# An enhanced motion planning approach by integrating driving heterogeneity and long-term trajectory prediction for automated driving systems

arXiv: https://arxiv.org/abs/2308.01369 · HTML: https://mlsanity.com/paper/2308.01369/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 10 of its 60 references that are in the map.
- First posted on arXiv 2 Aug 2023.

## Builds on (most cited first, 10 of 10)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Multimodal Motion Prediction with Stacked Transformers](https://mlsanity.com/paper/2103.11624/) (2021)
- [Transformer Networks for Trajectory Forecasting](https://mlsanity.com/paper/2003.08111/) (2020)
- [Cooper: Cooperative Perception for Connected Autonomous Vehicles based on 3D Point Clouds](https://mlsanity.com/paper/1905.05265/) (2019)
- [Multi-Agent Tensor Fusion for Contextual Trajectory Prediction](https://mlsanity.com/paper/1904.04776/) (2019)
- [Multi-Modal Trajectory Prediction of Surrounding Vehicles with Maneuver based LSTMs](https://mlsanity.com/paper/1805.05499/) (2018)
- [Probabilistic Vehicle Trajectory Prediction over Occupancy Grid Map via Recurrent Neural Network](https://mlsanity.com/paper/1704.07049/) (2017)
- [Naturalistic Driver Intention and Path Prediction using Recurrent Neural Networks](https://mlsanity.com/paper/1807.09995/) (2018)
- [Towards a Framework to Manage Perceptual Uncertainty for Safe Automated Driving](https://mlsanity.com/paper/1903.03438/) (2019)
- [Interaction-aware Kalman Neural Networks for Trajectory Prediction](https://mlsanity.com/paper/1902.10928/) (2019)

## Abstract (arXiv)

Navigating automated driving systems (ADSs) through complex driving environments is difficult. Predicting the driving behavior of surrounding human-driven vehicles (HDVs) is a critical component of an ADS. This paper proposes an enhanced motion-planning approach for an ADS in a highway-merging scenario. The proposed enhanced approach utilizes the results of two aspects: the driving behavior and long-term trajectory of surrounding HDVs, which are coupled using a hierarchical model that is used for the motion planning of an ADS to improve driving safety.