Road traffic capacity measurement method and device for automatic driving and electronic equipment

Abstract

Embodiments of the present application relate to a kind of road traffic capacity measurement method, device and electronic equipment for automatic driving, comprising: obtaining the lane type of each lane in the road section to be measured;According to lane type, determine at least one vehicle type allowed to pass in each lane;The headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate corresponding to each of at least one vehicle type and the probability of each vehicle type selecting the lane type of the m-th lane are obtained;According to the market penetration rate corresponding to each of each vehicle type in the m-th lane, the probability of each vehicle type selecting the lane type of the m-th lane, and the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the average headway of the m-th lane is obtained;Based on the average headway corresponding to each of each lane in all lanes, the total traffic capacity of the road section to be measured is determined.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a method, apparatus and electronic device for calculating road capacity for autonomous driving. Background Technology

[0002] With current technological advancements, new types of vehicles, represented by autonomous vehicles, are entering a period of rapid development and gradually integrating into the existing transportation system. For some time, road traffic will be characterized by a mix of autonomous (or other new types of vehicles) and traditional human-driven vehicles. During the development of autonomous driving technology, on the one hand, the operation of these new vehicles may require support from some roadside equipment (such as connected devices and road information monitoring equipment). On the other hand, due to safety and technological maturity factors, it is necessary to separate new vehicles from traditional vehicles as much as possible to avoid interference from sudden actions by traditional vehicle drivers, and to avoid potential risks associated with the immaturity of the technology (collisions with other vehicles or traffic chaos caused by frequent acceleration, deceleration, and lane changes by new vehicles). Therefore, special lane strategies for autonomous and other new vehicles have been proposed to promote their safe and stable integration into the existing transportation system.

[0003] Meanwhile, new types of vehicles, such as autonomous vehicles, utilize advanced technologies such as control equipment and connected devices to enhance their perception, decision-making, and control capabilities, enabling them to achieve beyond-line-of-sight perception, predictive decision-making, and precise control. Their microscopic operational characteristics on the road (acceleration time, acceleration distance, lane change distance, etc.) will differ from those of traditional vehicles.

[0004] Furthermore, current methods for calculating traffic capacity mainly rely on the simple summation of the traffic capacity of each lane, without considering the differences in lane separation methods and management strategies that lead to lane-changing weaving situations. Such weaving will affect lane traffic capacity, reducing the applicability and accuracy of traditional traffic capacity calculation methods.

[0005] In this context, using road capacity models based on traditional manned vehicles to assess traffic conditions in the new situation may lead to errors and hinder traffic decision-making. Summary of the Invention

[0006] This application provides a method, apparatus, and electronic device for calculating road capacity for autonomous driving, in order to solve the problem of inaccurate road capacity calculation in the prior art.

[0007] Firstly, this application provides a method for calculating road capacity, the method comprising:

[0008] Obtain the lane type for each lane in the road segment to be measured;

[0009] Based on the lane type, determine at least one type of vehicle that is allowed to travel in each lane;

[0010] Get the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each vehicle type in at least one vehicle type, and the probability of each vehicle type choosing the m-th lane. The m-th lane is any lane in the road segment to be tested, the i-th vehicle and the j-th vehicle are two adjacent vehicles, and m, i and j are all positive integers.

[0011] Based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane, the average headway of the m-th lane is obtained.

[0012] The total capacity of the road segment to be measured is determined based on the average headway for each lane in all lanes.

[0013] This method determines the permitted vehicle types in each lane based on the lane type of the road segment to be measured. It then determines the headway between adjacent vehicles based on their vehicle types. Furthermore, by obtaining the market penetration rate of each vehicle type and the probability of that vehicle type choosing a lane type, it determines the average headway for each lane. Finally, it determines the total capacity of the road segment to be measured based on the average headway for each lane. In this method, regardless of whether the vehicles are autonomous or traditionally driven, as long as the headway, market penetration rate, and probability of lane type selection of vehicles in each lane are determined, the capacity of the road segment to be measured can be accurately calculated. This solves the problem of inaccurate road capacity calculations caused by the addition of autonomous vehicles to the road in existing methods, providing strong data support for subsequent road decision-making.

