Social interactions for autonomous driving: A review and perspectives

W Wang, L Wang, C Zhang, C Liu… - Foundations and Trends …, 2022 - nowpublishers.com
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …

[HTML][HTML] How do autonomous vehicles decide?

S Malik, MA Khan, H El-Sayed, J Khan, O Ullah - Sensors, 2022 - mdpi.com
The advancement in sensor technologies, mobile network technologies, and artificial
intelligence has pushed the boundaries of different verticals, eg, eHealth and autonomous …

Uncertainties in onboard algorithms for autonomous vehicles: Challenges, mitigation, and perspectives

K Yang, X Tang, J Li, H Wang, G Zhong… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
Autonomous driving is considered one of the revolutionary technologies shaping humanity's
future mobility and quality of life. However, safety remains a critical hurdle in the way of …

Decision-making technology for autonomous vehicles: Learning-based methods, applications and future outlook

Q Liu, X Li, S Yuan, Z Li - 2021 IEEE International Intelligent …, 2021 - ieeexplore.ieee.org
Autonomous vehicles have a great potential in the application of both civil and military fields,
and have become the focus of research with the rapid development of science and …

Emergent social learning via multi-agent reinforcement learning

KK Ndousse, D Eck, S Levine… - … conference on machine …, 2021 - proceedings.mlr.press
Social learning is a key component of human and animal intelligence. By taking cues from
the behavior of experts in their environment, social learners can acquire sophisticated …

Surrealdriver: Designing generative driver agent simulation framework in urban contexts based on large language model

Y Jin, X Shen, H Peng, X Liu, J Qin, J Li, J Xie… - arXiv preprint arXiv …, 2023 - arxiv.org
Simulation plays a critical role in the research and development of autonomous driving and
intelligent transportation systems. However, the current simulation platforms exhibit …

A taxonomy and review of algorithms for modeling and predicting human driver behavior

K Brown, K Driggs-Campbell… - arXiv preprint arXiv …, 2020 - arxiv.org
We present a review and taxonomy of 200 models from the literature on driver behavior
modeling. We begin by introducing a mathematical framework for describing the dynamics of …

Maneuver-based trajectory prediction for self-driving cars using spatio-temporal convolutional networks

B Mersch, T Höllen, K Zhao… - 2021 IEEE/RSJ …, 2021 - ieeexplore.ieee.org
The ability to predict the future movements of other vehicles is a subconscious and effortless
skill for humans and key to safe autonomous driving. Therefore, trajectory prediction for …

[HTML][HTML] Could technology and intelligent transport systems help improve mobility in an emerging country? Challenges, opportunities, gaps and other evidence from …

F Alonso, M Faus, MT Tormo, SA Useche - Applied Sciences, 2022 - mdpi.com
Apart from constituting a topic of high relevance for transport planners and policymakers,
support technologies for traffic have the potential to bring significant benefits to mobility. In …

Use of social interaction and intention to improve motion prediction within automated vehicle framework: A review

DE Benrachou, S Glaser, M Elhenawy… - IEEE Transactions …, 2022 - ieeexplore.ieee.org
Human errors contribute to 94%(±2.2%) of road crashes resulting in fatal/non-fatal
causalities, vehicle damages and a predicament in the pathway to safer road systems …