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      Multivariable Optimisation for Waiting-Time Minimisation at Roundabout Intersections in a Cyber-Physical Framework

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          Abstract

          The evolution of communication networks offers new possibilities for development in the automotive industry. Smart vehicles will benefit from the possibility of connecting with the infrastructure and from an extensive exchange of data between them. Furthermore, new control strategies can be developed that benefit the advantages of these communication networks. In this endeavour, the main purposes considered by the automotive industry and researchers from academia are defined by: (i) ensuring people’s safety; (ii) reducing the overall costs, and (iii) improving the traffic by maximising the fluidity. In this paper, a cyber-physical framework (CPF) to control the access of vehicles in roundabout intersections composed of two levels is proposed. Both levels correspond to the cyber part of the CPF, while the physical part is composed of the vehicles crossing the roundabout. The first level, i.e., the edge-computing layer, is based on an analytical solution that uses multivariable optimisation to minimise the waiting times of the vehicles entering a roundabout intersection and to ensure a safe crossing. The second level, i.e., the cloud-computing layer, stores information about the waiting times and trajectories of all the vehicles that cross the roundabout and uses them for long-term analysis and prediction. The simulated results show the efficacy of the proposed method, which can be easily implemented on an embedded device for real-time operation.

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          The effect of roundabout design features on cyclist accident rate.

          Roundabouts are known to result in fewer traffic accidents than traditional intersections. However, this is to a lesser degree true for bicycles than for vehicles. In this paper, we aimed at establishing statistical relationships through Poisson regression and logistic regression analyses between yearly rate of cyclist accidents on one hand and roundabout geometry, age and traffic volume (vehicles and cyclists) on the other. We related all roundabout cyclist accidents recorded by the hospital emergency department of the town of Odense, Denmark, through the years 1999-2003 (N=171) to various geometric features, age and traffic volume of all roundabouts on the Danish island of Funen (N=88). Cyclist and vehicle volumes turned out to be significant predictors in most of our models-the higher the volumes, the more accidents. Moreover, potential vehicle speed was a significant predictor, and so was age of the roundabout-older roundabouts related to more accidents and higher accident probability. Excluding 48 single cyclist accidents strengthened the relationship between accidents on one hand and vehicle and cyclist volume and potential vehicle speed on the other. This stresses the significance of speed and traffic volume for traffic accidents with more than one partner involved. The 48 single cyclist accidents were significantly related to the traffic volume of cyclists only. Due to our limited number of observations, the models should be regarded as indicative.
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            A Recurrent Neural Network Solution for Predicting Driver Intention at Unsignalized Intersections

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              Optimal Control of Connected and Automated Vehicles at Roundabouts: An Investigation in a Mixed-Traffic Environment ⁎ ⁎This manuscript has been co-authored by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The US government retains and the publisher, by accepting the article for publication, acknowledges that the US government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for US government purposes. DOE will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan).

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                Author and article information

                Contributors
                Role: Academic Editor
                Journal
                Sensors (Basel)
                Sensors (Basel)
                sensors
                Sensors (Basel, Switzerland)
                MDPI
                1424-8220
                09 June 2021
                June 2021
                : 21
                : 12
                : 3968
                Affiliations
                [1 ]Department of Automatic Control and Applied Informatics, “Gheorghe Asachi” Technical University of Iasi, 700050 Iasi, Romania; pauca.ovidiu@ 123456ac.tuiasi.ro (O.P.); anca.maxim@ 123456ac.tuiasi.ro (A.M.)
                [2 ]Holistic Engineering and Technologies (he[a]t), Continental Automotive Romania, 700671 Iasi, Romania
                Author notes
                [* ]Correspondence: caruntuc@ 123456ac.tuiasi.ro
                Author information
                https://orcid.org/0000-0003-3108-2910
                https://orcid.org/0000-0003-4296-3860
                https://orcid.org/0000-0002-4026-2852
                Article
                sensors-21-03968
                10.3390/s21123968
                8226853
                bd87f1e2-ce7d-49ab-b26d-fa77109f1f2f
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( https://creativecommons.org/licenses/by/4.0/).

                History
                : 06 May 2021
                : 06 June 2021
                Categories
                Article

                Biomedical engineering
                roundabout intersection,cyber-physical system,waiting time minimisation,intelligent traffic systems

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