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@tonycaisy
tonycaisy committed May 21, 2024
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Expand Up @@ -26,39 +26,14 @@ Dive into our demos to see the agent skillfully navigating challenges and ensuri
We train DreamerV3 agents on our built-in tasks with a single 4090. Depending on the observation spaces, the memory overhead ranges from 10GB-20GB alongwith 3GB reserved for CARLA.

<table style="margin-left: auto; margin-right: auto;">
<tr>
<td class="center-text">Right turn hard</td>
<td class="center-text">Roundabout</td>
<td class="center-text">Left turn hard</td>
<td class="center-text">Lane merge</td>
<td class="center-text">Overtake</td>
</tr>
<tr>
<td><img src="./.assets/right_turn_hard.gif" style="width: 100%"></td>
<td><img src="./.assets/roundabout.gif" style="width: 100%"></td>
<td><img src="./.assets/left_turn_hard.gif" style="width: 100%"></td>
<td><img src="./.assets/lane_merge.gif" style="width: 100%"></td>
<td><img src="./.assets/overtake.gif" style="width: 100%"></td>
</tr>
</table>
| Right turn hard | Roundabout | Left turn hard | Lane merge | Overtake |
| :-------------: | :--------: | :------------: | :--------: | :------: |
| ![Right turn hard](./.assets/right_turn_hard.gif) | ![Roundabout](./.assets/roundabout.gif) | ![Left turn hard](./.assets/left_turn_hard.gif) | ![Lane merge](./.assets/lane_merge.gif) | ![Overtake](./.assets/overtake.gif) |

| Right turn hard | Roundabout | Left turn hard | Lane merge | Right turn simple |
| :-------------: | :--------: | :------------: | :--------: | :---------------: |
| ![Right turn hard](./.assets/right_turn_hard_camera.gif) | ![Roundabout](./.assets/roundabout_camera.gif) | ![Left turn hard](./.assets/left_turn_hard_camera.gif) | ![Lane merge](./.assets/lane_merge_camera.gif) | ![Right turn simple](./.assets/right_turn_simple_camera.gif) |

<table style="margin-left: auto; margin-right: auto;">
<tr>
<td class="center-text">Right turn hard</td>
<td class="center-text">Roundabout</td>
<td class="center-text">Left turn hard</td>
<td class="center-text">Lane merge</td>
<td class="center-text">Right turn simple</td>
</tr>
<tr>
<td><img src="./.assets/right_turn_hard_camera.gif" style="width: 100%"></td>
<td><img src="./.assets/roundabout_camera.gif" style="width: 100%"></td>
<td><img src="./.assets/left_turn_hard_camera.gif" style="width: 100%"></td>
<td><img src="./.assets/lane_merge_camera.gif" style="width: 100%"></td>
<td><img src="./.assets/right_turn_simple_camera.gif" style="width: 100%"></td>
</tr>
</table>

## :blossom: The Power of Intention Sharing

Expand All @@ -67,16 +42,20 @@ We train DreamerV3 agents on our built-in tasks with a single 4090. Depending on
Let's see how CarDreamer agents communicate and leverage intentions. Our experiment have demonstrated that through sharing intention, the policy learning is much easier! Specifically, a policy without knowing other agents' intentions can be conservative in our crossroad tasks; while intention sharing allows the agents to find the proper timing to cut in the traffic flow.

<table style="margin-left: auto; margin-right: auto;">
<tr>
<td class="center-text">Sharing waypoints vs. Without sharing waypoints</td>
<td class="center-text">Sharing waypoints vs. Without sharing waypoints</td>
</tr>
<tr>
<td><img src="./.assets/right_turn_hard.gif" style="width: 100%">&emsp;&emsp;&emsp;&emsp;&emsp;<img src="./.assets/right_turn_hard_no_wpt.gif" style="width: 100%"></td>
<td><img src="./.assets/left_turn_hard.gif" style="width: 100%">&emsp;&emsp;&emsp;&emsp;&emsp;<img src="./.assets/left turn raw.gif" style="width: 100%"></td>
</tr>
</table>

<!-- Table 1: Sharing waypoints vs. Without sharing waypoints -->
| Sharing waypoints vs. Without sharing waypoints | Sharing waypoints vs. Without sharing waypoints |
| :---------------------------------------------: | :---------------------------------------------: |
| **Right turn hard** | **Left turn hard** |
| ![Right turn hard](./.assets/right_turn_hard.gif) &emsp;&emsp;&emsp; ![Right turn hard no waypoint](./.assets/right_turn_hard_no_wpt.gif) | ![Left turn hard](./.assets/left_turn_hard.gif) &emsp;&emsp;&emsp;<img src="./.assets/left turn raw.gif" style="width: 100%"> |

<!-- Table 2: Full observability vs. Partial observability -->
| Full observability vs. Partial observability |
| :------------------------------------------: |
| **Right turn hard** |
| ![Right turn hard](./.assets/right_turn_hard.gif) &emsp;&emsp;&emsp; ![Right turn hard FOV](./.assets/right_turn_hard_fov.gif) |





Expand Down Expand Up @@ -179,6 +158,13 @@ If you find this repository useful, please cite this paper:
<sub><b>Shuangyu Cai</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/HanchuZhou">
<img src="https://avatars.githubusercontent.com/u/99316745?v=4" width="100;" alt="HanchuZhou"/>
<br />
<sub><b>Hanchu Zhou</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/gaodechen">
<img src="https://avatars.githubusercontent.com/u/2103562?v=4" width="100;" alt="gaodechen"/>
Expand All @@ -193,13 +179,6 @@ If you find this repository useful, please cite this paper:
<sub><b>junshanzhangJZ2080</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/HanchuZhou">
<img src="https://avatars.githubusercontent.com/u/99316745?v=4" width="100;" alt="HanchuZhou"/>
<br />
<sub><b>Hanchu Zhou</b></sub>
</a>
</td>
<td align="center">
<a href="https://github.com/ustcmike">
<img src="https://avatars.githubusercontent.com/u/32145615?v=4" width="100;" alt="ustcmike"/>
Expand Down

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