Cellular automaton model simulating spatiotemporal patterns, phase transitions and evolution concavity in traffic flow

Abstract

This paper firstly show that a recent model (Tian et al., Transpn. Res. B 71, 138-157, 2015) is not able to well replicate the evolution concavity in traffic flow, i.e. the standard deviation of vehicles increases in a concave/linear way along the platoon. Then we propose an improved model by introducing the safe speed, the logistic function of the randomization probability, and small randomization deceleration for low-speed vehicles into the model. Simulations show that the improved model can well reproduce the metastable states, the spatiotemporal patterns, the phase transition behaviors of traffic flow, and the evolution concavity of traffic oscillations. Validating results show that the empirical time series of traffic speed obtained from Floating Car Data can be well simulated as well.

References in corpus (9)

• Congested Traffic States in Empirical Observations and Microscopic Simulations
• Traffic and Related Self-Driven Many-Particle Systems
• Analysis of Optimal Velocity Model with Explicit Delay
• Mechanical restriction versus human overreaction triggering congested traffic states
• Three-phase traffic theory and two-phase models with a fundamental diagram in the light of empirical stylized facts
• Presence of Many Stable Nonhomogeneous States in an Inertial Car-Following Model
• Theoretical vs. Empirical Classification and Prediction of Congested Traffic States
• Microscopic driving theory with oscillatory congested states: model and empirical verification
• How human drivers control their vehicle

Cited by in corpus (1)

• Microscopic Theory of Traffic Flow Instability Governing Traffic Breakdown at Highway Bottlenecks: Growing Wave of Increase in Speed in Synchronized Flow