[0014] In conjunction with the first aspect, in the first embodiment of the first aspect of the present invention, the average headway of the m-th lane is obtained based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type selecting the lane type of the m-th lane, and the headway between the i-th vehicle and the j-th vehicle in the m-th lane. Specifically, this includes:

[0015] Based on the market penetration rate of the vehicle type of the i-th vehicle, the probability of a vehicle of the i-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the i-th vehicle appearing in the m-th lane is obtained.

[0016] Based on the market penetration rate of the vehicle type of the j-th vehicle, the probability of a vehicle of the j-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the j-th vehicle appearing in the m-th lane is obtained.

[0017] The average headway of the m-th lane is obtained based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles appears in the m-th lane.

[0018] In conjunction with the first aspect, in the second embodiment of the first aspect of the present invention, determining the total capacity of the road segment to be measured based on the average headway corresponding to each lane in all lanes includes:

[0019] The lane capacity of the m-th lane is determined based on the average headway of the m-th lane.

[0020] The total capacity of the road segment to be measured is determined based on the lane capacity of all lanes.

[0021] In conjunction with the second embodiment of the first aspect, in the third embodiment of the first aspect of the present invention, when the road segment to be measured includes two lane types and the two lane types are separated by a preset isolation form, the method further includes:

[0022] The method obtains the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second lane type, and the second probability of vehicles of the second lane type choosing the second lane type in the road segment to be measured. Here, the first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in the first lane type and the second lane type.

[0023] Based on the number of first lanes, the first market penetration rate, the first probability, the number of second lanes, the second market penetration rate, and the second probability, obtain the first weight of the first lane type and the second weight of the second lane type;

[0024] The total traffic capacity of the road segment to be measured is obtained based on the first average headway for lanes of the first lane type, the second average headway for lanes of the second lane type, the number of lanes of the first lane, the first weight, the second average headway for lanes of the second lane type, the number of lanes of the second lane, and the second weight.

[0025] In this method, when there are two lane types and the two lane types are separated by a preset isolation form, such as soft isolation forms like traffic markings, the capacity relationship between the two types can be obtained by using the market penetration rate of the vehicle types allowed to pass through each lane type and the probability of vehicles of each vehicle type choosing the lane type. (First weight and second weight) Based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, and the capacity relationship between the two lane types, the total capacity of the road segment to be measured can be determined. This method is more accurate than simply summing the capacity of each lane to obtain the total capacity of the entire road segment to be measured.

[0026] In conjunction with the third embodiment of the first aspect, in the fourth embodiment of the first aspect of the invention, the total traffic capacity of the road segment to be measured is obtained based on the first average headway, the number of first lanes, and the first weight of the first lane type, and the second average headway, the number of second lanes, and the second weight of the lanes corresponding to the second lane type, including:

[0027] Based on the first average headway of the first lane type, the first number of lanes, and the first weight, the first traffic capacity of the first lane type is obtained;

[0028] Based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of second lanes, and the second weight, the second traffic capacity of the second lane type is obtained.

[0029] The total capacity of the road segment to be measured is obtained based on the first and second capacity.

[0030] Secondly, this application provides a road capacity calculation device, which includes: an acquisition module, a determination module, and a processing module;

[0031] The acquisition module is used to acquire the lane type of each lane in the road segment to be measured;

[0032] The determination module is used to determine, based on the lane type, at least one type of vehicle allowed to pass in each lane;

[0033] The acquisition module is also used to acquire the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each vehicle type in at least one vehicle type, and the probability of each vehicle type choosing the lane type of the m-th lane. Here, the m-th lane is any lane in the road segment to be tested, the i-th vehicle and the j-th vehicle are two adjacent vehicles, and m, i and j are all positive integers.

[0034] The processing module is used to obtain the average headway of the m-th lane based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane; and to determine the total traffic capacity of the road segment to be measured based on the average headway of each lane in all lanes.

[0035] Optionally, the device includes:

[0036] The processing module is further configured to: obtain the probability that the i-th vehicle appears in the m-th lane based on the market penetration rate corresponding to the vehicle type of the i-th vehicle, the probability that vehicles of the i-th vehicle's vehicle type choose the m-th lane type, and the market penetration rate of each vehicle type among all vehicle types and the probability that vehicles of each vehicle type among all vehicle types choose the m-th lane type; obtain the probability that the j-th vehicle appears in the m-th lane based on the market penetration rate corresponding to the vehicle type of the j-th vehicle, the probability that vehicles of the j-th vehicle's vehicle type choose the m-th lane type, and the market penetration rate of each vehicle type among all vehicle types and the probability that vehicles of each vehicle type among all vehicle types choose the m-th lane type; and obtain the average headway of the m-th lane based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles appears in the m-th lane.

[0037] Optionally, the device includes:

[0038] The determination module is also used to determine the lane capacity of the m-th lane based on the average headway of the m-th lane; and to determine the total capacity of the road segment to be measured based on the lane capacity of all lanes.

[0039] Optionally, the device includes:

[0040] The acquisition module is also used to acquire the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second lane type, and the second probability of vehicles of the second lane type choosing the second lane type in the road segment to be measured. The first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in the first lane type and the second lane type.

[0041] The processing module is also used to obtain the first weight of the first lane type and the second weight of the second lane type based on the first number of lanes, the first market penetration rate, the first probability, the second number of lanes, the second market penetration rate, and the second probability; and to obtain the total traffic capacity of the road segment to be measured based on the first average headway corresponding to the lane of the first lane type, the second average headway corresponding to the lane of the second lane type, the first number of lanes, the first weight, the second average headway corresponding to the lane of the second lane type, the second number of lanes, and the second weight.

[0042] Optionally, the device includes:

[0043] The processing module is also used to obtain the first capacity of the first lane type based on the first average headway, the number of lanes, and the first weight; to obtain the second capacity of the second lane type based on the first average headway corresponding to the lanes of the first lane type, the second average headway corresponding to the lanes of the second lane type, the number of lanes, and the second weight; and to obtain the total capacity of the road segment to be measured based on the first capacity and the second capacity.

[0044] Thirdly, an electronic device is provided, including a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus;

[0045] Memory, used to store computer programs;

[0046] When a processor executes a program stored in memory, it implements the steps of the road capacity calculation method according to any embodiment of the first aspect.

[0047] Fourthly, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the road capacity calculation method as described in any embodiment of the first aspect. Attached Figure Description

[0048] Figure 1 This is a schematic flowchart of a road capacity calculation method provided in an embodiment of the present invention;

[0049] Figure 2 This is a schematic diagram of the method for calculating the average headway of a single lane provided in an embodiment of the present invention;

[0050] Figure 3 A schematic diagram illustrating the road capacity calculation method for two types of lane scenarios provided in this embodiment of the invention;

[0051] Figure 4 The lane scenario strategy diagram provided by this invention;

[0052] Figure 5 A schematic diagram illustrating the impact of autonomous driving market penetration and the proportion of non-connected autonomous driving on traffic capacity, provided by this invention.

[0053] Figure 6 This invention provides an overall flowchart of a road capacity calculation method.

[0054] Figure 7 This is a schematic diagram of a road capacity measurement device provided in an embodiment of the present invention;

[0055] Figure 8 This is a schematic diagram of an electronic device structure provided in an embodiment of the present invention. Detailed Implementation

[0056] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0057] To facilitate understanding of the embodiments of the present invention, further explanations and descriptions will be provided below with reference to the accompanying drawings and specific embodiments. These embodiments do not constitute a limitation on the embodiments of the present invention.

[0058] In view of the technical problems mentioned in the background, this application provides a method for calculating road capacity. Before introducing this method, we will first introduce several existing methods for calculating road capacity.

[0059] Road capacity is defined as the maximum hourly flow rate of vehicles that can be reasonably expected to pass through a lane or a point or uniform cross-section of a road under normal road, traffic, and control conditions, and specified quality of service requirements within a certain time period; that is, the number of vehicles passing through per hour. Its calculation method is as follows:

[0060]

[0061] Where, N max Let v be the theoretically achievable traffic capacity of a motor vehicle road segment, v be the constant speed of a motor vehicle (km / h), t0 be the minimum headway (s), and l0 be the minimum distance between vehicles (m).

[0062] Therefore, the theoretically achievable traffic capacity of a road segment depends on the ratio of vehicle speed to headway.

[0063] The safe front-to-front distance of motor vehicles, i.e., the minimum distance between the front of the vehicles, is shown in the following formula:

[0064] l0 = l f +l z +l a +l c (Formula 2)

[0065] Where l0 is the minimum distance between the front ends of the vehicles, l f l is the distance (m) the vehicle travels during the driver's reaction time. z The braking distance (m) of the vehicle, l a The safe distance between vehicles (m), l c The average length of the vehicle is (m).

