Holding Control Model for Real-Time Connection Protection
Eui-Hwan Chung, Amer Shalaby
Abstract
Eui-Hwan Chung, Amer Shalaby
Abstract
Transfer time is one of the most significant components of transit travel from the perspective of passengers. Even though transit agencies may have well-coordinated timetables among intersecting lines, an operational control method is necessary to maintain the coordinated transfers which may occasionally be disrupted due to unexpected delays of transit vehicles. One possible approach is Connection Protection (CP) through holding strategies. It involves holding a transit unit in order to wait for another transit unit that is planned to provide a coordinated transfer but has been delayed. This study develops a CP model to apply holding control to a receiving trip in order to protect the scheduled connection against delay of a feeder trip. The study incorporates the probabilistic nature of transit operations in formulating the cost function of the model, and accordingly makes more robust decisions for control. The developed model is evaluated based on a sensitivity analysis. The results show that the model improves transfer efficiency and reduces the waiting times of affected passengers.
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Transfer time is one of the most significant components of transit travel from the perspective of passengers. Even though transit agencies may have well-coordinated timetables among intersecting lines, an operational control method is necessary to maintain the coordinated transfers which may occasionally be disrupted due to unexpected delays of transit vehicles. One possible approach is Connection Protection (CP) through holding strategies. It involves holding a transit unit in order to wait for another transit unit that is planned to provide a coordinated transfer but has been delayed. This study develops a CP model to apply holding control to a receiving trip in order to protect the scheduled connection against delay of a feeder trip. The study incorporates the probabilistic nature of transit operations in formulating the cost function of the model, and accordingly makes more robust decisions for control. The developed model is evaluated based on a sensitivity analysis. The results show that the model improves transfer efficiency and reduces the waiting times of affected passengers.
Key concepts: Transit (satellite), Transfer (computing), Control (management), Sensitivity (control systems), Probabilistic logic, Order (exchange), Computer science, Operations research