Learning-Based Lane-Change Behaviour Detection for Intelligent and Connected Vehicles

Table 4

Description of KNN algorithm.

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Input:
Training object (x, y) ∈I and test object

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Processing:
Compute distance between z and every object (x, y) ∈I. Select I_z ⊆ I, the set of k closest training objects to z.

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Output:

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