The prediction of ice formation on motorways in Britain
Each winter, Britain spends up to £120 million spreading approximately 2 million tonnes of rock salt on our roads to keep them free of ice and snow. This thesis shows that it would be possible to significantly reduce the amount of salt spread, by improving the accuracy of the Road Danger Warnings issued to Highway Authorities. Each day in winter, the maintenance engineer receives a Road Danger Warning from his local weather centre. Unfortunately these Warnings are not very accurate because they are based on forecasts of minimum air temperature alone, rather than using road surface temperatures. During the winter of 1982/83, of 102 Road Danger Warnings issued to Hereford and Worcester County Council, only 32 were correct in predicting icy conditions on the MS motorway. This thesis presents a computer model to predict ice formation on roads up to 24 hours ahead. During the winter of 1978/79 instruments were installed in the M4 motorway to measure road surface temperature and wetness. The computer model has been tested retrospectively for 30 nights when the road surface temperature fell below 5°C. The predicted minimum road surface temperature has a root mean square error of 0.9°C. During the winters of 1982/83 and 1983/84, the model was tested in 'real time' against road surface temperatures measured automatically on the M5 and M6 motorways, giving a root mean square error of 1.5°C for 80 nights during 1.982/83, and 1.3°c for 120 nights during 1983/84. The form of the issued Road Danger Warnings has been changed from a simple sentence issued over the telephone or using telex, to a graph of predicted road surface temperature and wetness. An optimistic and a pessimistic graph is issued to give the maintenance engineer an idea of the certainty of the forecast. The thesis proposes a national network of automatic road surface monitoring sites. Each site would be linked to microcomputers in local weather centres, which would then run the prediction model and issue Road Danger Warnings accordingly. The information could then be sent to maintenance engineers using Prestel.