Can listening to more neighbours help CAVs be faster and safer?

Autor: Garg, Mohit, Bouroche, Mélanie

Connected Autonomous Vehicles (CAVs) are widely expected to improve traffic safety and efficiency by exploiting information from surrounding vehicles via V2V communication. A CAV typically adapts its speed based on information from the vehicle it fol

Externí odkaz: http://arxiv.org/abs/2304.01402

$\mathcal{L}_2$ and $\mathcal{L}_{\infty}$ stability analysis of heterogeneous traffic with application to parameter optimisation for the control of automated vehicles

Autor: Monteil, Julien, Bouroche, Melanie, Leith, Douglas J.

The presence of (partially) automated vehicles on the roads presents an opportunity to compensate the unstable behaviour of conventional vehicles. Vehicles subject to perturbations should (i) recover their equilibrium speed, (ii) react not to propaga

Externí odkaz: http://arxiv.org/abs/1609.07382

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Context-dependent reconfiguration of autonomous vehicles in mixed traffic

Autor: Horcas Aguilera, José Miguel, Monteil, Julian, Bouroche, Mélanie, Pinto, Mónica, Fuentes, Lidia, Clarke, Siobhán

Publikováno v: idUS: Depósito de Investigación de la Universidad de Sevilla
Universidad de Sevilla (US)
idUS. Depósito de Investigación de la Universidad de Sevilla
instname

Human drivers naturally adapt their behaviour depending on the traffic conditions, such as the current weather and road type. Autonomous vehicles need to do the same, in a way that is both safe and efficient in traffic composed of both conventional a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::5f8b214d1579f5556f7cb0cd6bc2ce24

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