54 results about "Macroscopic traffic flow model" patented technology

The invention relates to a short-time forecasting method for a traffic flow based on a macroscopic road network model, which comprises the following steps: (1) obtaining the input flow of the source node of a road network at a forecasting period, extracting the average speed of each road section at a previous forecasting period and determining the flow ratio of different turning directions at each intersection; (2) calculating the time of vehicles running to the tail of a queued vehicle queue, which are input on a road so as to obtain the number of the vehicles arriving at the tail of the queue at an iterative period; (3) determining the number of the vehicles which are correspondingly turned to leave the intersections by the conditions of the number of the vehicles queued at the intersections, the saturated leaving flow and the like; (4) accumulating to obtain the total number of the vehicles leaving the intersections at one forecasting period and converting to obtain the traffic flow within the forecasting period; and (5) updating the number of the queued vehicles as known data for iterative forecasting at the next time. The short-time forecasting method for the traffic flow based on the macroscopic road network model aims at the defects that the adaptability of the road network is poor, a great deal of training data are needed, the operation quantity in a microscopic model is large and the like, which exist in the prior art. The spatial information of an urban road network is fully utilized. The short-time forecasting method for the traffic flow based on the macroscopic road network model is based on a macroscopic traffic flow model, and the forecasting of the traffic flow of a road with high accuracy and good real-time property can be realized. Moreover, the short-time forecasting method for the traffic flow based on the macroscopic road network model is suitable for most of urban road networks.

The invention discloses a stable modeling method for a Payne-Whitham (PW) macroscopic traffic flow model. The method is used for solving the technical problem that the conventional PW macroscopic traffic flow model cannot directly handle a traffic jam problem. The invention adopts the technical scheme that: on the basis of the PW macroscopic traffic flow model, a relationship between the traffic jam problem and system stability is obtained by establishing a new traffic model, so the occurrence of traffic jam or other abnormal phenomena can be determined macroscopically from the angle of global stability, basic foundation is provided for traffic control and decision, and the method is directly applicable to handling of the traffic jam problem.

The invention discloses an urban network traffic flow simulation model based on lane group and intersection vehicle stream path lane group and intersection vehicle stream. The model is based on a lane group-based macroscopic traffic flow model, and a lane group vehicle stream shifting-in process in the model is simplified; according to the deficiencies of the traffic operation description simulation of the traffic impediment of an intersection caused by the overflow of traffic flow of the intersection of a lane group-based macroscopic traffic flow model, the concept of an in-intersection vehicle stream path is put forward according to a principle that a traffic flow shifts in and shifts out from a lane group; a traffic flow shift-in and shift-out process on the in-intersection vehicle stream path is adopted to simulate all possible vehicle stream release conflict impediment conditions in the intersection; and the lane group and intersection vehicle stream path-based traffic flow macroscopic simulation model is built. With the model of the invention adopted, the defect of complex parameter calibration and coefficient calculation of an existing model can be eliminated, and quick simulation method support can be provided for urban traffic jam active prevention and control and fast dredging.

The invention discloses a macroscopic traffic flow model modeling method based on a microcosmic OVDM car-following model for solving the technical problem that the current OVDM microcosmic traffic flow car-following model has poor suitability to macroscopic traffic flow. The technical scheme of the method is as follows: a new traffic model is established based on the analysis of the relevance between a space headway delta x and a vehicle average density rho. The relevance of system stability is obtained according to the new traffic model, and as the macroscopic traffic model is compared with a microcosmic traffic model, the relevance between the macroscopic traffic model and the microcosmic traffic model is obtained. And thus, the microcosmic traffic model and the macroscopic traffic model can be related to provide a basis for the control and the decision of the traffic, and the modeling method can be directly applied to the processing of the traffic jam problem in the macroscopic traffic flow.

The invention provides a microscopic traffic flow co-simulation platform fusing vehicle dynamics. The platform comprises a microscopic traffic flow simulation model, a vehicle dynamics model and a C#language-based interactive interface, wherein the microscopic traffic flow simulation model is used for planning a vehicle running track, simulating maneuver actions of vehicles and road shape graphs,and generating road shapes reflecting road curvatures and tilt degrees, vehicle positions and vehicle velocities and accelerations; the vehicle dynamics model is used for providing reliable vehicle performance indexes and inputting geometric setting parameters, path control parameters, velocity control parameters and the like output by the microscopic traffic simulation model to the vehicle dynamics model; and the C# language-based interactive interface is used for connecting the microscopic traffic flow simulation model with the vehicle dynamics model to realize interaction between the two models. The vehicle running track closer to reality can be generated, so that the deficiency of not considering real motion conditions of the vehicles in an existing microscopic traffic flow simulationmodel during road simulation is made up for.

