Duckietown Challenges | Home | Challenges | Submissions |
Last computed:
Rank (user) | User | Submission | complete | User label | Traveled distance↑ | Survival time↑ | Lateral deviation ↓ | Major infractions ↓ |
1 | Wei Gao 🇸🇬 | 1633 | 1/4 | First trial | 18.6 | 18. | 0.58 | 0.2 |
- | Wei Gao 🇸🇬 | 1839 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.61 | 0.4 |
- | Wei Gao 🇸🇬 | 1704 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.7 | 0.2 |
2 | Anton Mashikhin 🇷🇺 | 1579 | 1/4 | SAIC MOSCOW MML | 18.6 | 18. | 0.87 | 0.4 |
3 | Mikita Sazanovich 🇷🇺 | 1859 | 1/4 | JetBrains Research | 18.6 | 18. | 1.34 | 0.2 |
4 | Jonathan Plante 🇨🇦 | 1744 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
5 | Vincent Mai 🇨🇦 | 1033 | 1/4 | ROS-based Lane Following | 14.88 | 18. | 1.86 | 1.8 |
6 | Benjamin Ramtoula 🇨🇦 | 1063 | 1/4 | My ROS solution | 14.26 | 18. | 0.91 | 0.6 |
7 | Samuel Lavoie | 819 | 1/4 | Baby Duke | 13.02 | 18. | 0.89 | 2.2 |
8 | David Abraham | 1139 | 1/4 | Pytorch IL | 12.4 | 18. | 1.49 | 1.4 |
This list includes repeated entries from the same user and the entries from the organizers.
Rank (user) | User | Submission | complete | User label | Traveled distance↑ | Survival time↑ | Lateral deviation ↓ | Major infractions ↓ |
1 | Wei Gao 🇸🇬 | 1633 | 1/4 | First trial | 18.6 | 18. | 0.58 | 0.2 |
- | Wei Gao 🇸🇬 | 1631 | 1/4 | First trial | 18.6 | 18. | 0.6 | 0.2 |
- | Wei Gao 🇸🇬 | 1645 | 1/4 | First trial | 18.6 | 18. | 0.61 | 0.2 |
- | Wei Gao 🇸🇬 | 1839 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.61 | 0.4 |
- | Wei Gao 🇸🇬 | 1653 | 1/4 | First trial | 18.6 | 18. | 0.67 | 0.2 |
- | Wei Gao 🇸🇬 | 1596 | 1/4 | First trial | 18.6 | 18. | 0.67 | 0.2 |
- | Wei Gao 🇸🇬 | 1854 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.69 | 0.2 |
- | Wei Gao 🇸🇬 | 1639 | 1/4 | First trial | 18.6 | 18. | 0.69 | 0.2 |
- | Wei Gao 🇸🇬 | 1847 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.69 | 0.4 |
- | Wei Gao 🇸🇬 | 2056 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1818 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1766 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1704 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1646 | 1/4 | First trial | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1643 | 1/4 | First trial | 18.6 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1866 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.7 | 0.4 |
- | Wei Gao 🇸🇬 | 1782 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.71 | 0.2 |
- | Wei Gao 🇸🇬 | 1764 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.71 | 0.2 |
- | Wei Gao 🇸🇬 | 1703 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.71 | 0.2 |
- | Wei Gao 🇸🇬 | 1763 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.71 | 0.4 |
- | Wei Gao 🇸🇬 | 2068 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.72 | 0.2 |
- | Wei Gao 🇸🇬 | 1837 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.72 | 0.2 |
- | Wei Gao 🇸🇬 | 1761 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.72 | 0.2 |
- | Wei Gao 🇸🇬 | 1810 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.72 | 0.4 |
- | Wei Gao 🇸🇬 | 1768 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.73 | 0.2 |
- | Wei Gao 🇸🇬 | 1767 | 1/4 | NUS & Panasonic R&D Center Singapore | 18.6 | 18. | 0.73 | 0.2 |
- | Wei Gao 🇸🇬 | 1760 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 18.6 | 18. | 0.73 | 0.2 |
- | Wei Gao 🇸🇬 | 1602 | 1/4 | First trial | 18.6 | 18. | 0.73 | 0.2 |
- | Andrea Censi 🇨🇭 | 1896 | 1/4 | Copy of #1: sub 1633 by WEIGAO (First trial) | 18.6 | 18. | 0.74 | 0.2 |
- | Andrea Censi 🇨🇭 | 1898 | 1/4 | Copy of #2: sub 1579 by heyt0ny (SAIC MOSCOW MML) | 18.6 | 18. | 0.87 | 0.4 |
2 | Anton Mashikhin 🇷🇺 | 1579 | 1/4 | SAIC MOSCOW MML | 18.6 | 18. | 0.87 | 0.4 |
- | Andrea Censi 🇨🇭 | 1908 | 1/4 | Copy of #2: sub 1579 by heyt0ny (SAIC MOSCOW MML) | 18.6 | 18. | 0.89 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 1668 | 1/4 | SAIC MOSCOW MML | 18.6 | 18. | 0.91 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 1372 | 1/4 | SAIC MOSCOW MML | 18.6 | 18. | 0.93 | 0.6 |
- | Andrea Censi 🇨🇭 | 1909 | 1/4 | Copy of #3: sub 1859 by miksaz (JetBrains Research) | 18.6 | 18. | 1.34 | 0.2 |
- | Andrea Censi 🇨🇭 | 1899 | 1/4 | Copy of #3: sub 1859 by miksaz (JetBrains Research) | 18.6 | 18. | 1.34 | 0.2 |
3 | Mikita Sazanovich 🇷🇺 | 1859 | 1/4 | JetBrains Research | 18.6 | 18. | 1.34 | 0.2 |
- | Wei Gao 🇸🇬 | 1644 | 1/4 | First trial | 17.98 | 18. | 0.58 | 0.2 |
- | Wei Gao 🇸🇬 | 1843 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.59 | 0.2 |
- | Wei Gao 🇸🇬 | 1634 | 1/4 | First trial | 17.98 | 18. | 0.59 | 0.2 |
- | Wei Gao 🇸🇬 | 1765 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.59 | 0.4 |
- | Wei Gao 🇸🇬 | 1640 | 1/4 | First trial | 17.98 | 18. | 0.59 | 0.4 |
- | Wei Gao 🇸🇬 | 1835 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.6 | 0.2 |
- | Wei Gao 🇸🇬 | 1773 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.6 | 0.2 |
- | Wei Gao 🇸🇬 | 1762 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 17.98 | 18. | 0.6 | 0.2 |
- | Wei Gao 🇸🇬 | 1641 | 1/4 | First trial | 17.98 | 18. | 0.6 | 0.4 |
- | Wei Gao 🇸🇬 | 1811 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.61 | 0.2 |
- | Wei Gao 🇸🇬 | 1638 | 1/4 | First trial | 17.98 | 18. | 0.61 | 0.2 |
- | Wei Gao 🇸🇬 | 1841 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.62 | 0.2 |
- | Wei Gao 🇸🇬 | 1771 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.62 | 0.4 |
- | Wei Gao 🇸🇬 | 1642 | 1/4 | First trial | 17.98 | 18. | 0.63 | 0.2 |
- | Wei Gao 🇸🇬 | 1637 | 1/4 | First trial | 17.98 | 18. | 0.65 | 0.2 |
- | Wei Gao 🇸🇬 | 1636 | 1/4 | First trial | 17.98 | 18. | 0.68 | 0.4 |
- | Wei Gao 🇸🇬 | 1775 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.69 | 0.4 |
- | Wei Gao 🇸🇬 | 1757 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 17.98 | 18. | 0.69 | 0.4 |
- | Wei Gao 🇸🇬 | 1850 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.7 | 0.2 |
- | Wei Gao 🇸🇬 | 1814 | 1/4 | NUS & Panasonic R&D Center Singapore | 17.98 | 18. | 0.72 | 0.4 |
- | Mikita Sazanovich 🇷🇺 | 1755 | 1/4 | JetBrains Research | 17.98 | 18. | 1.12 | 0.4 |
- | Mikita Sazanovich 🇷🇺 | 1725 | 1/4 | JetBrains Research | 17.98 | 18. | 1.14 | 0.6 |
- | Manfred Diaz | 2190 | 1/4 | Tensorflow template | 16.74 | 18. | 0.84 | 0.4 |
- | Andrea Censi 🇨🇭 | 1900 | 1/4 | Copy of #4: sub 1684 by Jon (JP pipeline) | 16.74 | 18. | 1.05 | 1.8 |
4 | Jonathan Plante 🇨🇦 | 1744 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 1691 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 1690 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 1686 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 1685 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 1684 | 1/4 | JP pipeline | 16.74 | 18. | 1.05 | 1.8 |
- | Anton Mashikhin 🇷🇺 | 1318 | 1/4 | SAIC MOSCOW MML | 16.74 | 18. | 1.07 | 2.2 |
- | Wei Gao 🇸🇬 | 1739 | 1/4 | NUS&PANASONIC_R&D_SINGAPORE | 16.12 | 18. | 0.7 | 0.2 |
- | Mikita Sazanovich 🇷🇺 | 1710 | 1/4 | JetBrains Research | 16.12 | 16. | 1.02 | 0.4 |
- | Manfred Diaz | 990 | 1/4 | Tensorflow template | 15.5 | 18. | 0.84 | 0.6 |
- | Jonathan Plante 🇨🇦 | 709 | 1/4 | JP pipeline | 15.5 | 18. | 0.99 | 3.2 |
- | Mikita Sazanovich 🇷🇺 | 1496 | 1/4 | JetBrains Research | 14.88 | 18. | 0.94 | 2. |
5 | Vincent Mai 🇨🇦 | 1033 | 1/4 | ROS-based Lane Following | 14.88 | 18. | 1.86 | 1.8 |
6 | Benjamin Ramtoula 🇨🇦 | 1063 | 1/4 | My ROS solution | 14.26 | 18. | 0.91 | 0.6 |
- | Mikita Sazanovich 🇷🇺 | 1387 | 1/4 | JetBrains Research | 14.26 | 18. | 0.99 | 1.4 |
- | Mikita Sazanovich 🇷🇺 | 1549 | 1/4 | JetBrains Research | 13.64 | 18. | 0.91 | 1.6 |
- | Benjamin Ramtoula 🇨🇦 | 1174 | 1/4 | My ROS solution | 13.64 | 18. | 1.36 | 4.2 |
- | Anton Mashikhin 🇷🇺 | 1296 | 1/4 | SAIC MOSCOW MML | 13.02 | 18. | 0.71 | 0.8 |
7 | Samuel Lavoie | 819 | 1/4 | Baby Duke | 13.02 | 18. | 0.89 | 2.2 |
- | Vincent Mai 🇨🇦 | 1089 | 1/4 | ROS-based Lane Following | 13.02 | 18. | 1.42 | 3.2 |
- | Jonathan Plante 🇨🇦 | 1687 | 1/4 | JP pipeline | 13.02 | 14. | 0.86 | 1.4 |
- | Wei Gao 🇸🇬 | 1632 | 1/4 | First trial | 13.02 | 12. | 0.54 | 0.2 |
- | Mikita Sazanovich 🇷🇺 | 1580 | 1/4 | JetBrains Research | 12.4 | 18. | 0.89 | 1.4 |
- | Anton Mashikhin 🇷🇺 | 1289 | 1/4 | SAIC MOSCOW MML | 12.4 | 18. | 0.95 | 2. |
- | Anton Mashikhin 🇷🇺 | 1288 | 1/4 | SAIC MOSCOW MML | 12.4 | 18. | 0.95 | 2. |
- | Benjamin Ramtoula 🇨🇦 | 1134 | 1/4 | My ROS solution | 12.4 | 18. | 1.37 | 3.2 |
