CN117351747A - A traffic congestion control method, device and computer-readable storage medium - Google Patents

Abstract

The invention relates to a traffic jam control method, a traffic jam control device and a computer readable storage medium, and belongs to the technical field of traffic. Comprising the following steps: planning n paths which do not pass through the target area for the traffic flow to be passed through the target area in the k period, and carrying out random path distribution so that the traffic flow to be passed through the target area in the k period is 0; constructing a vehicle accumulated quantity flow conservation function of a k+1 period target area; calculating a maximum value of the vehicle accumulation number of the k+1 time period target area and a minimum value of the vehicle accumulation number of the k+1 time period target area based on the MFD curve and the MSD curve; calculating the maximum value of the inflow traffic flow of the k-period target area and the minimum value of the inflow traffic flow of the k-period target area; and calculating the green light time of the signal lamp of which the k time period enters the target area, so as to control the inflow traffic flow of the k time period target area. The method and the device give consideration to boundary control and path induction, relieve traffic jam, and improve the road network use efficiency and regional traffic safety.

Description

A traffic congestion control method, device and computer-readable storage medium

Technical field

The present invention relates to the field of transportation technology, and in particular, to a traffic congestion control method, device and computer-readable storage medium.

Background technique

With the acceleration of urbanization, the traffic congestion problem on urban roads is becoming more and more serious, and its impact on residents' travel is also increasing. Therefore, how to alleviate the traffic congestion problem is an urgent problem that needs to be solved.

Among modern methods of alleviating traffic congestion, vehicle path guidance and regional boundary control based on Macroscopic Fundamental Diagram (MFD) have become a hot topic. Based on MFD, the vehicle number interval with the highest regional traffic efficiency is obtained and regional vehicles are maintained within this range. within the interval, thereby maximizing the distribution of regional traffic. The existing MFD-based vehicle path guidance and area boundary control methods are roughly divided into two types: the first is a traffic control method that only focuses on boundary control. This method can effectively reduce vehicles from entering congested areas, but ignores the importance of vehicles path induction, so there are problems such as the inability to effectively utilize road network resources and the inability to provide optimal traffic flow path selection for vehicles; the second is a traffic control method that only focuses on path induction, which can effectively guide vehicles to choose smoother paths, but Ignoring the boundary control of vehicles leads to vehicles wandering on the roads outside the congestion area, wasting road resources, and failing to effectively utilize the road network capacity; therefore, existing methods of alleviating traffic congestion do not consider the synergy of boundary control and path induction. Optimization results in vehicles being unable to consider congestion and utilize road network resources at the same time when selecting paths.

In addition, existing methods to alleviate traffic congestion only focus on traffic efficiency and lack consideration for regional traffic safety. Relieving regional traffic congestion while reducing traffic accidents has an important impact on residents' travel and urban development.

To sum up, how to design a traffic congestion alleviation method that takes into account both boundary control and path induction while ensuring regional traffic safety is currently a problem that needs to be solved.

Contents of the invention

To this end, the technical problem to be solved by the present invention is to overcome the problem that the traffic congestion control method in the prior art cannot take into account boundary control and path induction, and does not consider regional traffic safety.

In order to solve the above technical problems, the present invention provides a traffic congestion control method, including:

Obtain the traffic flow to be crossed in the target area of k periods, plan n paths that do not pass through the target area for each traffic flow to be crossed, and perform random path allocation for each traffic flow to be crossed, so that the target of k period The traffic flow to be crossed in the area is 0;

Based on the non-driving vehicles in the target area of period k, the internal traffic flow of the target area of period k, the inflow traffic flow of the target area of period k and the outflow traffic flow of the target area of period k, the cumulative number of vehicles flow conservation in the target area of period k+1 is constructed. function;

The first vehicle cumulative value corresponding to the maximum traffic efficiency of the target area road network is obtained based on the MFD curve, and the second vehicle cumulative value corresponding to the minimum traffic safety of the target area road network is obtained based on the MSD curve, and based on the first vehicle cumulative value Calculate the maximum cumulative number of vehicles in the k+1 period target area and the minimum cumulative number of vehicles in the k+1 period target area with the second vehicle cumulative value;

The k period target is calculated based on the maximum cumulative number of vehicles in the k+1 period target area, the minimum cumulative number of vehicles in the k+1 period target area, and the cumulative vehicle number flow conservation function in the k+1 period target area. The maximum value of the inflow traffic flow in the area and the minimum value of the inflow traffic flow in the target area during k period;

The green time of the signal light entering the target area in k period is calculated based on the maximum value of the inflow traffic flow in the target area in k period and the minimum value of inflow traffic flow in the target area in k period, and the green time of the signal light entering the target area in k period is controlled. Thus, the inflow traffic flow into the target area during k period is controlled.

In one embodiment of the present invention, the conservation function of the cumulative number of vehicles in the target area during the k+1 period is:

N(k+1)=N(k)+T[q(k)+q _in (k)-q ^′ (k)-q _out (k)],

Among them, N(k+1) represents the cumulative number of vehicles in the target area during k+1 period, N(k) represents the number of non-driving vehicles in the target area during k period, and T represents the time interval between k period and k+1 period. , q(k) represents the internal traffic flow generated in the target area during k period, q _in (k) represents the inflow traffic flow into the target area during k period, q ^′ (k) represents the internal traffic flow completed in the target area during k period, q _out ( k) represents the outflow traffic flow of the target area during k period.

In one embodiment of the present invention, the calculation formula for the maximum cumulative number of vehicles in the target area during the k+1 period is:

N _max (k+1)=N ^MFD +α (N ^MSD -N ^MFD ),

Among them, N _max (k+1) represents the maximum cumulative number of vehicles in the target area during the k+1 period, N ^MFD represents the first cumulative vehicle value corresponding to the maximum traffic efficiency of the road network obtained based on the MFD curve, and N ^MSD represents the cumulative number of vehicles based on MSD The cumulative value of the second vehicle corresponding to the road network traffic safety obtained from the curve is the lowest, α is the preset parameter;

The calculation formula for the minimum cumulative number of vehicles in the target area during the k+1 period is:

N _min (k+1)=N ^MFD -α (N ^MSD -N ^MFD ),

Among them, N _min (k+1) represents the minimum cumulative number of vehicles in the target area during the k+1 period.

