Vehicle Fleet Data for Cost Efficient Real-Time Road Surface Assessment
摘要
Knowledge about road roughness is crucial for both vehicles and timely road maintenance work. The traditional approach is to derive roughness classes according to ISO8608 or IRI values from fine granular road surface profiles. As collecting such profiles relies on elaborated measuring devices and dedicated measurent campaigns, road assessment becomes costly and comparably slow. In this paper we introduce an approach to overcome these drawbacks. We show how to employ fleet data from common series vehicles to estimate ISO8608 roughness classes and IRI values. We demonstrate the effectiveness of our approach in a field study on more than 5,000 km of public roads in the Netherlands and millions of vehicle kilometers.