The application of de-icing salts to improve winter road safety,although necessary in cold climates,may adversely affect groundwater resources and degrade aquatic life in urban streams,if over-prescribed,and cause an ...The application of de-icing salts to improve winter road safety,although necessary in cold climates,may adversely affect groundwater resources and degrade aquatic life in urban streams,if over-prescribed,and cause an increase in crash rates,if under-prescribed.The main objective of this research is to develop algorithms for precision salt application rate(SAR)using advanced machine learning methods to achieve the desired road safety with less adverse environmental effects.This study highlights the importance of accurate realtime monitoring of pavement surface temperature and meteorological variables(i.e.,storm duration,hourly precipitation rate,and air temperature)as key factors in prescribing salt application rates during winter storm events.A new SAR model was trained/tested using a decade of historic salt application rates from a range of winter storm events on three different road classes.The application of this model can help road authorities to achieve greater road safety and reduce adverse environmental impacts,especially in the identified and mapped salt vulnerable areas.展开更多
Extreme weather conditions（i, e. snow storm） in winter time have caused significant travel disruptions and increased delay and traffic accidents. Snow plowing and salt spreading are the most common counter-measures ...Extreme weather conditions（i, e. snow storm） in winter time have caused significant travel disruptions and increased delay and traffic accidents. Snow plowing and salt spreading are the most common counter-measures for making our roads safer for motorists. To assist highway maintenance authorities with better planning and allocation of winter maintenance re- sources, this study introduces an analytical model to estimate the required number of trucks for spreading operation subjective to pre-specified service time constraints considering road geome- try, weather and traffic. The complexity of the research problem lies in dealing with heteroge- neous road geometry of road sections, truck capacities, spreading patterns, and traffic speeds under different weather conditions and time periods of an event. The proposed model is applied to two maintenance yards with seven road sections in New Jersey （USA）, which demonstrates itself fairly practical to be implemented, considering diverse operational conditions.展开更多
基金funded by the Ministry of Transportation of Ontario,and the Natural Sciences and Engineering Research Council of Canada,alliance grant#401643。
文摘The application of de-icing salts to improve winter road safety,although necessary in cold climates,may adversely affect groundwater resources and degrade aquatic life in urban streams,if over-prescribed,and cause an increase in crash rates,if under-prescribed.The main objective of this research is to develop algorithms for precision salt application rate(SAR)using advanced machine learning methods to achieve the desired road safety with less adverse environmental effects.This study highlights the importance of accurate realtime monitoring of pavement surface temperature and meteorological variables(i.e.,storm duration,hourly precipitation rate,and air temperature)as key factors in prescribing salt application rates during winter storm events.A new SAR model was trained/tested using a decade of historic salt application rates from a range of winter storm events on three different road classes.The application of this model can help road authorities to achieve greater road safety and reduce adverse environmental impacts,especially in the identified and mapped salt vulnerable areas.
基金supported by the New Jersey Department of Transportation and the Federal Highway Administration
文摘Extreme weather conditions（i, e. snow storm） in winter time have caused significant travel disruptions and increased delay and traffic accidents. Snow plowing and salt spreading are the most common counter-measures for making our roads safer for motorists. To assist highway maintenance authorities with better planning and allocation of winter maintenance re- sources, this study introduces an analytical model to estimate the required number of trucks for spreading operation subjective to pre-specified service time constraints considering road geome- try, weather and traffic. The complexity of the research problem lies in dealing with heteroge- neous road geometry of road sections, truck capacities, spreading patterns, and traffic speeds under different weather conditions and time periods of an event. The proposed model is applied to two maintenance yards with seven road sections in New Jersey （USA）, which demonstrates itself fairly practical to be implemented, considering diverse operational conditions.
