Sensor-based Flow Optimization on connected real-world intersections via a SUMO Feature Gap Analysis
summary
Project models real intersections in Erlangen to test whether SUMO can support a 5G-enabled, sensor-driven traffic light optimizer and proposes how to close missing features. SUMO covers basic detectors, lanes and TraCI control but lacks programmable Unix PLC emulation and full multi-intersection camera-origin-destination fusion, plus bespoke 5G vehicle‑to‑X roadside unit support. The concept builds XML map imports, multi-entry/exit detectors, a Python rule‑based controller that talks to TraCI and MQTT, and a PLC-like blocker; no live implementation yet, city agreed to one‑ or two‑day field trials.
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chapters (9)
- 0:00Introduction
- 0:58Problem Statement From the point of view from the city of Aalen
- 2:19Use Case - Traffic flow optimization
- 3:54Solution Approach
- 6:41Current built-in sensors (Signal location diagram)
- 8:17Traffic Light Signals
- 9:48Requirements Analysis
- 14:36Technical Concept
- 17:23Next Steps
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