Method for forecasting influence range of highway traffic incident on basis of microscopic simulation
A technology for traffic incidents and highways, applied in software simulation/interpretation/simulation, program control devices, etc., to achieve the effects of improving estimation accuracy and accuracy, expanding the scope of application, and ensuring data quality
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[0058] Example one
[0059] In this embodiment, a method for predicting the impact range of highway traffic incidents based on micro-simulation is provided, which can be implemented according to the following steps:
[0060] Step 1: Obtain real-time toll data and historical toll data of the expressway network.
[0061] The main content of expressway toll data includes information such as the current time when the vehicle enters the expressway, the toll station code that enters the expressway, the time to leave the expressway, the toll station code that leaves the expressway, and the vehicle type. By counting the toll data of entering / leaving the same toll station during the same time period of entering the expressway, the data of expressway traffic demand by time period can be obtained. The time granularity of a traffic demand matrix is 5 minutes, the horizontal axis and the vertical axis of the matrix are the toll station numbers included in the road network, and the diagonal ele...
Example Embodiment
[0072] Example two
[0073] In this embodiment, a method for predicting the impact range of highway traffic incidents based on micro-simulation is provided, which can be implemented according to the following steps:
[0074] step 1:
[0075] Store the information of vehicles that have completed their trip and leave the expressway in the toll station exit information table. The fields in the table can include: entry time, entry code, exit time, exit code, license plate number, and vehicle type.
[0076] Step 2:
[0077] The traffic incident information is stored in the traffic incident information table. The fields in the table may include: incident time, incident road section, direction, station location, number of lanes passable before the incident and the number of lanes passable after the incident.
[0078] Step 3:
[0079] The deviation of the estimated OD relative to the historical OD is defined as a state vector, and the deviation is subject to an autoregressive process:
[0080] ...
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