Literature DB >> 11088643

Congested traffic states in empirical observations and microscopic simulations

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Abstract

We present data from several German freeways showing different kinds of congested traffic forming near road inhomogeneities, specifically lane closings, intersections, or uphill gradients. The states are localized or extended, homogeneous or oscillating. Combined states are observed as well, like the coexistence of moving localized clusters and clusters pinned at road inhomogeneities, or regions of oscillating congested traffic upstream of nearly homogeneous congested traffic. The experimental findings are consistent with a recently proposed theoretical phase diagram for traffic near on-ramps [D. Helbing, A. Hennecke, and M. Treiber, Phys. Rev. Lett. 82, 4360 (1999)]. We simulate these situations with a continuous microscopic single-lane model, the "intelligent driver model," using empirical boundary conditions. All observations, including the coexistence of states, are qualitatively reproduced by describing inhomogeneities with local variations of one model parameter. We show that the results of the microscopic model can be understood by formulating the theoretical phase diagram for bottlenecks in a more general way. In particular, a local drop of the road capacity induced by parameter variations has essentially the same effect as an on-ramp.

Entities:  

Year:  2000        PMID: 11088643     DOI: 10.1103/physreve.62.1805

Source DB:  PubMed          Journal:  Phys Rev E Stat Phys Plasmas Fluids Relat Interdiscip Topics        ISSN: 1063-651X


  14 in total

1.  Percolation transition in dynamical traffic network with evolving critical bottlenecks.

Authors:  Daqing Li; Bowen Fu; Yunpeng Wang; Guangquan Lu; Yehiel Berezin; H Eugene Stanley; Shlomo Havlin
Journal:  Proc Natl Acad Sci U S A       Date:  2014-12-31       Impact factor: 11.205

2.  Assessing the Impacts of Autonomous Vehicles on Road Congestion Using Microsimulation.

Authors:  Areej Malibari; Akito Higatani; Wafaa Saleh
Journal:  Sensors (Basel)       Date:  2022-06-10       Impact factor: 3.847

3.  Theory and Simulation for Traffic Characteristics on the Highway with a Slowdown Section.

Authors:  Dejie Xu; Baohua Mao; Yaping Rong; Wei Wei
Journal:  Comput Intell Neurosci       Date:  2015-05-18

4.  Reliable multihop broadcast protocol with a low-overhead link quality assessment for ITS based on VANETs in highway scenarios.

Authors:  Alejandro Galaviz-Mosqueda; Salvador Villarreal-Reyes; Hiram Galeana-Zapién; Javier Rubio-Loyola; David H Covarrubias-Rosales
Journal:  ScientificWorldJournal       Date:  2014-07-15

5.  Analysis of vehicle-following heterogeneity using self-organizing feature maps.

Authors:  Jie Yang; Ruey Long Cheu; Xiucheng Guo; Alicia Romo
Journal:  Comput Intell Neurosci       Date:  2014-11-05

6.  A model to identify urban traffic congestion hotspots in complex networks.

Authors:  Albert Solé-Ribalta; Sergio Gómez; Alex Arenas
Journal:  R Soc Open Sci       Date:  2016-10-12       Impact factor: 2.963

7.  Empirical study of lane-changing behavior on three Chinese freeways.

Authors:  Mingmin Guo; Zheng Wu; Huibing Zhu
Journal:  PLoS One       Date:  2018-01-24       Impact factor: 3.240

8.  A computational model for driver's cognitive state, visual perception and intermittent attention in a distracted car following task.

Authors:  Jami Pekkanen; Otto Lappi; Paavo Rinkkala; Samuel Tuhkanen; Roosa Frantsi; Heikki Summala
Journal:  R Soc Open Sci       Date:  2018-09-05       Impact factor: 2.963

9.  Reliable freestanding position-based routing in highway scenarios.

Authors:  Gabriel A Galaviz-Mosqueda; Raúl Aquino-Santos; Salvador Villarreal-Reyes; Raúl Rivera-Rodríguez; Luis Villaseñor-González; Arthur Edwards
Journal:  Sensors (Basel)       Date:  2012-10-24       Impact factor: 3.576

10.  Traffic experiment reveals the nature of car-following.

Authors:  Rui Jiang; Mao-Bin Hu; H M Zhang; Zi-You Gao; Bin Jia; Qing-Song Wu; Bing Wang; Ming Yang
Journal:  PLoS One       Date:  2014-04-16       Impact factor: 3.240

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