The invention is suitable for the traffic field and provides a short-time traffic flow prediction method and device. The short-time traffic flow prediction method comprises steps that a macro trafficflow model is acquired; a state vector, a state equation, an observation vector and an observation equation are determined; a data assimilation system framework for traffic flow prediction is constructed; observation data of different observation period types are classified and sampled; historical observation data are fused, and missing observation values at the present time period are completed based on the adjusted data assimilation method of set Kalman filtering; based on the data assimilation method, model parameters of a macroscopic traffic flow model are corrected and adjusted; the macroscopic traffic flow model after model parameter adjustment is utilized to predict the traffic flow in the future. The short-time traffic flow prediction method is advantaged in that the traffic flow in the future can be predicted, moreover, online adjustment is realized, and the short-time traffic flow prediction method is easy to promote.

The invention discloses a modified car-following microscopic traffic flow modeling method considering a plurality of cars in the front. The technical problem that signal lamps cannot be controlled at crossroads due to the fact that a prior car-following model is inconsistent with actual traffic conditions is solved. The variance ratio of optimized rate of a plurality of cars in the front relative to car distances, delay time of front car action and weighting factors of front car action are introduced in a traffic flow velocity model, parameters such as the number of cars in the front and the delay time and weighting factors of front car action are considered and adjusted in accordance with actual traffic conditions, the novel established microscopic traffic flow model is actual, and the traffic flow modeling technical problems in the new road design, management of the prior road operation and control of signal lamps of crossroads are solved.

The invention relates to a system theory analysis and control method, in particular to a macroscopic traffic flow model branch-and-bound analysis and control method for blocking a road, and belongs to the field of road traffic flow analysis and control. According to the method, two equivalent variable substitutions are introduced to transform a traffic flow problem into a system stability problem, and therefore whether the traffic is blocked up or other abnormal phenomena are caused is judged macroscopically from the point of overall stability. Branch-and-bound analysis is carried out on the model after equivalence transformation, the balance point of the system is solved uniformly, and branch points causing the change of the character of the system are found out. Corresponding control schemes are designed according to the different branch points, the unstable branch points of the system are changed into the stable branch points, or the unstable branch points are removed to be changed into the stable area of the system, namely, the stable running state of the traffic flow, and the actual operation can be achieved by controlling the opening and closing time of an entrance ramp adjusting rod and setting a variable information display board.

The invention discloses an urban traffic jam identification method based on a virus propagation theory. The method comprises the following steps: 1, establishing an urban traffic jam propagation model based on the SIS virus propagation theory; 2, calculating the congestion proportion of the road section; and 3, recognizing the state of the road section based on the HHT model. Compared with the prior art, the method has the following positive effects: 1) simplicity: a simple virus propagation process is used to describe space-time characteristics of congestion in an urban road network during propagation, and the defect that a microscopic traffic flow model needs great data and calculation capability can be overcome, and the defect that a macroscopic traffic flow model cannot describe the propagation process can be overcome; and 2) accuracy: the HHT model is used for recognizing the traffic state of a road section and judging whether congestion happens or not, the algorithm can capture the change rule of traffic data in time, all internal information of original data is basically reserved, and balance between the data size and the information amount is achieved to a certain degree.

To solve the technical problem that an existing car-following model and actual traffic conditions are inconsistent so that the traffic flow statistics and intersection signal lamp control cannot be achieved, the invention provides an electron hole microscopic traffic flow modeling method in a density unsaturation state. According to the method, random variation of front car influences in a traffic flow speed model under the multi-lane conditions is considered according to four actual traffic conditions including normal queuing, traffic signal lamps stopping running cars, inserting of other cars caused by too large car following distances and car inserting of a current lane caused by too large car following distances of adjacent lanes, parameters such as equivalence speeds and traffic flow density of a macroscopic traffic flow model are introduced simultaneously, and car running lanes and influences of the car running lanes on the adjacent lanes are considered. The built novel microscopic traffic flow model is close to reality, and the traffic flow modeling technology in new roads design existing road running management and intersection signal lamp control is achieved.

