| | Require: Road segment features space: |
| | Outputs: Road segment embedded features space: |
| (1) | Define encoder parameters: |
| (2) | Input layer: . |
| (3) | Hidden layer1: , Activation = ReLu. |
| (4) | Hidden layer2: , Activation = ReLu. |
| (5) | Hidden layer3: , Activation = ReLu. |
| (6) | Hidden layer4: , Activation = ReLu. |
| (7) | Embedding layer , Activation = ReLu. |
| (8) | Define decoder parameters: |
| (9) | Hidden layer1: , Activation = ReLu. |
| (10) | Hidden layer2: , Activation = ReLu. |
| (11) | Hidden layer3: , Activation = ReLu. |
| (12) | Hidden layer4: , Activation = ReLu. |
| (13) | Output layer: , activation = Sigmoid. |
| (14) | Define DAE model: model(encoder, decoder) |
| (15) | fordo |
| (16) | Fit input feature vectors to DAE model. |
| (17) | Initialise weights randomly. |
| (18) | Obtain reconstructed feature vectors . |
| (19) | Compute the error difference: |
| (20) | while error difference is not converging do |
| (21) | Update weight parameters. |
| (22) | end while |
| (23) | Store weights parameters. |
| (24) | Obtain the embedding features vector |
| (25) | |
| (26) | end for |
| (27) | Return embedding space features |
