Fleet size estimation for spreading operation considering road geometry,weather and traffic

来源 :Journal of Traffic and Transportation Engineering(English Ed | 被引量 : 0次 | 上传用户:shibihu
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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 resources,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 geometry,weather and traffic.The complexity of the research problem lies in dealing with heterogeneous 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. Extreme weather conditions (iesnow storm) in winter time have have 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 resources, 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 geometry, weather and traffic. The complexity of the research problem lies in dealing with heterogeneous 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 ibility Practical to be implemented, considering diverse operational conditions.
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