Project

Generating Synthetic Scenarios to Test an AI-Enabled Traffic Measurement System

Period
1 April–31 August 2022
Project manager
Markus Borg

Traffic is complex! It is the sum of road design, road user behavior, and their interactions. Understanding this dynamic is central to making the transport system efficient, safe, and sustainable — in line with the UN Sustainable Development Goals 11 and 3. Viscando offers Al-enabled data-driven solutions for traffic analysis, safety diagnostics, intelligent traffic control, naturalistic data collection, and extended perception at the very core of smart cities and autonomous driving. This is enabled by Viscando’s proprietary AI- and stereo vision-based infrastructure sensor OTUS3D, which is used for collection of accurate traffic movement data.

Software quality assurance (QA) must evolve as systems increasingly rely on AI. Building on initial work on simulation-based testing, we will develop evolutionary algorithms to generate test scenarios in CARLA that stress OTUS3D to its limits. As part of the project's results, we will develop a digital model of an intersection in Lindholmen. The project's results will support development of robust measurement systems for smart city and autonomous driving applications.

Short facts

Research area
Safety performance evaluation
Financier(s)
SAFER Pre-Studies Phase 5
Partners
RISE
Lund University
Viscando
Project type
SAFER Pre-study