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Pavement maintenance activities often involve lane closures, leading to traffic congestion and causing increases in road users' travel times. Scheduling of such activities should minimize the increases in travel times to all the travelers at network level. This article presents a hybrid methodology for scheduling of pavement maintenance activities involving lane closure in a network consisting of freeways and arterials, using genetic algorithm (GA) as an optimization technique, coupled with a traffic-simulation model to estimate the total travel time of road users in the road network. The application of this scheduling method is demonstrated through a hypothetical problem consisting of assigning three maintenance teams to handle 10 job requests in a network in 1 day. After 10 generations of genetic evolution with a population size of four, the hybrid GA-simulation model recommended a schedule that reduced the network total travel time by 5.1%, compared to the initial solution.

A laboratory test to assess the clogging potential of porous asphalt mixtures is useful as part of a rational design procedure of using these mixtures for construction of pavement surface friction courses. Two prerequisites for the laboratory assessment are ( a) the ability to measure an engineering parameter indicative of the mixture’s drainage capacity, and ( b) the availability of a repeatable procedure of introducing materials into the mixture to create clogging. A laboratory clogging test to cause deterioration in the drainage capacity of typical porous mixtures is described here. Monitoring of the changes in drainage capacity during the test is made possible by the use of recently developed equipment to measure permeability. The proposed clogging test procedure was applied to evaluate four porous asphalt mixtures. Test results suggest that the procedure was able to ( a) produce significant degrees of deterioration in the drainage capacities of the mixtures, and ( b) differentiate the different behaviors of the four mixes under the clogging treatment of the test.

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