What spatial resolution do we need for a route-based road weather decision support system?

Since their implementation, road weather information systems have mostly relied on point measurements from outstations to initiate and verify daily forecasts. Initially, spatial extrapolation was achieved by thermal mapping, but this is gradually being replaced by route-based forecasting techniques. Both techniques are similar in the sense that they use a point measurement, often taken from an outstation, to provide a spatial forecast of road surface temperatures around the road network at varying resolutions. A substantial research effort has been undertaken to understand and model the complex environmental conditions and mechanisms responsible for the variation in road surface temperatures around the road network. In particular, the interaction of varying geographical parameters around the road network (e.g. altitude, land use, road construction, topography, etc.) has been used to develop local climatological models and route-based forecasting products. By considering the needs of winter maintenance engineers, this paper reviews the current state of the art and takes a critical look at the embedding of forecast products into decision support systems. This is achieved by considering a case study of how road surface temperature and condition vary across the width of a road profile, instead of just lengthways along a road. It is shown that temperature and condition both vary significantly across the profile, which immediately raises questions about the validity of current surveying and modelling practices. This has implications for both the resolution of route-based forecasting products as well as user confidence in automated decision support systems.

[1]  I. D. Watson,et al.  The determination of view-factors in urban canyons , 1984 .

[2]  J. Shao,et al.  Spectral analysis and sensitivity tests for a numerical road surface temperature prediction model , 1991 .

[3]  P J Lister,et al.  Thermal mapping: Reliability and repeatability , 2007 .

[4]  Xin Yao,et al.  Dynamic salting route optimisation using evolutionary computation , 2005, 2005 IEEE Congress on Evolutionary Computation.

[5]  Torbjörn Gustavsson,et al.  Thermal mapping – a technique for road climatological studies , 1999 .

[6]  Lee Chapman,et al.  A geomatics-based road surface temperature prediction model , 2006 .

[7]  L. Chapman,et al.  Modelling of road surface temperature from a geographical parameter database. Part 2: Numerical , 2001 .

[8]  Lee Chapman,et al.  Sky‐view factor approximation using GPS receivers , 2002 .

[10]  Torbjörn Gustavsson,et al.  Road Climate in Cities:A Study of the Stockholm Area, South‐East Sweden , 2001 .

[11]  A. Fujimoto,et al.  Effects of Vehicle Heat on Road Surface Temperature of Dry Condition , 2008 .

[12]  L. Chapman,et al.  The influence of traffic on road surface temperatures: implications for thermal mapping studies , 2005 .

[13]  Y. Delage,et al.  METRo: A New Model for Road-Condition Forecasting in Canada , 2001 .

[14]  H. Handa,et al.  Robust route optimization for gritting/salting trucks: a CERCIA experience , 2006, IEEE Computational Intelligence Magazine.

[15]  W. Gallus,et al.  CONCEPTUAL AND SCALING EVALUATION OF VEHICLE TRAFFIC THERMAL EFFECTS ON SNOW/ICE-COVERED ROADS , 2002 .

[16]  Lee Chapman,et al.  Real-Time Sky-View Factor Calculation and Approximation , 2004 .

[17]  William P. Mahoney,et al.  The U.S. Federal Highway Administration winter road Maintenance Decision Support System (MDSS): Recent enhancements & refinements , 2008 .

[18]  T. Lyons,et al.  Comments on “The Determination of View-Factors in Urban Canyons” , 1985 .

[19]  L. Chapman,et al.  Thermal imaging of railways to identify track sections prone to buckling , 2006 .

[20]  Lee Chapman,et al.  Potential Applications of Thermal Fisheye Imagery in Urban Environments , 2007, IEEE Geoscience and Remote Sensing Letters.

[21]  Lee Chapman,et al.  Verification of route-based road weather forecasts , 2010 .

[22]  Lee Chapman,et al.  Parameterizing road construction in route-based road weather models: can ground-penetrating radar provide any answers? , 2011 .