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 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 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 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.