MK
M.J. Knöll
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A Matter of Time
Development of an Indicator Framework to Evaluate Schedule Alignment with Passenger-Desired Arrival Times in Public Transport Networks
Public transport timetables are frequently redeveloped to fit within operational, structural and contractual constraints. In specific, passenger-oriented timetables are usually evaluated with a special focus on travel time, waiting time, transfers, reliability and fare cost. However, there are activities in people’s daily lives that have a fixed and recurring start time. This means that individual passengers care about the time they arrive at a specific location.
Therefore, a public transport service can perform well according conventional measures, while still not accommodating a passenger’s ideal arrival time. This is specifically important for locations to which many users converge, resulting in recurring schedules (e.g. schools, higher education institutions, shift-based work places, transport hubs). Despite these ideal arrival times, existing timetable design and evaluation methods do not consider passenger-oriented synchronization. Rather, they predominantly focus on time durations, reliability, or transfer synchronization. Hence, this thesis aims to develop a generic schedule alignment indicator framework. This framework evaluates how well scheduled vehicles align with passenger-desired arrival time window at relevant activity locations. To obtain this goal, the concepts of schedule delay (i.e. the divergence between desired and actual arrival times) are operationalized to be used in an applied public transport context.
The main research question that governs this process is: What constitutes a generic evaluation framework to evaluate timetable quality with respect to passenger-desired arrival times at activity locations?
The framework utilizes different stages to convert data inputs into a measurable timetable indicator. First, relevant activity locations are selected by connecting them to nearby stops using walking accessibility, and analyzing the demand of those stops. Then, their relevance is determined using the total amount of location users, combined with the mode share of public transport. When it comes to the construction of the desired arrival time windows, activity start times need to be obtained or estimated. In order to construct a window, the earliest, ideal, and latest arrival moment are defined relative to the activity start time. From these points, a triangular scoring function is constructed, with a score of 1 at the ideal moment and 0 at/outside the boundaries of the window. The arrival windows are transferred to the public transport stops using estimated egress times. To evaluate a timetable, the scheduled arrival times are scored using the scoring functions. With an impact-based weight, different score aggregations can be done according to the desired insights (e.g. on stop, route or network-wide level). In case of data unavailabilities, the framework relies on fallback methods to change individual steps in a modular way.
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Therefore, a public transport service can perform well according conventional measures, while still not accommodating a passenger’s ideal arrival time. This is specifically important for locations to which many users converge, resulting in recurring schedules (e.g. schools, higher education institutions, shift-based work places, transport hubs). Despite these ideal arrival times, existing timetable design and evaluation methods do not consider passenger-oriented synchronization. Rather, they predominantly focus on time durations, reliability, or transfer synchronization. Hence, this thesis aims to develop a generic schedule alignment indicator framework. This framework evaluates how well scheduled vehicles align with passenger-desired arrival time window at relevant activity locations. To obtain this goal, the concepts of schedule delay (i.e. the divergence between desired and actual arrival times) are operationalized to be used in an applied public transport context.
The main research question that governs this process is: What constitutes a generic evaluation framework to evaluate timetable quality with respect to passenger-desired arrival times at activity locations?
The framework utilizes different stages to convert data inputs into a measurable timetable indicator. First, relevant activity locations are selected by connecting them to nearby stops using walking accessibility, and analyzing the demand of those stops. Then, their relevance is determined using the total amount of location users, combined with the mode share of public transport. When it comes to the construction of the desired arrival time windows, activity start times need to be obtained or estimated. In order to construct a window, the earliest, ideal, and latest arrival moment are defined relative to the activity start time. From these points, a triangular scoring function is constructed, with a score of 1 at the ideal moment and 0 at/outside the boundaries of the window. The arrival windows are transferred to the public transport stops using estimated egress times. To evaluate a timetable, the scheduled arrival times are scored using the scoring functions. With an impact-based weight, different score aggregations can be done according to the desired insights (e.g. on stop, route or network-wide level). In case of data unavailabilities, the framework relies on fallback methods to change individual steps in a modular way.
