Abstract
A healthy road network plays a significant role in the socio-economic development of any country. Road management authorities struggle with pavement repair approaches and the finances to keep the existing road network to its best functionality. It has been observed that real-time road condition monitoring can drastically reduce road and vehicle maintenance expenses. There are various methods to analyze road health, but most are either expensive, costly, time-consuming, labor-intensive, or imprecise. This study aims to design a low-cost smart road health monitoring system to identify the road section for maintenance. An automized sensor-based system is developed to assist the road sections for repair and rehabilitation. The proposed system is mounted in a vehicle and the data have been collected for a more than 1000 km road network. The data have been processed using SPSS, and it shows that the proposed system is adequate for detecting the road quality. It is concluded that the proposed system can identify the vulnerable sections to add to the pavement maintenance plan. In the future, the created application can be launched as a smart citizen app where each car driver can install this application and can monitor the road quality automatically.
Highlights
The monitoring of road surface conditions has grown increasingly crucial in recent years
An adequately maintained road network is vital for the safety and consistency of cars traveling on that road and the health and safety of individuals using the roads
Manual visuals helped the researchers to classify in a better way and removal of few noise points such as (1) sensors were detached due to jerks and spikes were recorded, (2) a car was moved to the broken patch or sides or cat-eyes on the road and (3) sudden brakes
Summary
The monitoring of road surface conditions has grown increasingly crucial in recent years. Road surfaces that are well-maintained improve road user safety and comfort [1]. It is critical to continuously monitor road conditions to improve the transportation systems, user safety, and comfort. According to a US Department of Transportation study, road conditions are an important aspect of road quality. The amount of roughness of road surfaces is an important index that measures road health. Dynamic road conditions contribute to unpredictable driving behavior and vehicle depreciation, which can have an economic impact and, in some cases, result in injuries and fatalities. An effective system for mapping road health can dramatically improve driving and pedestrian safety [5,6,7,8]
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