Controle do fluxo principal em autoestradas por meio de veículos cooperativos equipados com controle adaptativo de cruzeiro

Jéssica Aquino Chaves, Rodrigo Castelan Carlson, Eduardo Rauh Müller, Werner Kraus Jr.

Resumo


O Controle do Fluxo Principal (CFP) em autoestradas é um método de controle de tráfego que regula o fluxo de veículos a montante de um gargalo a fim de maximizar o escoamento do fluxo de tráfego na autoestrada. Usando Limites de Velocidade Variáveis (LVV) como atuador do CFP, é analisada a influência de diferentes taxas de penetração de veículos cooperativos no tráfego. Veículos cooperativos foram equipados com Controle Adaptativo de Cruzeiro e recebem como valor de referência o LVV da seção autoestrada em que se encontram. Simulações com o simulador microscópico de tráfego AIMSUN mostraram que o aumento da taxa de penetração contribuiu para o aumento do desempenho. Em cenários cuja taxa de penetração é de 10%, houve uma melhoria de desempenho de 25%. A presença de mais de 50% de veículos cooperativos tem um efeito positivo nas condições de tráfego. Porém, é necessária uma estratégia auxiliar para facilitar a inserção dos veículos ao fluxo principal em gargalos da autoestrada ativados por rampas de acesso.


Palavras-chave


Controle do Fluxo Principal; Limites Variáveis de Velocidade; Veículos cooperativos.

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Referências


Carlson, R. C.; I. Papamichail e M. Papageorgiou (2013) Mainstream traffic flow control on freeways using variable speed limits. Transportes, v. 21, n. 3, p. 56–65. DOI: 10.4237/transportes.v21i3.694

Davis, L. (2016) Improving traffic flow at a 2-to-1 lane reduction with wirelessly connected, adaptive cruise control vehicles. Physica A: Statistical Mechanics and its Applications, v. 451, p. 320–332. DOI: 10.1016/j.physa.2016.01.093

Dowling, R.; A. Skabardonis e V. Alexiadis (2004) Traffic analysis toolbox volume III: guidelines for applying traffic microsimula-tion modeling software, Publication No. FHWA-HRT-04-040, U.S. Department of Transportation, Federal Highway Admin-istration.

Kayacan, E. (2017) Multiobjective H∞ Control for String Stability of Cooperative Adaptive Cruise Control Systems. IEEE Transactions on Intelligent Vehicles, v. 2, n. 1, p. 52–61. DOI: 10.1109/TIV.2017.2708607

Gipps, P. G. (1981) A behavioural car-following model for computer simulation. Transportation Research Part B: Methodolog-ical, v. 15, n. 2, p. 105–111. DOI: 10.1016/0191-2615(81)90037-0

Grumert, E.; X. Ma e A. Tapani (2015) Analysis of a cooperative variable speed limit system using microscopic traffic simula-tion. Transportation Research Part C: Emerging Technologies, v. 52, p. 173–186. DOI: 10.1016/j.trc.2014.11.004

Harms, I. M. e K. A. Brookhuis (2016) Dynamic traffic management on a familiar road: failing to detect changes in variable speed limits. Transportation Research Part F: Traffic Psychology and Behaviour, v. 38, p. 37–46. DOI: 10.1016/j.trf.2016.01.005

Hegyi, A.; B. Netten; M. Wang; W. Schakel; T. Schreiter; Y. Yuan; B. van Arem e T. Alkim (2013) A cooperative system based variable speed limit control algorithm against jam waves - an extension of the SPECIALIST algorithm. The 16th Interna-tional IEEE Conference on Intelligent Transportation Systems, p. 973–978. DOI: 10.1109/ITSC.2013.6728358

Iordanidou, G. R.; C. Roncoli; I. Papamichail e M. Papageorgiou (2014) Feedback-based mainstream traffic flow control for multiple bottlenecks on motorways. IEEE Transactions on Intelligent Transportation Systems, v. 16, n. 2, p. 610–621. DOI: 10.1109/TITS.2014.2331985

Kesting, A; M. Treiber; M. Schönhof e D. Helbing (2007) Extending adaptive cruise control to adaptive driving strategies. Transportation Research Record: Journal of the Transportation Research Board, n. 2000, p. 16–27. DOI: 10.3141/2000-03

