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.