The invention provides a mixed user travel inducing method considering air pollution exposure, and based on individual optimal users (UE) considering individual optimal travel time, individual optimalusers (EUE) considering individual travel health and Nash Equilibrium users (ECN) considering travel health in a traffic network, a macro traffic flow model based on a Bureau of Public Road (BPR) function is adopted, a macro vehicle exhaust emission estimation model and a Gaussian misty rain model are adopted form an integrated model to describe the whole process of vehicle exhaust from generation, diffusion to final action on humans. Then travel time cost in a road network and influence of air pollution on humans are estimated and are provided to travelers by publishing means such as a variable information board, a mobile phone client and a mobile device, thereby guiding mixed users in the road network to make a reasonable path choice. The mixed user travel inducing method considering air pollution exposure provided by the invention plays an important role in managing and relieving traffic congestion and exhaust pollution by traffic organizations, and the influence of air pollution on the travelers can be reduced.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on a Jiang-Wu-Zhu macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and predication control of blocked road turns and a variable information plate based on the Jiang-Wu-Zhu macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on a Phillips macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and predication control of blocked road turns and a variable information plate based on the Phillips macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on an LWR (Lighthill-Whitham-Richards) macroscopic traffic flow model, which is used for solving a technical problem of poor real-time property of the traditional FPGA online predication control method. A technical scheme is as follows: through carrying out approximate discrete processing on the model, establishing a parallel processing flow and designing a dynamic data storage scheme, predication controls of a sealed road ramp entrance and a variable information board based on the LWR macroscopic traffic flow model are achieved by using the FPGA. Therefore, traffic flow density and running speed on a highway are effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on a discrete macroscopic traffic flow model D, which is used for solving a technical problem of poor real-time property of the traditional FPGA online predication control method. A technical scheme is as follows: through carrying out approximate discrete processing on the model, establishing a parallel processing flow and designing a dynamic data storage scheme, predication controls of a sealed road ramp entrance and a variable information board based on the discrete macroscopic traffic flow model D are achieved by using the FPGA. Therefore, traffic flow density and running speed on a highway are effectively controlled in real time.

The invention discloses a traffic flow simulation system based on an FPGA (Field Programmable Gate Array) array unified intelligent structure and a simulation method based on the system. In order to implement the online predictive control for traffic flows in different environments, the system adopts an FPGA array as a hardware platform to avoid the condition of insufficient FPGA resources; and based on the platform, a plurality of existing macroscopic traffic flow models are synthesized in one model, and the model can be adjusted through choosing different coefficients; variable information display boards are fused in the model; the approximate discretization processing is implemented for the model; a parallel processing flow is built; a dynamic data storage scheme is designed; and the traffic flow prediction based on the model is realized; road bottlenecks are found out according to defined state variables, and control solutions for ramp entry control and the variable information display boards are given out, so that the traffic flow densities and the travelling speeds of expressways can be effectively controlled in real time by adopting different macroscopic traffic flow models under different conditions.

The invention discloses a stability modeling method of a macroscopic traffic flow viscosity model, which is used to solve the technical problem that the existing models are difficult to directly deal with the problem of traffic congestion. The technical solution is to establish a new traffic model on the basis of the existing model to obtain the relationship between traffic congestion and system stability, so as to determine whether there will be traffic congestion or other abnormal phenomena from a macro perspective by using the perspective of global stability , provide a basic basis for traffic control and decision-making, and be directly applied to deal with traffic congestion problems.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on a Ross macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and predication control of blocked road turns and a variable information plate based on the Ross macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on an Aw-Rascle macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and the predication control of blocked road turns and a variable information plate based on the Aw-Rascle macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on a Kuhne macroscopic traffic flow model, which is used for solving a technical problem of poor real-time property of the traditional FPGA online predication control method. A technical scheme is as follows: through carrying out approximate discrete processing on the model, establishing a parallel processing flow and designing a dynamic data storage scheme, predication controls of a sealed road ramp entrance and a variable information board based on the Kuhne macroscopic traffic flow model are achieved by using the FPGA. Therefore, traffic flow density and running speed on a highway are effectively controlled in real time.

