VISSIM

PTV Vissim: Whether comparing junction geometries, analysing public transport priority schemes or considering the effects of certain signalling – PTV Vissim allows you to simulate traffic patterns exactly. Motorised private transport, goods transport, rail and road related public transport, pedestrians and cyclists – as the world’s leading software for microscopic traffic simulation, PTV Vissim displays all road users and their interactions in one model. Scientifically sound motion models provide a realistic modelling of all road users. The software offers flexibility in several respects: the concept of links and connectors allows users to model geometries with any level of complexity. Attributes for driver and vehicle characteristics enable individual parameterisation. Furthermore, a large number of interfaces provide seamless integration with other systems for signal controllers, traffic management or emissions models. PTV Vissim is rounded off with comprehensive analysis options, creating a powerful tool for the evaluation and planning of urban and extra-urban transport infrastructure. For example, the simulation software may be used to create detailed computational results or impressive 3D animations for different scenarios. It is the perfect way to present convincing and comprehensible planned infrastructure measures to decision-makers and the public.


References in zbMATH (referenced in 13 articles )

Showing results 1 to 13 of 13.
Sorted by year (citations)

  1. Zhang, Yue; Cassandras, Christos G.; Li, Wei; Mosterman, Pieter J.: A discrete-event and hybrid traffic simulation model based on SimEvents for intelligent transportation system analysis in Mcity (2019)
  2. Bian, Chentong; Yin, Guodong; Xu, Liwei; Zhang, Ning: Virtual belt algorithm for the management of isolated autonomous intersection (2018)
  3. Jing, Binbin; Xu, Jianmin: A general maximum progression model to concurrently synchronize left-turn and through traffic flows on an arterial (2018)
  4. Louati, Ali; Darmoul, Saber; Elkosantini, Sabeur; ben Said, Lamjed: An artificial immune network to control interrupted flow at a signalized intersection (2018)
  5. Liu, Meiqi; Shen, Lixiao; Jin, Sheng: Modeling capacity of shared right-turn lanes considering right turn on red and lag green time of right-turn (2017)
  6. Cristiani, Emiliano; Sahu, Smita: On the micro-to-macro limit for first-order traffic flow models on networks (2016)
  7. Wang, Li; Li, Dai; He, Zhonghe; Ma, Xuhui: Urban traffic network control based on cluster consensus of multi-agent systems (2014)
  8. Anusha, S. P.; Anand, R. A.; Vanajakshi, L.: Data fusion based hybrid approach for the estimation of urban arterial travel time (2012)
  9. Kretz, Tobias: The dynamic distance potential field in a situation with asymmetric bottleneck capacities (2010)
  10. Jiang, Zhu; Huang, Yong-Xuan: Parametric calibration of speed-density relationships in mesoscopic traffic simulator with data mining (2009) ioport
  11. Kretz, Tobias: Pedestrian traffic: on the quickest path (2009)
  12. Mandiau, René; Champion, Alexis; Auberlet, Jean-Michel; Espié, Stéphane; Kolski, Christophe: Behaviour based on decision matrices for a coordination between agents in a urban traffic simulation. (2008) ioport
  13. Al-Deek, Haitham M.; Mohamed, Ayman A.; Malone, Linda: A new stochastic discrete-event micro simulation model for evaluating traffic operations at electronic toll collection plazas (2005)