In one embodiment of the present invention, the calculation formula for the maximum value of the inflow traffic flow in the target area during the k period is:

Among them, q _c (k) represents the traffic flow to be crossed in the target area during k period;

The calculation formula for the minimum value of the inflow traffic flow in the target area during the k period is:

In one embodiment of the present invention, calculating the green time of the signal light entering the target area in the k period based on the maximum value of the incoming traffic flow in the k period target area and the minimum value of the outgoing traffic flow in the k period target area includes:

When q _in,min (k)≤q _min ,

Among them, q _in,min (k) represents the minimum value of the inflow traffic flow into the target area during k period, q _min represents the traffic flow that can enter the target area when the signal lights of all intersections entering the target area are the shortest green light time, g _{i, j} (k) represents the green time of the j-th signal light at the i-th intersection entering the target area in period k, g _min represents the shortest green time of the signal light, m represents the number of intersections entering the target area, and x represents the number of intersections entering the target area. Number of signals at each intersection;

When q _in,max (k)≥q _max ,

Among them, q _in,max (k) represents the maximum inflow traffic flow into the target area during k period, q _max represents the traffic flow that can enter the target area when the signal lights of all intersections entering the target area are the longest green light time, and g _max Indicates the longest green time of the signal light.

In one embodiment of the present invention, when q _in,min (k) ≥ q _min , and q _in,max (k) ≤ q _max ,

Calculate the minimum passable traffic flow at the j-th signal light of the i-th intersection entering the target area in k-period based on the minimum value of the inflow traffic flow into the target area during k-period;

Calculate the shortest green time of the j-th signal light at the i-th intersection entering the target area during the k period based on the minimum value of the traffic flow that can pass at the j-th signal light at the i-th intersection entering the target area during the k period;

Calculate the maximum passable traffic flow at the j-th signal light of the i-th intersection entering the target area in k-period based on the maximum value of the inflow traffic flow into the target area during k-period;

The longest green time of the j-th signal light at the i-th intersection entering the target area during the k-period is calculated based on the maximum value of the traffic flow that can pass at the j-th signal light at the i-th intersection entering the target area during the k-period.

In one embodiment of the present invention, the calculation formula for the minimum passable traffic flow at the j-th signal light of the i-th intersection entering the target area in the k period is:

Among them, f _{i,j_min} (k) represents the minimum value of the traffic flow that can pass at the j-th signal light of the i-th intersection entering the target area during the k period, and h _i,j (k) represents the minimum value of the traffic flow that can be passed at the j-th signal light at the i-th intersection entering the target area during the k period. The traffic flow controlled by the j-th signal light at the i-th intersection;

The calculation formula for the shortest green light time of the j-th signal light at the i-th intersection entering the target area in the k period is:

g _{i,j_min} (k)＝t _loss +f _{i,j_min} (k)h _t ,

Among them, g _{i, j_min} (k) represents the shortest green time of the j-th signal light at the i-th intersection entering the target area in period k, t _loss represents the green light loss time, and h _t represents the saturated headway;

The calculation formula for the maximum passable traffic flow at the j-th signal light at the i-th intersection entering the target area during the k period is:

Among them, f _{i,j_max} (k) represents the maximum value of the traffic flow that can pass at the j-th signal light of the i-th intersection entering the target area during the k period;

The calculation formula for the longest green light time of the j-th signal light at the i-th intersection entering the target area in the k period is:

g _{i,j_max} (k)＝t _loss +f _{i,j_max} (k)h _t ,

Among them, g _{i,j_max} (k) represents the longest green time of the j-th signal light at the i-th intersection entering the target area in the k period.

In one embodiment of the present invention, the traffic flows to be crossed in the target area for k periods are obtained, n paths that do not pass through the target area are planned for each traffic flow to be crossed, and each traffic flow to be crossed is Random path assignment includes:

Based on obtaining the traffic flow to be passed through the target area in k time periods, n paths that do not pass through the target area are planned for each traffic flow to be passed through, and the probability of each path being selected is calculated based on the impedance of each path. The formula for calculating the probability of a path being selected is:

in, Indicates the probability that the rth path that does not pass through the target area between the starting point O and the end point D in the k period is selected, c _r represents the impedance of the rth path that does not pass through the target area, and n represents the path from the starting point O to the end point D. The number of paths between them that do not pass through the target area, θ is a constant;

Based on the probability that n paths are selected, n probability intervals between [0,1] are constructed, and the n probability intervals are expressed as:

For the traffic flow to be crossed in the target area, a number greater than 0 and less than 1 is randomly generated. If the number falls in the dth probability interval among the n probability intervals, it is the traffic flow of the target area to be crossed. The traffic flow assigns the dth path that does not pass through the target area.

The invention also provides a traffic congestion control device, including:

The path induction module is used to obtain the traffic flow to be crossed in the target area for k periods, plan n paths that do not pass through the target area for each traffic flow to be crossed, and conduct a random path for each traffic flow to be crossed. Distribute so that the traffic flow to be crossed in the target area during k period is 0;

The flow conservation function building module is used to construct the k+1 period based on the non-driving vehicles in the target area of k period, the internal traffic flow of the target area of k period, the inflow traffic flow of the target area of k period, and the outflow traffic flow of the target area of k period. The cumulative number of vehicles flow conservation function in the target area;

The first calculation module is used to obtain the first vehicle cumulative value corresponding to the maximum traffic efficiency of the target area road network based on the MFD curve, and obtain the second vehicle cumulative value corresponding to the minimum traffic safety of the target area road network based on the MSD curve, and based on The first vehicle cumulative value and the second vehicle cumulative value calculate the maximum cumulative number of vehicles in the target area during the k+1 period and the minimum cumulative number of vehicles in the target area during the k+1 period;

The second calculation module is used to calculate the maximum cumulative number of vehicles in the target area during the k+1 period, the minimum cumulative number of vehicles in the target area during the k+1 period, and the cumulative number of vehicles in the target area during the k+1 period. The flow conservation function calculates the maximum value of the inflow traffic flow in the target area during k period and the minimum value of the inflow traffic flow in the target area in k period;

The third calculation module is used to calculate the green time of the signal light entering the target area in the k period based on the maximum value of the inflow traffic flow in the target area in the k period and the minimum value of the inflow traffic flow in the target area in the k period, by controlling the entry in the k period The green time of the signal light in the target area thereby controls the inflow traffic flow into the target area during k period.

The present invention also provides a computer-readable storage medium. A computer program is stored on the computer-readable storage medium. When the computer program is executed by a processor, the steps of the above-mentioned traffic congestion control method are implemented.

