Top Tweets for #LaneChangePrediction
The imbalance issue in #LaneChangePrediction (much #LaneKeeping and few #LaneChange s) can also be fight by adapting the threshold for discretizing the softmax output into categorical decisions.
Many of those techniques are based on the #ROCCurve.
In highway traffic #LaneChange s are rare.
For #LaneChangePrediction this is complicating the training of a #MachineLearning based model and evaluating it afterwards.
See https://t.co/z7PqXoVWMm for how we worked on this issue with different sampling methods.
In highway driving #LaneChangePrediction of vehicles constitutes a valuable information of their future motion. Beside other vehicles causing or hindering a #LaneChange, further factors influence driver behavior.
See https://t.co/PrtAFE6ynm for more information.
For highway targeted #ADAS in mass market applications #LaneChangePrediction represents a valuable information. We developed a #NeuralNetworks based classifier & analyzed the dependence on labeling methods.
https://t.co/bOAcDjwYdr
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