Track: Engineering Management

Abstract

The pavement structure is a key component of the road network and transportation infrastructure worldwide. Major investments have been made in the United Arab Emirates (UAE) for the building of a wide road network connecting local cities and neighbouring countries. Regular inspection and maintenance in a timely manner are critical to maintain good ride quality and driving safety levels. As a significant component of pavement analysis, longer pavement monitoring is very important for the transportation system. Different sensing technologies have been dedicated to enhancing sensitivity, functionality, and performance since the middle of the 20th century. IRI is a measure of pavement roughness and it is a widely accepted performance index. Transportation agencies expend considerable resources using profiler vans to collect pavement roughness data. The use of existing accelerometers in smartphones as a collection of sensors is a possible alternative to collecting pavement performance equivalent data at a substantially lower cost and a higher degree of temporal resolution. To investigate the feasibility of such an approach, a prototype smartphone application was employed in this paper to collect International Roughness Index (IRI) data. The IRI data was obtained from three routes in the Northern Emirates in the UAE using a prototype program running on an Android smartphone. The analysis of collected data shows that consistent IRI values from various data collection runs can be generated by the proposed smartphone application focusing on other factors such as vehicle speed and vehicle type. Moreover, it is found that the average IRI data sets collected are strongly correlated with the measured IRI data collected by the Federal Road Department of Transportation using profiler vans.The pavement structure is a key component of the road network and transportation infrastructure worldwide. Major investments have been made in the United Arab Emirates (UAE) for the building of a wide road network connecting local cities and neighbouring countries. Regular inspection and maintenance in a timely manner are critical to maintain good ride quality and driving safety levels. As a significant component of pavement analysis, longer pavement monitoring is very important for the transportation system. Different sensing technologies have been dedicated to enhancing sensitivity, functionality, and performance since the middle of the 20th century. IRI is a measure of pavement roughness and it is a widely accepted performance index. Transportation agencies expend considerable resources using profiler vans to collect pavement roughness data. The use of existing accelerometers in smartphones as a collection of sensors is a possible alternative to collecting pavement performance equivalent data at a substantially lower cost and a higher degree of temporal resolution. To investigate the feasibility of such an approach, a prototype smartphone application was employed in this paper to collect the International Roughness Index (IRI) data. The IRI data was obtained from three routes in the Northern Emirates in the UAE using a prototype program running on an Android smartphone. The analysis of collected data shows that consistent IRI values from various data collection runs can be generated by the proposed smartphone application focusing on other factors such as vehicle speed and vehicle type. Moreover, it is found that the average IRI data sets collected are strongly correlated with the measured IRI data collected by the Federal Road Department of Transportation using profiler vans.