Before controlling the cumulative number of vehicles in the target area, the traffic congestion control method provided by the present invention first performs path induction on the traffic flow to be passed through the target area, so that it can reach the destination without passing through the target area, which reduces Road congestion in the target area improves the overall use efficiency of the road network; in addition, this application is calculated based on the first cumulative vehicle value corresponding to the maximum traffic efficiency of the road network and the second cumulative vehicle value corresponding to the lowest traffic safety of the road network. The maximum and minimum cumulative number of vehicles in the target area are calculated, and the maximum and minimum values of the inflow traffic flow in the target area are obtained based on the maximum and minimum cumulative number of vehicles. By controlling the green time of the signal light entering the target area, the inflow into the target area is achieved. The traffic flow is between the maximum value and the minimum value, thereby controlling the cumulative number of vehicles in the target area, taking into account both the traffic efficiency and the safety of the road network; therefore, the traffic congestion control method provided by this application takes into account both It provides boundary control and path guidance, alleviates traffic congestion, and improves the overall efficiency of the road network. In addition, it also improves traffic safety while ensuring the traffic efficiency of the road network.

Description of drawings

In order to make the content of the present invention easier to understand clearly, the present invention will be further described in detail below based on specific embodiments of the present invention and in conjunction with the accompanying drawings, wherein

Figure 1 is a schematic flow chart of a traffic congestion control method provided by the present invention;

Figure 2 is a schematic diagram of a target area path induction provided by the present invention;

Figure 3 is a schematic diagram of a traffic flow interaction process in a target area provided by the present invention;

Figure 4 is a schematic diagram of an MFD curve provided by the present invention;

Figure 5 is a schematic diagram of an MSD curve provided by the present invention;

Figure 6 is a schematic diagram of MFD and MSD curves based on the target area provided by the present invention;

Figure 7 is a schematic diagram of a traffic congestion control principle provided by the present invention;

Figure 8 is a schematic structural diagram of a traffic congestion control device provided by the present invention;

Figure 9 is a schematic diagram of a SUMO road network model provided by an embodiment of the present invention;

Figure 10 is a schematic diagram of MFD curves under different CAV permeabilities provided by the embodiment of the present invention;

Figure 11 is a schematic diagram of MSD curves under different CAV permeabilities provided by the embodiment of the present invention;

Figure 12 is a schematic diagram of the evaluation indicators of the method provided by this application applied to different CAV penetration rate scenarios; among them, (a) in Figure 12 is a schematic diagram of the cumulative number of arriving vehicles curve used in different CAV penetration rate scenarios using the method provided by this application. Figure 12 (b) is a schematic diagram of the weighted average flow curve of the application method applied to different CAV penetration scenarios, and (c) in Figure 12 is a schematic diagram of the total delay curve of the application method applied to different CAV penetration scenarios;

Figure 13 is a schematic diagram comparing the MFD curves before and after control under the 80% CAV penetration rate scenario;

Figure 14 is a schematic diagram comparing the evaluation indicators before and after control under the 80% CAV penetration rate scenario; among them, (a) in Figure 14 is a comparison diagram of the total delay curve before and after control under the 80% penetration rate scenario, and (b) in Figure 14 is 80 Schematic diagram comparing the curves of the cumulative number of arriving vehicles before and after control under the % penetration rate scenario;

Figure 15 is a schematic diagram comparing the MSD curves before and after control under 80% CAV penetration rate;

Figure 16 is a schematic diagram of the number of road vehicles in the road network shown in Figure 9 before and after using the method of the present application to control; wherein (a) in Figure 16 is a schematic diagram of the number of road vehicles before using the method of the present application to control, and (a) in Figure 16 is a schematic diagram of the number of road vehicles before using the method of the present application to control. b) is a schematic diagram of the number of road vehicles controlled by the method of this application.

Detailed ways

The present invention will be further described below in conjunction with the accompanying drawings and specific examples, so that those skilled in the art can better understand and implement the present invention, but the examples are not intended to limit the present invention.

Please refer to Figure 1. Figure 1 is a traffic congestion control method provided by this application, which specifically includes:

S10: Obtain the traffic flow to be crossed in the target area during k period, plan n paths that do not pass through the target area for each traffic flow to be crossed, and perform random path allocation for each traffic flow to be crossed, so that k The traffic flow to be crossed in the target area during the period is 0;

S20: Construct the cumulative number of vehicles in the target area in period k+1 based on the non-driving vehicles in the target area in period k, the internal traffic flow in the target area in period k, the inflow traffic flow in the target area in period k, and the outflow traffic flow in the target area in period k. Flow conservation function;

S30: Obtain the first vehicle cumulative value corresponding to the maximum traffic efficiency of the target area road network based on the MFD curve, obtain the second vehicle cumulative value corresponding to the minimum traffic safety of the target area road network based on the MSD curve, and based on the first vehicle The cumulative value and the second vehicle cumulative value calculate the maximum cumulative number of vehicles in the target area during the k+1 period and the minimum cumulative number of vehicles in the target area during the k+1 period;

S40: Calculate k based on the maximum cumulative number of vehicles in the k+1 time period target area, the minimum cumulative number of vehicles in the k+1 time period target area, and the cumulative vehicle number flow conservation function in the k+1 time period target area. The maximum value of the incoming traffic flow in the target area during the time period and the minimum value of the incoming traffic flow in the target area during the k time period;

S50: Calculate the green time of the signal light entering the target area in k period based on the maximum value of the inflow traffic flow in the target area in k period and the minimum value of inflow traffic flow in the target area in k period, and control the green time of the signal light entering the target area in k period. The green light time thus controls the inflow traffic flow in the target area during k period.

Before controlling the number of vehicles in the target area, the traffic congestion control method provided by this application first conducts path induction on the traffic flow to be passed through the target area, so that it can reach the end point without passing through the target area, which not only alleviates the target Road congestion in the area also improves road utilization in other areas; when controlling the number of vehicles in the target area, the cumulative value of the first vehicle corresponding to the maximum traffic efficiency of the road network and the maximum traffic safety of the road network are combined The corresponding second vehicle cumulative value obtains the upper and lower limits of the cumulative number of vehicles in the target area. Since the cumulative number of vehicles in the target area is closely related to the inflow traffic flow in the target area, the inflow traffic flow in the target area is calculated based on the upper and lower limits. upper and lower limits. Finally, the green time of the signal light entering the target area is calculated based on the upper and lower limits of the inflow traffic flow in the target area. By controlling the green light time, the inflow traffic flow in the target area is controlled, so that the cumulative number of vehicles in the target area can balance efficiency and traffic safety. within the quantity range. The method provided by this application not only combines path induction and boundary control, but also comprehensively considers road network traffic efficiency and road network traffic safety when performing boundary control, effectively alleviating traffic congestion while ensuring regional traffic safety.

