Thesis Topics 2020/21

Master Theses:

Modal Split 

Discovering the share of different means of transport is an important component for developing sustainable transport system. In this thesis, the initial modal split model will be created using some stochastic data. Then, using online data (such as traffic count), the model will be calibrated  on short time intervals. 

This thesis topic is in collaboration with ITS Lab and Tartu City.

Contact: Kaveh Khoshkhah

Development of a driving cycle for urban buses in Tartu

In order to evaluate the performance and feasibility of a new powertrain, driving cycles has been widely applied to represent real driving conditions.  Since the driving behavior varies with the local conditions, typical driving cycles are needed considering local conditions, such as  weather, terrain, and traffic status. Based on the GPS data, a typical driving cycle for buses in Tartu will be developed.

This thesis topic is in collaboration with ITS Lab, Tartu City and OsloMet.

Contact: Amnir Hadachi

Feasibility analysis and optimal charging infrastructure placement strategy for city bus system electrification

Based on the GPS data of buses, the energy needed of each bus route under different weather can be derived. Therefore, the feasibility of different electric bus technologies should be analyzed. Considering the bus schedule and route-level energy consumption, optimal charging infrastructure placement and charging strategies should be developed considering battery life and lifecycle cost.

This thesis topic is in collaboration with ITS Lab, Tartu City and OsloMet.

Contact: Amnir Hadachi

State-full Masking of Dynamic Objects for Visual Simultaneous Localization and Mapping

Advancing in the direction of reducing the time complexity of masking the moving objects Visual SLAM input. It was proven in previous research MaskRCNN is accurate but can hardly achieve 10FPS.
Objective is to employ state estimation techniques to track the moving objects and update the masking information faster then actual detection rate.

Contact: Artjom Lind

Bachelor Theses:


Author: Mozhgan

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