- | Benjamin Ramtoula 🇨🇦 | 1136 | 1/4 | My ROS solution | 12.4 | 18. | 1.43 | 3.2 |
- | Benjamin Ramtoula 🇨🇦 | 1191 | 1/4 | My ROS solution | 12.4 | 18. | 1.48 | 5.2 |
8 | David Abraham | 1139 | 1/4 | Pytorch IL | 12.4 | 18. | 1.49 | 1.4 |
- | Mikita Sazanovich 🇷🇺 | 1518 | 1/4 | JetBrains Research | 11.78 | 18. | 0.89 | 1.8 |
- | Anton Mashikhin 🇷🇺 | 1287 | 1/4 | SAIC MOSCOW MML | 11.78 | 18. | 0.94 | 2.2 |
- | Benjamin Ramtoula 🇨🇦 | 1140 | 1/4 | My ROS solution | 11.78 | 18. | 1.39 | 3.6 |
- | Vincent Mai 🇨🇦 | 1894 | 1/4 | ROS-based Lane Following | 11.78 | 14. | 1.19 | 0.6 |
- | Wei Gao 🇸🇬 | 1585 | 1/4 | First trial | 11.78 | 12. | 0.54 | 0.6 |
- | Mikita Sazanovich 🇷🇺 | 1389 | 1/4 | JetBrains Research | 11.78 | 12. | 0.67 | 1. |
- | Mikita Sazanovich 🇷🇺 | 1499 | 1/4 | JetBrains Research | 11.16 | 18. | 0.84 | 1.6 |
- | Benjamin Ramtoula 🇨🇦 | 957 | 1/4 | My ROS solution | 11.16 | 18. | 1.08 | 0.2 |
- | Vincent Mai 🇨🇦 | 1121 | 1/4 | ROS-based Lane Following | 10.54 | 18. | 1.57 | 7.2 |
- | Vincent Mai 🇨🇦 | 993 | 1/4 | ROS-based Lane Following | 10.54 | 18. | 1.61 | 7.6 |
- | Vincent Mai 🇨🇦 | 1110 | 1/4 | ROS-based Lane Following | 10.54 | 18. | 1.64 | 7.2 |
- | Mikita Sazanovich 🇷🇺 | 1383 | 1/4 | RL solution | 10.54 | 14. | 0.83 | 1.8 |
9 | Orlando Marquez 🇨🇦 | 455 | 1/4 | PyTorch DDPG template | 9.92 | 18. | 1.38 | 1.4 |
- | Orlando Marquez 🇨🇦 | 454 | 1/4 | PyTorch DDPG template | 9.92 | 18. | 1.38 | 1.4 |
- | Orlando Marquez 🇨🇦 | 436 | 1/4 | PyTorch DDPG template | 9.92 | 18. | 1.38 | 1.4 |
- | Vincent Mai 🇨🇦 | 1104 | 1/4 | ROS-based Lane Following | 9.92 | 18. | 1.57 | 6.8 |
- | Vincent Mai 🇨🇦 | 1115 | 1/4 | ROS-based Lane Following | 9.92 | 18. | 1.61 | 7.2 |
- | Benjamin Ramtoula 🇨🇦 | 1058 | 1/4 | My ROS solution | 9.92 | 18. | 1.66 | 3.4 |
- | Vincent Mai 🇨🇦 | 986 | 1/4 | ROS-based Lane Following | 9.92 | 18. | 1.96 | 3.4 |
- | Mikita Sazanovich 🇷🇺 | 1390 | 1/4 | JetBrains Research | 9.92 | 12. | 0.65 | 1.4 |
- | Benjamin Ramtoula 🇨🇦 | 1087 | 1/4 | My ROS solution | 9.92 | 12. | 1.28 | 1.4 |
- | Orlando Marquez 🇨🇦 | 441 | 1/4 | PyTorch DDPG template | 9.3 | 18. | 1.37 | 1. |
- | Orlando Marquez 🇨🇦 | 463 | 1/4 | PyTorch DDPG template | 9.3 | 18. | 1.37 | 1.2 |
- | Orlando Marquez 🇨🇦 | 440 | 1/4 | PyTorch DDPG template | 9.3 | 18. | 1.37 | 1.6 |
- | Vincent Mai 🇨🇦 | 1120 | 1/4 | ROS-based Lane Following | 9.3 | 18. | 1.59 | 7.2 |
- | Vincent Mai 🇨🇦 | 1090 | 1/4 | ROS-based Lane Following | 9.3 | 14. | 1.23 | 3.2 |
- | Wei Gao 🇸🇬 | 1591 | 1/4 | First trial | 9.3 | 10. | 0.3 | 0.2 |
- | Wei Gao 🇸🇬 | 1598 | 1/4 | First trial | 9.3 | 10. | 0.41 | 0.2 |
- | Samuel Lavoie | 1079 | 1/4 | Fast Duke | 9.3 | 10. | 0.58 | 0.4 |
- | Andrea Censi 🇨🇭 | 1901 | 1/4 | Copy of #5: sub 1033 by VincentMai (ROS-based Lane Following) | 9.3 | 10. | 1.18 | 2.4 |
- | Anton Mashikhin 🇷🇺 | 1243 | 1/4 | SAIC MOSCOW MML | 8.68 | 12. | 0.76 | 0.2 |
- | Mikita Sazanovich 🇷🇺 | 1494 | 1/4 | JetBrains Research | 8.68 | 10. | 0.43 | 0.4 |
10 | Philippe Lacaille | 985 | 1/4 | Dolores' Awakening | 8.68 | 10. | 0.59 | 0.8 |
- | Jonathan Plante 🇨🇦 | 1230 | 1/4 | JP pipeline | 8.68 | 10. | 0.64 | 1. |
- | Vincent Mai 🇨🇦 | 1892 | 1/4 | ROS-based Lane Following | 8.68 | 10. | 0.7 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1180 | 1/4 | My ROS solution | 8.68 | 10. | 0.79 | 2.2 |
- | Benjamin Ramtoula 🇨🇦 | 700 | 1/4 | My modified ROS-based Lane Following | 8.06 | 12. | 0.92 | 2. |
- | Mikita Sazanovich 🇷🇺 | 1661 | 1/4 | JetBrains Research | 8.06 | 8. | 0.51 | 0.2 |
11 | Hristo Vrigazov 🇧🇬 | 1552 | 1/4 | Visteon perception team | 7.44 | 18. | 0.91 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1141 | 1/4 | My ROS solution | 7.44 | 10. | 0.68 | 2.8 |
- | Hristo Vrigazov 🇧🇬 | 1647 | 1/4 | Visteon perception team | 6.82 | 18. | 1.02 | 1. |
- | Hristo Vrigazov 🇧🇬 | 1551 | 1/4 | Tensorflow template | 6.82 | 18. | 1.02 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1183 | 1/4 | My ROS solution | 6.82 | 18. | 1.14 | 6.4 |
- | Vincent Mai 🇨🇦 | 984 | 1/4 | ROS-based Lane Following | 6.82 | 18. | 1.93 | 3. |
- | Vincent Mai 🇨🇦 | 1117 | 1/4 | ROS-based Lane Following | 6.82 | 12. | 0.94 | 5.8 |
- | Vincent Mai 🇨🇦 | 1129 | 1/4 | ROS-based Lane Following | 6.82 | 12. | 0.99 | 5.2 |
- | Benjamin Ramtoula 🇨🇦 | 1083 | 1/4 | My ROS solution | 6.82 | 10. | 0.5 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1145 | 1/4 | My ROS solution | 6.82 | 10. | 0.76 | 2.8 |
- | Mikita Sazanovich 🇷🇺 | 1384 | 1/4 | JetBrains Research | 6.82 | 8. | 0.43 | 0.8 |
- | Vincent Mai 🇨🇦 | 1130 | 1/4 | ROS-based Lane Following | 6.2 | 18. | 1.07 | 9. |
- | Manfred Diaz | 2192 | 1/4 | Tensorflow template | 6.2 | 8. | 0.31 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 1244 | 1/4 | SAIC MOSCOW MML | 6.2 | 8. | 0.5 | 1.2 |
- | Philippe Lacaille | 992 | 1/4 | Dolores' Awakening | 6.2 | 6. | 0.32 | 0.4 |
- | David Abraham | 964 | 1/4 | Pytorch IL | 6.2 | 6. | 0.35 | 0.6 |
- | Samuel Lavoie | 1081 | 1/4 | Fast Duke | 6.2 | 6. | 0.51 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 884 | 1/4 | SAIC MOSCOW MML | 5.58 | 16. | 0.74 | 7.4 |
- | Mikita Sazanovich 🇷🇺 | 764 | 1/4 | RL solution | 5.58 | 14. | 1. | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1789 | 1/4 | My ROS solution | 5.58 | 14. | 1.52 | 4.6 |
- | Hristo Vrigazov 🇧🇬 | 1870 | 1/4 | Visteon perception team | 5.58 | 12. | 0.71 | 0.2 |
- | Manfred Diaz | 501 | 1/4 | Tensorflow template | 5.58 | 10. | 0.49 | 0.4 |
12 | Marius Hodel | 1832 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
- | Liam Paull 🇨🇦 | 1786 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
- | Liam Paull 🇨🇦 | 1746 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
13 | Zhenming Yang 🇨🇳 | 1495 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
- | Zhenming Yang 🇨🇳 | 1491 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
14 | shandonguniversity &&Inspur 🇨🇳 | 1482 | 1/4 | Inspur CNN | 5.58 | 10. | 0.56 | 0.2 |
15 | Inspur- team 🇨🇳 | 1363 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 1269 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
16 | Allen Ou | 590 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
- | Liam Paull 🇨🇦 | 502 | 1/4 | Tensorflow template | 5.58 | 10. | 0.56 | 0.2 |
17 | Tri Cao 🇺🇸 | 1521 | 1/4 | Tensorflow template | 5.58 | 10. | 0.58 | 0.4 |
- | Tri Cao 🇺🇸 | 1515 | 1/4 | Tensorflow template | 5.58 | 10. | 0.58 | 0.4 |
- | Dzenan Lapandic | 459 | 1/4 | Tensorflow template | 5.58 | 8. | 0.3 | 0.2 |
- | Samuel Lavoie | 372 | 1/4 | Tensorflow template | 5.58 | 8. | 0.3 | 0.2 |
- | Manfred Diaz | 350 | 1/4 | Tensorflow template | 5.58 | 8. | 0.3 | 0.2 |
- | Mikita Sazanovich 🇷🇺 | 1484 | 1/4 | JetBrains Research | 5.58 | 8. | 0.31 | 0.4 |
- | David Abraham | 1077 | 1/4 | Pytorch IL | 5.58 | 8. | 0.37 | 0.4 |
- | David Abraham | 1054 | 1/4 | Pytorch IL | 5.58 | 8. | 0.37 | 0.4 |
- | Manfred Diaz | 2197 | 1/4 | Tensorflow template | 5.58 | 8. | 0.48 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 853 | 1/4 | SAIC MOSCOW MML | 5.58 | 8. | 0.58 | 1.6 |
- | Vincent Mai 🇨🇦 | 1036 | 1/4 | ROS-based Lane Following | 5.58 | 8. | 0.77 | 1.6 |
- | Samuel Lavoie | 1080 | 1/4 | Fast Duke | 5.58 | 6. | 0.4 | 0.4 |
- | Jonathan Plante 🇨🇦 | 1218 | 1/4 | JP pipeline | 5.58 | 6. | 0.42 | 1. |
- | Dzenan Lapandic | 515 | 1/4 | Baseline solution using imitation learning from logs | 4.96 | 18. | 0.72 | 0. |
- | Florian Golemo | 1322 | 1/4 | Tuned lane controller - ETHZ baseline extension | 4.96 | 18. | 1.06 | 0.2 |
- | Hristo Vrigazov 🇧🇬 | 1648 | 1/4 | Visteon perception team | 4.96 | 14. | 0.99 | 0.2 |
- | Zhenming Yang 🇨🇳 | 1543 | 1/4 | Tensorflow template | 4.96 | 10. | 0.52 | 0.6 |
- | Tri Cao 🇺🇸 | 1519 | 1/4 | Tensorflow template | 4.96 | 10. | 0.52 | 0.6 |
18 | Petra Csereoka 🇷🇴 | 1378 | 1/4 | Tensorflow template | 4.96 | 10. | 0.52 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 1295 | 1/4 | SAIC MOSCOW MML | 4.96 | 8. | 0.39 | 0.2 |
- | Manfred Diaz | 2194 | 1/4 | Tensorflow template | 4.96 | 6. | 0.32 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 701 | 1/4 | My modified ROS-based Lane Following | 4.96 | 6. | 0.43 | 0.2 |
- | Manfred Diaz | 2193 | 1/4 | Tensorflow template | 4.96 | 6. | 0.44 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1209 | 1/4 | My ROS solution | 4.96 | 6. | 0.46 | 2.6 |
- | David Abraham | 1045 | 1/4 | Pytorch IL | 4.34 | 18. | 1.24 | 2.2 |
- | Orlando Marquez 🇨🇦 | 893 | 1/4 | Imitating | 4.34 | 18. | 1.55 | 6.2 |
