Feasibility Study: Al-based Passenger Counting System for Public Transit

This thesis is dedicated to the subject of artificial intelligence and how it might contribute to public transport. Thereby, AI based object recognition for counting passengers in public transport shall be applied and compared with the existing infrared counting technology.

Peraic Martin Hrvoje, 2019

Bachelor Thesis, Basler Verkehrs-Betriebe
Betreuende Dozierende: Stephan Jüngling
Keywords: AI, deep learning, computer vision, automated passenger counting system, public transportation, feasibility study, mobileSDD, Google Coral, Edge Device Computing, TNW,
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Over 350 000 passengers are transported daily by the Basler Verkehrs-Betriebe. Many of these passengers hold a season ticket, which is offered by the Tarifverbund Nordwerstschweiz (TNW). The TNW compensates all public transport providers based on the number of passengers transported. Therefore, all operators must provide verifiable passenger counts. Recent breakthroughs in AI based object recognition enable reliable real-time object detection. Combined with a tracking, the aim is to determine whether this technology can be used to count passengers in public transport.
Various edge devices optimized for AI were evaluated for the development of a stand-alone prototype. Object recognition and tracking algorithms were studied. In this respect, already documented implementations were reviewed. The knowledge acquired was later applied for the development of the prototype. After completion of an executable prototype, various experiments to compare both systems were conducted in a laboratory environment. Finally, the total costs of both systems were assessed. For this purpose, active contracts of the supplier were studied and analyzed.
This thesis enabled the client to gain initial experience in the field of artificial intelligence. Algorithms for the recognition and tracking of objects, both proven and new, form the central area of interest. Subsequently, the knowledge acquired was applied for the development of an AI-based passenger counting system. Thereby it became obvious that for the adaptation of such AI-based systems a reorganization of the IT must first take place. New methodologies that allow fast and efficient operation must be established and applied. Thus, potential challenges during development and implementation can be efficiently handled. During a laboratory experiment, the developed system was compared with the existing infrared technology. It became apparent that AI-based passenger counting is feasible although it does not yet pose a competition for the existing solution. Additionally, the experiments revealed potential weaknesses of the current infrared system, which were handed over to the customer for further investigation. Finally, the comparisons in investment and maintenance costs highlighted the potential cost savings by switching to AI-based passenger counting.
Studiengang: Business Information Technology (Bachelor)
Fachbereich der Arbeit: Andere
Vertraulichkeit: öffentlich
Art der Arbeit
Bachelor Thesis
Basler Verkehrs-Betriebe, Basel
Autorinnen und Autoren
Peraic Martin Hrvoje
Betreuende Dozierende
Stephan Jüngling
Sprache der Arbeit
Business Information Technology (Bachelor)
Standort Studiengang
AI, deep learning, computer vision, automated passenger counting system, public transportation, feasibility study, mobileSDD, Google Coral, Edge Device Computing, TNW,