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Optimization of public transport route assignment via travel time reliability
Besides the impacts and importance in planning transportation networks, travel time reliability (TTR) is increasingly becoming a driving factor for commuting patterns. However, the implementation of TTR in route assignment is still not very common due to the discrete nature of scheduled services. Within day dynamics are usually modelled depending on various service characteristic factors such as regularity, frequency and information. However, in this research, frequency and regularity related factors were of prime focus to find the parameters and their values that can represent TTR in impedance functions to evaluate their impingements in public transport route assignment models. Perceived journey time (PJT) was optimized based on deterministic dynamic network model optimization for various TTR parameters based on data available for the city of Halle and later confirmed via simulative modelling in PTV Visum. Four different scenarios were generated in scenario management for each PJT value deduced from the Poisson parameter value in the optimization model. Comparison of these scenarios based on optimally decided penalties with the base scenario without TTR identified the most reliable lines. An appreciable change in journey times had been noticed depicting the strong effect of TTR in route assignment. Results obtained can pave way for developers to introduce a smart feature of choosing a reliable travel option in journey planners instead of the shortest one and for planners to evaluate large city models.
Optimization of public transport route assignment via travel time reliability
Besides the impacts and importance in planning transportation networks, travel time reliability (TTR) is increasingly becoming a driving factor for commuting patterns. However, the implementation of TTR in route assignment is still not very common due to the discrete nature of scheduled services. Within day dynamics are usually modelled depending on various service characteristic factors such as regularity, frequency and information. However, in this research, frequency and regularity related factors were of prime focus to find the parameters and their values that can represent TTR in impedance functions to evaluate their impingements in public transport route assignment models. Perceived journey time (PJT) was optimized based on deterministic dynamic network model optimization for various TTR parameters based on data available for the city of Halle and later confirmed via simulative modelling in PTV Visum. Four different scenarios were generated in scenario management for each PJT value deduced from the Poisson parameter value in the optimization model. Comparison of these scenarios based on optimally decided penalties with the base scenario without TTR identified the most reliable lines. An appreciable change in journey times had been noticed depicting the strong effect of TTR in route assignment. Results obtained can pave way for developers to introduce a smart feature of choosing a reliable travel option in journey planners instead of the shortest one and for planners to evaluate large city models.
Optimization of public transport route assignment via travel time reliability
Bilal, Muhammad Tabish (author) / Sarwar, Samra (author) / Giglio, Davide (author)
2021-06-16
2345644 byte
Conference paper
Electronic Resource
English
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