The invention discloses a Papasgeorgiou-E macroscopic traffic flow model-based FPGA (Field Programmable Gate Array) online predicting control method for solving the technical problem of poor real-time property of a traditional FPGA prediction control method. The technical scheme is as follows: the FPGA online predicting control method comprises the following steps of: establishing a parallel processing flow and designing a dynamic data storage scheme by carrying out model approximate discretization processing; and realizing the prediction and the control over a closed road turn and a variable information sign on the basis of the Papasgeorgiou-E macroscopic traffic flow model. According to the FPGA online predicting control method, the real-time effective control over the traffic flow density and the travel speed of an expressway is realized.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on a Xue-Dai macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and predication control of blocked road turns and a variable information plate based on the Xue-Dai macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on a Kerner-Konhauser macroscopic traffic flow model. The FPGA online predication control method is used for solving the technical problem that the conventional FPGA predication control method has poor instantaneity. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and predication control of blocked road turns and a variable information plate based on the Kerner-Konhauser macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention relates to a short-time forecasting method for a traffic flow based on a macroscopic road network model, which comprises the following steps: (1) obtaining the input flow of the source node of a road network at a forecasting period, extracting the average speed of each road section at a previous forecasting period and determining the flow ratio of different turning directions at each intersection; (2) calculating the time of vehicles running to the tail of a queued vehicle queue, which are input on a road so as to obtain the number of the vehicles arriving at the tail of the queue at an iterative period; (3) determining the number of the vehicles which are correspondingly turned to leave the intersections by the conditions of the number of the vehicles queued at the intersections, the saturated leaving flow and the like; (4) accumulating to obtain the total number of the vehicles leaving the intersections at one forecasting period and converting to obtain the traffic flow within the forecasting period; and (5) updating the number of the queued vehicles as known data for iterative forecasting at the next time. The short-time forecasting method for the traffic flow based on the macroscopic road network model aims at the defects that the adaptability of the road network is poor, a great deal of training data are needed, the operation quantity in a microscopic model is large and the like, which exist in the prior art. The spatial information of an urban road network is fully utilized. The short-time forecasting method for the traffic flow based on the macroscopic road network model is based on a macroscopic traffic flow model, and the forecasting of the traffic flow of a road with high accuracy and good real-time property can be realized. Moreover, the short-time forecasting method for the traffic flow based on the macroscopic road network model is suitable for most of urban road networks.

The invention discloses a Zhang macroscopic traffic flow model-based FPGA (Field Programmable Gate Array) online predicting control method for solving the technical problem of poor real-time property of a traditional FPGA prediction control method. The technical scheme is as follows: the FPGA online predicting control method comprises the following steps of: establishing a parallel processing flow and designing a dynamic data storage scheme by carrying out model approximate discretization processing; and realizing the prediction and the control over a closed road turn and a variable information sign on the basis of the Zhang macroscopic traffic flow model. According to the FPGA online predicting control method, the real-time effective control over the traffic flow density and the travel speed of an expressway is realized.

The invention provides a traffic jam monitoring forecast method based on a macroscopic traffic flow model with a dissipation item, and aims to overcome the technical defect that the existing traffic flow model is difficult to directly monitor and forecast traffic jams. The method obtains vehicle speed, density and flow information through video images of a monitoring camera, and forecasts traffic jams which will occur according to the newly established traffic jam model to solve the technical problem that the traffic jams cannot be forecasted in time.

The invention discloses an FPGA (Field Programmable Gate Array) online prediction control method based on an Aw-Rascle macroscopic traffic flow model. The technical problem that the conventional FPGA prediction control method has poor instantaneity can be solved. According to the technical scheme, a parallel processing flow is established by carrying out approximate discretization on the model; a dynamical data storage scheme is designed; and the predication control of blocked road turns and a variable information plate based on the Aw-Rascle macroscopic traffic flow model is realized by using an FPGA. Therefore, traffic flow density and a running speed of an expressway can be effectively controlled in real time.

The invention discloses a Zhang macroscopic traffic flow model-based FPGA (Field Programmable Gate Array) online predicting control method for solving the technical problem of poor real-time property of a traditional FPGA prediction control method. The technical scheme is as follows: the FPGA online predicting control method comprises the following steps of: establishing a parallel processing flow and designing a dynamic data storage scheme by carrying out model approximate discretization processing; and realizing the prediction and the control over a closed road turn and a variable information sign on the basis of the Zhang macroscopic traffic flow model. According to the FPGA online predicting control method, the real-time effective control over the traffic flow density and the travel speed of an expressway is realized.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on a Payne macroscopic traffic flow model, which is used for solving a technical problem of poor real-time property of the traditional FPGA online predication control method. A technical scheme is as follows: through carrying out approximate discrete processing on the model, establishing a parallel processing flow and designing a dynamic data storage scheme, predication controls of a sealed road ramp entrance and a variable information board based on the Payne macroscopic traffic flow model are achieved by using the FPGA. Therefore, traffic flow density and running speed on a highway are effectively controlled in real time.

The invention discloses an FPGA (Field Programmable Gate Array) online predication control method based on a macroscopic traffic flow model formulated by Wu Zheng, which is used for solving a technical problem of poor real-time property of the traditional FPGA online predication control method. A technical scheme is as follows: through carrying out approximate discrete processing on the model, establishing a parallel processing flow and designing a dynamic data storage scheme, predication controls of a sealed road ramp entrance and a variable information board based on the macroscopic traffic flow model formulated by Wu Zheng are achieved by using the FPGA. Therefore, traffic flow density and running speed on a highway are effectively controlled in real time.