- | Mikita Sazanovich 🇷🇺 | 758 | 1/4 | RL solution | 4.34 | 16. | 0.92 | 0.6 |
- | Vincent Mai 🇨🇦 | 1116 | 1/4 | ROS-based Lane Following | 4.34 | 10. | 0.68 | 4.6 |
- | Philippe Lacaille | 988 | 1/4 | Dolores' Awakening | 4.34 | 6. | 0.27 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 1304 | 1/4 | SAIC MOSCOW MML | 4.34 | 6. | 0.28 | 0.2 |
19 | Diego Charrez 🇵🇪 | 1479 | 1/4 | Tensorflow | 4.34 | 6. | 0.34 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 860 | 1/4 | SAIC MOSCOW MML | 4.34 | 6. | 0.41 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 859 | 1/4 | SAIC MOSCOW MML | 4.34 | 6. | 0.41 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 856 | 1/4 | SAIC MOSCOW MML | 4.34 | 6. | 0.41 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 858 | 1/4 | SAIC MOSCOW MML | 4.34 | 6. | 0.46 | 0.2 |
- | Diego Charrez 🇵🇪 | 1352 | 1/4 | PyTorch Sagemaker template | 3.72 | 18. | 0.26 | 8.4 |
- | Anton Mashikhin 🇷🇺 | 644 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.72 | 18. | 0.29 | 8.4 |
- | Vincent Mai 🇨🇦 | 1122 | 1/4 | ROS-based Lane Following | 3.72 | 12. | 0.67 | 4.4 |
- | Philippe Lacaille | 994 | 1/4 | Dolores' Awakening | 3.72 | 6. | 0.29 | 0.2 |
- | Vincent Mai 🇨🇦 | 1029 | 1/4 | ROS-based Lane Following | 3.72 | 6. | 0.35 | 1.8 |
- | Vincent Mai 🇨🇦 | 1093 | 1/4 | ROS-based Lane Following | 3.72 | 6. | 0.41 | 1.4 |
- | Jonathan Plante 🇨🇦 | 577 | 1/4 | JP pipeline | 3.72 | 6. | 0.43 | 2.6 |
- | Jonathan Plante 🇨🇦 | 543 | 1/4 | JP pipeline | 3.72 | 6. | 0.43 | 2.6 |
- | Vincent Mai 🇨🇦 | 1895 | 1/4 | ROS-based Lane Following | 3.72 | 6. | 0.49 | 0.2 |
- | Jonathan Plante 🇨🇦 | 909 | 1/4 | JP pipeline | 3.72 | 4. | 0.19 | 0.4 |
- | Jonathan Plante 🇨🇦 | 881 | 1/4 | JP pipeline | 3.72 | 4. | 0.19 | 0.4 |
- | Jonathan Plante 🇨🇦 | 708 | 1/4 | JP pipeline | 3.72 | 4. | 0.26 | 0.6 |
20 | Pravish Sainath 🇨🇦 | 1319 | 1/4 | PyTorch DDPG template | 3.1 | 18. | 0.26 | 8.4 |
- | Pravish Sainath 🇨🇦 | 1085 | 1/4 | PyTorch DDPG template | 3.1 | 18. | 0.26 | 8.4 |
21 | Ruixiang Zhang 🇨🇦 | 904 | 1/4 | stay simple | 3.1 | 18. | 0.26 | 8.4 |
- | Ruixiang Zhang 🇨🇦 | 903 | 1/4 | PyTorch DDPG template | 3.1 | 18. | 0.26 | 8.4 |
- | Anton Mashikhin 🇷🇺 | 729 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.1 | 18. | 1.29 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 727 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.1 | 18. | 1.29 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 645 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.1 | 18. | 1.29 | 0.8 |
22 | Gunshi Gupta 🇨🇦 | 1268 | 1/4 | ROS-based Lane Following | 3.1 | 18. | 1.54 | 7.8 |
- | Gunshi Gupta 🇨🇦 | 1290 | 1/4 | ROS-based Lane Following | 3.1 | 18. | 1.79 | 7.8 |
- | Vincent Mai 🇨🇦 | 1086 | 1/4 | ROS-based Lane Following | 3.1 | 16. | 1.09 | 4.6 |
- | Anton Mashikhin 🇷🇺 | 745 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.1 | 6. | 0.29 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 744 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 3.1 | 6. | 0.29 | 0.2 |
- | David Abraham | 1012 | 1/4 | Pytorch IL | 3.1 | 4. | 0.12 | 0.2 |
- | Philippe Lacaille | 982 | 1/4 | Dolores' Awakening | 3.1 | 4. | 0.18 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 1157 | 1/4 | My ROS solution | 3.1 | 4. | 0.24 | 0.6 |
- | Jonathan Plante 🇨🇦 | 486 | 1/4 | JP pipeline | 2.48 | 18. | 0.82 | 6.4 |
- | Hristo Vrigazov 🇧🇬 | 1886 | 1/4 | Visteon perception team | 2.48 | 12. | 0.5 | 4.8 |
- | Orlando Marquez 🇨🇦 | 929 | 1/4 | Imitating | 2.48 | 12. | 0.68 | 1.2 |
- | Benjamin Ramtoula 🇨🇦 | 1154 | 1/4 | My ROS solution | 2.48 | 8. | 0.21 | 5.8 |
- | Mikita Sazanovich 🇷🇺 | 1381 | 1/4 | RL solution | 2.48 | 4. | 0.11 | 0.4 |
- | Philippe Lacaille | 997 | 1/4 | Dolores' Awakening | 2.48 | 4. | 0.13 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 724 | 1/4 | My modified ROS-based Lane Following | 2.48 | 4. | 0.15 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 857 | 1/4 | SAIC MOSCOW MML | 2.48 | 4. | 0.19 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1200 | 1/4 | My ROS solution | 2.48 | 4. | 0.19 | 0.8 |
- | Hristo Vrigazov 🇧🇬 | 1829 | 1/4 | Visteon perception team | 2.48 | 4. | 0.22 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 694 | 1/4 | ROS-based Lane Following | 2.48 | 4. | 0.22 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1066 | 1/4 | My ROS solution | 2.48 | 4. | 0.22 | 0.4 |
- | Philippe Lacaille | 987 | 1/4 | Dolores' Awakening | 2.48 | 4. | 0.22 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 923 | 1/4 | My ROS solution | 2.48 | 4. | 0.23 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 887 | 1/4 | SAIC MOSCOW MML | 2.48 | 4. | 0.24 | 1. |
- | Hristo Vrigazov 🇧🇬 | 1812 | 1/4 | Visteon perception team | 2.48 | 4. | 0.25 | 0.2 |
- | Hristo Vrigazov 🇧🇬 | 1804 | 1/4 | Visteon perception team | 2.48 | 4. | 0.25 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1826 | 1/4 | My ROS solution | 2.48 | 4. | 0.26 | 0.8 |
- | Hristo Vrigazov 🇧🇬 | 2060 | 1/4 | Visteon perception team | 2.48 | 4. | 0.27 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 1977 | 1/4 | My ROS solution | 2.48 | 4. | 0.27 | 1.2 |
- | Hristo Vrigazov 🇧🇬 | 1884 | 1/4 | Visteon perception team | 2.48 | 4. | 0.28 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1108 | 1/4 | My ROS solution | 2.48 | 4. | 0.31 | 0.6 |
- | Gunshi Gupta 🇨🇦 | 1235 | 1/4 | ROS-based Lane Following | 1.86 | 10. | 0.73 | 2.8 |
- | Gunshi Gupta 🇨🇦 | 1254 | 1/4 | ROS-based Lane Following | 1.86 | 10. | 0.75 | 3.4 |
- | Vincent Mai 🇨🇦 | 965 | 1/4 | ROS-based Lane Following | 1.86 | 8. | 0.39 | 1.2 |
- | Anton Mashikhin 🇷🇺 | 851 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Anton Mashikhin 🇷🇺 | 846 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Anton Mashikhin 🇷🇺 | 832 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Anton Mashikhin 🇷🇺 | 831 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Anton Mashikhin 🇷🇺 | 830 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Anton Mashikhin 🇷🇺 | 829 | 1/4 | SAIC MOSCOW MML | 1.86 | 6. | 0.18 | 1.6 |
- | Orlando Marquez 🇨🇦 | 1038 | 1/4 | Imitating | 1.86 | 6. | 0.2 | 2.2 |
- | Philippe Lacaille | 916 | 1/4 | Dolores' Awakening | 1.86 | 6. | 0.35 | 0.2 |
- | Jonathan Plante 🇨🇦 | 569 | 1/4 | JP pipeline | 1.86 | 6. | 0.37 | 2. |
- | Philippe Lacaille | 921 | 1/4 | Dolores' Awakening | 1.86 | 6. | 0.39 | 0.2 |
23 | Tien Nguyen | 1225 | 1/4 | ROS-based Lane Following | 1.86 | 6. | 0.48 | 1. |
24 | Mandana Samiei 🇨🇦 | 687 | 1/4 | ROS-based Lane Following | 1.86 | 6. | 0.56 | 1.4 |
- | Anton Mashikhin 🇷🇺 | 952 | 1/4 | SAIC MOSCOW MML | 1.86 | 4. | 0.09 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1815 | 1/4 | My ROS solution | 1.86 | 4. | 0.11 | 1.2 |
- | Anton Mashikhin 🇷🇺 | 820 | 1/4 | SAIC MOSCOW MML | 1.86 | 4. | 0.12 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 809 | 1/4 | My modified ROS-based Lane Following | 1.86 | 4. | 0.13 | 0.2 |
- | Philippe Lacaille | 983 | 1/4 | Dolores' Awakening | 1.86 | 4. | 0.13 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 1825 | 1/4 | My ROS solution | 1.86 | 4. | 0.15 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 1195 | 1/4 | My ROS solution | 1.86 | 4. | 0.15 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 697 | 1/4 | My modified ROS-based Lane Following | 1.86 | 4. | 0.19 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 1167 | 1/4 | My ROS solution | 1.86 | 4. | 0.19 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 1203 | 1/4 | My ROS solution | 1.86 | 4. | 0.19 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1828 | 1/4 | My ROS solution | 1.86 | 4. | 0.2 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 730 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 1.86 | 4. | 0.23 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1202 | 1/4 | My ROS solution | 1.86 | 4. | 0.23 | 0.4 |
- | Vincent Mai 🇨🇦 | 1890 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.05 | 0.2 |
- | Vincent Mai 🇨🇦 | 1216 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.07 | 0.2 |
- | Vincent Mai 🇨🇦 | 1211 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.07 | 0.2 |
- | Vincent Mai 🇨🇦 | 1205 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.07 | 0.2 |
- | Vincent Mai 🇨🇦 | 1214 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.08 | 0.2 |
- | Vincent Mai 🇨🇦 | 1213 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.09 | 0.2 |
