Evaluating Road Hazard Maintenance Efficiency Using Citizen Science Data to Improve Road Safety

Abstract

Accidents caused by road hazards can be prevented through regular inspections by road management agencies. To this end, traffic agencies allocate substantial budgets and workforces to maintain the performance of roads. Additionally, traffic agencies require comprehensive data such as the classifications and sizes of road hazards. However, collecting spatial-temporal data on various road hazards is challenging, and evaluating it comprehensively with respect to work efficiency and budget allocation is difficult due to stakeholder interests across agencies. This study proposes a process of evaluating operational efficiency in terms of maintaining roads and preventing hazards by analyzing citizen scientist-based data. First, we collected data from drivers through a mobile application and applied text mining techniques to classify each complaint into several types of road hazard maintenance. Second, we developed an indicator to measure operational efficiency using the processed data and evaluated each regional agency per each type of maintenance. The results of this study provide evidence that specific types of road hazards occur prominently under specific agencies. In addition, the time required to provide maintenance for identical road hazards can vary among agencies. These results suggest that the maintenance budget for the entire national highway may need to be distributed differently based upon regional characteristics.