Master Thesis: Statistical Modeling of Simulation Data to Characterize Traffic Congestion in AGV Systems
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
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- Departments
- Engineering
- Locations
- Gothenburg
- Remote status
- Hybrid Remote
Gothenburg
Some of the good things that 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 for all our employees 👟 -
6 weeks’ vacation! ☀️❄️
-
Work time reduction
It gives you around 7 extra days off per year 👍 -
Free parking outside our office
There are many available parking lots 🚗, and also charging stations for you who drive an electric car 🔌 -
Home office equipment
... like an office chair, extra screens and more to give you good ergonomics and working conditions also when working from home. You will get a pair of noise cancelling headphones together with a work computer, computer bag and phone 🎧💻 -
Career opportunities within the company
We have employees who have worked with us for many years in different roles and departments 🚀 -
Day of Caring
Every year we take one day to clean the west coast beaches together 🗑️ -
Collective agreement, occupational pension, wellness allowance
Workplace & Culture
Our culture defines who we are. Our people, our behavior and our relationships are at the core of everything we do. We are convinced that a strong, positive, and open culture is what leverages the success of our vision & mission.
About Kollmorgen Automation AB
We are developing software for Automated Guided Vehicles (AGVs) and mobile robots. Our leading technology enables the AGVs to operate smarter, safer and more efficiently. Kollmorgen is a global company and the AGV team is based in Mölndal, Sweden.
The majority of our engineers work with software development and test but there are also hardware engineers, application engineers and UX designers.
Together we develop NDC Solutions which includes everything you need for excellent control of Automated Guided Vehicles (AGVs).
Master Thesis: Statistical Modeling of Simulation Data to Characterize Traffic Congestion in AGV Systems
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