- | Vincent Mai 🇨🇦 | 1198 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.09 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1740 | 1/4 | My ROS solution | 1.86 | 2. | 0.09 | 0.4 |
- | David Abraham | 963 | 1/4 | Pytorch IL | 1.86 | 2. | 0.1 | 0. |
- | Anton Mashikhin 🇷🇺 | 1303 | 1/4 | SAIC MOSCOW MML | 1.86 | 2. | 0.1 | 0.2 |
- | Vincent Mai 🇨🇦 | 1204 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.1 | 0.2 |
- | Vincent Mai 🇨🇦 | 1189 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.1 | 0.2 |
- | Jonathan Plante 🇨🇦 | 840 | 1/4 | JP pipeline | 1.86 | 2. | 0.1 | 0.4 |
- | Jonathan Plante 🇨🇦 | 807 | 1/4 | JP pipeline | 1.86 | 2. | 0.1 | 0.4 |
- | David Abraham | 1013 | 1/4 | Pytorch IL | 1.86 | 2. | 0.11 | 0. |
- | David Abraham | 962 | 1/4 | Pytorch IL | 1.86 | 2. | 0.11 | 0. |
- | Vincent Mai 🇨🇦 | 1188 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.11 | 0.2 |
- | Jonathan Plante 🇨🇦 | 726 | 1/4 | JP pipeline | 1.86 | 2. | 0.11 | 0.2 |
- | Vincent Mai 🇨🇦 | 1132 | 1/4 | ROS-based Lane Following | 1.86 | 2. | 0.11 | 0.4 |
- | Philippe Lacaille | 973 | 1/4 | Dolores' Awakening | 1.86 | 2. | 0.11 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 721 | 1/4 | My modified ROS-based Lane Following | 1.86 | 2. | 0.13 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 810 | 1/4 | My modified ROS-based Lane Following | 1.86 | 2. | 0.13 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1823 | 1/4 | My ROS solution | 1.86 | 2. | 0.14 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 814 | 1/4 | My modified ROS-based Lane Following | 1.86 | 2. | 0.15 | 0. |
- | Orlando Marquez 🇨🇦 | 910 | 1/4 | Imitating | 1.24 | 18. | 0.3 | 0. |
- | Gunshi Gupta 🇨🇦 | 1241 | 1/4 | ROS-based Lane Following | 1.24 | 10. | 0.59 | 3.2 |
- | Mikita Sazanovich 🇷🇺 | 762 | 1/4 | RL solution | 1.24 | 8. | 0.37 | 0.2 |
25 | Krishna Murthy Jatavallabhula 🇨🇦 | 1147 | 1/4 | gym_duckietown + opencv | 1.24 | 8. | 0.39 | 0.2 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1143 | 1/4 | gym_duckietown + opencv | 1.24 | 8. | 0.39 | 0.2 |
- | Gunshi Gupta 🇨🇦 | 1247 | 1/4 | ROS-based Lane Following | 1.24 | 8. | 0.41 | 2.6 |
- | Gunshi Gupta 🇨🇦 | 1236 | 1/4 | ROS-based Lane Following | 1.24 | 8. | 0.5 | 2.8 |
- | Mikita Sazanovich 🇷🇺 | 757 | 1/4 | RL solution | 1.24 | 6. | 0.21 | 1.4 |
- | Mandana Samiei 🇨🇦 | 890 | 1/4 | ROS-based Lane Following | 1.24 | 6. | 0.31 | 0.2 |
- | Tien Nguyen | 1173 | 1/4 | ROS-based Lane Following | 1.24 | 6. | 0.39 | 2.2 |
- | Jonathan Plante 🇨🇦 | 542 | 1/4 | JP pipeline | 1.24 | 4. | 0.05 | 1.8 |
- | Jonathan Plante 🇨🇦 | 579 | 1/4 | JP pipeline | 1.24 | 4. | 0.06 | 0.6 |
- | Jonathan Plante 🇨🇦 | 447 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0. |
- | Liam Paull 🇨🇦 | 1743 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0.2 |
- | Liam Paull 🇨🇦 | 1742 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0.2 |
- | Aleksandar Petrov 🇨🇭 | 779 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0.2 |
- | Jonathan Plante 🇨🇦 | 703 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0.2 |
- | David Abraham | 609 | 1/4 | Random execution | 1.24 | 4. | 0.09 | 0.2 |
- | Jonathan Plante 🇨🇦 | 448 | 1/4 | Random execution | 1.24 | 4. | 0.1 | 0. |
26 | Maxim Kuzmin 🇷🇺 | 395 | 1/4 | Random execution | 1.24 | 4. | 0.1 | 0.2 |
- | Samuel Lavoie | 1030 | 1/4 | Crazy Duke | 1.24 | 4. | 0.1 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 358 | 1/4 | PyTorch template | 1.24 | 4. | 0.1 | 1.2 |
- | Andrea Censi 🇨🇭 | 1271 | 1/4 | Random execution | 1.24 | 4. | 0.11 | 0. |
- | Andrea Censi 🇨🇭 | 795 | 1/4 | Random execution | 1.24 | 4. | 0.11 | 0. |
27 | Zijian Dong 🇨🇳 | 782 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 4. | 0.11 | 0. |
28 | Jahanvi Kolte 🇺🇸 | 422 | 1/4 | Random execution | 1.24 | 4. | 0.11 | 0. |
- | Anton Mashikhin 🇷🇺 | 906 | 1/4 | SAIC MOSCOW MML | 1.24 | 4. | 0.11 | 0.2 |
- | Ruixiang Zhang 🇨🇦 | 466 | 1/4 | Random execution | 1.24 | 4. | 0.11 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 951 | 1/4 | SAIC MOSCOW MML | 1.24 | 4. | 0.11 | 0.4 |
- | Zhenming Yang 🇨🇳 | 1488 | 1/4 | Random execution | 1.24 | 4. | 0.12 | 0. |
- | Andrea Censi 🇨🇭 | 765 | 1/4 | Random execution | 1.24 | 4. | 0.12 | 0. |
- | Liam Paull 🇨🇦 | 389 | 1/4 | Random execution | 1.24 | 4. | 0.12 | 0. |
- | Liam Paull 🇨🇦 | 672 | 1/4 | Random execution | 1.24 | 4. | 0.12 | 0.2 |
- | David Abraham | 624 | 1/4 | PyTorch template | 1.24 | 4. | 0.12 | 1.2 |
- | Ruixiang Zhang 🇨🇦 | 468 | 1/4 | PyTorch template | 1.24 | 4. | 0.12 | 1.2 |
29 | Patrick Pfreundschuh 🇨🇭 | 872 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 4. | 0.13 | 0. |
- | Maxim Kuzmin 🇷🇺 | 394 | 1/4 | Random execution | 1.24 | 4. | 0.13 | 0. |
- | Petra Csereoka 🇷🇴 | 1324 | 1/4 | Random execution | 1.24 | 4. | 0.13 | 0.2 |
30 | Yun Chen 🇨🇦 | 1280 | 1/4 | Random execution | 1.24 | 4. | 0.13 | 0.2 |
- | Yun Chen 🇨🇦 | 690 | 1/4 | Random execution | 1.24 | 4. | 0.13 | 0.2 |
- | Pravish Sainath 🇨🇦 | 954 | 1/4 | PyTorch template | 1.24 | 4. | 0.13 | 1. |
31 | Siyan Zheng 🇺🇸 | 419 | 1/4 | PyTorch template | 1.24 | 4. | 0.13 | 1. |
- | Samuel Lavoie | 607 | 1/4 | PyTorch template | 1.24 | 4. | 0.13 | 1.2 |
- | Pravish Sainath 🇨🇦 | 908 | 1/4 | PyTorch template | 1.24 | 4. | 0.13 | 1.4 |
32 | Iban Harlouchet 🇨🇦 | 651 | 1/4 | PyTorch template | 1.24 | 4. | 0.13 | 1.4 |
- | Julian Zilly | 799 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.14 | 0. |
- | Manish Prajapat | 794 | 1/4 | AMOD18-AIDO | 1.24 | 4. | 0.14 | 0. |
- | David Abraham | 611 | 1/4 | Random execution | 1.24 | 4. | 0.14 | 0. |
33 | Tina Chu | 897 | 1/4 | Random execution | 1.24 | 4. | 0.14 | 0.2 |
34 | Marta Tintore 🇨🇭 | 786 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 4. | 0.14 | 0.2 |
- | Samuel Lavoie | 629 | 1/4 | PyTorch template | 1.24 | 4. | 0.14 | 1. |
- | Orlando Marquez 🇨🇦 | 844 | 1/4 | Imitating | 1.24 | 4. | 0.15 | 0. |
35 | hanxue liang | 784 | 1/4 | Random execution | 1.24 | 4. | 0.15 | 0. |
- | Wei Gao 🇸🇬 | 1498 | 1/4 | First trial | 1.24 | 4. | 0.15 | 0.2 |
- | Dzenan Lapandic | 768 | 1/4 | Random execution | 1.24 | 4. | 0.15 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1821 | 1/4 | My ROS solution | 1.24 | 4. | 0.15 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 595 | 1/4 | PyTorch template | 1.24 | 4. | 0.15 | 1. |
- | Dzenan Lapandic | 1607 | 1/4 | Panos rgb inv_kine manual | 1.24 | 4. | 0.16 | 0. |
- | Tri Cao 🇺🇸 | 1508 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.16 | 0. |
- | Tri Cao 🇺🇸 | 1505 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.16 | 0. |
- | Tri Cao 🇺🇸 | 1398 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.16 | 0. |
- | Tri Cao 🇺🇸 | 1306 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.16 | 0. |
- | Andrea Censi 🇨🇭 | 1314 | 1/4 | Random execution | 1.24 | 4. | 0.16 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1824 | 1/4 | My ROS solution | 1.24 | 4. | 0.16 | 1. |
36 | Laurent Mandrile | 613 | 1/4 | PyTorch template | 1.24 | 4. | 0.16 | 1. |
- | Samuel Lavoie | 1034 | 1/4 | Young Duke | 1.24 | 4. | 0.16 | 1.2 |
37 | Liu Sam 🇹🇼 | 592 | 1/4 | PyTorch template | 1.24 | 4. | 0.16 | 1.2 |
- | Vincent Mai 🇨🇦 | 1088 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.16 | 1.6 |
- | Zhenming Yang 🇨🇳 | 1490 | 1/4 | Random execution | 1.24 | 4. | 0.17 | 0.2 |
38 | Vadim Volodin 🇷🇺 | 680 | 1/4 | Random execution | 1.24 | 4. | 0.17 | 0.2 |
- | Liam Paull 🇨🇦 | 392 | 1/4 | PyTorch template | 1.24 | 4. | 0.17 | 1. |
- | Pravish Sainath 🇨🇦 | 360 | 1/4 | PyTorch template | 1.24 | 4. | 0.17 | 1. |
- | Tri Cao 🇺🇸 | 574 | 1/4 | PyTorch template | 1.24 | 4. | 0.17 | 1.2 |
- | Dzenan Lapandic | 1606 | 1/4 | Panos grayscale inv_kine manual | 1.24 | 4. | 0.18 | 0. |
- | Tri Cao 🇺🇸 | 1379 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.18 | 0. |
39 | Martin Shin 🇭🇰 | 756 | 1/4 | PyTorch template | 1.24 | 4. | 0.18 | 0.8 |
- | Pravish Sainath 🇨🇦 | 355 | 1/4 | PyTorch template | 1.24 | 4. | 0.18 | 1. |
- | Anton Mashikhin 🇷🇺 | 426 | 1/4 | PyTorch template | 1.24 | 4. | 0.18 | 1.4 |
- | Gunshi Gupta 🇨🇦 | 759 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.19 | 0.2 |
- | Laurent Mandrile | 623 | 1/4 | PyTorch template | 1.24 | 4. | 0.19 | 0.8 |
- | Yun Chen 🇨🇦 | 626 | 1/4 | PyTorch template | 1.24 | 4. | 0.19 | 1. |
40 | Suzanne Petryk | 1805 | 1/4 | Solution using imitation learning from logs | 1.24 | 4. | 0.2 | 0. |
- | Tri Cao 🇺🇸 | 1380 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.2 | 0. |
- | Gunshi Gupta 🇨🇦 | 1266 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.2 | 0. |
