Zobrazeno 1 - 10
of 161
pro vyhledávání: '"Calvert, P. C."'
The integration of autonomous vehicles (AVs) into transportation systems presents an unprecedented opportunity to enhance road safety and efficiency. However, understanding the interactions between AVs and human-driven vehicles (HVs) at intersections
Externí odkaz:
http://arxiv.org/abs/2410.12538
Autor:
Rahmani, Saeed, Rieder, Sabine, de Gelder, Erwin, Sonntag, Marcel, Mallada, Jorge Lorente, Kalisvaart, Sytze, Hashemi, Vahid, Calvert, Simeon C.
The rapid development of automated vehicles (AVs) promises to revolutionize transportation by enhancing safety and efficiency. However, ensuring their reliability in diverse real-world conditions remains a significant challenge, particularly due to r
Externí odkaz:
http://arxiv.org/abs/2410.08491
Autor:
Mathiesen, Frederik Baymler, Romao, Licio, Calvert, Simeon C., Laurenti, Luca, Abate, Alessandro
In this paper, we present a novel data-driven approach to quantify safety for non-linear, discrete-time stochastic systems with unknown noise distribution. We define safety as the probability that the system remains in a given region of the state spa
Externí odkaz:
http://arxiv.org/abs/2410.06662
Current approaches to identifying driving heterogeneity face challenges in comprehending fundamental patterns from the perspective of underlying driving behavior mechanisms. The concept of Action phases was proposed in our previous work, capturing th
Externí odkaz:
http://arxiv.org/abs/2407.17518
This study proposes a unified theory and statistical learning approach for traffic conflict detection, addressing the long-existing call for a consistent and comprehensive methodology to evaluate the collision risk emerging in road user interactions.
Externí odkaz:
http://arxiv.org/abs/2407.10959
Lane-changing (LC) is a challenging scenario for connected and automated vehicles (CAVs) because of the complex dynamics and high uncertainty of the traffic environment. This challenge can be handled by deep reinforcement learning (DRL) approaches, l
Externí odkaz:
http://arxiv.org/abs/2407.02521
The use of partially automated driving systems raises concerns about potential responsibility issues, posing risk to the system safety, acceptance, and adoption of these technologies. The concept of meaningful human control has emerged in response to
Externí odkaz:
http://arxiv.org/abs/2402.08080
As the deployment of autonomous vehicles (AVs) in mixed traffic flow becomes increasingly prevalent, ensuring safe and smooth interactions between AVs and human agents is of critical importance. How road users resolve conflicts at intersections has s
Externí odkaz:
http://arxiv.org/abs/2308.13839
Current approaches to identifying driving heterogeneity face challenges in capturing the diversity of driving characteristics and understanding the fundamental patterns from a driving behaviour mechanism standpoint. This study introduces a comprehens
Externí odkaz:
http://arxiv.org/abs/2307.16843
Car-Following (CF), as a fundamental driving behaviour, has significant influences on the safety and efficiency of traffic flow. Investigating how human drivers react differently when following autonomous vs. human-driven vehicles (HV) is thus critic
Externí odkaz:
http://arxiv.org/abs/2305.18921