Specifically, in this application, the traffic flow to be passed through the target area during k period refers to the traffic flow that is expected to flow into the target area during k period and whose end point is not within the target area. This part of the traffic flow flows into the target area during k period, but because its end point It is not within the target area, so it will flow out of the target area during k period; the internal traffic flow of the target area during k period refers to the traffic flow whose starting point and end point are both within the target area. This part of the traffic flow refers to the traffic flow that is within the target area during k period. The traffic flow of the area; the inflow traffic flow into the target area during k period refers to the traffic flow expected to flow into the target area during k period and end at the target area; the traffic flow out of the target area during k period refers to the traffic flow expected to flow out of the target area during k period and end at the target area. Traffic flow that is not within the target area.

Please refer to Figure 2. Figure 2 is a schematic diagram of path induction for traffic flow to be passed through a target area in k time periods provided by an embodiment of the present application. Area 1 in the figure is the target area, and O represents the traffic flow to be passed through the target area in k time periods. Passing the starting point of traffic flow q _c (k), D represents the end point of the traffic flow q _c (k) to be passed through in the target area during k period. Since the starting point and end point of q _c (k) are both in area 2, but most Most vehicles will choose the path with the smallest impedance, that is, passing through target area 1. This will cause congestion on specific roads in the road network and reduce the overall efficiency of the road network. Therefore, it is necessary to route this part of the traffic flow so that it does not pass through the target area. You can reach the end point in area 1.

Specifically, in step S10, the path allocation step for the target area of k period to be passed through the traffic flow includes:

S100: Based on obtaining the traffic flow to be passed through the target area in k period, plan n paths that do not pass through the target area for each traffic flow to be passed through, and calculate the probability of each path being selected based on the impedance of each path, so The formula for calculating the probability of each path being selected is:

in, Indicates the probability that the rth path that does not pass through the target area between the starting point O and the end point D in the k period is selected, c _r represents the impedance of the rth path that does not pass through the target area, and n represents the path from the starting point O to the end point D. The number of paths between them that do not pass through the target area, θ is a constant;

S102: Construct n probability intervals between [0,1] based on the probability of n paths being selected. The n probability intervals are expressed as:

S103: Randomly generate a number greater than 0 and less than 1 for the traffic flow to be crossed in the target area. If the number falls in the dth probability interval among the n probability intervals, it is the traffic flow to be crossed in the target area. Assign the dth path across the traffic flow that does not pass through the target area.

For example, when there are 3 paths from the starting point O to the end point D that do not pass through the target area, and the probability of each path being selected is 1/3, then the corresponding 3 probabilities between [0,1] The interval is: [0,1/3], [1/3,2/3], [2/3,1], if for the target area from the starting point O to the end point D, the number is randomly generated by the traffic flow to be crossed. is 1/5 and falls in the first probability interval, then the first path is assigned to the traffic flow to be crossed.

Please refer to Figure 3, which is a schematic diagram of traffic flow interaction in a target area provided by this application;

Specifically, the conservation function of the cumulative number of vehicles in the k+1 period target area constructed in step S20 is:

N(k+1)=N(k)+T[q(k)+q _in (k)-q′(k)-q _out (k)],

Among them, N(k+1) represents the cumulative number of vehicles in the target area during k+1 period, N(k) represents the number of non-driving vehicles in the target area during k period, T represents the length of k period, and q(k) represents k period The internal traffic flow generated by the target area, q _in (k) represents the inflow traffic flow into the target area during k period, q′(k) represents the internal traffic flow completed in the target area during k period, q _out (k) represents the internal traffic flow of the target area during k period. Outflow traffic flow.

Since the incoming traffic flow in the target area may be divided into controlled traffic flow and uncontrolled traffic flow, in some embodiments of the present application, the control of the incoming traffic flow in the target area is mainly aimed at the controlled traffic flow, That is, q _in (k) in the embodiment of this application is the controlled traffic flow. Specifically, the calculation formula of the uncontrolled traffic flow is:

q _{in_u} (k)=βQ _in (k),

Among them, Q _in (k) represents all incoming traffic flows in the target area during k period, including controlled traffic flows and uncontrolled traffic flows, and β is the proportion coefficient.

Therefore, in some preferred embodiments, the calculation formula for the cumulative number of vehicles in the target area during the k+1 period is: N(k+1)=N(k)+T[q(k)+q _in (k)+βQ _in (k)-q'(k)-q _out (k)], further, in step S40, the maximum and minimum values of the inflow traffic flow q _in (k) of the target area in the k period can also be calculated based on this The formula is used to calculate the total number of vehicles in the target area more accurately.

Please refer to Figure 4. Figure 4 is a schematic diagram of an MFD curve provided by an embodiment of the present application. For a road network with uniform density, the MFD curve describes the unimodal relationship between the cumulative number of vehicles N and the weighted average flow rate ^qw . It can be Measure the traffic efficiency of the road network; it can be seen from the figure that when the cumulative traffic volume is less than N ^MFD , the greater the cumulative number of vehicles in the road network, the greater its weighted flow. When the cumulative traffic volume is greater than N ^MFD , the road network's The larger the cumulative number of vehicles, the smaller the weighted flow. When the cumulative traffic volume reaches N _max , the entire road network is completely blocked and the weighted flow is 0. Therefore, when the cumulative traffic volume is near N ^MFD , the traffic efficiency of the road network is maintained. At higher values, it can effectively alleviate regional congestion.

Please refer to Figure 5. Figure 5 is a schematic diagram of an MSD curve provided by an embodiment of the present application, which describes the unimodal relationship between the cumulative number of vehicles N and the accident rate S. When the cumulative traffic volume is near N ^MSD , the road network There are the most conflicts and the lowest safety. Therefore, it is necessary to control the cumulative traffic volume in a range far away from N ^MSD to improve the traffic safety of the road network.

Please refer to Figure 6. Figure 6 is a schematic diagram of the MFD and MSD curves of a target area provided by an embodiment of the present application. In the figure, N ^lb and N ^ub respectively represent the cumulative number of vehicles when taking into account the traffic efficiency of the road network and the safety of the road network. Maximum and minimum values, this application calculates the cumulative number of vehicles in the target area during the k+1 period based on the first cumulative vehicle value corresponding to the highest traffic efficiency of the road network and the second cumulative vehicle value corresponding to the lowest traffic safety of the road network, Controlling the cumulative number of vehicles in the target area within this interval can not only achieve higher traffic efficiency within the control interval but also ensure regional traffic safety.