- | Orlando Marquez 🇨🇦 | 930 | 1/4 | Imitating | 1.24 | 4. | 0.2 | 0. |
- | David Abraham | 605 | 1/4 | Random execution | 1.24 | 4. | 0.2 | 0.2 |
- | Yun Chen 🇨🇦 | 1584 | 1/4 | PyTorch DDPG template | 1.24 | 4. | 0.2 | 0.6 |
- | Orlando Marquez 🇨🇦 | 843 | 1/4 | Imitating | 1.24 | 4. | 0.21 | 0. |
- | Vincent Mai 🇨🇦 | 974 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.22 | 0. |
- | Mikita Sazanovich 🇷🇺 | 642 | 1/4 | Random execution | 1.24 | 4. | 0.24 | 0.2 |
- | Gianmarco Bernasconi | 774 | 1/4 | Not Random execution | 1.24 | 4. | 0.25 | 0.2 |
- | Liam Paull 🇨🇦 | 712 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.26 | 0. |
- | Orlando Marquez 🇨🇦 | 833 | 1/4 | Baseline solution using imitation learning from logs | 1.24 | 4. | 0.26 | 0.2 |
- | Tina Chu | 1307 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.27 | 0. |
- | Iban Harlouchet 🇨🇦 | 1111 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.27 | 0. |
- | Mandana Samiei 🇨🇦 | 699 | 1/4 | ROS-based Lane Following | 1.24 | 4. | 0.3 | 0.4 |
41 | Alessandro Morra | 778 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.04 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 1852 | 1/4 | My ROS solution | 1.24 | 2. | 0.04 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1713 | 1/4 | My ROS solution | 1.24 | 2. | 0.05 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 1702 | 1/4 | My ROS solution | 1.24 | 2. | 0.06 | 0. |
- | Anton Mashikhin 🇷🇺 | 1305 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.06 | 0. |
- | Alessandro Morra | 776 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.06 | 0. |
- | Jonathan Plante 🇨🇦 | 705 | 1/4 | JP pipeline | 1.24 | 2. | 0.06 | 0. |
- | Diego Charrez 🇵🇪 | 1478 | 1/4 | Tensorflow | 1.24 | 2. | 0.06 | 0.2 |
42 | Martin Weiss 🇨🇦 | 1187 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.06 | 0.2 |
- | Martin Weiss 🇨🇦 | 1160 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.06 | 0.2 |
- | Martin Weiss 🇨🇦 | 1149 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.06 | 0.2 |
- | Martin Weiss 🇨🇦 | 1146 | 1/4 | PyTorch template | 1.24 | 2. | 0.06 | 0.2 |
- | Martin Weiss 🇨🇦 | 1138 | 1/4 | PyTorch template | 1.24 | 2. | 0.06 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 854 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.06 | 0.2 |
43 | Cliff Li | 787 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.06 | 0.2 |
- | Cliff Li | 783 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.06 | 0.2 |
44 | Yannick Berdou | 777 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.06 | 0.2 |
45 | Benson Kuan | 769 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.06 | 0.2 |
- | Jonathan Plante 🇨🇦 | 704 | 1/4 | Random execution | 1.24 | 2. | 0.06 | 0.2 |
- | Jonathan Plante 🇨🇦 | 548 | 1/4 | JP pipeline | 1.24 | 2. | 0.06 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 494 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 1.24 | 2. | 0.06 | 0.2 |
- | Jonathan Plante 🇨🇦 | 476 | 1/4 | JP pipeline | 1.24 | 2. | 0.06 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 2041 | 1/4 | My ROS solution | 1.24 | 2. | 0.06 | 0.4 |
- | Vincent Mai 🇨🇦 | 1889 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.07 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 723 | 1/4 | My modified ROS-based Lane Following | 1.24 | 2. | 0.07 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 722 | 1/4 | My modified ROS-based Lane Following | 1.24 | 2. | 0.07 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 2043 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1752 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 0.2 |
- | Wei Gao 🇸🇬 | 1548 | 1/4 | First trial | 1.24 | 2. | 0.07 | 0.2 |
- | Vincent Mai 🇨🇦 | 1215 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.07 | 0.2 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1123 | 1/4 | gym_duckietown + opencv | 1.24 | 2. | 0.07 | 0.2 |
- | Ruixiang Zhang 🇨🇦 | 1056 | 1/4 | stay young | 1.24 | 2. | 0.07 | 0.2 |
- | Ruixiang Zhang 🇨🇦 | 1053 | 1/4 | stay young | 1.24 | 2. | 0.07 | 0.2 |
- | David Abraham | 1051 | 1/4 | Pytorch IL | 1.24 | 2. | 0.07 | 0.2 |
- | David Abraham | 1050 | 1/4 | Pytorch IL | 1.24 | 2. | 0.07 | 0.2 |
- | Philippe Lacaille | 976 | 1/4 | Dolores' Awakening | 1.24 | 2. | 0.07 | 0.2 |
- | Philippe Lacaille | 975 | 1/4 | Dolores' Awakening | 1.24 | 2. | 0.07 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1813 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 2054 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 2044 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1973 | 1/4 | My ROS solution | 1.24 | 2. | 0.07 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1193 | 1/4 | My ROS solution | 1.24 | 2. | 0.08 | 0. |
- | Wei Gao 🇸🇬 | 1547 | 1/4 | First trial | 1.24 | 2. | 0.08 | 0.2 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1133 | 1/4 | gym_duckietown + opencv | 1.24 | 2. | 0.08 | 0.2 |
- | David Abraham | 1105 | 1/4 | Pytorch IL | 1.24 | 2. | 0.08 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 2049 | 1/4 | My ROS solution | 1.24 | 2. | 0.08 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1978 | 1/4 | My ROS solution | 1.24 | 2. | 0.09 | 0. |
- | Vincent Mai 🇨🇦 | 1208 | 1/4 | ROS-based Lane Following | 1.24 | 2. | 0.09 | 0. |
- | Manfred Diaz | 2191 | 1/4 | Tensorflow template | 1.24 | 2. | 0.09 | 0.2 |
- | Wei Gao 🇸🇬 | 1582 | 1/4 | First trial | 1.24 | 2. | 0.09 | 0.2 |
- | Ruixiang Zhang 🇨🇦 | 1109 | 1/4 | stay young | 1.24 | 2. | 0.09 | 0.2 |
- | Philippe Lacaille | 977 | 1/4 | Dolores' Awakening | 1.24 | 2. | 0.09 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1065 | 1/4 | My ROS solution | 1.24 | 2. | 0.09 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 1165 | 1/4 | My ROS solution | 1.24 | 2. | 0.1 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 702 | 1/4 | My modified ROS-based Lane Following | 1.24 | 2. | 0.1 | 0. |
- | Maxim Kuzmin 🇷🇺 | 398 | 1/4 | Random execution | 1.24 | 2. | 0.1 | 0. |
- | Wei Gao 🇸🇬 | 1589 | 1/4 | First trial | 1.24 | 2. | 0.1 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1064 | 1/4 | My ROS solution | 1.24 | 2. | 0.1 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 2039 | 1/4 | My ROS solution | 1.24 | 2. | 0.1 | 0.6 |
46 | Amaury Camus 🇨🇭 | 780 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.1 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 2040 | 1/4 | My ROS solution | 1.24 | 2. | 0.1 | 1. |
- | Benjamin Ramtoula 🇨🇦 | 1096 | 1/4 | My ROS solution | 1.24 | 2. | 0.11 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 1092 | 1/4 | My ROS solution | 1.24 | 2. | 0.11 | 0. |
- | Philippe Lacaille | 971 | 1/4 | Dolores' Awakening | 1.24 | 2. | 0.11 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1830 | 1/4 | My ROS solution | 1.24 | 2. | 0.11 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 850 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.11 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 845 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.11 | 0.6 |
- | Anton Mashikhin 🇷🇺 | 828 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.11 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 2057 | 1/4 | My ROS solution | 1.24 | 2. | 0.11 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 847 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.12 | 0. |
- | Anton Mashikhin 🇷🇺 | 821 | 1/4 | SAIC MOSCOW MML | 1.24 | 2. | 0.12 | 0. |
- | Liam Paull 🇨🇦 | 1785 | 1/4 | Random execution | 1.24 | 2. | 0.12 | 0.2 |
- | Liam Paull 🇨🇦 | 1783 | 1/4 | Random execution | 1.24 | 2. | 0.12 | 0.2 |
- | Liam Paull 🇨🇦 | 1754 | 1/4 | Random execution | 1.24 | 2. | 0.12 | 0.2 |
47 | Edoardo Gabbi 🇮🇹 | 792 | 1/4 | Random execution | 1.24 | 2. | 0.12 | 0.2 |
48 | Tomasz Firynowicz | 772 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.12 | 0.2 |
49 | Simon Schaefer 🇨🇭 | 770 | 1/4 | AMOD18-AIDO not that random execution | 1.24 | 2. | 0.12 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 521 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 1.24 | 2. | 0.12 | 0.8 |
- | Anton Mashikhin 🇷🇺 | 516 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 1.24 | 2. | 0.12 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1851 | 1/4 | My ROS solution | 1.24 | 2. | 0.12 | 1.2 |
- | Benjamin Ramtoula 🇨🇦 | 2037 | 1/4 | My ROS solution | 1.24 | 2. | 0.14 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1055 | 1/4 | My ROS solution - param 3 | 0.62 | 18. | 0.07 | 16. |
