A Kinematic Model for Trajectory Prediction in General Highway Scenarios

by Cyrus Anderson at UM FCAV

Introduction

This paper presents a novel kinematic model to predict vehicles' trajectories in general scenarios, including simultaneous lane changes by multiple vehicles and heavy occlusions. More details are given in the preprint at https://arxiv.org/abs/2103.16673.

Datasets

The NGSIM and highD datasets are used to evaluate the method, whose root folder should be set in utils.py. The default setup uses datasets as a symbolic link:

baselines/
datasets/
|__tt_format
    |__10hz
         |__ngsim/
             |__i80/
             |__us101/
         |__highd/
|__ngsim/
    |__i-80/
    |__us-101/
|__highd-dataset-v1.0/

where the raw datasets (NGSIM and highD) are converted to tt_format for evaluation. Conversion uses the tools in loading_utils/dataset_conversion.py. The un-formatted ngsim folder contains the NGSIM dataset (dataset portal and homepage). The highd-dataset-v1.0 folder contains the highD dataset (homepage).

(Note: There may be small errors when first loading the NGSIM data due to small inconsistencies between the folder name formats/column names of the US-101 and I-80 datasets - manually changing them can solve this.)

Predict Trajectories

Predictions can be made by running

python driver.py

Dependencies

• NumPy
• SciPy
• pandas
• matplotlib