An Information Retrieval Approach for Robust Prediction of Road Surface States
| Autor: | Jae-Hyung Park, Kwanho Kim |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
road surface state detection
road surface radar smart highway information retrieval machine learning ranking and scoring functions exponential moving average Similarity (geometry) Computer science 010103 numerical & computational mathematics computer.software_genre 01 natural sciences Biochemistry Article Analytical Chemistry Search engine Text mining 0502 economics and business 0101 mathematics Electrical and Electronic Engineering Instrumentation 050210 logistics & transportation Information retrieval business.industry 05 social sciences Function (mathematics) Atomic and Molecular Physics and Optics Identification (information) Road surface State (computer science) Data mining business computer |
| Zdroj: | Sensors (Basel, Switzerland) Sensors; Volume 17; Issue 2; Pages: 262 |
| ISSN: | 1424-8220 |
| Popis: | Recently, due to the increasing importance of reducing severe vehicle accidents on roads (especially on highways), the automatic identification of road surface conditions, and the provisioning of such information to drivers in advance, have recently been gaining significant momentum as a proactive solution to decrease the number of vehicle accidents. In this paper, we firstly propose an information retrieval approach that aims to identify road surface states by combining conventional machine-learning techniques and moving average methods. Specifically, when signal information is received from a radar system, our approach attempts to estimate the current state of the road surface based on the similar instances observed previously based on utilizing a given similarity function. Next, the estimated state is then calibrated by using the recently estimated states to yield both effective and robust prediction results. To validate the performances of the proposed approach, we established a real-world experimental setting on a section of actual highway in South Korea and conducted a comparison with the conventional approaches in terms of accuracy. The experimental results show that the proposed approach successfully outperforms the previously developed methods. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|