- | Mikita Sazanovich 🇷🇺 | 754 | 1/4 | PyTorch DDPG template | 0.62 | 18. | 0.16 | 0. |
- | Mikita Sazanovich 🇷🇺 | 755 | 1/4 | RL solution | 0.62 | 18. | 0.28 | 0. |
- | Jonathan Plante 🇨🇦 | 550 | 1/4 | JP pipeline | 0.62 | 18. | 0.4 | 0. |
- | David Abraham | 1246 | 1/4 | Pytorch IL | 0.62 | 18. | 0.42 | 11.4 |
- | Ruixiang Zhang 🇨🇦 | 1000 | 1/4 | stay simple | 0.62 | 18. | 0.45 | 8. |
- | Ruixiang Zhang 🇨🇦 | 915 | 1/4 | stay simple | 0.62 | 18. | 0.45 | 8. |
- | Mikita Sazanovich 🇷🇺 | 717 | 1/4 | PyTorch DDPG template | 0.62 | 18. | 0.45 | 8. |
50 | Anna Tsalapova 🇷🇺 | 1913 | 1/4 | Copy of #50: sub 396 by anna.tsalapova (simple submition) | 0.62 | 18. | 0.89 | 0. |
- | Vadim Volodin 🇷🇺 | 397 | 1/4 | Random execution | 0.62 | 18. | 0.89 | 0. |
- | Anna Tsalapova 🇷🇺 | 396 | 1/4 | simple submition | 0.62 | 18. | 0.89 | 0. |
- | Andrea Censi 🇨🇭 | 1912 | 1/4 | Copy of #50: sub 396 by anna.tsalapova (simple submition) | 0.62 | 18. | 0.98 | 0. |
51 | ????????? ??????? | 428 | 1/4 | Random execution | 0.62 | 18. | 0.98 | 0. |
- | Anton Mashikhin 🇷🇺 | 849 | 1/4 | SAIC MOSCOW MML | 0.62 | 14. | 0.18 | 10.4 |
- | Anton Mashikhin 🇷🇺 | 737 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 12. | 0.15 | 8. |
- | Anton Mashikhin 🇷🇺 | 732 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 12. | 0.15 | 8. |
- | Anton Mashikhin 🇷🇺 | 731 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 12. | 0.15 | 8. |
- | Jonathan Plante 🇨🇦 | 485 | 1/4 | JP pipeline | 0.62 | 12. | 0.55 | 5.8 |
- | Jonathan Plante 🇨🇦 | 489 | 1/4 | JP pipeline | 0.62 | 8. | 0.1 | 1.2 |
- | Jonathan Plante 🇨🇦 | 488 | 1/4 | JP pipeline | 0.62 | 8. | 0.1 | 1.2 |
- | Jonathan Plante 🇨🇦 | 479 | 1/4 | JP pipeline | 0.62 | 8. | 0.23 | 0.8 |
- | Jonathan Plante 🇨🇦 | 478 | 1/4 | JP pipeline | 0.62 | 8. | 0.38 | 0.8 |
- | Jonathan Plante 🇨🇦 | 504 | 1/4 | JP pipeline | 0.62 | 6. | 0.01 | 4.4 |
- | Jonathan Plante 🇨🇦 | 507 | 1/4 | JP pipeline | 0.62 | 6. | 0.01 | 4.6 |
- | Jonathan Plante 🇨🇦 | 506 | 1/4 | JP pipeline | 0.62 | 6. | 0.01 | 4.6 |
- | Jonathan Plante 🇨🇦 | 508 | 1/4 | JP pipeline | 0.62 | 6. | 0.03 | 1.4 |
- | Jonathan Plante 🇨🇦 | 517 | 1/4 | JP pipeline | 0.62 | 6. | 0.08 | 4.6 |
- | Philippe Lacaille | 917 | 1/4 | Dolores' Awakening | 0.62 | 6. | 0.27 | 0. |
- | Jonathan Plante 🇨🇦 | 537 | 1/4 | JP pipeline | 0.62 | 4. | 0.05 | 2. |
- | Jonathan Plante 🇨🇦 | 484 | 1/4 | JP pipeline | 0.62 | 4. | 0.06 | 0.8 |
- | Andrea Censi 🇨🇭 | 740 | 1/4 | Copy of #15: sub 574 by trimcao (PyTorch template) | 0.62 | 4. | 0.06 | 1. |
- | David Abraham | 1158 | 1/4 | Pytorch IL | 0.62 | 4. | 0.07 | 2.8 |
- | David Abraham | 1153 | 1/4 | Pytorch IL | 0.62 | 4. | 0.07 | 3.6 |
- | Pravish Sainath 🇨🇦 | 364 | 1/4 | PyTorch template | 0.62 | 4. | 0.08 | 1. |
- | Bhairav Mehta | 356 | 1/4 | PyTorch DDPG template | 0.62 | 4. | 0.08 | 1.2 |
- | Samuel Lavoie | 606 | 1/4 | PyTorch template | 0.62 | 4. | 0.08 | 1.4 |
- | Orlando Marquez 🇨🇦 | 928 | 1/4 | Imitating | 0.62 | 4. | 0.09 | 0.2 |
- | Laurent Mandrile | 616 | 1/4 | PyTorch template | 0.62 | 4. | 0.09 | 1. |
- | Jonathan Plante 🇨🇦 | 584 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1. |
- | Jonathan Plante 🇨🇦 | 667 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.2 |
- | Jonathan Plante 🇨🇦 | 635 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.2 |
- | Jonathan Plante 🇨🇦 | 583 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.2 |
- | Jonathan Plante 🇨🇦 | 582 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.2 |
- | Jonathan Plante 🇨🇦 | 512 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.2 |
- | Jonathan Plante 🇨🇦 | 514 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 1.4 |
- | Benjamin Ramtoula 🇨🇦 | 959 | 1/4 | My ROS solution - param 1 | 0.62 | 4. | 0.09 | 1.6 |
- | Jonathan Plante 🇨🇦 | 503 | 1/4 | JP pipeline | 0.62 | 4. | 0.09 | 3.4 |
- | Jonathan Plante 🇨🇦 | 637 | 1/4 | JP pipeline | 0.62 | 4. | 0.1 | 1.2 |
- | Jonathan Plante 🇨🇦 | 636 | 1/4 | JP pipeline | 0.62 | 4. | 0.1 | 1.2 |
52 | Aoming Liu | 788 | 1/4 | Random execution | 0.62 | 4. | 0.11 | 0.2 |
- | Mikita Sazanovich 🇷🇺 | 655 | 1/4 | DDPG | 0.62 | 4. | 0.11 | 0.8 |
- | Gunshi Gupta 🇨🇦 | 1260 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.11 | 1.6 |
53 | Eric Lu | 1311 | 1/4 | Baseline solution using imitation learning from logs | 0.62 | 4. | 0.12 | 0. |
- | Iban Harlouchet 🇨🇦 | 660 | 1/4 | PyTorch template | 0.62 | 4. | 0.12 | 1. |
- | Orlando Marquez 🇨🇦 | 926 | 1/4 | Imitating | 0.62 | 4. | 0.12 | 1.6 |
- | Julian Zilly | 767 | 1/4 | Tuned lane controller - ETHZ baseline extension | 0.62 | 4. | 0.13 | 0.2 |
- | Mandana Samiei 🇨🇦 | 423 | 1/4 | PyTorch template | 0.62 | 4. | 0.14 | 0.8 |
- | Gunshi Gupta 🇨🇦 | 1234 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.14 | 1.4 |
- | Samuel Lavoie | 614 | 1/4 | PyTorch template | 0.62 | 4. | 0.16 | 1.2 |
- | Hristo Vrigazov 🇧🇬 | 938 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.17 | 0. |
- | Gunshi Gupta 🇨🇦 | 1249 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.17 | 1. |
- | Orlando Marquez 🇨🇦 | 1155 | 1/4 | Imitating | 0.62 | 4. | 0.19 | 0.6 |
- | Mikita Sazanovich 🇷🇺 | 1377 | 1/4 | RL solution | 0.62 | 4. | 0.2 | 1.6 |
- | Gunshi Gupta 🇨🇦 | 1245 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.25 | 1.2 |
- | Gunshi Gupta 🇨🇦 | 1237 | 1/4 | ROS-based Lane Following | 0.62 | 4. | 0.25 | 1.2 |
- | David Abraham | 1043 | 1/4 | Pytorch IL | 0.62 | 2. | 0.02 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 1301 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.03 | 0. |
- | Orlando Marquez 🇨🇦 | 1039 | 1/4 | Imitating | 0.62 | 2. | 0.03 | 0. |
- | David Abraham | 1015 | 1/4 | Pytorch IL | 0.62 | 2. | 0.03 | 0. |
- | Bhairav Mehta | 432 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.03 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 2067 | 1/4 | My ROS solution | 0.62 | 2. | 0.03 | 0.4 |
- | Martin Weiss 🇨🇦 | 1107 | 1/4 | PyTorch template | 0.62 | 2. | 0.03 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 674 | 1/4 | PyTorch template | 0.62 | 2. | 0.03 | 0.4 |
- | Gunshi Gupta 🇨🇦 | 1258 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.04 | 0. |
- | Gunshi Gupta 🇨🇦 | 1255 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.04 | 0. |
- | Mandana Samiei 🇨🇦 | 1219 | 1/4 | Improved ROS-based Lane Following | 0.62 | 2. | 0.04 | 0. |
- | Orlando Marquez 🇨🇦 | 1016 | 1/4 | Imitating | 0.62 | 2. | 0.04 | 0. |
- | Mandana Samiei 🇨🇦 | 885 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.04 | 0. |
- | Anton Mashikhin 🇷🇺 | 523 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.04 | 0. |
- | Jonathan Plante 🇨🇦 | 465 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.04 | 0. |
- | Tri Cao 🇺🇸 | 1525 | 1/4 | Baseline solution using imitation learning from logs | 0.62 | 2. | 0.04 | 0.2 |
- | Pravish Sainath 🇨🇦 | 1217 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.2 |
- | Pravish Sainath 🇨🇦 | 1091 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.2 |
- | Benjamin Ramtoula 🇨🇦 | 1820 | 1/4 | My ROS solution | 0.62 | 2. | 0.04 | 0.4 |
- | Diego Charrez 🇵🇪 | 1604 | 1/4 | Tensorflow | 0.62 | 2. | 0.04 | 0.4 |
- | Diego Charrez 🇵🇪 | 1603 | 1/4 | Tensorflow | 0.62 | 2. | 0.04 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 1159 | 1/4 | My ROS solution | 0.62 | 2. | 0.04 | 0.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1127 | 1/4 | gym_duckietown + opencv | 0.62 | 2. | 0.04 | 0.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1126 | 1/4 | gym_duckietown + opencv | 0.62 | 2. | 0.04 | 0.4 |
- | Mandana Samiei 🇨🇦 | 878 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 536 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.4 |
- | Liam Paull 🇨🇦 | 408 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.4 |
- | Tien Nguyen | 1166 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.04 | 0.6 |
- | Laurent Mandrile | 1002 | 1/4 | Tensorflow template | 0.62 | 2. | 0.04 | 0.6 |
- | Samuel Lavoie | 808 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.04 | 0.6 |
- | Iban Harlouchet 🇨🇦 | 653 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.04 | 0.6 |
- | Diego Charrez 🇵🇪 | 1583 | 1/4 | Tensorflow | 0.62 | 2. | 0.05 | 0. |
- | Bhairav Mehta | 1242 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.05 | 0. |
- | Iban Harlouchet 🇨🇦 | 1152 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.05 | 0. |
- | David Abraham | 1044 | 1/4 | Pytorch IL | 0.62 | 2. | 0.05 | 0. |
