Active intelligent traffic flow induction method

Abstract

The invention provides an active intelligent traffic flow induction method which includes the following steps that an intersection implementing mechanism obtains the real-time vehicle road condition information of a current intersection through a radio frequency sensing module, analyzes a road congestion degree, and adjusts a signal light lighting time strategy in real time at any time for a roadin a congestion direction. According to the method, for a vehicle with the starting of a navigation signal, best smooth route information can be provided for a running vehicle at any time according toa driving destination and the situation of a road ahead, and the effective diversion of the vehicle is induced. An induction center issues warning information or re-plans a driving route for the vehicle expected to pass through an intersection according to the congestion status of each intersection. According to the method, the congestion of urban traffic can be effectively prevented, the trafficefficiency of the urban traffic is improved, the operating cost of the urban traffic is reduced, and the traffic conditions of the urban traffic are effectively improved.

Description

technical field [0001] The invention belongs to the field of intelligent traffic, in particular to an active intelligent traffic flow induction method. Background technique [0002] In recent years, the number of motor vehicles in major cities has increased dramatically. Although urban traffic construction and traffic management departments have invested a lot of manpower, financial resources and material resources in the construction of traffic road network and traffic management technology facilities, urban traffic congestion, traffic safety accidents, and difficult driving and parking cannot be avoided. become a common problem in major cities. Because of the randomness and irregularity of traffic participation, traffic managers cannot plan in advance, which intensifies the pressure on urban traffic management. [0003] The existing traffic management system is mainly based on manual intervention and management, supplemented by intersection signal control, with few road ...

AI Technical Summary

Problems solved by technology

[0005] (1) Non-dynamic: In China, the high cost of sensing equipment limits the large-scale and large-scale deployment of intelligent transportation systems, and a small amount of road surface information collection is concentrated on the main nodes of the road network mainly at intersections. Comprehensive and effective collection of various information in the traffic system, unable to dynamically and accurately reflect the exact state of the traffic system

[0006] (2) Non-global: The existing intelligent transportation system project planning and construction are independent of each other, the information collected by each system cannot communicate with each other, and the interfaces between systems or equipment of different equipment manufacturers are not open, resulting in the analysis and judgment of traffic conditions. The potential coordination effect of traffic information between systems may lead to repeated construction of systems or functions and repeated collection of data information. The judgment results of independent systems are not comprehensive and overall

[0007] (3) Non-automatic: The current intelligent transportation system has a single means of information collection, and the accuracy of traffic decision-making cannot be guaranteed. The operation and decision-making of the system require a lot of manual participation, manual intervention and manual discrimination, and the level of intelligence and automation is low

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