41 results about "Traffic pollution" patented technology

The invention belongs to the technical field of vehicle management, in particular a smart urban cloud computing parking management system and an implementation method. The system comprises a parking space monitoring component, a parking lot monitoring unit, a data processing center unit, a remote parking space publishing unit, a remote paring space booking unit and a remote settlement unit. Through the system, events related to parking can be more conveniently managed, an invalid traffic flow produced by looking up a parking space is reduced, the traffic conditions of roads around the parking lot are improved, the traffic pollution is correspondingly reduced, the distribution of the parking demand on time and space is balanced, the utilization rate of a parking facility is increased, the efficiency of the entire traffic system is increased, and the economic vigor of a commercial district is improved.

The invention relates to the field of environmental protection and aims at providing a mobile monitoring system for displaying air environmental quality pollution level of a road in real time. The system is capable of achieving real-time monitoring of pollutant discharge of an on-road motor vehicle, instantaneously learning the road traffic pollution degree and guiding green travel of people, and is beneficial to improvement of the environment monitoring management level. According to the technical scheme, the mobile monitoring system for displaying the air environmental quality pollution level of the road in real time is characterized by comprising a plurality of vehicle-mounted fixed ends with data acquisition and transmission modules, and a data receiving terminal with a data receiving module, wherein the plurality of vehicle-mounted fixed ends are arranged on various vehicles through adsorption devices separately; the data receiving terminal is arranged in an environmental management department; and each data acquisition and transmission module comprises various monitoring sensors, a digital transmission module, a GPS module, a power module and a mainboard connecting various components.

The invention discloses a method for quantizing urban motor vehicle emission load based on resident trip analysis, belonging to the technical field of intelligent traffic. The method comprises the following steps: analyzing resident trip characteristics; predicting traffic volume; determining an emission factor by means of a road experiment; calculating the emission load of motor vehicle pollutants; and evaluating environment. In the method, the practical resident trip situation information obtained by investigation is combined with a vehicle emission model, and traffic investigation data is reasonably linked with motor vehicle environment evaluation so as to calculate the motor vehicle emission load within a certain area in the urban; and by utilizing the method, necessary basic data and important parameters for total wide-zone emission load estimation of the urban traffic can be accurately and objectively provided, and practical data and decision support can be provided for controlling traffic pollution and realizing the urban traffic planning for sustainable development and the like. The method has the advantages of high accuracy and high efficiency, and is convenient to implement on the basis of fully utilizing the existing traffic investigation data.

The invention provides a vehicle travelling guiding system based on internet of vehicles and a method for guiding vehicle travelling, belonging to the field of navigation apparatuses. The vehicle trip guiding system includes a route planning unit, a road condition information acquisition unit, and a road condition data service center, the route planning unit is used as a terminal to be arranged on a vehicle, and based on the road passing speed information of the passing road, the travelling route between the departure and the destination is planned. The road condition information acquisition unit is arranged on the vehicle, the real-time position of the vehicle, the passing direction of the vehicle, and the real-time passing speed of the vehicle can be timely monitored, the road condition data service center is in communication connection with the route planning unit and the road condition information acquisition unit via wireless network. The system improves the travelling efficiency, reduces the travelling cost, alleviates the traffic pressure, and reduces the traffic pollution.

