Optimizing snowplow routes using all-new perspectives: road users and winter road maintenance operators

Abstract

Snowplowing is an indispensable part of winter road maintenance because it contributes to improving drivers’ mobility and safety. Most prior studies, however, limit focus to operational aspects without considering interaction with road users. This paper aims to minimize travel time in the traffic system while still maintaining the efficiency of plowing activities. The k-truck plowing with the precedence model was formulated to link road users with snowplow activities. The tabu search algorithm then followed to optimize the order of precedence of snowplow routes. Furthermore, the discrete-event simulation was used to quantify the effectiveness of the proposed method based on different scenarios and fleet sizes, and to illustrate the potential benefit of integrating both the operators’ and users’ perspectives. The methodological framework developed herein can be used to design a routing strategy that improves the performance of the snowplow trucks by reducing both plowing completion and road users’ total travel time.