# Enhancing Accuracy and Robustness of Steering Angle Prediction with Attention Mechanism

arXiv: https://arxiv.org/abs/2211.11133 · HTML: https://mlsanity.com/paper/2211.11133/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 16 of its 29 references that are in the map.
- First posted on arXiv 21 Nov 2022.

## Builds on (most cited first, 16 of 16)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [Deep Residual Learning for Image Recognition](https://mlsanity.com/paper/1512.03385/) (2015)
- [Explaining and Harnessing Adversarial Examples](https://mlsanity.com/paper/1412.6572/) (2014)
- [Towards Deep Learning Models Resistant to Adversarial Attacks](https://mlsanity.com/paper/1706.06083/) (2017)
- [Fully Convolutional Networks for Semantic Segmentation](https://mlsanity.com/paper/1411.4038/) (2014)
- [Going Deeper with Convolutions](https://mlsanity.com/paper/1409.4842/) (2014)
- [Residual Attention Network for Image Classification](https://mlsanity.com/paper/1704.06904/) (2017)
- [Attention to Scale: Scale-aware Semantic Image Segmentation](https://mlsanity.com/paper/1511.03339/) (2015)
- [An Analysis of Adversarial Attacks and Defenses on Autonomous Driving Models](https://mlsanity.com/paper/2002.02175/) (2020)
- [Adversarial Attack and Defense of YOLO Detectors in Autonomous Driving Scenarios](https://mlsanity.com/paper/2202.04781/) (2022)
- [Self-Driving Car Steering Angle Prediction Based on Image Recognition](https://mlsanity.com/paper/1912.05440/) (2019)
- [Adversarial Attacks, Regression, and Numerical Stability Regularization](https://mlsanity.com/paper/1812.02885/) (2018)
- [Grow-Push-Prune: aligning deep discriminants for effective structural network compression](https://mlsanity.com/paper/2009.13716/) (2020)
- [Multi-Modal Fusion for Sensorimotor Coordination in Steering Angle Prediction](https://mlsanity.com/paper/2202.05500/) (2022)
- [Self-Driving Car Steering Angle Prediction: Let Transformer Be a Car Again](https://mlsanity.com/paper/2204.12748/) (2022)
- [Aggregated Sparse Attention for Steering Angle Prediction](https://mlsanity.com/paper/1803.05785/) (2018)

## Abstract (arXiv)

In this paper, our focus is on enhancing steering angle prediction for autonomous driving tasks. We initiate our exploration by investigating two veins of widely adopted deep neural architectures, namely ResNets and InceptionNets. Within both families, we systematically evaluate various model sizes to understand their impact on performance. Notably, our key contribution lies in the incorporation of an attention mechanism to augment steering angle prediction accuracy and robustness. By introducing attention, our models gain the ability to selectively focus on crucial regions within the input data, leading to improved predictive outcomes. Our findings showcase that our attention-enhanced models not only achieve state-of-the-art results in terms of steering angle Mean Squared Error (MSE) but also exhibit enhanced adversarial robustness, addressing critical concerns in real-world deployment. For example, in our experiments on the Kaggle SAP and our created publicly available datasets, attention can lead to over 6% error reduction in steering angle prediction and boost model robustness by up to 56.09%.