"PhD Modeling and Simulation of Mass Cycling Dynamics for Sustainable Cities"

PhD Modeling and Simulation of Mass Cycling Dynamics for Sustainable Cities

100%, Zurich, fixed-term

The Traffic Engineering group (SVT) of the Institute for Transport Planning and Systems (IVT) at ETH Zurich intends to develop scalable optimization systems for operational support in large-scale road networks. Modeling and simulation are powerful tools for the development and validation of traffic management and control strategies in urban and freeway environments. At the same time, data-driven methodologies and machine learning offer new opportunities for optimal traffic management strategies but often they lack physical intuition, which creates obstacles towards large-scale deployment and public acceptability.

Project background

The average trip length in Swiss cities is under 14km, with around 60% of trips below 6km. Despite the potential for healthier, more sustainable alternatives, nearly half of the total distance traveled is by car (BFS & ARE 2023). Bicycles play a key role in recent initiatives (e.g., EBike-City, ETH Zurich) aimed at building sustainable, vibrant future cities. However, bicycles are still seen by transportation experts and users as a complementary mode to cars. There is limited understanding of how mass cycling impacts traffic efficiency and transport operations due to several reasons:

• Insufficient infrastructure capacity for bicycles to be a primary mode for short and medium distances.
• Lack of real-world observations to reveal cyclists’ behavior, i.e., lateral and longitudinal dynamics, safety perception, reaction time, anticipation, and decision-making.
• Absence of comprehensive simulation frameworks with realistic models to provide quantifiable data on generalized studies on cycling path capacity, reductions in emissions noise and congestion as well as feasibility for mixed traffic (cars and bicycles).

This project will use experimental observations with a large number of cyclists in order to understand and model their moving behavior (lateral and longitudinal), their interactions (conflicts and cooperations), and their traffic flow characteristics (capacity, safety, efficiency). Within the project, a Model Suite will be developed with an API that can communicate with major simulation software such as SUMO, Aimsun, and Vissim, to enable large-scale mass cycling simulations. Extensive simulations will be conducted in order to understand multimodal traffic dynamics and propose novel solutions toward future sustainable cities.

Job description

The doctoral researcher is expected to conduct research in the following areas:

• Traffic modeling and simulation
• Multimodality
• Adaptive infrastructure
• Traffic management and control

The applicant is expected to:

• Publish in top journals and scientific conferences
• Participate in research proposal preparation
• Guide/follow semester projects at BSc/MSc level
• Teach within the SVT course programme
• Contribute to the operation of the group and the Institute

Profile

You ideally have a Master’s degree in engineering, mathematics, computer science, or related fields. You are highly motivated, determined, and have excellent communication and writing skills (proficient spoken and written English is required).

Moreover, the following skills are expected of a promising candidate:

• Strong background in applied mathematics and data analysis
• Interest in traffic modeling and simulation
• Strong experience with programming
• Team working and communication skills. Knowledge of the German language is a plus.

Workplace

We offer

You enjoy working in an interactive international environment with other doctoral students, post-docs, and senior scientists, referring continuously to practical problems and solutions. You have a keen interest in traffic engineering. This position will be available as of March 2025 or upon agreement.

ETH Zurich is a family-friendly employer with excellent working conditions. You can look forward to an exciting working environment, cultural diversity, and attractive offers and benefits.

Please note that we exclusively accept applications submitted through our online application portal.

Working, teaching and research at ETH Zurich

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