A risk-based approach to winter road surface condition classification
Author(s) -
Liping Fu,
Lalita Thakali,
Tae J. Kwon,
Taimur Usman
Publication year - 2017
Publication title -
canadian journal of civil engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.323
H-Index - 62
eISSN - 1208-6029
pISSN - 0315-1468
DOI - 10.1139/cjce-2016-0215
Subject(s) - adverse weather , index (typography) , road surface , aggregate (composite) , environmental science , risk assessment , collision , transport engineering , computer science , meteorology , statistics , engineering , civil engineering , mathematics , geography , materials science , computer security , world wide web , composite material
This paper presents a risk-based approach for classifying the road surface conditions of a highway network under winter weather events. A relative risk index (RRI) is developed to capture the effect of adverse weather conditions on the collision risk of a highway in reference to the normal driving conditions. Based on this index, multiple risk factors related to adverse winter weather conditions can be considered either jointly or separately. The index can also be used to aggregate different types of road conditions observed on any given route into a single class for risk-consistent condition classification and reporting. Two example applications are shown to illustrate the advantages of the proposed approach.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom