Microscopic traffic flow models are a class of scientific models of vehicular traffic dynamics.
In contrast, to macroscopic models, microscopic traffic flow models simulate single vehicle-driver units, so the dynamic variables of the models represent microscopic properties like the position and velocity of single vehicles.
Also known as time-continuous models, all car-following models have in common that they are defined by ordinary differential equations describing the complete dynamics of the vehicles' positions and velocities . It is assumed that the input stimuli of the drivers are restricted to their own velocity , the net distance (bumper-to-bumper distance) to the leading vehicle (where denotes the vehicle length), and the velocity of the leading vehicle. The equation of motion of each vehicle is characterized by an acceleration function that depends on those input stimuli:
In general, the driving behavior of a single driver-vehicle unit might not merely depend on the immediate leader but on the vehicles in front. The equation of motion in this more generalized form reads:
Optimal velocity model (OVM)
Velocity difference model (VDIFF)
Wiedemann model (1974)
Gipps' model (Gipps, 1981)
Intelligent driver model (IDM, 1999)
DNN based anticipatory driving model (DDS, 2021)
Cellular automaton (CA) models use integer variables to describe the dynamical properties of the system. The road is divided into sections of a certain length and the time is discretized to steps of . Each road section can either be occupied by a vehicle or empty and the dynamics are given by updated rules of the form:
(the simulation time is measured in units of and the vehicle positions in units of ).
The time scale is typically given by the reaction time of a human driver, . With fixed, the length of the road sections determines the granularity of the model. At a complete standstill, the average road length occupied by one vehicle is approximately 7.5 meters.
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Learn how to describe, model and control urban traffic congestion in simple ways and gain insight into advanced traffic management schemes that improve mobility in cities and highways.
Learn how to describe, model and control urban traffic congestion in simple ways and gain insight into advanced traffic management schemes that improve mobility in cities and highways.
Covers the fundamental diagram in traffic flow modeling and discusses field observations, empirical data, speed-density relations, bottlenecks, and capacity drop phenomena.
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