Specifically, the calculation formula for the maximum cumulative number of vehicles in the target area during the k+1 period in step S30 is:

N _max (k+1)=N ^MFD +α (N ^MSD -N ^MFD ),

Among them, N _max (k+1) represents the maximum cumulative number of vehicles in the target area during the k+1 period, N ^MFD represents the first cumulative vehicle value corresponding to the maximum traffic efficiency of the road network obtained based on the MFD curve, and N ^MSD represents the cumulative number of vehicles based on MSD The cumulative value of the second vehicle corresponding to the road network traffic safety obtained from the curve is the lowest, α is the preset parameter;

The calculation formula for the minimum cumulative number of vehicles in the target area during the k+1 period is:

N _min (k+1)=N ^MFD -α (N ^MSD -N ^MFD ),

Among them, N _min (k+1) represents the minimum cumulative number of vehicles in the target area during the k+1 period.

Further, the embodiment of the present application calculates the inflow traffic flow of the target area in k time periods based on the maximum and minimum values of the cumulative number of vehicles in the k+1 time period target area and the flow conservation function of the cumulative number of vehicles in the k+1 time period target area in step S20. The maximum and minimum values are used to control the cumulative number of vehicles in the target area in k+1 time periods by controlling the inflow traffic flow into the target area in k time periods.

Specifically, the calculation formula for the maximum value of the inflow traffic flow in the target area during k period in step S40 is:

Among them, q _c (k) represents the traffic flow to be crossed in the target area during k period;

The calculation formula for the minimum value of the inflow traffic flow in the target area during the k period is:

Since the traffic flow to be passed through the target area is routed before controlling the number of vehicles in the target area, that is, the traffic flow that originally passed through the target area in period k will not proceed to the target area, so the inflow into the target area in period k The traffic flow also includes the traffic flow to be passed through the original target area.

Further, in the embodiment of the present application, the traffic flow entering the target area is controlled by controlling the green time of the signal light entering the target area.

Specifically, in step S50, the green time of the signal light entering the target area in k period is calculated based on the maximum value of the inflow traffic flow in the target area in k period and the minimum value of the inflow traffic flow in the target area in k period. By controlling the green time of the signal light entering the target area in k period, The green light time to control the inflow traffic flow in the target area during k period includes:

When q _in,min (k)≤q _min ,

Among them, q _in,min (k) represents the minimum value of the inflow traffic flow into the target area during k period, q _min represents the traffic flow that can enter the target area when the signal lights of all intersections entering the target area are the shortest green light time, g _{i, j} (k) represents the green time of the j-th signal light at the i-th intersection entering the target area in period k, g _min represents the shortest green time of the signal light, m represents the number of intersections entering the target area, and x represents the number of intersections entering the target area. Number of signals at each intersection;

For example, when the signal lights entering the target area meet the shortest green light time g _min of the crosswalk, the traffic flow that can enter the target area is 50, and the minimum inflow traffic flow into the target area during k period is 30. At this time, the target area is entered The green time of all traffic lights is the shortest green time.

When q _in,max (k)≥q _max ,

Among them, q _in,max (k) represents the maximum inflow traffic flow into the target area during k period, q _max represents the traffic flow that can enter the target area when the signal lights of all intersections entering the target area are the longest green light time, and g _max Indicates the longest green time of the signal light;

For example, when the signal lights entering the target area are all set to the longest green light time g _max , the traffic flow that can enter the target area is 200, and the maximum inflow traffic flow into the target area during k period is 300. At this time, entering the target The green time of all traffic lights in the area is the longest green time.

When q _in,min (k) ≥ q _min , and q _in,max (k) ≤ q _max , the green light of each signal light entering the target area needs to be calculated based on the maximum and minimum values of the inflow traffic flow in the target area during k period time, which specifically includes:

Calculate the minimum passable traffic flow at the j-th signal light of the i-th intersection entering the target area in k-period based on the minimum value of the inflow traffic flow into the target area during k-period;

Specifically, the calculation formula for the minimum passable traffic flow at the j-th signal light at the i-th intersection entering the target area in the k period is:

Among them, f _{i,j_min} (k) represents the minimum value of the traffic flow that can pass at the j-th signal light of the i-th intersection entering the target area during the k period, and h _i,j (k) represents the minimum value of the traffic flow that can be passed at the j-th signal light at the i-th intersection entering the target area during the k period. The traffic flow controlled by the j-th signal light at the i-th intersection;

Calculate the shortest green time of the j-th signal light at the i-th intersection entering the target area during the k period based on the minimum value of the traffic flow that can pass at the j-th signal light at the i-th intersection entering the target area during the k period;

Specifically, the calculation formula for the shortest green light time of the j-th signal light at the i-th intersection entering the target area in the k period is:

g _{i,j_min} (k)＝t _loss +f _{i,j_min} (k)h _t ,

Among them, g _{i, j_min} (k) represents the shortest green time of the j-th signal light at the i-th intersection entering the target area in period k, t _loss represents the green light loss time, and h _t represents the saturated headway;

Based on the maximum value of traffic flow that can enter the target area during k period, calculate the maximum value of traffic flow that can pass at the jth signal light of the i-th intersection entering the target area during k period;

Specifically, the calculation formula for the maximum passable traffic flow at the j-th signal light of the i-th intersection entering the target area in the k period is:

Among them, f _{i,j_max} (k) represents the maximum value of the traffic flow that can pass at the j-th signal light of the i-th intersection entering the target area during the k period;

Calculate the longest green time of the j-th signal light at the i-th intersection entering the target area during k period based on the maximum passable traffic flow at the j-th signal light at the i-th intersection entering the target area during k period;

Specifically, the calculation formula for the longest green light time of the j-th signal light at the i-th intersection entering the target area in the k period is:

g _{i,j_max} (k)＝t _loss +f _{i,j_max} (k)h _t ,

Among them, g _{i,j_max} (k) represents the longest green time of the j-th signal light at the i-th intersection entering the target area in the k period.

Optionally, in some embodiments of this application, the Dijkstra algorithm can also be used to calculate the shortest path in real time and perform path allocation for the incoming traffic flow in the target area during k periods, so as to further alleviate traffic congestion on the road network and improve the overall efficiency of the road network.

Figure 7 is a schematic diagram of the control principle of the traffic congestion control method provided by this application. The entire control process is divided into two layers. The upper layer calculates the cumulative vehicle number interval with the best comprehensive traffic efficiency and safety based on the MFD curve and the MSD curve. , calculate the critical value of traffic flow that can flow into the target area based on the vehicle number accumulation interval and feed this value back to the lower-layer controller. The lower-layer controller controls the vehicle number accumulation value in the target area to the vehicle number accumulation value through boundary control and path induction. within the interval.

