# parksim

**Repository Path**: q5yy/parksim

## Basic Information

- **Project Name**: parksim
- **Description**: No description available
- **Primary Language**: Unknown
- **License**: GPL-3.0
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2025-01-03
- **Last Updated**: 2025-01-03

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# ParkSim
![](https://img.shields.io/badge/language-python-blue)
![](https://img.shields.io/github/license/XuShenLZ/ParkSim)
![](https://img.shields.io/badge/ROS-foxy-red)

Vehicle simualtion and behavior prediction in parking lots.

Authors: Xu Shen (xu_shen@berkeley.edu), Alex Wong, Neelay Velingker, Matthew Lacayo, Nidhir Guggilla

## Install
1. Clone this repo
2. In the `/python` folder of this repo, do `pip install -e .` (A virtualenv is recommended)
3. If components of [DLP dataset](https://github.com/MPC-Berkeley/dlp-dataset) is needed, install the DLP package and request data according to the instructions there.
4. If [pytorch](https://pytorch.org/) is needed, please install the correct version based on your OS and hardware.
5. We use [ROS2 Foxy](https://docs.ros.org/en/foxy/index.html) for simulation. You would need that installed if you want to run vehicle simulation.

## [ParkPredict+](https://arxiv.org/abs/2204.10777)

ParkPredict+: Multimodal Intent and Motion Prediction for Vehicles in Parking Lots with CNN and Transformer

Authors: Xu Shen, Matthew Lacayo, Nidhir Guggilla, Francesco Borrelli

> **Note**: You don't need ROS for ParkPredict+.

<div align=center>
<img height="300" src="docs/multimodal_1.gif"/>  <img height="300" src="docs/multimodal_2.gif"/>
<img height="300" src="docs/multimodal_3.gif"/>  <img height="300" src="docs/multimodal_4.gif"/>
</div>

### Usage
See [this document](https://github.com/XuShenLZ/ParkSim/tree/main/python/parksim/trajectory_predict) for instruction.
1. A pre-trained intent prediction model can be [downloaded here](https://drive.google.com/file/d/1LVQJRQmjGfGchxhMRchiZRCjrlFDVch-/view?usp=sharing).
2. A pre-trained trajectory prediction model can be [downloaded here](https://drive.google.com/file/d/1c9KQXwFMRIYPJo1sXJKepoBcrEme_HxU/view?usp=sharing).