# Joint Attention in Driver-Pedestrian Interaction: from Theory to Practice

arXiv: https://arxiv.org/abs/1802.02522 · HTML: https://mlsanity.com/paper/1802.02522/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 7 Feb 2018.

## Built on by (most cited first, 4 of 4)

- [Behavioral Intention Prediction in Driving Scenes: A Survey](https://mlsanity.com/paper/2211.00385/) (2022)
- [IntFormer: Predicting pedestrian intention with the aid of the Transformer architecture](https://mlsanity.com/paper/2105.08647/) (2021)
- [SalM2: An Extremely Lightweight Saliency Mamba Model for Real-Time Cognitive Awareness of Driver Attention](https://mlsanity.com/paper/2502.16214/) (2025)
- [WatchPed: Pedestrian Crossing Intention Prediction Using Embedded Sensors of Smartwatch](https://mlsanity.com/paper/2208.07441/) (2022)

## Abstract (arXiv)

Today, one of the major challenges that autonomous vehicles are facing is the ability to drive in urban environments. Such a task requires communication between autonomous vehicles and other road users in order to resolve various traffic ambiguities. The interaction between road users is a form of negotiation in which the parties involved have to share their attention regarding a common objective or a goal (e.g. crossing an intersection), and coordinate their actions in order to accomplish it. In this literature review we aim to address the interaction problem between pedestrians and drivers (or vehicles) from joint attention point of view. More specifically, we will discuss the theoretical background behind joint attention, its application to traffic interaction and practical approaches to implementing joint attention for autonomous vehicles.