Best Practices for Road Weather Management Version 2.0
Title:
Salting Route Optimisation using XRWIS and Evolutionary Computation
Abstract:
With limited resources and treatment time constraints, it is imperative that salting routes are planned in advance for efficient and effective winter road maintenance. To aid this process, a salting route optimisation system which combines evolutionary algorithms with the neXt generation Road Weather Information System (XRWIS) has been developed. The system can cope with large-scale instances in the real world within reasonable computation times, to the extent that daily dynamic salting route optimisation can be realised. However, the use of a dynamic system, that each day adjusts salting routes in line with forecast road temperatures, may increase complexity to the extent that user error will occur in the treatment regime. Therefore, a robust (static) solution of salting route optimisation is also presented. Here, the emphasis is placed on thermally ranking optimised routes so that the 'warmer' routes could be left untreated on marginal nights.
Source(s):
13th Standing International Road WEather Conference (SIRWEC), University of Birmingham (United Kingdom) and Okayama University (Japan)
Date: 2006
Author:
Chapman, Handa, Yao, Thornes
Keywords:
Decision support
Route choice
Road Weather Information System (RWIS)
Pavement condition
Pavement temperature
Forecast/Prediction
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