The invention provides a unidirectional trunk line green wave coordination control self-adaptive adjusting method, which completes identification and detection of vehicle information by adopting a video identification technology, calculates a traffic flow density when detecting an average speed of the vehicles, adjusts a green time ratio of an intersection according to the traffic flow density, reasonably allocates road resources, accelerates the emptying of queuing vehicles in a branch, reduces interference of vehicle incoming and outgoing of the branch on a green wave effect, and optimizes agreen wave implementation effect. The unidirectional trunk line green wave coordination control self-adaptive adjusting method has the beneficial effects of monitoring traffic flow conditions arriving at the intersection in real time by adopting a video identification technology, dividing a vehicle queuing region, starting green wave signal self-adaptive adjustment when the vehicles in the queuing region exceeds a set threshold value, identifying and recording license plate numbers of the queuing vehicles, measuring and calculating an average driving speed of the vehicles in the road sectionwhen the vehicles arrive at a downstream intersection, predicting a time when the queue arrives at a next intersection, and adjusting a phase difference according to a preset strategy. The unidirectional trunk line green wave coordination control self-adaptive adjusting method achieves the purpose of reducing the average delay time of the vehicles so as to improve road traffic passing capacity andreducing urban traffic pollution.

The invention discloses an intelligent prediction method and system for a road traffic pollution source, and belongs to the field of traffic pollution and environment monitoring. The method comprises the steps of obtaining first traffic flow information and vehicle identification information collected by a first detector within a first period of time; obtaining second traffic flow information collected by a second detector within a second period of time; conducting statistics on the occupation rate of vehicle types of vehicles driven in a first road within the first period of time and the occupation rate of emission standards of the vehicle types according to the vehicle identification information and urban in-use vehicle information base; obtaining urban road network traffic flow dynamic information within the first period of time according to the first and second traffic flow information and an urban road network structure chart, and predicting the urban traffic flow information within the second period of time; calculating the urban emission load within the second period of time by means of the occupation rate of the vehicle types, the occupation rate of the emission standards of the vehicle types, vehicle emission coefficients and the urban traffic flow information within the second period of time.

The invention discloses a scenic area road traffic pollution early-warning device based on a remote sensing technique. Atmospheric laser measurement systems are arranged at measuring points of three to five commanding heights, and all of the atmospheric laser measurement systems are connected to a server; a monitoring result device which is used for detecting the concentration of pollutants of a scenic area road traffic environment air roadside fixed routine monitoring station is connected to the server; a monitoring device of a scenic area combined environment air fixed routine monitoring station is connected to the server; in consideration of various advantages and disadvantages of a current area environment monitoring platform, according to the geographic feature of 'on three sides are cloud-capped hills, on one the busy town' of a West Lake scenic area, NO2 and other chemical substances which are mainly generated by road traffic in the scenic area are monitored in real time by constructing an atmospheric remote sensing and remote measuring platform at the commanding heights around the West Lake.

The present invention provides a vehicle activity level analysis method facing real-time road network discharge assessment. The method takes achieving of dynamic discharge assessment in a road trafficactual operation condition as a target, a vehicle activity level analysis method is established according to the disclosed real-time traffic road condition information so as to support the road network level real-time traffic pollution assessment. The method concretely comprises the steps of: taking the real-time dynamic traffic information as a basis, constructing a data collection and processing method of employing the real-time traffic road condition information to obtain operation parameters facing dynamic discharge assessment, establishing a corresponding relation model based on relatedrelations of real-time traffic road condition and the road section average speed and the road section average speed and the road section real-time flow, establishing a vehicle activity analysis methodof real-time road condition-road section speed-road section flow, and combining a vehicle pollution discharge measurement model to achieve dynamic discharge assessment in the road traffic operation condition.

The invention discloses a short-term traffic forecasting method based on a multi-task multi-view learning model. The method comprises the following steps: 1, constructing a space-time data model individually for each road segment; 2, constructing a multi-core learning model; 3, constructing an objective function by adopting a multi-task multi-view feature learning model; 4, introducing a particleswarm optimization algorithm to optimize the objective function obtained in the step 3; and 5, repeating the steps 1 and 2 for any road segment to obtain input features, bringing the input features into an optimized objective function, and realizing short-term traffic prediction for any road segment. The method realizes the efficient prediction of short-term traffic, solves the problem that the spatial-temporal heterogeneity and the global prediction ability of the model can not reach equilibrium, solves the problem of parameter optimization of the model, and can be widely used in urban planning, human mobility survey, automobile navigation, emergency response, space-time accessibility analysis and traffic pollution modeling.

