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Passenger behavior analysis on the basis of digital data provides an opportunity to improve the quality of transport services

Public transport has long been more than just a service - it is the face of modern cities, and the variety of mobility options is increasingly becoming a field for experimentation and innovation. Behind the visible part of this system, however, there is a significant amount of information, research and rules that allow the transport system to be structured in a way that satisfies its users.

The answer to the questions "Does the public transport currently meet the needs of passengers?" And "How could the available services be improved in the future?" lies in the behavior of the users. In this regard, the INNOAIR project partners from Plovdiv University "Paisii Hilendarski" conducted an "Passenger behavior analysis" towards existing services and opportunities to reflect it in the process of improving urban transport.

“A passenger behavior is the way that passenger think, feel, reason, make judgement and select different products and services, directly related to their travel.” All these components can be taken into account in the analysis of passenger behavior. As structured data can be used in a very large number of models, the analysis of Plovdiv University is based mainly on digital information available from historical databases and time series for the location of transport (GPS information), as well as ticket sales (information about tickets, as well as the preferred type of tickets).

The study combines information from different sources - data on the location of individual vehicles, preliminary schedules, traffic and passenger traffic at stops and time zones, analysis of traffic and congestion to provide integrated measures of the quality of services provided. Tracking these indicators and complying them with the schedules and timetables of urban transport is an opportunity to adapt the transport to the requirements of users and to better meet their needs. An important feature of the approach used is that each of the indicators changes according to the dynamic urban environment. This means that the dynamics of the selected indicators is as important as their absolute values, because it allows to act proactively and potential problems to be solved prematurely.

The passengers behaviour anlaysis shows that they have the greatest need for reliability and security when choosing transport. Uncertainty about the time of arrival, departure and duration of travel on the vehicle causes users to feel anxious.

A specific problem addressed in the study is the modeling of urban transport delays. The use of random processes that allow abrupt changes in the observed values allows to cover the critical cases in which due to unexpected events, such as accidents, incidents or sudden changes in traffic, the discrepancies with the preliminary schedule are drastically increased. The obtained models allow to identify the critical sections on the individual routes and to take preventive measures in cases when the probability of the next big delay increases. In addition, follow-up reactions help to accumulate information and enrich the models and allow for overall optimization of transport schemes.

The results of the analysis will contribute to the decision-making on the introduction of "on-demand green public transportation" and to the testing of the "congestion" charge model - measures that aim to improve air quality and will be implemented within the INNOAIR project.

The full analysis can be found in English here.

INNOAIR project is co-financed by the European Regional Development Fund through the Urban Innovative Actions Initiative.

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