Traffic Map Movie Forecasting 2020
- Study high-resolution traffic movies of entire cities
- Predict future traffic flows
- Discover underlying rules and patterns
15 July: Main competition goes live
6 October: Release of pollution data & bonus challenge
1 November: Submission deadline
6 November: Abstract and code submission deadline
10 November: Presentation submission deadline
12 November: Evaluation of submissions announced / NeurIPS conference invitations confirmed
14 November: Deadline to submit individual presentations to Neurips
6-12 December: NeurIPS Vancouver
Building on its success at NeurIPS 2019, the Traffic4cast competition is going into its second year offering new challenges and opportunities. This year’s dataset will be derived from an order of magnitude more data. We are collecting data from multiple cities of different size, geography, culture, and economy. The core challenge will be to predict short-term large-scale traffic states in all the cities. Participants can investigate differences and similarities in traffic patterns between the cities, and explore master models trained on multiple cities. The dataset will be augmented by new static and dynamic features, such as street maps properties, points of interest, and air pollution. Bonus challenges invite participants to explore the effects of these additional features.
Interested in revolutionizing our understanding of mobility?
Join our forums now to help shape this year’s competition!
The incredibly creative solutions last year revealed surprising insights:
- Our simple movies provided sufficient information to make state-of-the-art traffic predictions.
- Additional traffic attributes (weather, road map properties) are of value for bonus challenges and improve more complex models.
- It may be possible to separate rules underlying traffic dynamics from city-specific forecasts (transfer learning).
The solutions presented at the Traffic4cast competition track at NeurIPS 2019 are published in the Proceedings of Machine Learning Research.
Data example from Traffic4cast 2019.