Master thesis - V2X-based Hazard Detection for eBike

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Bosch R&D Center Lund stands for modern development in cutting-edge technology in the areas of connectivity, security, mobility solutions and AI. We are growing rapidly and looking for people to join us on our mission to become the Bosch Group’s 1st address for secure connected mobility solutions. We are working on a range of interesting projects, with a particular focus on software development for the automotive industry, eBike and Internet of Things.

Problem statement

As the ecosystem of micro-mobility grows, ensuring the safety of eBike riders through V2X (Vehicle-to-Everything) technology is becoming increasingly important. A key challenge is bringing sophisticated hazard detections such as identifying approaching vehicles—to the constrained environment of eBike embedded system.

Current V2X solutions often demand significant computational power. To make these safety features viable, we need to integrate and optimize existing software solutions to run efficiently on low-power, real-time operating systems. The challenge lies in processing incoming V2X data and triggering real-time alerts on a bike display without oversubscribing the limited system resources.

Proposed solution

This thesis aims to develop a functional prototype of a V2X hazard detection system integrated into an embedded environment based on FreeRTOS. The focus is on the "receiving" end of the V2X chain: processing environmental data to detect threats (e.g., cars on a collision course) and notifying the rider.

Implementation and evaluation:

• Integration: Adapt existing V2X software libraries/stacks to a FreeRTOS-based embedded environment.

• Logic Development: Identify and notify of relevant objects (cars) based on incoming data streams.

• Optimization: Ensure the system meets real-time requirements while operating within the performance constraints of an embedded microcontroller (focusing strictly on detection, not transmission).

• Prototyping: Develop a functional "proof-of-concept" where warnings are successfully triggered on a bike display.

• Benchmarking: Measure latency, CPU usage, and memory footprint to evaluate the feasibility of the solution for production.

To be successful in the project you need:

• To be a Master student(s) in Embedded Systems, Computer Science, Electrical Engineering, or similar.

• Strong C programming skills, with experience or a deep interest in FreeRTOS or other real-time operating systems (RTOS).

• Knowledge of embedded systems architecture and resource-constrained development.