- | Mikita Sazanovich 🇷🇺 | 839 | 1/4 | RL solution | 0.62 | 2. | 0.05 | 0. |
- | Mikita Sazanovich 🇷🇺 | 838 | 1/4 | RL solution | 0.62 | 2. | 0.05 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 693 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.05 | 0. |
- | Mandana Samiei 🇨🇦 | 691 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.05 | 0. |
- | Anton Mashikhin 🇷🇺 | 498 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.05 | 0. |
- | Bhairav Mehta | 415 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.05 | 0.2 |
- | Diego Charrez 🇵🇪 | 1477 | 1/4 | Tensorflow | 0.62 | 2. | 0.05 | 0.4 |
- | David Abraham | 1046 | 1/4 | Pytorch IL | 0.62 | 2. | 0.05 | 0.4 |
- | Mandana Samiei 🇨🇦 | 424 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.05 | 0.4 |
- | Bhairav Mehta | 386 | 1/4 | PyTorch DDPG baseline | 0.62 | 2. | 0.05 | 0.4 |
- | Bhairav Mehta | 346 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.05 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 2052 | 1/4 | My ROS solution | 0.62 | 2. | 0.05 | 0.6 |
- | Liam Paull 🇨🇦 | 410 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.05 | 0.6 |
- | Liam Paull 🇨🇦 | 1741 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.06 | 0. |
- | Yun Chen 🇨🇦 | 841 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.06 | 0. |
- | Philippe Lacaille | 742 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.06 | 0. |
- | Anton Mashikhin 🇷🇺 | 627 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.06 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 2065 | 1/4 | My ROS solution | 0.62 | 2. | 0.06 | 0.2 |
- | Philippe Lacaille | 979 | 1/4 | Dolores' Awakening | 0.62 | 2. | 0.06 | 0.4 |
- | Jonathan Plante 🇨🇦 | 578 | 1/4 | JP pipeline | 0.62 | 2. | 0.06 | 0.4 |
- | Jonathan Plante 🇨🇦 | 558 | 1/4 | JP pipeline | 0.62 | 2. | 0.06 | 0.4 |
- | Jonathan Plante 🇨🇦 | 553 | 1/4 | JP pipeline | 0.62 | 2. | 0.06 | 0.4 |
- | Philippe Lacaille | 417 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.06 | 0.4 |
- | Jonathan Plante 🇨🇦 | 573 | 1/4 | JP pipeline | 0.62 | 2. | 0.06 | 0.6 |
- | Jonathan Plante 🇨🇦 | 554 | 1/4 | JP pipeline | 0.62 | 2. | 0.06 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 1853 | 1/4 | My ROS solution | 0.62 | 2. | 0.06 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1822 | 1/4 | My ROS solution | 0.62 | 2. | 0.07 | 0. |
- | Tri Cao 🇺🇸 | 1510 | 1/4 | Baseline solution using imitation learning from logs | 0.62 | 2. | 0.07 | 0. |
- | Anton Mashikhin 🇷🇺 | 1302 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.07 | 0. |
- | Tien Nguyen | 1176 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.07 | 0. |
- | Iban Harlouchet 🇨🇦 | 1142 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.07 | 0. |
54 | Luca Bonamini | 798 | 1/4 | Random execution | 0.62 | 2. | 0.07 | 0. |
- | Mandana Samiei 🇨🇦 | 639 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.07 | 0. |
- | Mandana Samiei 🇨🇦 | 1206 | 1/4 | Improved ROS-based solution | 0.62 | 2. | 0.07 | 0.2 |
- | Jonathan Plante 🇨🇦 | 556 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 0.2 |
- | Gunshi Gupta 🇨🇦 | 661 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.07 | 0.4 |
- | Jonathan Plante 🇨🇦 | 552 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 0.4 |
- | Bhairav Mehta | 385 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.07 | 0.6 |
- | Bhairav Mehta | 369 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.07 | 0.6 |
- | Liam Paull 🇨🇦 | 1787 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.07 | 0.8 |
- | Pravish Sainath 🇨🇦 | 919 | 1/4 | PyTorch template | 0.62 | 2. | 0.07 | 0.8 |
- | Jonathan Plante 🇨🇦 | 568 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 0.8 |
- | Jonathan Plante 🇨🇦 | 564 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 0.8 |
- | Jonathan Plante 🇨🇦 | 530 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 0.8 |
- | Jonathan Plante 🇨🇦 | 566 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 1. |
- | Jonathan Plante 🇨🇦 | 562 | 1/4 | JP pipeline | 0.62 | 2. | 0.07 | 1. |
- | Liam Paull 🇨🇦 | 1756 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Gunshi Gupta 🇨🇦 | 1263 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Gunshi Gupta 🇨🇦 | 1228 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Tien Nguyen | 1223 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Iban Harlouchet 🇨🇦 | 1197 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Iban Harlouchet 🇨🇦 | 1172 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 1164 | 1/4 | My Improved ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 1161 | 1/4 | My Improved ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 871 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Philippe Lacaille | 870 | 1/4 | Dolores' Awakening | 0.62 | 2. | 0.08 | 0. |
- | Bhairav Mehta | 869 | 1/4 | Dolores' Awakening | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 867 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Philippe Lacaille | 864 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Bhairav Mehta | 806 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 720 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 679 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Mandana Samiei 🇨🇦 | 638 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
- | Bhairav Mehta | 413 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0. |
55 | Aneri Muni | 781 | 1/4 | AMOD18-AIDO not that random execution | 0.62 | 2. | 0.08 | 0.2 |
- | Maxim Kuzmin 🇷🇺 | 681 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.08 | 0.2 |
- | Jonathan Plante 🇨🇦 | 576 | 1/4 | JP pipeline | 0.62 | 2. | 0.08 | 0.4 |
- | Bhairav Mehta | 376 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.08 | 0.4 |
- | Benjamin Ramtoula 🇨🇦 | 2050 | 1/4 | My ROS solution | 0.62 | 2. | 0.08 | 0.6 |
- | Gunshi Gupta 🇨🇦 | 1233 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.08 | 0.6 |
- | Jonathan Plante 🇨🇦 | 571 | 1/4 | JP pipeline | 0.62 | 2. | 0.08 | 0.8 |
- | Bhairav Mehta | 349 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.08 | 1. |
56 | Wenhui Zhang 🇺🇸 | 1386 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Gunshi Gupta 🇨🇦 | 1261 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Gunshi Gupta 🇨🇦 | 1256 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Tien Nguyen | 1221 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Mandana Samiei 🇨🇦 | 1220 | 1/4 | Improved ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Iban Harlouchet 🇨🇦 | 1184 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Tien Nguyen | 1178 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Mandana Samiei 🇨🇦 | 1061 | 1/4 | bazinga!!! | 0.62 | 2. | 0.09 | 0. |
- | Mandana Samiei 🇨🇦 | 1059 | 1/4 | bazinga!!! | 0.62 | 2. | 0.09 | 0. |
- | Mandana Samiei 🇨🇦 | 866 | 1/4 | Improved ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Philippe Lacaille | 751 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Vadim Volodin 🇷🇺 | 714 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Anna Tsalapova 🇷🇺 | 686 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Vadim Volodin 🇷🇺 | 683 | 1/4 | Random execution | 0.62 | 2. | 0.09 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 416 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.09 | 0. |
- | Allen Ou | 589 | 1/4 | Random execution | 0.62 | 2. | 0.09 | 0.2 |
- | Anton Mashikhin 🇷🇺 | 675 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 534 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 531 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 527 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 526 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 525 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 524 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Anton Mashikhin 🇷🇺 | 493 | 1/4 | AI DL RL MML XXXL 2k18 yoo | 0.62 | 2. | 0.09 | 0.4 |
- | Liam Paull 🇨🇦 | 1395 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.09 | 0.6 |
- | Jonathan Plante 🇨🇦 | 581 | 1/4 | JP pipeline | 0.62 | 2. | 0.09 | 0.8 |
- | Jonathan Plante 🇨🇦 | 580 | 1/4 | JP pipeline | 0.62 | 2. | 0.09 | 0.8 |
57 | Guoxiang Zhou | 1534 | 1/4 | Random execution | 0.62 | 2. | 0.1 | 0. |
