Master Thesis: Statistical Modeling of Simulation Data to...

Are you looking for an opportunity to influence the future of transportation systems and automated vehicle technologies? 

This thesis offers you the opportunity to engage in cutting-edge research that combines data analytics, simulation, and visualization to address real-world challenges in traffic management and automated system.

Background

An Automated Guided Vehicle (AGV) system is a fleet of mobile robots that automatically transport goods in a network of fixed virtual roads, designed according to the specification of the warehouse. Understanding traffic congestion dynamics is crucial for optimizing AGV operations and improving overall system efficiency. By understanding and characterizing congestion dynamics, we can pinpoints areas of improvement and develop strategies to enhance traffic flow within AGV networks.

Goal of the thesis

This thesis aims to develop a robust statistical model capable of providing detailed predictions and insights into traffic congestion, and to gain an enhanced understanding of traffic management effectiveness, contributing to future improvements in AGV systems and simulation techniques.

Method

• Model Development: Build statistical models, potentially including estimating conditional probabilities and performing cross-correlation analysis, that describes how traffic demand translates into congestion based on the specific characteristics of the road network and traffic rules.
• Data Enhancement: Advance the data extraction methods established in the bachelor thesis to include more complex, event-driven data collection techniques. This will enable a deeper analysis of congestion states and their triggers over time.
• Model Validation and Analysis: Test the model's predictive accuracy against historical simulation data and refine it based on iterative feedback to ensure it generalizes well across various traffic scenarios.
• Visualization and User Interaction: Develop advanced visualization tools to illustrate both the model’s predictions and actual traffic flows, enhancing spatial-temporal understanding of congestion. Additionally, create an interactive interface for simulation operators to engage with the model’s outputs.

About you

• Have a strong background in statistics, data science, or machine learning;
• Want to apply your knowledge to solve real-world problems in traffic management;
• Are enthusiastic about contributing to significant advancements in the field of simulation and are keen to develop practical, impactful solutions. 

Number of students

2

Thesis Level

Master

Language

Thesis is to be written in English

Starting date

August 2024

Location

Kollmorgen Automation Office in Mölndal, Sweden

Additional information

We will provide computers and you will get great support from your supervisor and other colleagues!

All students are compensated after the thesis is submitted and the final work meets the quality standard that is generally accepted by the university and presented at Kollmorgen.

Send in your application by submitting a CV and/or information about your studies and a short sentence about why you find this project interesting. If you get selected, the next step will be to have discussions with us to finalize the idea . Selection takes place on an ongoing basis, welcome with your application!

Some of the good things we offer

• Innovation Days every twelve weeks - a 24-hour event for the whole company to dig deeper, explore new areas and solve problems!
  
• Gym at the office filled with machines for strength and fitness that is always open and free to use when you need a break in your thesis work
  
• A bicycle storage and free car parking outside our office
  
• Participate in our events such as monthly breakfast meetings, Day of Caring (every year we take one day to clean the west coast beaches together) etc
  
• Good fair trade coffee (or tea) with fresh milk (every student who has been up late to study for an exam know how important coffee is) ☕
  
• Fresh fruit if you get hungry

Contact Information

If you have any questions about the thesis, you are welcome to contact

Check out more open positions ,
ℹ️ follow us on Facebook ,
get to know us better through our Candidate Blog ,
️ and see videos about our products at our YouTube channel!