A two-lane cellular automata microscopic traffic simulation method for simulating dynamic lane-changing behavior

A micro-traffic simulation and cellular automata technology, applied in the field of traffic engineering, can solve problems that do not conform to real traffic conditions and cannot be well simulated.

Active Publication Date: 2018-12-14
SOUTHEAST UNIV
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Problems solved by technology

[0008] The present invention just aims at the problem that the real lane-changing process cannot be well simulated in the prior art and does not conform to the real traffic conditions, and provides a micro-traffic simulation method of dual-lane cellular automata for simulating dynamic lane-changing behavior. It can well simulate the real operation of vehicles in the two-lane traffic s...

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  • A two-lane cellular automata microscopic traffic simulation method for simulating dynamic lane-changing behavior

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Embodiment 1

[0040] A two-lane cellular automaton micro-traffic simulation method for simulating dynamic lane-changing behavior, such as figure 1 shown, including the following steps:

[0041] S1. Determine the basic parameters of the simulation system: the basic parameters include at least the scale N of the simulation system, the total number of simulated vehicles M, and the maximum vehicle speed V max and the simulation time T, where the size N of the simulation system refers to the length of the simulation lane, that is, the number of cells contained in each simulation lane. The entire two-lane cellular automaton simulation system has 2N cells in total. A vehicle occupies a cell, and its speed can take values ​​0,1,2,...,V max .

[0042] S2. Create a two-lane cellular automaton micro-traffic simulation system and initialize the system. In the created simulation system, the value of each cell is 0 or 1; 0 means that the cell is not occupied by a simulated vehicle. 1 means that the ce...

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Abstract

The invention discloses a two-lane cellular automata microscopic traffic simulation method for simulating dynamic lane-changing behavior. The method comprises the following steps: (1) determining basic parameters of a simulation system; (2) creating the simulation system and initializing the system; (3) changing lanes, including checking lane change motive, calculating intensity index of lane change motive, determining lane change distance and lane change probability, and carrying out lane change operation; (4) evolutionary updating, including acceleration, prediction of vehicle speed, deceleration, stochastic moderation and motion; (5) calculating the critical traffic parameters of density, speed and rate of the traffic flow. The invention better simulates the real operation situation ofa vehicle in a two-lane traffic system, and can reflect the dynamic change of driving psychology and driving behavior and the complex dynamic process of interaction between vehicles, simulate the dynamic lane-changing behavior of drivers more truly, and provide scientific guidance for the planning, design and management of the traffic system.

Description

[0001] Field [0002] The invention relates to the technical field of traffic engineering, in particular to a microcosmic traffic simulation method of a two-lane cellular automaton for simulating dynamic lane changing behavior. Background technique [0003] Cellular automata is a dynamic model that is discrete in time, space, and state, and has the ability to simulate the spatiotemporal evolution of complex systems. After being introduced into the transportation field, it has developed rapidly. The single-lane cellular automaton simulation system was developed first, and has been the most widely researched and developed because of its advantages of simple structure, intuitive image, and easy simulation. However, the single-lane cellular automaton model cannot simulate the phenomenon of vehicles changing lanes between different lanes when simulating the movement of vehicles, so it cannot analyze and study the driver's overtaking behavior. [0004] In order to overcome the lim...

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Application Information

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IPC IPC(8): G06F17/50
CPCG06F30/20
Inventor 张国强陈峻
Owner SOUTHEAST UNIV
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