The invention provides an urban discrete traffic network design method based on target assignment. In the planning of urban transportation network, it is often necessary to consider the requirements of setting certain target traffic in order to control traffic congestion, traffic pollution, service level, etc., the so-called target distribution problem. In order to make rational use of road resources and make the service level of each road section close to the design goal, the present invention establishes a method for urban discrete traffic network design based on target distribution. The method comprises following steps: (1) constructing a two-layer planning model; the upper target is to minimize the mean square error of the actual service level and design goal of each road segment; theconstraint condition is the capital budget, the decision variable is the construction plan of the candidate road segment, and the lower layer is the user equilibrium; (2) using the iterative optimization algorithm to solve the model; (3) describing the specific implementation method and the effectiveness of the method combining the Nguyen-Dupuis network commonly used in traffic network analysis.

The patent of the invention discloses an urban road separating pedestrians from vehicles. All the components of the cross section of the urban road are not arranged on one horizontal plane, and are designed into concave or convex trapezoidal cross sections; green belts are designed into inclined planes meeting the head room of sidewalks to separating vehicles from pedestrians, so that motor vehicles driven on the bottom surfaces or (the top surfaces) and pedestrians walking on the top surfaces or (the bottom surfaces) have different ways and are not mutually interfered; pedestrian posterns or pedestrian footbridges are arranged at intersections, and pedestrian zebra crossings and pedestrian traffic lights are needless. The urban road separating pedestrians from vehicles avoids the phenomenon that the pedestrians and the vehicles are crowded in the same road, avoids traffic accidents of the pedestrians and the vehicles, provides convenience for the old, children, the disabled and other people in crossing the road, reduces damage to human beings caused by traffic pollution such as exhaust gas, noises, vibration and dust, and facilitates laying, repairing and maintaining various urban pipelines.

The invention discloses a shared network driver and passenger matching method based on a bipartite graph. The method comprises the steps that a passenger submits a ride sharing request and uploads theride sharing request to a cloud server, the cloud server receives the request of each passenger and the positions and passenger carrying information of all taxies in the taxi set; the taxies meetingthe maximum number of passagners are screened according to a request of each passagner, wherein the taxis meet the constraint of passagners on the taxis and the time constraint to acquire candidate taxi sets corresponding to requests of the passengers; performing many-to-many matching on all the requests and all the candidate taxies to obtain optimal matching between the taxies and the requests, and orders are generated according to matching results; for unaccepted requests, the cloud server matches the unaccepted requests cyclically until all requests are accepted or no taxi can meet requestconstraints. The invention can be suitable for many-to-many ride-sharing matching of multiple passengers and multiple vehicles, the ride-sharing rate can be substantially increased, and traffic pollution is reduced.

The invention discloses a multifunctional urban road. According to the multifunctional urban road, the cross section of the urban road is designed into a convex trapezoidal cross section, greenbelts are designed into inclined planes capable of meeting a head room requirement of side pavements and separating motor vehicles from pedestrians, the motor vehicles are driven on the top surface, and the pedestrians walk on the bottom surface, so that the motor vehicles and the pedestrians move on the different ways and cannot be influenced by each other; underground passages, bus stations, up-down steps and motor vehicle up-down ramps are arranged at intersections, pedestrian zebra crossings and traffic lights are omitted, the traffic problem between the motor vehicles and the pedestrians can be avoided, the traffic accident between the pedestrians and the motor vehicles can be eliminated, various crowds including old people, children, disabled people and the like can conveniently pass through a road, and harms caused by traffic pollutions including exhaust gas, noise, vibration, dust and the like to human bodies are reduced; as parking places are arranged in the underground passages, the travelling and the parking are integrated, the utilization rate of urban lands is increased, and the multifunctional urban road is simple in structure and low in manufacturing cost and is convenient and applicable.

