Curbside parking is associated with various adverse impacts on urban traffic networks and is rarely recommended. However, there are cases where parking demand dictates the establishment of on-street parking lanes. Proper planning of the number and type of curbside parking lanes to be located is essential for maximizing roadway capacity and minimizing the resulting impacts of parking operations on the network’s performance. This paper develops a bi-level mathematical programming model for planning and sizing curbside parking lanes in an urban network. The model is solved using a genetic algorithm and demonstrated for a medium-sized urban network.
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