# Artificial Intelligence Methods in In-Cabin Use Cases: A Survey

arXiv: https://arxiv.org/abs/2101.02082 · HTML: https://mlsanity.com/paper/2101.02082/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- Builds on 10 of its 83 references that are in the map.
- First posted on arXiv 6 Jan 2021.

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

- [Predicting the Driver's Focus of Attention: the DR(eye)VE Project](https://mlsanity.com/paper/1705.03854/) (2017)
- [Recurrent Neural Networks for Driver Activity Anticipation via Sensory-Fusion Architecture](https://mlsanity.com/paper/1509.05016/) (2015)
- [Brain4Cars: Car That Knows Before You Do via Sensory-Fusion Deep Learning Architecture](https://mlsanity.com/paper/1601.00740/) (2016)
- [Real-time Distracted Driver Posture Classification](https://mlsanity.com/paper/1706.09498/) (2017)
- [POSEidon: Face-from-Depth for Driver Pose Estimation](https://mlsanity.com/paper/1611.10195/) (2016)
- [Driver Intention Anticipation Based on In-Cabin and Driving Scene Monitoring](https://mlsanity.com/paper/2006.11557/) (2020)
- [Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances](https://mlsanity.com/paper/1904.10500/) (2019)
- [Real-Time Driver State Monitoring Using a CNN Based Spatio-Temporal Approach](https://mlsanity.com/paper/1907.08009/) (2019)
- [Reinforcement Learning-based Thermal Comfort Control for Vehicle Cabins](https://mlsanity.com/paper/1704.07899/) (2017)
- [A Supervised Learning Concept for Reducing User Interaction in Passenger Cars](https://mlsanity.com/paper/1711.04518/) (2017)

## Built on by (most cited first, 3 of 3)

- [Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations](https://mlsanity.com/paper/2210.11584/) (2022)
- [Multi-modality action recognition based on dual feature shift in vehicle cabin monitoring](https://mlsanity.com/paper/2401.14838/) (2024)
- [MultiFuser: Multimodal Fusion Transformer for Enhanced Driver Action Recognition](https://mlsanity.com/paper/2408.01766/) (2024)

## Abstract (arXiv)

As interest in autonomous driving increases, efforts are being made to meet requirements for the high-level automation of vehicles. In this context, the functionality inside the vehicle cabin plays a key role in ensuring a safe and pleasant journey for driver and passenger alike. At the same time, recent advances in the field of artificial intelligence (AI) have enabled a whole range of new applications and assistance systems to solve automated problems in the vehicle cabin. This paper presents a thorough survey on existing work that utilizes AI methods for use-cases inside the driving cabin, focusing, in particular, on application scenarios related to (1) driving safety and (2) driving comfort. Results from the surveyed works show that AI technology has a promising future in tackling in-cabin tasks within the autonomous driving aspect.