Based on the traffic congestion control method provided by the above embodiments, embodiments of the present application also provide a traffic congestion control device. As shown in Figure 8, the device includes a path induction module 10, a flow conservation function building module 20, and a first calculation module. 30. The second calculation module 40 and the third calculation module 50; the traffic congestion control device of this embodiment is used to implement the aforementioned traffic congestion control method, so the specific implementation of the traffic congestion control device can be seen from the implementation of the traffic congestion control method mentioned above. Example part, for example, the path induction module 10 is used to implement step S10 in the above-mentioned traffic congestion control method; the flow conservation function building module 20 is used to implement step S20 in the above-mentioned traffic congestion control method; the first calculation module 30 is used to implement the above-mentioned traffic congestion control method Step S30 in the control method; the second calculation module 40 is used to implement step S40 in the above-mentioned traffic congestion control method; the third calculation module 50 is used to implement step S50 in the above-mentioned traffic congestion control method, so the specific implementation can refer to the corresponding respective The description of some embodiments will not be repeated here.

Embodiments of the present application also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program. When the computer program is executed by a processor, the steps of the above-mentioned traffic congestion control method are implemented.

In order to verify the effectiveness of the method provided in this application, the embodiment of this application was also tested using a road network in a certain city:

This application uses SUMO software to build various mixed traffic flow simulation environments. Urban Traffic Simulation (Simulation of Urban Mobility, SUMO) is a highly movable, microscopic and continuous traffic simulation package designed to handle large-scale road networks, which can simulate A road network for a given traffic demand consisting of single or multiple vehicles, where each vehicle has a well-defined trajectory and moves individually through the network. In addition, SUMO software also provides all the applications needed to prepare and perform traffic simulations, as well as a large number of tools and development packages for users to develop. This application integrates the basic simulation functions of traditional open source traffic micro-simulation software and conducts secondary development on it. The estimated path flow can be input into the road network for simulation, feedback and calibration.

Specifically, the schematic diagram of the SUMO road network model constructed by this application is shown in Figure 9. Area 1 in the figure is the target area, representing the high-density urban center, and area 2 represents the transportation distribution area.

In this road network, the cycle length of each intersection is in the range of 80 to 120s, and each intersection has 3 to 4 signal lights. For controlled intersections, the initial green time of the signal lights flowing into the target area is set to 28s. , the shortest green light time is 10s, and the longest green light time is 42s. When calculating the green light time, consider the loss time t _loss of 4s and the saturated headway _ht of 2s. There is a yellow light time of 3s after each signal light. There is no full red time. The number of vehicles in the target area is accumulated every 100s. The value is controlled once, and the entire simulation time is 30 minutes.

In order to study the control effect of the control method provided by this application in various mixed traffic flow environments, the embodiments of this application were tested at six different levels of CAV penetration rates (0%, 20%, 40%, 60%, 80%, 100 %) scenario, where CAV penetration rate refers to the ratio of the number of vehicles using Connected and Autonomous Vehicle technology to the total number of vehicles on urban roads.

Due to the different penetration rates of CAVs in mixed traffic flow environments, they will have different MFD curves and MSD curves. Figure 10 shows a schematic diagram of the MFD curves of six different levels of CAV penetration rates. It can be seen that the MFD curves in the road network The cumulative value of the number of vehicles corresponding to the maximum traffic efficiency gradually increases as the CAV penetration rate increases; Figure 11 shows a schematic diagram of the MSD curves of six different levels of CAV penetration rates. In the MSD curve, the corresponding number of vehicles corresponds to the minimum traffic safety of the road network. The cumulative value gradually decreases as the CAV penetration rate increases, and for different CAV penetration rates, the average risk rates of TTC ≤ 1.5 are: 5.16% (ρ = 80%), 7.31% (ρ = 60%), 8.86 % (ρ=40%), 9.68% (ρ=20%), 10.76% (ρ=0%); therefore, the cumulative intervals of the number of vehicles in the target area are also different under different levels of CAV penetration scenarios.

This embodiment uses the CACC model to describe the following and relaxing behavior of CAVs, the IDM model to describe the following and relaxing behavior of HVs (human-driven vehicles), and uses TTC to evaluate the safety of the road network.

Among them, the Cooperative Adaptive Cruise Control (CACC) model is a following model based on inter-vehicle communication, aiming to achieve coordinated driving between fleet vehicles. This model takes into account the relative speed and distance between vehicles. and acceleration, combined with inter-vehicle communication to achieve efficient operation of the fleet. Specifically, each vehicle obtains the involved information through wireless communication, including speed and acceleration, and then adjusts its own speed and distance according to certain algorithms and control strategies. Achieve stable following and avoid collision.

Intelligent Driver Model (IDM) is a following model based on driver behavior modeling. It is used to describe the acceleration and speed changes of vehicles. This model takes into account the distance between vehicles, relative speed, expected speed and The driver's comfort preference. Based on these factors, the IDM model can control the movement of the vehicle by calculating the optimal acceleration. Specifically, when the vehicle is too close to the vehicle in front, the IDM model will reduce the speed of the vehicle to maintain a safe distance. When the distance is long, the IDM model increases vehicle speed to maintain smooth traffic.

TTC (Time-to-Collision) is an indicator that measures the risk of collision between two vehicles. The expected collision time is calculated based on the relative speed and distance between the two vehicles. The smaller the value of TTC, the higher the probability of collision. When the value of TTC is lower than a certain threshold, if the driver's reaction is delayed or the vehicle's braking efficiency is poor, a traffic accident may occur. Therefore, the frequency with which TTC is recorded can be used as a measure of road network safety. When TTC If the value is less than 1.5s, it is considered dangerous.

Please refer to Figure 12. Figure 12 shows a schematic diagram of the evaluation indicators obtained after using the method provided by this application for control in different levels of CAV penetration scenarios. As can be seen from (a) in the figure, the penetration of 6 CAVs The cumulative number of arriving vehicles under the rate is: 3095 (ρ=0%), 3277 (ρ=20%), 3612 (ρ=40%), 4077 (ρ=60%), 4505 (ρ=80%), 5170 (ρ=100%); It can be seen from (b) in the figure that the weighted average flow rate under the six CAV permeabilities increases with the increase in permeability; it can be seen from (c) in the figure that the weighted average flow rate under the six CAV permeabilities increases. The total delay time under CAV penetration decreases as penetration increases.

As shown in Table 1, the comparative data of various indicators under 6 different levels of CAV penetration scenarios provided by the embodiment of this application:

Table 1

It can be seen from the data in Table 1 that using the method provided by this application can effectively control traffic congestion, improve the overall efficiency of the road network, and also ensure regional traffic safety.

