A high fidelity traffic simulation model based on cellular automata and car-following concepts

Ghulam H. Bham, Rahim F. Benekohal

Research output: Contribution to journalArticlepeer-review


A high fidelity cell based traffic simulation model (CELLSIM) has been developed for simulation of high volume of traffic at the regional level. Straightforward algorithms and efficient use of computational resources make the model suitable for real time traffic simulation. The model formulation uses concepts of cellular automata (CA) and car-following (CF) models, but is more detailed than CA models and has realistic acceleration and deceleration models for vehicles. A simple dual-regime constant acceleration model has been used that requires minimal calculation compared to detailed acceleration models used in CF models. CELLSIM is simpler than most CF models; a simplified car-following logic has been developed using preferred time headway. Like CA models, integer values are used to make the model run faster. Space is discretized in small intervals and a new concept of percent space occupancy (SOC) is used to measure traffic congestion. CELLSIM performs well in congested and non-congested traffic conditions. It has been validated comprehensively at the macroscopic and microscopic levels using two sets of field data. Comparison of field data and CELLSIM for trajectories, average speed, density and volume show very close agreement. Statistical comparison of macroscopic parameters with other CF models indicates that CELLSIM performs as good as detailed CF models. Stability analyses conducted using mild and severe disturbances indicate that CELLSIM performs well under both conditions.

Original languageEnglish (US)
Pages (from-to)1-32
Number of pages32
JournalTransportation Research Part C: Emerging Technologies
Issue number1
StatePublished - Feb 2004


  • Car-following models
  • Cellular automata
  • Model validation
  • Space occupancy
  • Traffic simulation

ASJC Scopus subject areas

  • Transportation
  • Automotive Engineering
  • Civil and Structural Engineering
  • Management Science and Operations Research


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