of auxiliary through lanes at signalised intersections

Browne, Nicholas Raymond (2019) Developing a model for the utilisation of auxiliary through lanes at signalised intersections. [USQ Project]

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Additional through lanes are quite often added at signalised intersections to increase their capacity, these are known as auxiliary through lanes (ATLs). The amount of traffic that uses these lanes relative to the adjacent continuous through lanes (the lane utilisation) is often quite low. This research project aimed to develop a model for predicting the utilisation of these lanes.

The capacity of intersections is often the limiting factor in determining the capacity of a road. Being able to predict this capacity at the planning stage accurately is critical in determining the success or longevity of a potential project. At intersections with ATLs installed, the utilisation of the ATL is a crucial factor in determining the capacity of that intersection. Previous research has indicated that the length of these lanes may be used to assess their utilisation, but to date, determination of a relationship between these two values has not occurred. This project intended to build on this research to develop a relationship between ATL length and utilisation, as well as including other variables that may improve the model accuracy.

This research selected57intersectionapproachesacross Australia for inclusion as case study sites. The ATL utilisation for each site was determined, and critical variables were collected, including ATL length, degree of saturation and traffic signal timing parameters. Multiple variable correlation and linear regression methods were implemented to determine the relationship between different combinations of these variables. The strongest of these were then used to compare the model to other methods of ATL prediction identified in the literature review.

The study found that the relationship between single variables and the ATL utilisation were quite weak. However, the results show a moderately strong relationship when variables were combined using multiple regression analysis. The combination of variables that gave the most robust relationship were the number of lanes, cycle time, degree of saturation, ATL departure and approach lengths and the speed limit in that order of significance.

The model developed by this study compares well against other ATL utilisation prediction models in the limited testing undertaken within this study.

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Item Type: USQ Project
Item Status: Live Archive
Faculty/School / Institute/Centre: Historic - Faculty of Health, Engineering and Sciences - School of Civil Engineering and Surveying (1 Jul 2013 - 31 Dec 2021)
Supervisors: Somasundaraswaran, Soma
Qualification: Bachelor of Engineering (Honours) (Civil)
Date Deposited: 23 Aug 2021 00:50
Last Modified: 26 Jun 2023 05:53

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