- This topic has 6 replies, 7 voices, and was last updated 1 year, 11 months ago by
Christian Eichenberger.
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May 3, 2019 at 14:16 #415
Ali Soleymani
ParticipantWe provide a unique data set derived from trajectories of raw GPS position fixes (consisting of a latitude, a longitude, a time stamp, as well as the vehicle speed and driving direction recorded at the time). The data is made available by HERE Technologies and originates from a large fleet of probe vehicles which recorded their movements in multiple culturally and socially diverse metropolitan areas around the world throughout the course of an entire year. The full data that we share with the scientific community is based on the unprecedented number of over 1011 probe-points, corresponding to over 300,000 frames, which at a 24 frame/s play rate would give in excess of three hours data-movie footage.
Specifically, the aggregation procedure involves the following steps:
- Spatial tessellation of the study area: the study area is tessellated in regular grid cells. We select all probe points which intersect one of the cells and were recorded in the selected time interval.
- Aggregation of probe points: Probe points are grouped based on their spatial and temporal attributes, i.e., the grid cell their location falls into and the 5 minute time bin within which their time stamp belongs.
- Core channels: We compute the mean speed, volume, and direction of traffic.
- Generation of video frames: The encoded values are stored in a tensor of the form (t; h;w; c) where t is the number of individual 5 minute time bins, i.e., the number of frames, while h and w denote the height and width of the frame grid cells, and c stands for the number of data channels, with c = 3 when using only a single channel for each traffic state feature.
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This topic was modified 4 years, 5 months ago by
IARAI.
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This topic was modified 4 years, 5 months ago by
IARAI.
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This topic was modified 4 years, 4 months ago by
Dr David Kreil.
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This topic was modified 4 years, 4 months ago by
Dr David Kreil.
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This topic was modified 4 years, 4 months ago by
Dr David Kreil.
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This topic was modified 4 years, 4 months ago by
Dr David Kreil.
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This topic was modified 4 years, 2 months ago by
Dr David Kreil.
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June 6, 2019 at 19:42 #763
siderste
ParticipantHello,
I see in the text that “Core channels: We compute the mean speed, volume, and direction of traffic.”
but in the image above i notice that red is refer to volume and green to speed.
could you please elaborate if the R (red) channel refers to volume and G (green) channel refers to speed?
Thanks!
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June 12, 2019 at 11:40 #769
Anonymous
InactiveHello,
I can confirm that the red channel (colour value) is proportional to what could loose be called the volume, so let me explain what I mean by that. In fact, it is the number of “probe points” (GPS coordinates with time stamps) received from a partial collection of all our sources, capped at a minimum and maximum level and normalized over the year and aggregated in the roughly 100mx100m and 5min interval space-time windows. All these capped numbers are then mapped proportionally to the interval [1,255] after which they are rounded to the nearest integer colour value (between 1 to 255). Note that some of the underlying probes generating this data might emit “probe points” at different time intervals – yet the procedure above only counts the points that arrive during a given time interval.
Hope that helps. Thanks for your interest.
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July 23, 2019 at 22:13 #884
gnosisyu
ParticipantHello,
I have several questions about the dataset. Since time bin is 5 mins and this competition expect model to predict next 15 mins. I assume we are asked to build a video prediction model to predict next-3 frames. I am wondering how long is the input sequence. Expect for the movie footage, do we have access to other type of data like date, time (e.g. 4 pm.) or population map?
Thanks!
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July 25, 2019 at 16:09 #901
David Jonietz
ParticipantHi gnosisyu, thanks for your interest in the competition. As you can see from the test data set, we provide data for 60 min previous to each prediction point in time. Of course, however, it is up to you to decide how much of that information you actually feed into your model.
With regards to your second question, we only provide the traffic data. If you choose to incorporate other additional data sources, you are of course more than welcome to do so.
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September 19, 2019 at 14:47 #3098
dominikbucher
ParticipantHi all
We were wondering if you could let us know the geographic extent of the maps and the projection resp. coordinate system used to generate them?
Thanks!
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October 8, 2021 at 17:06 #25710
Christian Eichenberger
MemberClosing this 2019 thread.
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- The topic ‘Traffic4cast Challenge 2019 – The Data’ is closed to new replies.