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Traffic congestion leads to a sharp increase in fuel consumption and exhaustemissions, which easily leads to air pollution and fuel waste. Based onFukui-Ishibashi (FI) model, this paper studies particulate matter(PM) emissionand energy dissipation of traffic flow by considering the maximum speed, mixingratio and random slowing probability. Simulation results show that the energydissipation of the traffic flow consisting of the same length and differentmaximum velocity is associated with the maximum velocity. The greater themaximum velocity, the more the energy consumes. When the maximum velocity isdifferent, the PM emission is similar to the change of energy consumption.Moreover, for the same maximum velocity and different mixing ratio, the energydissipation and the PM emission related to the mixing ratio. There are themaximum fuel consumption and emission value in the maximum flow. For the samemaximum velocity and length of vehicles, their energy consumption and emissionare determined by random slowing probability.

Research on PM emission and energy consumption of mixed traffic flow based on cellular automata FI model