The embodiment of this application also takes 80% CAV penetration rate as an example to compare various indicators before and after using the control method provided by this application. The comparison results are as follows:

Please refer to Figure 13. Figure 13 is a schematic diagram comparing the MFD curves before and after control. It can be seen from the figure that the data points on the MFD curve after control are more concentrated than before control. This is because the purpose of path induction and boundary control is to The traffic volume is controlled within a given range, which results in the MFD curve being more convergent; in addition, the MFD curve is obviously shifted to the upper left after control, indicating that the cumulative traffic volume in the target area is small and the average weighted flow is high, proving that under this control The road network achieves better traffic efficiency under the method.

Please refer to Figure 14. Figure 14 is a schematic diagram of the comparison curve of the total delay time and cumulative arriving vehicles before and after control. From (a) in the figure, it can be seen that after the control of the road network, the average weighted flow of the road network increased by 4.48 %, the total delay time of vehicles gradually decreases; as can be seen from (b) in the figure, after controlling the path, the cumulative number of vehicle arrivals increased from 4505 to 4835 within 30 minutes, an increase of 7.33%. This is because path induction directs vehicles from congested areas to non-congested areas, so vehicles in congested areas can evacuate quickly and guided vehicles can reach their destinations faster.

Please refer to Figure 15. Figure 15 is a schematic diagram comparing the MSD curves before and after control. It can be seen from the figure that when the cumulative number of vehicles is between 0 and 800, the safety of the road network is improved under control.

Please refer to Figure 16. Figure 16 is a schematic diagram of the road network traffic situation before and after controlling the road network model shown in Figure 9. (a) in the figure is a schematic diagram of the road network traffic situation before control, and (b) in the figure is A schematic diagram of the traffic situation of the road network after control. The dark area indicates that there are more vehicles on this path, and the light area indicates that there are fewer vehicles on this path. As can be seen from the figure, before control, there are more vehicles on most paths in the target area, and There are fewer vehicles on the path outside the target area. After control, the number of vehicles on some roads in the target area decreases, and the number of vehicles on some roads outside the target area increases, making the traffic flow distribution of the entire road network more even.

Those skilled in the art will understand that embodiments of the present application may be provided as methods, systems, or computer program products. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment that combines software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) having computer-usable program code embodied therein.

The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each process and/or block in the flowchart illustrations and/or block diagrams, and combinations of processes and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing device to produce a machine, such that the instructions executed by the processor of the computer or other programmable data processing device produce a use A device for realizing the functions specified in one process or multiple processes of the flowchart and/or one block or multiple blocks of the block diagram.

These computer program instructions may also be stored in a computer-readable memory that causes a computer or other programmable data processing apparatus to operate in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including the instruction means, the instructions The device implements the functions specified in a process or processes of the flowchart and/or a block or blocks of the block diagram.

These computer program instructions may also be loaded onto a computer or other programmable data processing device, causing a series of operating steps to be performed on the computer or other programmable device to produce computer-implemented processing, thereby executing on the computer or other programmable device. Instructions provide steps for implementing the functions specified in a process or processes of a flowchart diagram and/or a block or blocks of a block diagram.

Obviously, the above-mentioned embodiments are only examples for clear explanation and are not intended to limit the implementation. For those of ordinary skill in the art, other changes or modifications may be made based on the above description. An exhaustive list of all implementations is not necessary or possible. The obvious changes or modifications derived therefrom are still within the protection scope of the present invention.

Claims (10)

1. A traffic congestion control method, characterized by comprising:

obtaining traffic flows to be traversed in a k-period target area, planning n paths which do not traverse the target area for each traffic flow to be traversed, and carrying out random path allocation on each traffic flow to be traversed so that the traffic flow to be traversed in the k-period target area is 0;

Constructing a vehicle accumulated quantity flow conservation function of the k+1 time period target area based on the non-running vehicles in the k time period target area, the internal traffic flow of the k time period target area, the inflow traffic flow of the k time period target area and the outflow traffic flow of the k time period target area;

acquiring a first vehicle accumulated value corresponding to the maximum traffic efficiency of the road network of the target area based on the MFD curve, acquiring a second vehicle accumulated value corresponding to the minimum traffic safety of the road network of the target area based on the MSD curve, and calculating the maximum value of the vehicle accumulated number of the target area in the k+1 period and the minimum value of the vehicle accumulated number of the target area in the k+1 period based on the first vehicle accumulated value and the second vehicle accumulated value;

calculating the maximum value of the inflow traffic flow of the k-period target area and the minimum value of the inflow traffic flow of the k-period target area based on the maximum value of the vehicle accumulation number of the k+1-period target area, the minimum value of the vehicle accumulation number of the k+1-period target area and the vehicle accumulation number flow conservation function of the k+1-period target area;

and calculating the green time of the signal lamp of which the k time period enters the target area based on the maximum value of the inflow traffic flow of the k time period target area and the minimum value of the inflow traffic flow of the k time period target area, and controlling the inflow traffic flow of the k time period target area by controlling the green time of the signal lamp of which the k time period enters the target area.

2. The traffic congestion control method according to claim 1, wherein the vehicle cumulative number flow conservation function of the k+1 period target area is:

N(k+1)＝N(k)+T[q(k)+q _in (k)-q ^′ (k)-q _out (k)]，

wherein N (k+1) represents the vehicle accumulation number of the target area in the k+1 period, N (k) represents the number of non-traveling vehicles in the target area in the k period, T represents the duration of the k period, q (k) represents the internal traffic flow generated in the target area in the k period, q _in (k) Inflow traffic flow representing k-period target area, q ^′ (k) Internal traffic flow, q, representing completion of k-period target region _out (k) Representing the outgoing traffic flow of the k-period target area.

3. The traffic congestion control method according to claim 2, wherein the calculation formula of the maximum value of the cumulative number of vehicles in the target area in the k+1 period is:

N _max (k+1)＝N ^MFD +α(N ^MSD -N ^MFD )，

wherein N is _max (k+1) represents the maximum value of the cumulative number of vehicles in the target region in the k+1 period, N ^MFD Representing a corresponding first vehicle accumulated value N when the road network traffic efficiency obtained based on the MFD curve is maximum ^MSD Representing a second vehicle accumulated value corresponding to the lowest road network traffic safety obtained based on the MSD curve, wherein alpha is a preset parameter;

the calculation formula of the minimum value of the vehicle accumulation number of the k+1 period target area is as follows:

N _min (k+1)＝N ^MFD -α(N ^MSD -N ^MFD )，

Wherein N is _min (k+1) represents the minimum value of the cumulative number of vehicles in the target area in the k+1 period.

