Intersection Lab 0.3.0

Changes

• A smaller, better Deep RL network. The Deep RL controller's network now has one hidden layer of 128 units instead of two. In tests on scenarios held back from training, one layer gave lower person delay than two on every layout, and doubling the training didn't close the gap. The networks were retrained for 800 episodes (train all 800 900 dqn).

• Deep RL's benchmark results improve on every layout:

  Person delay	Arterial	Major/minor	Town	T-intersection
  0.2.2	31.1 s	34.3 s	40.0 s	13.1 s
  0.3.0	19.4 s	24.4 s	30.0 s	11.7 s

  Pedestrian waits under Deep RL also fall by 4 to 10 s on the four-way layouts. On the T-intersection they stay long, at about 46 s, because pedestrian delay isn't part of what the network is trained to reduce.

• The Hybrid controller is unchanged. Retrained with one hidden layer, it did worse on the town layout and the T-intersection, so it keeps its earlier networks. Every other controller is unchanged too.

• The README, the insights write-up and the app's training hint are updated to match.

Downloads

Signed and notarized installers for macOS (DMG), signed installers for Windows x64 and arm64 (MSI, ZIP), and Linux packages (deb, rpm, tar.gz) for x86_64 and aarch64. Checksums are in SHA256SUMS.txt. The browser version is on the project's GitHub Pages site.

Full Changelog: v0.2.2...v0.3.0