Master Thesis Worker

Transport is at the core of modern society. Imagine using your expertise to shape sustainable transport and infrastructure solutions for the future. If you seek to make a difference on a global scale, working with next-gen technologies and the sharpest collaborative teams, then we could be a perfect match.

Master thesis proposal
How AEB systems make urban buses safer for passengers and vulnerable road users?

Problem Description
Buses are an essential means of urban transportation and are generally considered safe. However, crashes involving buses can cause severe injuries and fatalities to vulnerable road users (VRUs) such as pedestrians and cyclists. In order to protect VRUs, Advanced Driver Assistance Systems (ADAS) are being developed and introduced to the market. One of these ADAS, is an Automatic Emergency Braking (AEB) system that uses forward-facing sensors to detect potential collisions [1]. If a collision is imminent and the driver does not react, the system automatically applies the brakes to prevent or reduce the severity of the crash.

While effective in many scenarios, we do not, however, know the occurrence of false positives (FP) [2]. FPs are events where the system triggers unnecessary braking in response to, for example, harmless objects, ambiguous environmental cues, or newly emerging micromobility vehicles. Such false activations not only degrade drivers' trust and passenger comfort but can also lead to passenger injuries. Current safety performance assessments of these systems lack the inclusion of false positives especially in complex driving conditions. Accurate assessment is important to quantify the expected real-world benefit of these systems for passenger and VRU protection.

Objectives
This Thesis Aims To Develop And Evaluate Methods For Detecting False Positives In AEB Activation Using Real-world Driving Data That Includes Vehicle Kinematic Signals (speed, Acceleration, Yaw Rate), And Video Recordings From Forward- And Side-facing Cameras. The Objectives Are

• to propose a methodology for using ground truth data to detect FP that includes
• finding automatically flagged events where AEB is triggered
• reviewing, labeling, and classifying the events from the field data into FP
• quantifying FP braking rate
• to analyze patterns in FP AEB activations by correlating kinematic features, environment context and infrastructure
• to validate the proposed methods on a representative dataset of real-world driving scenarios, with quantitative evaluation of both safety (collision avoidance) and operational performance (false activation reduction).

Prerequisites: Python or Matlab.

Number of students: 1 ‐ 2.

Information And Contact
Volvo: Zain Zubair, ) (financial compensation from Volvo will be awarded to the students)

Chalmers: Jordanka Kovaceva )

References
[1] Knight et al., (2022), The Transport for London Bus Safety Standard: Advanced Emergency Braking (AEB).

[2] Wikipedia contributors, Confusion matrix, matrix, 2025, [Online].

We value your data privacy and therefore do not accept applications via mail.

Who We Are And What We Believe In
We are committed to shaping the future landscape of efficient, safe, and sustainable transport solutions. Fulfilling our mission creates countless career opportunities for talents across the group's leading brands and entities.

Applying to this job offers you the opportunity to join
Volvo Group
. Every day, you will be working with some of the sharpest and most creative brains in our field to be able to leave our society in better shape for the next generation. We are passionate about what we do, and we thrive on teamwork. We are almost 100,000 people united around the world by a culture of care, inclusiveness, and empowerment.

At
Volvo Buses
you join one of the world's leading providers of sustainable people transport solutions. What we do affects millions of people around the world: passengers, drivers, customers; in fact, entire cities and countries. This job gives you the opportunity to work with the future of people transportation and infrastructure. We have a strong culture of working together to help each other, sharing knowledge and experience. Together, we shape the world we want to live in.