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Technical University of Munich
Technical University of Munich

Open PhD Position - DFG Project: Value of Time estimation considering Automated Vehicle Impacts (VOTAVI) (TSE 128)

Description of the Chair

The Chair of Transportation Systems Engineering (TSE) undertakes research in the transportation field with a specific focus on modeling and simulating transportation systems, implementing data science and data analytics in transport and human factors analysis, and machine learning and deep learning. The TSE chair researches multimodal and unimodal freight and passenger transport demand and supply modeling, allowing for contributions to the optimization, calibration, and validation of transport models. In this direction, the application of big data acquisition and analysis and the use of flexible data-driven models are examined. The TSE chair also contributes to analyzing human factors in transport-related fields such as road safety modeling, behavioral economics applications, and modeling of factors that affect user engagement in transportation systems. 

Project description

The value of travel time (VOT) is crucial in various areas, such as travel demand modeling, transport policy, and investment evaluation. VOT is influenced by factors like trip purpose, transport mode, and distance traveled, allowing for a more accurate assessment of cost-benefit analyses. The emergence of autonomous modes, like autonomous vehicles (AVs) and Urban Air Mobility (UAM), has transformed the perception of VOT. AVs enable individuals to engage in various tasks while traveling, prompting new challenges in VOT estimation and attracting increased research attention. 

 

Traditional travel surveys used surveys and data loggers, later transitioning to smartphone apps for digital travel surveys. These apps offer advantages like high user penetration and extensive data collection. However, challenges remain, including limited use of Stated Preference (SP) surveys for individual trips. The VOTAVI project aims to address these challenges by developing an innovative smartphone app for joint Revealed Preference (RP)/ Stated Preference (SP) surveys in the Autonomous Vehicle era, contributing to improved user preference inference and unbiased Value of Time estimation. The app will be developed using the MotionTag SDK: https://api.motion-tag.de/developer/ios. 

Requirements

  • Have an MSc degree in a relevant field (e.g., transportation engineering, data science, computer science). 

  • Be enthusiastic about researching transport-related projects -- understanding the fundamentals of transportation systems and modelling will be a plus. 

  • Have strong analytical skills. 

  • Have excellent research, academic writing, and presentation skills. 

  • Experience in Swift and CocoaPods is considered a plus. 

  • A desire to write understandable and robust code.

  • Knowledge in building SDKs / Apps.

  • Professional proficiency in English.

  • Knowledge of the German language will be considered a plus.

  • Driven, reliable, good level of self-organization, team player! 

  • Knowledge of machine learning is a plus. 

In addition to the above, candidates must fulfill the general TUM admission requirements: https://www.gs.tum.de/en/gs/applicants/application/requirements/ 

Conditions of Employment

Following the Public Sector Collective Agreement of Länder (TV-L), TUM offers a competitive compensation package. This position is a 100% TV-L 13. More information on the offered wages can be found at https://oeffentlicher-dienst.info/tv-l/allg/.

TUM is an equal-opportunity employer. Qualified women are particularly encouraged to apply. Applicants with disabilities are treated with preference, given comparable qualifications. 

Application

Interested applicants who fit the requirements of the position are asked to send the following to apply.vvs@ed.tum.de: 

• A curriculum vitae 

• Academic transcripts 

• A motivation letter 

• The names and contact information of three references

 

Please include the position ID ([TSE_128]) and your name in the email subject. Review of applications will begin immediately and continue until the position is filled.

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