4. The traffic congestion control method according to claim 3, wherein the calculation formula of the maximum value of the inflow traffic flow of the k-period target area is:

wherein q _c (k) Representing the traffic flow to be traversed by the k-period target region;

the calculation formula of the minimum value of the inflow traffic flow of the k-period target area is as follows:

5. the traffic congestion control method according to claim 1, wherein calculating the green light time of the signal lamp of the k-period entering the target area based on the inflow traffic flow maximum value of the k-period target area and the outflow traffic flow minimum value of the k-period target area includes:

when q _in,min (k)≤q _min In the time-course of which the first and second contact surfaces,wherein q _in,min (k) Minimum value of inflow traffic flow representing k-period target area, q _min Traffic flow capable of entering target area when signal lamps of all intersections entering target area are the shortest green lamp time, g _i，j (k) Green time of jth signal lamp representing kth intersection of k period entering target area, g _min The shortest green lamp time of the signal lamps is represented, m represents the number of intersections entering the target area, and x represents the number of signal lamps at each intersection entering the target area;

When q _in，max (k)≥q _max In the time-course of which the first and second contact surfaces,wherein q _in，max (k) Represents the maximum value of the inflow traffic flow of the target area of the k period, q _max Traffic flow capable of entering target area when signal lamps of all intersections entering target area are at longest green time, g _max Indicating the longest green time of the signal.

6. The traffic congestion control method according to claim 5, wherein when q _in，min (k)≥q _min And q _in,max (k)≤q _max In the time-course of which the first and second contact surfaces,

calculating the minimum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k time period entering the target area based on the minimum value of the traffic flow flowing into the target area of the k time period;

calculating the shortest green light time of the jth signal lamp of the ith intersection of the k period entering the target area based on the minimum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k period entering the target area;

calculating the maximum value of the traffic flow which can pass through at the jth signal lamp of the ith intersection of the k period entering the target area based on the maximum value of the traffic flow flowing into the target area of the k period;

and calculating the longest green time of the jth signal lamp of the ith intersection of the k period entering the target area based on the maximum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k period entering the target area.

7. The traffic congestion control method according to claim 6, wherein,

the calculation formula of the minimum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k period entering target area is as follows:

wherein f _{i,j_min} (k) A minimum value of traffic flow which can pass through a jth signal lamp of an ith intersection entering a target area in a k period, h _i,j (k) Representing the traffic flow of the k period controlled by the jth signal lamp entering the ith intersection of the target area;

the calculation formula of the shortest green lamp time of the jth signal lamp of the kth intersection of the k period entering the target area is as follows:

g _{i,j_min} (k)＝t _loss +f _{i,j_min} (k)h _t ，

wherein g _{i,j_min} (k) The shortest green lamp time, t, of the jth signal lamp representing the ith intersection where the k period enters the target area _loss Indicating the green light loss time, h _t Representing a saturated headway;

the calculation formula of the maximum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k period entering target area is as follows:

wherein f _{i,j_max} (k) Representing the maximum value of the traffic flow which can pass through the jth signal lamp of the ith intersection of the k period entering the target area;

the calculation formula of the longest green time of the jth signal lamp of the ith intersection of the k period entering the target area is as follows:

g _{i，j_max} (k)＝t _loss +f _{i，j_max} (k)h _t ，

Wherein g _{i，j_max} (k) Representing the longest green time of the jth signal lamp of the ith intersection where the k period enters the target area.

8. The traffic congestion control method according to claim 1, wherein obtaining traffic flows to be traversed by the target area of the k period, planning n paths not traversing the target area for each traffic flow to be traversed, and performing random path allocation for each traffic flow to be traversed comprises:

based on the traffic flow to be traversed of the target area of the k period, planning n paths which do not traverse the target area for each traffic flow to be traversed, and calculating the probability of each path being selected based on the impedance of each path, wherein the probability calculation formula of each path being selected is as follows:

wherein,representing the probability that the r-th path between the start point O and the end point D of the k period is not selected through the target area c _r Indicating that the r-th strip does not pass throughThe path impedance of the target area, n represents the number of paths from the start point O to the end point D, which do not pass through the target area, and θ is a constant;

constructing n probability intervals between [0,1] based on probabilities that n paths are selected, the n probability intervals being expressed as:

and randomly generating a number which is more than 0 and less than 1 for the traffic flow to be passed through the target area, and if the number falls in the d probability interval in the n probability intervals, distributing the d path which does not pass through the target area for the traffic flow to be passed through the target area.

9. A traffic congestion control apparatus, characterized by comprising:

the route guidance module is used for acquiring the traffic flow to be traversed in the k-period target area, planning n routes which do not traverse the target area for each traffic flow to be traversed, and carrying out random route distribution on each traffic flow to be traversed so that the traffic flow to be traversed in the k-period target area is 0;

the flow conservation function construction module is used for constructing a vehicle accumulation quantity flow conservation function of the k+1 time period target area based on the non-running vehicles in the k time period target area, the internal traffic flow of the k time period target area, the inflow traffic flow of the k time period target area and the outflow traffic flow of the k time period target area;

the first calculation module is used for acquiring a first vehicle accumulation value corresponding to the maximum traffic efficiency of the road network of the target area based on the MFD curve, acquiring a second vehicle accumulation value corresponding to the minimum traffic safety of the road network of the target area based on the MSD curve, and calculating the maximum value of the vehicle accumulation number of the target area in the k+1 period and the minimum value of the vehicle accumulation number of the target area in the k+1 period based on the first vehicle accumulation value and the second vehicle accumulation value;

the second calculation module is used for calculating the maximum value of the inflow traffic flow of the k time period target area and the minimum value of the inflow traffic flow of the k time period target area based on the maximum value of the vehicle accumulation number of the k+1 time period target area, the minimum value of the vehicle accumulation number of the k+1 time period target area and the vehicle accumulation number flow conservation function of the k+1 time period target area;

And the third calculation module is used for calculating the green time of the signal lamp of which the k period enters the target area based on the maximum value of the inflow traffic flow of the k period target area and the minimum value of the inflow traffic flow of the k period target area, and controlling the inflow traffic flow of the k period target area by controlling the green time of the signal lamp of which the k period enters the target area.

10. A computer readable storage medium, characterized in that the computer readable storage medium has stored thereon a computer program which, when executed by a processor, implements the steps of the traffic congestion control method according to any one of claims 1-8.