...
Public transport timetables are frequently redeveloped to fit within operational, structural and contractual constraints. In specific, passenger-oriented timetables are usually evaluated with a special focus on travel time, waiting time, transfers, reliability and fare cost. However, there are activities in people’s daily lives that have a fixed and recurring start time. This means that individual passengers care about the time they arrive at a specific location.
Therefore, a public transport service can perform well according conventional measures, while still not accommodating a passenger’s ideal arrival time. This is specifically important for locations to which many users converge, resulting in recurring schedules (e.g. schools, higher education institutions, shift-based work places, transport hubs). Despite these ideal arrival times, existing timetable design and evaluation methods do not consider passenger-oriented synchronization. Rather, they predominantly focus on time durations, reliability, or transfer synchronization. Hence, this thesis aims to develop a generic schedule alignment indicator framework. This framework evaluates how well scheduled vehicles align with passenger-desired arrival time window at relevant activity locations. To obtain this goal, the concepts of schedule delay (i.e. the divergence between desired and actual arrival times) are operationalized to be used in an applied public transport context.
The main research question that governs this process is: What constitutes a generic evaluation framework to evaluate timetable quality with respect to passenger-desired arrival times at activity locations?
The framework utilizes different stages to convert data inputs into a measurable timetable indicator. First, relevant activity locations are selected by connecting them to nearby stops using walking accessibility, and analyzing the demand of those stops. Then, their relevance is determined using the total amount of location users, combined with the mode share of public transport. When it comes to the construction of the desired arrival time windows, activity start times need to be obtained or estimated. In order to construct a window, the earliest, ideal, and latest arrival moment are defined relative to the activity start time. From these points, a triangular scoring function is constructed, with a score of 1 at the ideal moment and 0 at/outside the boundaries of the window. The arrival windows are transferred to the public transport stops using estimated egress times. To evaluate a timetable, the scheduled arrival times are scored using the scoring functions. With an impact-based weight, different score aggregations can be done according to the desired insights (e.g. on stop, route or network-wide level). In case of data unavailabilities, the framework relies on fallback methods to change individual steps in a modular way.
Therefore, a public transport service can perform well according conventional measures, while still not accommodating a passenger’s ideal arrival time. This is specifically important for locations to which many users converge, resulting in recurring schedules (e.g. schools, higher education institutions, shift-based work places, transport hubs). Despite these ideal arrival times, existing timetable design and evaluation methods do not consider passenger-oriented synchronization. Rather, they predominantly focus on time durations, reliability, or transfer synchronization. Hence, this thesis aims to develop a generic schedule alignment indicator framework. This framework evaluates how well scheduled vehicles align with passenger-desired arrival time window at relevant activity locations. To obtain this goal, the concepts of schedule delay (i.e. the divergence between desired and actual arrival times) are operationalized to be used in an applied public transport context.
The main research question that governs this process is: What constitutes a generic evaluation framework to evaluate timetable quality with respect to passenger-desired arrival times at activity locations?
The framework utilizes different stages to convert data inputs into a measurable timetable indicator. First, relevant activity locations are selected by connecting them to nearby stops using walking accessibility, and analyzing the demand of those stops. Then, their relevance is determined using the total amount of location users, combined with the mode share of public transport. When it comes to the construction of the desired arrival time windows, activity start times need to be obtained or estimated. In order to construct a window, the earliest, ideal, and latest arrival moment are defined relative to the activity start time. From these points, a triangular scoring function is constructed, with a score of 1 at the ideal moment and 0 at/outside the boundaries of the window. The arrival windows are transferred to the public transport stops using estimated egress times. To evaluate a timetable, the scheduled arrival times are scored using the scoring functions. With an impact-based weight, different score aggregations can be done according to the desired insights (e.g. on stop, route or network-wide level). In case of data unavailabilities, the framework relies on fallback methods to change individual steps in a modular way.