The invention relates to a method and system for estimating urban mobile source pollution emission by using incomplete information. The method comprises steps that a road section is divided into two types according to the data density obtained on the road section, specifically including an information missing road section lacking traffic mode information due to sparse collected data and an information complete road section with enough dense data; a continuous speed field and a deduced flow value are constructed for the information complete road section through the motor vehicle driving related data, and a corresponding traffic emission value is calculated through a microscopic emission factor model according to the continuous speed field and the deduced flow value; a graph convolution unit and a gating linear unit are used for respectively extracting topological characteristics of a road network and time sequence dependence of motor vehicle emission sequences on a road section with complete information, so emission sequences on a road section with information missing are reconstructed, and missing emission distribution information is filled up. According to the method, more traffic modes and emission distribution characteristics are mined by using less urban traffic data, and the urban road section level traffic pollution emission refined estimation task is realized.

The invention provides an urban road traffic pollutant emission monitoring system. The system comprises a data collection subsystem, a data analysis subsystem and an information publishing device, wherein the data collection subsystem is used for collecting and processing traffic pollutant emission data on each traffic road and corresponding traffic flow, road alignment and weather information; the analysis module is used for analyzing the data sent by the data collection subsystem, quantitatively and qualitatively analyzing the influence mechanism of traffic flow, road alignment and weather on traffic pollutant emission, mining the inner link between the traffic flow, road alignment and weather and traffic pollutant emission and outputting an analysis result of the inner link; and the information publishing device is used for displaying the analysis result.

The invention relates to a traffic pollution early warning method and a system thereof. The method comprises the following steps of receiving dynamic traffic data collected by urban road monitoring stations in real time; converting the dynamic traffic data into traffic activity level data required by a pollutant emission estimation model; inputting the traffic activity level data and basic vehicle parameters into the pollutant emission estimation model so as to acquire a vehicle pollutant emission list of an urban road; and when an emission amount of at least one pollutant in the vehicle pollutant emission list exceeds a threshold in a first early warning threshold group and / or an emission intensity of at least one pollutant exceeds a threshold in a second early warning threshold group, emitting early warning notification. The method and the system have an advantage that two factors of an emission amount of the vehicle pollutant and air quality are simultaneously considered so that accurate and timely early warning is realized.

The invention discloses a traffic pollution emission mobile edge calculation scheduling method based on an information physical system, designs a mobile edge calculation system architecture based on the information physical system, and performs virtualization abstraction on an intelligent vehicle. Task queue modeling is carried out according to calculation task requirements of a specific place; based on a distributed strategy, Voronoi algorithm realization is provided for an intelligent vehicle task allocation problem. For an Internet of Vehicles edge computing scene, an intelligent vehicle isproposed to arrive at a specified road section to collect vehicle information, a VSP model is deployed and applied to perform a traffic pollution emission computing task, a case simulation experimentis performed, and a result shows that the method is effective. Practical application of mobile edge calculation in the Internet of Vehicles improves the scheduling efficiency of intelligent vehiclesand provides theoretical support for promoting stable operation of the system.

A traffic pollution indicator mounts to an air vent of a car or other vehicle to detect pollution and present pollution information to passengers. The traffic pollution indicator includes one or more sensors for detecting pollution, one or more microcontrollers and one or more communication devices to communicate with one or more display devices. Pollution is typically detected as a change in pollution levels by the traffic pollution indicator. Various display devices or a screen of the traffic pollution indicator present sensor information, in various visual representations, to passengers.

The invention discloses a cross-free continuous traffic system for a T-junction lane and a control method of the cross-free continuous traffic system. Contravariant interchange lanes are arranged at road junctions; each contravariant interchange lane is an X-shaped overpass formed by crossing an upper passage and a lower passage; and the construction on brand-new efficient urban road traffic systems and overall construction on urban safe walking passages and bicycle passages at traffic lights of most road junctions are cancelled. Meanwhile, the cross-free continuous traffic system has very important practical significance in comprehensively increasing the operating efficiencies of urban roads, improving the living quality of people and the livable levels of cities and reducing urban traffic pollution.