- | Bhairav Mehta | 1239 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Iban Harlouchet 🇨🇦 | 1212 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Mandana Samiei 🇨🇦 | 1052 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Gianmarco Bernasconi | 817 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Mikita Sazanovich 🇷🇺 | 789 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Vincent Mai 🇨🇦 | 746 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 713 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 695 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Mandana Samiei 🇨🇦 | 692 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0. |
- | Jonathan Plante 🇨🇦 | 539 | 1/4 | Random execution | 0.62 | 2. | 0.1 | 0. |
- | Liam Paull 🇨🇦 | 1749 | 1/4 | Template for ROS Submission | 0.62 | 2. | 0.1 | 0.2 |
- | Andrea Censi 🇨🇭 | 1270 | 1/4 | Random execution | 0.62 | 2. | 0.1 | 0.2 |
- | David Abraham | 608 | 1/4 | Random execution | 0.62 | 2. | 0.1 | 0.2 |
- | Gunshi Gupta 🇨🇦 | 1238 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.1 | 0.8 |
- | Benjamin Ramtoula 🇨🇦 | 1788 | 1/4 | My ROS solution | 0.62 | 2. | 0.11 | 0. |
- | Yun Chen 🇨🇦 | 1279 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Gunshi Gupta 🇨🇦 | 1265 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Philippe Lacaille | 875 | 1/4 | Dolores' Awakening | 0.62 | 2. | 0.11 | 0. |
- | Gunshi Gupta 🇨🇦 | 818 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 719 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Mandana Samiei 🇨🇦 | 715 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 711 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 698 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Mandana Samiei 🇨🇦 | 678 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Dzenan Lapandic | 513 | 1/4 | Baseline solution using imitation learning from logs | 0.62 | 2. | 0.11 | 0. |
- | Mandana Samiei 🇨🇦 | 490 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Mandana Samiei 🇨🇦 | 460 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Bhairav Mehta | 414 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.11 | 0. |
- | Jonathan Plante 🇨🇦 | 538 | 1/4 | Random execution | 0.62 | 2. | 0.11 | 0.2 |
- | Amaury Camus 🇨🇭 | 773 | 1/4 | AMOD18-AIDO not that random execution | 0.62 | 2. | 0.11 | 0.4 |
- | David Abraham | 615 | 1/4 | PyTorch template | 0.62 | 2. | 0.11 | 0.8 |
- | Jonathan Plante 🇨🇦 | 570 | 1/4 | JP pipeline | 0.62 | 2. | 0.11 | 1. |
- | Gunshi Gupta 🇨🇦 | 1259 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Iban Harlouchet 🇨🇦 | 1162 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Mandana Samiei 🇨🇦 | 1156 | 1/4 | My Improved ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Bhairav Mehta | 868 | 1/4 | Dolores' Awakening | 0.62 | 2. | 0.12 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 710 | 1/4 | My modified ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Anna Tsalapova 🇷🇺 | 685 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Maxim Kuzmin 🇷🇺 | 684 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Gunshi Gupta 🇨🇦 | 676 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.12 | 0. |
- | Gunshi Gupta 🇨🇦 | 1264 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.13 | 0. |
- | Bhairav Mehta | 1262 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.13 | 0. |
- | Tien Nguyen | 1222 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.13 | 0. |
- | Hristo Vrigazov 🇧🇬 | 933 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.14 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 886 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.14 | 0. |
- | Siyan Zheng 🇺🇸 | 487 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.14 | 0. |
- | Yun Chen 🇨🇦 | 1554 | 1/4 | PyTorch DDPG template | 0.62 | 2. | 0.14 | 0.4 |
- | Iban Harlouchet 🇨🇦 | 1175 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.15 | 0. |
- | Mandana Samiei 🇨🇦 | 682 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.15 | 0. |
- | Hristo Vrigazov 🇧🇬 | 456 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.15 | 0. |
- | Iban Harlouchet 🇨🇦 | 1207 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Tien Nguyen | 1177 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Iban Harlouchet 🇨🇦 | 1150 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Vincent Mai 🇨🇦 | 969 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Philippe Lacaille | 801 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Maxim Kuzmin 🇷🇺 | 761 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Mandana Samiei 🇨🇦 | 696 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Mandana Samiei 🇨🇦 | 688 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.16 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 438 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.17 | 0. |
- | Tien Nguyen | 1224 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Iban Harlouchet 🇨🇦 | 1210 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Tien Nguyen | 1181 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Tien Nguyen | 1179 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Vincent Mai 🇨🇦 | 972 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Vincent Mai 🇨🇦 | 748 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Mandana Samiei 🇨🇦 | 652 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.18 | 0. |
- | Iban Harlouchet 🇨🇦 | 1124 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.19 | 0. |
- | Julian Zilly | 646 | 1/4 | ROS-based Lane Following | 0.62 | 2. | 0.19 | 0. |
- | Benjamin Ramtoula 🇨🇦 | 812 | 1/4 | My modified ROS-based Lane Following | -0. | 18. | 0.36 | 8.4 |
- | Yun Chen 🇨🇦 | 1619 | 1/4 | PyTorch DDPG template | -0. | 18. | 0.42 | 8.4 |
- | Diego Charrez 🇵🇪 | 1975 | 1/4 | PyTorch Sagemaker template | -0. | 18. | 0.43 | 8.4 |
- | Diego Charrez 🇵🇪 | 1887 | 1/4 | PyTorch Sagemaker template | -0. | 18. | 0.43 | 8.4 |
- | Yun Chen 🇨🇦 | 1654 | 1/4 | PyTorch DDPG template | -0. | 18. | 0.43 | 8.4 |
- | Yun Chen 🇨🇦 | 1635 | 1/4 | PyTorch DDPG template | -0. | 18. | 0.43 | 8.4 |
- | Yun Chen 🇨🇦 | 1630 | 1/4 | PyTorch DDPG template | -0. | 18. | 0.43 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1119 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.43 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1113 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.43 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1112 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.43 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1100 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.43 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1148 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.46 | 8.4 |
- | Krishna Murthy Jatavallabhula 🇨🇦 | 1135 | 1/4 | gym_duckietown + opencv | -0. | 18. | 0.46 | 8.4 |
- | Benjamin Ramtoula 🇨🇦 | 813 | 1/4 | My modified ROS-based Lane Following | -0. | 18. | 0.52 | 8.4 |
- | Jonathan Plante 🇨🇦 | 842 | 1/4 | JP Pipeline | -0. | 18. | 0.68 | 0. |
- | David Abraham | 1014 | 1/4 | Pytorch IL | -0. | 18. | 1.23 | 8. |
- | shandonguniversity &&Inspur 🇨🇳 | 1481 | 1/4 | Nvidia CNN | -0. | 4. | 0.01 | 2. |
- | Inspur- team 🇨🇳 | 1394 | 1/4 | Nvidia CNN | -0. | 4. | 0.01 | 2. |
- | Benjamin Ramtoula 🇨🇦 | 961 | 1/4 | My ROS solution - param 3 | -0. | 2. | 0.04 | 0.6 |
- | Benjamin Ramtoula 🇨🇦 | 960 | 1/4 | My ROS solution - param 2 | -0. | 2. | 0.06 | 0.6 |
- | Pravish Sainath 🇨🇦 | 1047 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.5 | 8.2 |
- | Yun Chen 🇨🇦 | 1569 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.52 | 8.2 |
- | Yun Chen 🇨🇦 | 1248 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.64 | 8.4 |
- | Pravish Sainath 🇨🇦 | 1049 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.76 | 8. |
- | Yun Chen 🇨🇦 | 1281 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.82 | 8.4 |
- | Ruixiang Zhang 🇨🇦 | 902 | 1/4 | PyTorch DDPG template | -0.62 | 18. | 0.91 | 8.6 |
- | Florian Golemo | 1321 | 1/4 | PyTorch DDPG template | -0.62 | 16. | 0.89 | 7.8 |
- | Anton Mashikhin 🇷🇺 | 628 | 1/4 | AI DL RL MML XXXL 2k18 yoo | -1.86 | 18. | 0.21 | 8.4 |
- | Anton Mashikhin 🇷🇺 | 522 | 1/4 | AI DL RL MML XXXL 2k18 yoo | -1.86 | 18. | 0.22 | 8.4 |
- | Anton Mashikhin 🇷🇺 | 495 | 1/4 | AI DL RL MML XXXL 2k18 yoo | -1.86 | 18. | 0.22 | 8.4 |
- | Yun Chen 🇨🇦 | 1282 | 1/4 | PyTorch template | -2.48 | 18. | 0.26 | 8.4 |
- | Ruixiang Zhang 🇨🇦 | 1201 | 1/4 | stay young | -2.48 | 18. | 0.26 | 8.4 |
58 | Jason Chun Lok Li 🇭🇰 | 956 | 1/4 | PyTorch template | -2.48 | 18. | 0.26 | 8.4 |
- | Pravish Sainath 🇨🇦 | 955 | 1/4 | PyTorch template | -2.48 | 18. | 0.26 | 8.4 |
- | Martin Weiss 🇨🇦 | 894 | 1/4 | PyTorch template | -2.48 | 18. | 0.26 | 8.4 |