An internet of things prototype to quantify the lateral wheel path distributions of local roads in New Zealand

Abstract

ABSTRACT The actual lateral wheel path distribution (LWD) on roads differs from the design assumptions. This leads to premature deterioration of chip-sealed pavements in the form of flushing and ravelling resulting in subsequent maintenance costs. The location of LWD is key to calibrating the variable-rate bitumen spray bar used to minimise flushing and ravelling during chip seal construction. Current methods used to estimate the location of LWD rely on visual inspection. This is subjective and reliant on individual expertise. This study aims to automate obtaining LWD by developing an Internet of Things (IoT) prototype to locate the LWDs. This prototype was tested by collecting LWDs from 22 locations in Christchurch, New Zealand. Results show that narrow roads exhibit a concentrated wheel path distribution. Specifically, increasing single lane carriageway width leads to a significant rise in the standard deviation (spread) and position of the LWDs among 22 locations investigated. Cycle lanes or parking bays significantly influence the location and distribution of LWD. There is no clear link between road camber and LWD. The findings can be used to improve the calibration of the variable-rate bitumen spray bar and inform pavement and traffic engineers to enhance construction and maintenance practices. .