Abstract
To enhance the assessment of the network capacity for a given urban road system, the effects of the parking management strategies at destination areas are supposed to be considered in the network capacity assessment model. This study provides an extended road network capacity model which takes into consideration both the parking supply and parking pricing at each traffic zone. The network capacity model is formulated as a bilevel programming problem, with the maximization of total trip generation in the upper level and the combined trip distribution and traffic assignment (CTDTA) problem in the lower level. To reasonably characterize the impacts of the parking pricing and parking delay due to the congestion effect, two classes of travel demand are involved in the CTDTA model. An efficient and practical algorithm is provided for the solution of the bilevel network capacity model. Numerical experiments show the advantages of the proposed model and also demonstrate the effect of the parking supply and parking pricing on the assessment results of the road network capacity.
Highlights
The existing research on the road network capacity considering parking supply and parking pricing has the following inadequacies: (1) only some of the factors were involved in the network capacity assessment, so the effect of the urban parking management strategies cannot be evaluated comprehensively [19]; (2) incomplete to characterize the impact of destination congestion on the network-wide travel demand pattern [3], which may result in impractical O-D demand pattern for the maximum network capacity; (3) not consider the difference among the motor travelers and, causes the underestimate [4] or overestimate [24] to the total network capacity
E remaining of this paper is organized as follows. e section presents the new urban road network capacity model with parking supply and parking demand. en, section 3 provides an efficient solution algorithm for our proposed model formulated as bilevel programming
(b) e travelers associated with the fixed demand can only change the paths to minimize the individual travel cost, which is characterized by the user equilibrium principle. e travelers associated with the variable demand can change both the paths and destinations to minimize the total travel cost, which will be characterized by the combined trip distribution and traffic assignment model
Summary
Without considering the effect of destination congestions (i.e., the parking search time increases as the destination demand), the network capacity is overestimated in the situation “Without Destination Cost”. Based on the proposed network capacity model incorporated with parking strategies, we analyze the effect of parking supply and parking pricing on the network-wide capacity . With the same parking pricing strategy, the effect of the parking supply on the network-wide capacity is analyzed. Compared with the base scenario, the total network capacity is increased from 198.46 to 221.87. Expanding the parking supply at such destination areas can effectively enhance the network-wide capacity. Expanding the capacities on the other destinations will have a small effect on the network-wide capacity
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