Pairing, or bunching, of vehicles on a public transportation line influences the adaptive choice at stops due to the random headways and waiting times it determines. In order to ensure consistency with the characteristics of service perturbations, as represented by a transit operation model, it is important to identify the headway distributions representing service perturbations. A stochastic simulation model is developed for a one-way transit line, which accounts for several service characteristics (dwell time at stops, capacity constraint and arrivals during the dwell time). Samples of headways at the main stops are utilized to build histograms of the headway’s frequencies by their length, which allow to identify the functional forms and parameters of the headway distributions. For these stops, density plots of consecutive headways are also produced. Sensitivity analysis is carried out to identify the effect of key parameters (dispatching headway, maximum load and running time).
Transit vehicles’ headway distribution and service irregularity / Bellei, G; Gkoumas, Konstantinos. - In: PUBLIC TRANSPORT. - ISSN 1866-749X. - STAMPA. - 2:(2010), pp. 269-289. [10.1007/s12469-010-0024-7]
Transit vehicles’ headway distribution and service irregularity
GKOUMAS, Konstantinos
2010
Abstract
Pairing, or bunching, of vehicles on a public transportation line influences the adaptive choice at stops due to the random headways and waiting times it determines. In order to ensure consistency with the characteristics of service perturbations, as represented by a transit operation model, it is important to identify the headway distributions representing service perturbations. A stochastic simulation model is developed for a one-way transit line, which accounts for several service characteristics (dwell time at stops, capacity constraint and arrivals during the dwell time). Samples of headways at the main stops are utilized to build histograms of the headway’s frequencies by their length, which allow to identify the functional forms and parameters of the headway distributions. For these stops, density plots of consecutive headways are also produced. Sensitivity analysis is carried out to identify the effect of key parameters (dispatching headway, maximum load and running time).I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.