Challenges / IEEE ICDM Contest: TomTom Traffic Prediction for Intelligent GPS Navigation
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Summary
The data mining challenge, IEEE ICDM Contest: TomTom Traffic Prediction for Intelligent GPS Navigation, is over now. It attracted 575 participating teams, of whom over 100 submitted solutions, most of them many times: the total number of solutions was close to 5000. Best algorithms achieved nearly 3-fold improvement over baseline solutions in predicting traffic congestion and jams. We thank all participants for their effort and congratulate the winners! We also thank TomTom company and the President of Warsaw for their support of the contest. The Winners
Jams:
GPS:
![]() After ICDM Contest Workshop in Sydney. From left: Paweł Gora, Marcin Wojnarski (organizers), Łukasz Romaszko, Benjamin Hamner, Carlos J. Gil Bellosta (winners), Ralf-Peter Schäfer (TomTom) Top SolutionsTop solutions are now described on TunedIT Blog, see Part 1 and Part 2 of the blog post. Comment below the posts if you want to ask the authors any questions. ICDM Contest WorkshopDuring ICDM conference, the ICDM Contest Workshop will be organized, where top solutions will be presented by their authors. The Workshop will take place on December 14th (Tue), at the ICDM conference venue at the University of Technology, Sydney, Building 5 (Haymarket Campus). Key points presented at the Workshop will be repeated on the following day (Wed, Dec 15th, 14:00 - 15:30) during shorter ICDM Contest Overview Session, as a part of the main conference programme. We invite everyone to attend! Detailed Programme 13:30 - 14:00 Introductory Report
14:00 - 14:30 TomTom: Insights about TomTom's Traffic Technology
14:30 - 15:00 Task 1 (solution 2): A convex combination of models for predicting road traffic
15:00 - 15:30 Task 1 (solution 3): Predicting Future Traffic Congestion from Automated Traffic Recorder Readings with an Ensemble of Random Forests 15:30 - 16:00 Coffee Break (30 min)
16:00 - 16:30 Task 2 (solution 1): IEEE ICDM 2010 Contest: Traffic Prediction - Jams
16:30 - 17:00 Task 2 (solution 2): Ensemble-based Method for Task 2: Predicting Traffic Jams
17:00 - 17:30 Task 3 (solution 1): Predicting Travel Times with Context-Dependent Random Forests by Modeling Local and Aggregate Traffic Flow
17:30 - 18:00 Task 3 (solution 2): Traffic Velocity Prediction Using GPS Data: IEEE ICDM Contest Task 3 Report Post-challenge ResearchAll challenge resources are published now in the challenge folder in Repository and everyone can use them as a basis for new research. They are divided into three subfolders: Traffic, Jams and GPS. The following resources are available:
Post-challenge SubmissionsPost-challenge submissions per se are not supported. Instead, TunedIT provides a versatile framework for evaluation of new solutions against any evaluation procedure and dataset, not only the ones used for the challenge. Thus, you may prepare derived versions of challenge resources and compare test results with the original ones. You may also control access rights to your resources and remove once uploaded solutions. To use the framework, upload a solution file to your home folder in Repository and evaluate it with TunedTester, giving the following names of the evaluation procedure and datasets in TT window (plus give the full name of your algorithm, as shown on its Repository page): Traffic:
Jams:
GPS:
If you wish, you may choose to send results to Knowledge Base. They can be viewed and analyzed afterwards by everyone on KB pages. For example, the following links generate post-challenge leaderboards with results corresonding to the same evaluation setup as used in the challenge (the same evaluation procedures and datasets):
When you open KB page, notice that there may be several evaluation procedures or datasets on the drop-down lists. Every choice generates a different chart. Also, there is the Raw Results tab where all the results are presented in tabular form and can be downloaded as CSV files. Raw Results tab contains also hyper-links to Repository pages of particular algorithms and datasets. Public files |