Research Article
Automatic Parking Controller with a Twin Artificial Neural Network Architecture
Table 3
Success rate of automatic parking depending on test conditions.
| Test condition | Kinematic parameters of main/virtual vehicle (L/lw) | Initial heading angle (°) | No. of test | No. of successes | No. of failures | Success rate (%) |
| Case 1 | (3.6/2.52)/(3.6/2.52) | ±0 | 10,000 | 9,941 | 59 | 99.4 | Case 2 | (3.4/2.38)/(3.4/2.38) | ±0 | 10,000 | 9,901 | 99 | 99.0 | Case 3 | (3.8/2.66)/(3.8/2.66) | ±0 | 10,000 | 9,546 | 454 | 95.5 | Case 4 | (3.4/2.38)/(3.6/2.52) | ±0 | 10,000 | 9,978 | 22 | 99.8 | Case 5 | (3.6/2.52)/(3.6/2.52) | +3 | 10,000 | 9,799 | 201 | 98.0 | Case 6 | (3.6/2.52)/(3.6/2.52) | +5 | 10,000 | 9,436 | 574 | 94.4 |
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