The invention discloses a bridge supporting device, an installation method thereof and a bridge supporting system. The bridge supporting device comprises supporting bearings, seismic isolation bearings and installation seats, wherein the supporting bearings are fixed on a bridge pier and fixedly connected to an upper structure; the installation seats are fixed on the bridge pier and positioned onthe sides of the supporting bearings; and the seismic isolation bearings are fixed to the installation seats and fixedly connected to the upper structure. The bridge supporting device, the installation method thereof and the bridge supporting system separate the conventional functions from the seismic isolation function of the bearings. The whole bridge supporting system has a simple structure, greatly decreases the bridge cost and reduces traffic pollution.

The invention discloses a traffic signal lamp and an application method thereof, relating to traffic equipment and markings, and solving the problem that the time-space utilization rate of a present intersection is low. The traffic signal lamp comprises a straight-going standby signal lamp and a left-turning standby signal lamp, each of the straight-going standby signal lamp and the left-turning standby signal lamp is composed of a lamp housing, light-emitting diodes (LEDs) and a circuit board, wherein the circuit board is fixed on the lamp housing, and the LEDs are welded on the circuit board; and each of straight-going standby signal lamp and the left-turning standby signal lamp can display three colors and three shapes, thereby indicating six traffic states. The traffic signal lamp and the application method thereof can improve the time-space utilization rate of the intersection, alleviate traffic jams, reduce time and space delay, reduce traffic pollution, substantially improve passing capability of the intersection, and have great popularization values and social benefits.

The invention provides a method for evaluating uncertain traffic pollution gas emission control plans. On the basis of analyzing various factors influencing selection of traffic pollution gas emission control plans, with reference to the monitoring data of road traffic pollution gas emission and the experience of experts, and through analyzing the sensitivity of different risk attitudes of decision makers to sorting of the alternative traffic pollution gas emission control plans a plurality of satisfactory plans are selected from alternative traffic pollution gas emission control plans such as speed limiting, one-way traffic, traffic channeling and signal timing and sorted, thus obtaining a best plan. The method is mainly applied to intelligent decision making analysis used for evaluating the advantage and disadvantage of a plurality of uncertain traffic pollution gas emission control plans, so as to provide decision making support for the management to select the best traffic pollution gas emission control emergency plan.

The patent of the invention discloses an urban road separating pedestrians from vehicles. All the components of the cross section of the urban road are not arranged on one horizontal plane, and are designed into concave or convex trapezoidal cross sections; green belts are designed into inclined planes meeting the head room of sidewalks to separating vehicles from pedestrians, so that motor vehicles driven on the bottom surfaces or (the top surfaces) and pedestrians walking on the top surfaces or (the bottom surfaces) have different ways and are not mutually interfered; pedestrian posterns or pedestrian footbridges are arranged at intersections, and pedestrian zebra crossings and pedestrian traffic lights are needless. The urban road separating pedestrians from vehicles avoids the phenomenon that the pedestrians and the vehicles are crowded in the same road, avoids traffic accidents of the pedestrians and the vehicles, provides convenience for the old, children, the disabled and other people in crossing the road, reduces damage to human beings caused by traffic pollution such as exhaust gas, noises, vibration and dust, and facilitates laying, repairing and maintaining various urban pipelines.

