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Project Description

Autonomous and advanced driver assistance systems benefit from anticipating attainable longitudinal and lateral acceleration to plan safe maneuvers in dynamic environments. Short‑horizon capability prediction complements trajectory forecasting by limiting planning to what the vehicle can achieve given current state and actuator limits. When towing a trailer, combined-system dynamics and hitch interactions narrow feasible envelopes, increasing the need for predictive safety margins in evasive and stability‑critical maneuvers.

A generic abstraction that elevates individual actuator capabilities to vehicle-level capability can provide clear constraints for prediction modules and downstream planning. This capability-aware prediction aligns with industry efforts to improve safety, robustness, and deployment efficiency in automated driving.

Scope

This thesis develops a generic method that abstracts actuator capabilities (e.g., braking, propulsion, steering) into vehicle-level constraints and predicts a forward capability envelope over a short horizon for vehicles and vehicle–trailer combinations. It focuses on formulation, modular software prototyping, and comparative evaluations. Development and validation occur in a simulation environment.

Objectives

• Define a vehicle-level capability envelope for near-term maneuvering that captures attainable longitudinal and lateral acceleration given current state and actuator limits.
• Extend the representation to vehicle–trailer combinations with minimal added parameters, preserving a modular abstraction boundary.
• Develop a prediction method, mapping estimated actuator capabilities to a forward envelope over a finite horizon with uncertainty awareness.
• Implement a generic software prototype with clear inputs and outputs for integration with planning stacks.

Expected Outcomes

• A conceptual framework and notation for capability envelopes unifying solo vehicle and vehicle–trailer use cases for short-horizon prediction.
• A generic algorithm that lifts actuator-level constraints to vehicle-level capability and forecasts a horizon-based envelope with uncertainty.
• A reference implementation and evaluation on representative scenarios illustrating safety-critical benefits for evasive maneuvers

Your skills and background

• Master’s degree in Automotive Engineering, Control Systems, or Electrical Engineering.
• Strong background in Vehicle Dynamics and Control Systems
• Strong programming skills in Python and MATLAB/Simulink
• Experience with Simulation Environments such as MATLAB/Simulink, CarMaker, or Driving Simulators.
• Knowledge of actuator systems (brakes, propulsion, steering) and basic stability control strategies and their vehicle‑level effects.
• Experience with or understanding of trailer dynamics and combined vehicle–trailer behavior is advantageous.
• Strong analytical and problem‑solving skills

This thesis project is for 2 students who together need to have the required skills and background. Applicants may specify a preferred partner in their cover letter.

Why you should join Zeekr Tech Eu

We are engineers, developers, and innovators from around the world. Joined together by entrepreneurship, our unique blend of global culture, and a belief in a smarter more sustainable future. At Zeekr Tech Eu we fast-track innovation and transform ideas into pioneering technology solutions, doing your master thesis here is no different. We are convinced that a thesis project is a major contribution to our innovation capabilities and long-term development. You'll have a great opportunity to use your skills and creativity to push the boundaries of what´s possible.

What happens when you apply
If this sounds interesting and you match the requirements, please don't hesitate to submit your application with a CV and cover letter. Shortlisted candidates will be contacted for an interview to further discuss the project's details and expectations. 

Supervisor: Karthik Prasad, Expert Motion Systems, karthik.prasad@zeekrtech.eu, please contact for more information about the project

Starting date: January 2026

Last application date: 2025-11-04

Apply today. We will perform ongoing selection during the application period. We look forward to hearing from you!

Please note that due to GDPR regulations, we can only accept applications sent through the recruitment system, not via email or other channels.