Highlights The quantity, location and signalization of pedestrian crosswalk network are optimized simultaneously. Pedestrian and vehicle cost are integrated in a multi-objective optimization framework. More crosswalks may not contribute much additional improvement in pedestrian crossing cost under some conditions. Two-stage crosswalks are more favorable than one-stage ones for both pedestrian and vehicles.
Abstract In many cases, pedestrian crossing demands are distributed discretely along an arterial segment. Demand origins, destinations and crosswalks comprise a pedestrian crossing network. An integrated model for optimizing the quantity, locations and signal settings of mid-block crosswalks simultaneously is proposed to best trade-off the operational performances between pedestrians and vehicles. Pedestrian behavior of choosing crosswalks is captured under a discrete demand distribution. Detour distance and delay at signalized crosswalks are formulated as a measure of pedestrian crossing cost. Maximum bandwidths are modeled in analytical expressions as a measure of vehicular cost. To solve the proposed model, the Non-dominated Sorting Genetic Algorithm II (NSGA II) based algorithm is designed and employed to obtain the Pareto frontier efficiently. From the numerical study, it is found that there exists an optimal number of mid-block crosswalks. Excess available crosswalks may make no contributions to improvement in pedestrian cost when the constraint of the minimum interval between crosswalks and vehicular cost are taken into account. Two-stage crosswalks are more favorable than one-stage ones for the benefits of both pedestrian and vehicles. The study results show promising properties of the proposed method to assist transportation engineers in properly designing mid-block crosswalks along a road segment.
Optimization of mid-block pedestrian crossing network with discrete demands
Transportation Research Part B: Methodological ; 73 ; 103-121
2014-12-18
19 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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