Master's Thesis: Real-Time Traffic

Vor 4 Tagen

Innere Stadt Vienna, Österreich Kapsch Group Vollzeit

Kapsch is one of Austria's most successful global technology companies. With its comprehensive ITS (Intelligent Transportation Systems) portfolio, Kapsch is actively addressing the challenges of the present and the future with intelligent mobility solutions in a wide range of application areas. As a family-owned company founded in 1892 and headquartered in Vienna, Kapsch can look back on 130 years of experience with the future.

Title:
Real-Time Web-Based Visualization of Vehicle and Pedestrian Detections with Trajectories on a Map Overlay

Introduction:
The increasing deployment of deep learning-based detection systems in urban environments necessitates efficient and scalable visualization solutions for vehicle and pedestrian detections. This thesis aims to develop a web-based application that visualizes real-time traffic participant detections and trajectories on a street or satellite map. The system will overlay detected positions, classifications (e.g., car, truck, bus, pedestrian, bicyclist), and trajectories on a bird's-eye or isometric view map. A key focus will be on identifying suitable map providers and visualization technologies, ensuring high performance and scalability. A prototype implementation will be developed and evaluated based on visualization efficiency, usability, and real-time performance.

Objectives

  • Literature Review: Research existing techniques for visualizing traffic data in real-time applications.
  • Technology Evaluation: Identify and compare suitable map providers (e.g., OpenStreetMap, Google Maps, Mapbox) and visualization technologies (e.g., WebGL, , ), along with GIS frameworks.
  • System Design: Develop a web-based architecture capable of handling large numbers of traffic participants in real time.
  • Prototype Implementation: Build a proof-of-concept application that ingests geolocation data and displays real-time detections and trajectories.
  • Performance Evaluation: Assess the system's performance in terms of rendering speed, accuracy, and scalability.

Your Profile

  • Required Background Studies in Computer Science, Software Engineering, Information Technology, Geoinformatics or related fields
  • Fluent English skills
  • Interest in technology
  • Willingness and ability to work independently
  • Excellent communication and teamwork skills
  • Conscientiousness and reliability
  • Strong analytical skills with a precise and structured approach
  • Start: Immediately
  • Duration: 3–6 months
  • Successful completion of the master's thesis will be rewarded with €3,000.

Contact
Edwin Frühwirth

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