Capacity Constrained Accessibility

This study proposes an enhanced measure of accessibility which explicitly takes into consideration circumstances when the capacity of the transport infrastructure or service, e.g. public transit, is limited. When capacity is constrained, passengers may suffer longer waiting time, resulting in delay or cancellation of the trips. To define and measure the accessibility with capacity constraints, the authors introduce a new approach to estimate the expected waiting time and the probability of forgoing trips, based on M/G B /1 type of queuing scenario and discrete event simulation. The impacts of capacity constraints are then formally incorporated into the new accessibility measure: Capacity Constrained Accessibility (CCA). To illustrate the differences between CCA and standard measure, this study estimates the accessibility patterns in the Beijing-Tianjin (China) corridor and the accessibility changes thanks to the Beijing-Tianjin Intercity High-speed Railway (BTIHSR). The authors simulate and compare CCA and standard measures in five queuing scenarios with varying assumptions of passenger arrival distributions, train service distributions, and system loads. The results show that 1) under a quasi-real peak-hour conditions between Beijing and Tianjin, CCA is 97.3% of the standard measure; 2) under low demand condition, CCA is equal to the standard measure—CCA is compatible with and absorbs stand measure as a special case; 3) under the scenario with very high demand and unreliable timetable, CCA is almost reduced to the level before BTIHSR, i.e. the contribution of the new infrastructure to accessibility is mostly eliminated. The authors conclude that without considering capacity constraint, standard accessibility measure overestimates the contribution of new infrastructure or service; the new CCA measure effectively incorporates the impact of capacity constraints and provides a more realistic representation than standard measure.