PRJ-03 · UCSC Capstone Project

RSS: Vehicle Sensing and Driver Awareness

Outcome: Currently developing a vehicle mounted driver awareness system that combines radar, cameras, and vehicle data to detect surrounding vehicles and estimate distance and relative motion. I designed the sensing architecture and am developing the ranging and decision logic used to turn raw sensor measurements into useful information about nearby traffic.

Placeholder: RSS system hero shot
Fig. 1 — Current RSS prototype platform and sensing hardware. [Replace with staged system photo.]

What I Did

  • Designed the system architecture combining radar, camera sensing, and vehicle data for surrounding traffic awareness.
  • Evaluated radar technologies and sensor configurations for vehicle ranging, relative motion measurement, and prototype integration.
  • Selected the SparkFun XM125 platform using the Acconeer A121 60 GHz pulsed coherent radar for initial ranging and presence characterization.
  • Developing relative motion and spacing logic that converts measured vehicle position and velocity into driver relevant information.

Motivation

Modern vehicles increasingly use radar, cameras, and vehicle data to build an awareness model of surrounding traffic, while older vehicles generally lack this level of sensing. RSS is being developed as a retrofit driver awareness platform for a 2015 Acura MDX, with the goal of combining external sensing and vehicle data to estimate where surrounding vehicles are, how quickly those relationships are changing, and when those changes become relevant to the driver. The project is currently in the prototype and subsystem characterization phase.

Placeholder: system block diagram
Fig. 2 — Proposed sensing architecture combining radar, cameras, vehicle data, and driver awareness processing.
Placeholder: receiver PCB
Fig. 3 — SparkFun XM125 radar development hardware using the Acconeer A121 60 GHz pulsed coherent radar.

Results

RSS is currently in development, so final system performance has not yet been characterized. The current design phase has established the sensing architecture and selected the XM125/A121 radar platform for initial ranging and presence testing. Current work is focused on characterizing usable vehicle detection range, measurement stability, relative motion behavior, and physical sensor placement before integrating camera based vehicle detection and vehicle data.

Technical Details

The current prototype is centered on the Acconeer A121 60 GHz pulsed coherent radar through the SparkFun Qwiic XM125 development board. The radar platform supports configurable distance and presence detection applications, allowing the same hardware to be characterized for both ranging and motion related sensing. SparkFun's June 2026 XM125 documentation provides the current development workflow, while the 2.0+ Arduino library separates distance and presence operation into dedicated interfaces. The planned system combines these radar measurements with wide angle camera based vehicle detection and vehicle data from the 2015 Acura MDX. Relative distance and velocity measurements will then feed kinematic and spacing logic used to interpret surrounding traffic behavior.

Placeholder: measurement plot
Fig. 4 — Radar distance and relative motion characterization. [Replace with measured XM125 test data as development progresses.]
Role
Systems & sensing development
Team
2 active, 2 onboarding
Timeline
July 2026 – Present
Context
UCSC Capstone Project
Tools
SparkFun XM125, Acconeer A121, Python, CAD, 3D printing
Skills
Radar sensing · Sensor fusion · Relative kinematics · Systems integration
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