How do active road users act around autonomous vehicles? An inverse reinforcement learning approach

Author:

Alozi Abdul Razak,Hussein Mohamed

Publisher

Elsevier BV

Reference80 articles.

1. Apprenticeship learning via inverse reinforcement learning;Abbeel;Proceedings, Twenty-First International Conference on Machine Learning, ICML,2004

2. Evaluating the safety of autonomous vehicle–pedestrian interactions: an extreme value theory approach;Alozi;Analytic Methods in Accident Research,2022

3. Active road user Interactions with autonomous vehicles: a proactive safety assessment;Alozi;Transp. Res. Rec.,2023

4. Enhancing autonomous vehicle hyperawareness in busy traffic environments: a machine learning approach;Alozi;Accid. Anal. Prev.,2024

5. Alsaleh, R., Sayed, T., 2021b. Microscopic modeling of cyclists interactions with pedestrians in shared spaces: a Gaussian process inverse reinforcement learning approach. Transport. A: Transport Sci. Doi: 10.1080/23249935.2021.1898487.

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1. How do Automated Vehicles Influence Other Road Users and Sometimes Elicit Uncivil Behaviors?;Proceedings of the 16th International Conference on Automotive User Interfaces and Interactive Vehicular Applications;2024-09-11

2. How would autonomous vehicles behave in real-world crash scenarios?;Accident Analysis & Prevention;2024-07

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