Kattan, L.; B. Khondaker; O. Derushkina e E. Poosarla (2015) A probe-based variable speed limit system. Journal of Intelligent Transportation Systems, v. 19, n. 4, p. 339–354. DOI: 10.1080/15472450.2014.936294

Khondaker, B. e L. Kattan (2015a) Variable speed limit: an overview. Transportation Letters, v. 7, n. 5, p. 264–278. DOI: 10.1179/1942787514Y.0000000053

Khondaker, B. e L. Kattan (2015b) Variable speed limit: a microscopic analysis in a connected vehicle environment. Transpor-tation Research Part C: Emerging Technologies, v. 58, p. 146–159. DOI: 10.1016/j.trc.2015.07.014

Lin, T.-W.; S.-L. Hwang,e P. A. Green (2009) Effects of time-gap settings of adaptive cruise control (ACC) on driving perfor-mance and subjective acceptance in a bus driving simulator. Safety Science, v. 47, n. 5, p. 620-625. DOI: 10.1016/j.ssci.2008.08.004

Müller, E. R.; R. C. Carlson; W. Kraus e M. Papageorgiou (2015) Microsimulation analysis of practical aspects of traffic control with variable speed limits. IEEE Transactions on Intelligent Transportation Systems, v. 16, n. 1, p. 512–523. DOI: 10.1109/TITS.2014.2374167

Müller, E. R.; R. C. Carlson e W. Kraus (2016) Cooperative mainstream traffic flow control on freeways. IFAC-PapersOnLine. v. 49, n. 32, p. 89–94. DOI: 10.1016/j.ifacol.2016.12.195

Ntousakis, I. A.; I. K. Nikolos e M. Papageorgiou (2015) On microscopic modelling of adaptive cruise control systems. Trans-portation Research Procedia, v. 6, p. 111–127. DOI: 10.1016/j.trpro.2015.03.010

Papageorgiou, M.; C. Diakaki, V. Dinopoulou, A. Kotsialos e Wang, Y. (2003). Review of road traffic control strategies. Proceed-ings of the IEEE, 91(12), 2043-2067. DOI: 10.1109/JPROC.2003.819610

Papageorgiou, M.; E. Kosmatopoulos e I. Papamichail (2008) Effects of variable speed limits on motorway traffic flow. Trans-portation Research Record: Journal of the Transportation Research Board, n. 2047, v. 37–48. DOI: 10.3141/2047-05

Riggins, G.; R. Bertini; W. Ackaah e M. Margreiter (2016). Evaluation of driver compliance to displayed variable advisory speed limit systems: comparison between Germany and the U.S. Transportation Research Procedia, v. 15, p. 640–651. DOI: 10.1016/j.trpro.2016.06.054

Roncoli, C.; M. Papageorgiou e I. Papamichail (2015) Traffic flow optimisation in presence of vehicle automation and com-munication systems – Part II: optimal control for multi-lane motorways. Transportation Research Part C: Emerging Technol-ogies, v. 57, p. 260–275. DOI: 10.1016/j.trc.2015.05.011

Scarinci, R. e B. Heydecker (2014) Control concepts for facilitating motorway on-ramp merging using intelligent vehi-cles. Transport Reviews, v. 34, n. 6, p. 775–797. DOI: 10.1080/01441647.2014.983210

Shladover, S.; D. Su e X. Lu (2012) Impacts of cooperative adaptive cruise control on freeway traffic flow. Transportation Research Record: Journal of the Transportation Research Board, n. 2324, p. 63–70. DOI: 10.3141/2324-08

Soriguera, F.; I. Martínez-Josemaría e M. Menéndez (2015) Experimenting with dynamic speed limits on freeways. TRB 94th Annual Meeting Compendium of Papers, Washington, D.C., USA.

Wang, M.; W. Daamen; S. P. Hoogendoom e B. van Arem (2014) Rolling horizon control framework for driver assistance sys-tems. Part I: Mathematical formulation and non-cooperative systems. Transportation Research Part C: Emerging Technolo-gies, v. 40, p. 290–311. DOI: 10.1016/j.trc.2013.11.023




DOI: https://doi.org/10.14295/transportes.v26i3.1629

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Direitos autorais 2018 Jéssica Aquino Chaves, Rodrigo Castelan Carlson, Eduardo Rauh Müller, Werner Kraus Jr.

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TRANSPORTES (ISSN: 2237-1346) é uma publicação da ANPET - Associação Nacional de Pesquisa e Ensino em Transportes (www.anpet.org.br)