The invention discloses a short-term traffic forecasting method based on a multi-task multi-view learning model. The method comprises the following steps: 1, constructing a space-time data model individually for each road segment; 2, constructing a multi-core learning model; 3, constructing an objective function by adopting a multi-task multi-view feature learning model; 4, introducing a particleswarm optimization algorithm to optimize the objective function obtained in the step 3; and 5, repeating the steps 1 and 2 for any road segment to obtain input features, bringing the input features into an optimized objective function, and realizing short-term traffic prediction for any road segment. The method realizes the efficient prediction of short-term traffic, solves the problem that the spatial-temporal heterogeneity and the global prediction ability of the model can not reach equilibrium, solves the problem of parameter optimization of the model, and can be widely used in urban planning, human mobility survey, automobile navigation, emergency response, space-time accessibility analysis and traffic pollution modeling.

The invention provides a traffic information determining method and a traffic pollution emission predicting method. The traffic information determining method and a traffic pollution emission predicting method realize road speed estimation through carrying out deep multi-layer self-attention processing on historical road speeds in a plurality of historical periods, and realize road flow estimationthrough performing deep key-value pair attention processing on candidate attribute information and candidate road flow of a plurality of similar roads, thereby estimating the missing road speed and road flow respectively according to change features of different traffic information, improving the precision and reliability of traffic information, performs traffic pollution emission prediction on the basis of the traffic information, and improving the precision of the traffic pollution emission prediction.

The invention discloses a traffic pollution control method and system and a storage medium, and the method comprises the following steps: obtaining original tail gas monitoring data and traffic flow information data, and carrying out the preprocessing; and inputting the processed data into a preset traffic pollution management and control model, and outputting a management and control strategy. Aconstruction method of the traffic pollution management and control model comprises the following steps: collecting exhaust monitoring data and preprocessing the exhaust monitoring data; constructinga traffic pollution reinforcement learning model; and setting a traffic pollution control model strategy algorithm and performing training based on the data processed in the step S201. The long-term return optimal value function is estimated by using the deep Q network to overcome the problem of overlarge action state space, and the time sequence dependence of the exhaust environment system is constructed by using the mixed environment state, so that an effective traffic flow and speed limiting strategy is formulated to reduce traffic pollution.

The invention discloses a method and system for intelligently predicting road traffic pollution sources, belonging to the field of traffic pollution and environmental monitoring. The method includes: acquiring first traffic flow information and vehicle identification information collected by a first detector within a first time period ; Obtain the second traffic flow information collected by the second detector in the first time period; according to the vehicle identification information and the city's vehicle information database, count the vehicles driving on the first type of road in the first time period According to the first and second traffic flow information and the city's road network structure map, the city's road network traffic flow dynamic information in the first time period is obtained, and thus the forecast The city's traffic flow information in the second time period; use the proportion of vehicle types and the proportion of each vehicle type emission standard, vehicle emission coefficient and the city's traffic flow information in the second time period to calculate the city's emissions in the second time period quantity.

The invention is suitable for the technical field of environmental monitoring, and provides a pollutant emission monitoring method and device and terminal equipment. The method comprises the steps ofobtaining the road information of a to-be-monitored road, and obtaining the target width of the to-be-monitored road based on the road information; obtaining environmental data of the to-be-monitoredroad, and obtaining a concentration mean value of at least one pollutant based on the environmental data; and based on the target width of the to-be-monitored road and the concentration mean value ofthe at least one pollutant, calculating the traffic pollutant discharge amount of the to-be-monitored road. According to the method, the target width of the road and the concentration mean value of the pollutants are utilized, so that the calculated emission of the traffic pollutants is more accurate.

The invention discloses a traffic discharge pollution visualization early warning method, which includes the basic data information of the monitoring area; extracts the characteristics of the relative position information; selects the optimal air quality monitoring station and the optimal traffic road node; constructs the prediction of air pollutants model; build a pollutant concentration prediction model for any monitoring point and correct it; perform visual early warning of urban traffic pollution emissions in the monitoring area. The invention also discloses a system for realizing the traffic discharge pollution visualization early warning method. The method of the invention can perform real-time prediction and early warning of real-time dynamic air pollutants at any point in the road traffic coverage area, and the method of the invention has high reliability and good practicability.