[0066] The distance the vehicle travels within the driver's reaction time can be expressed as:

[0067]

[0068] Where v is the constant speed of the vehicle (km / h) and t is the driver's reaction time (s).

[0069] The braking distance of a vehicle can be expressed as:

[0070]

[0071] Where v is the constant speed of the vehicle (km / h). denoted as the longitudinal friction coefficient between the tire and the road surface (dimensionless), and i is the road slope, which is "+" for uphill and "-" for downhill.

[0072] Therefore, the theoretically achievable traffic capacity of a single motor vehicle lane is:

[0073]

[0074] This method belongs to the basic theoretical method for calculating traffic capacity. However, because parameters such as the reaction time of drivers in autonomous vehicles are different from those in traditional manned vehicles, this method is not accurate enough when applied to autonomous vehicle scenarios.

[0075] The proposed methods for calculating road capacity for autonomous driving are based on a combination of field measurements and simulations. These methods assume that new types of vehicles, such as autonomous vehicles, have already been widely deployed. They obtain the occupancy rate of these new vehicles through actual observation, acquire headway values ​​through numerical simulation, and then calculate road capacity. However, this approach is only suitable for situations where new types of vehicles, such as autonomous vehicles, are already in widespread use. It is difficult to apply this method to road management's assessment and prediction of the potential impact of these new vehicles before their widespread adoption.

[0076] Furthermore, existing studies rarely consider the differences in vehicle interaction between regular lanes and special lanes caused by the isolation methods. The resulting differences in lane capacity may lead to significant variations, which have been largely unexplored.

[0077] Based on this, this application provides a method for calculating road capacity, see details below. Figure 1 As shown, Figure 1 This is a schematic flowchart of a road capacity calculation method provided by an embodiment of the present invention. The method includes the following steps:

[0078] Step 110: Obtain the lane type of each lane in the road segment to be measured.

[0079] Step 120: Determine at least one vehicle type permitted to travel in each lane, based on the lane type.

[0080] Specifically, the road segment to be measured includes at least one lane. Lane types include, but are not limited to, special lanes and non-special lanes. Special lanes can include lanes with at least one traffic restriction policy for the types of vehicles that can travel there, such as full-time bus lanes, time-limited bus lanes, single-occupant lanes, and high-occupant lanes. Non-special lanes include lanes that can be used by all vehicle types. Therefore, at least one type of vehicle allowed to travel in each lane can be determined by the lane type.

[0081] Step 130: Obtain the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each vehicle type, and the probability of each vehicle type choosing the lane type of the m-th lane.

[0082] Specifically, the m-th lane is any lane in the road segment to be tested, and the i-th and j-th vehicles are two adjacent vehicles, where m, i, and j are all positive integers. The headway between the two vehicles is determined by the vehicle types of the i-th and j-th vehicles. The market penetration rate of each vehicle type in the m-th lane and the probability of each vehicle type choosing the m-th lane can be obtained through market research, observation, or other methods. Vehicle types include, but are not limited to, traditional manned cars, autonomous vehicles, and traditional manned buses.

[0083] In one alternative example, there are currently two main types of vehicles operating on urban expressways: cars and buses.

[0084] Currently, autonomous vehicles are mainly divided into two categories: The first category is non-connected autonomous vehicles based on single-vehicle sensor control, which rely entirely on onboard equipment for perception, decision-making, and control. The second category is vehicles that are connected to the network and coordinate control with their own vehicle. These vehicles can use connected communication devices to obtain real-time road information from other vehicles, roadside devices, etc., and then make decisions and control accordingly; these are connected autonomous vehicles.

[0085] When autonomous driving technology is applied to buses and cars, there may be six types of vehicles on the road: (1) traditional manned cars (H-car); (2) traditional manned buses (H-bus); (3) non-connected autonomous cars (A-car); (4) non-connected autonomous buses (A-bus); (5) connected autonomous cars (C-car); and (6) connected autonomous buses (C-bus).

[0086] (1) and (2) are collectively referred to as traditional manned vehicles, while (3), (4), (5), and (6) are collectively referred to as autonomous vehicles. The proportion of each type of vehicle on the road, i.e., the market penetration rate, can be expressed as ρ. H-C (H-car), ρ H-B (H-bus), ρ A-C (A-car), ρ A-B (A-bus), ρ C-C (C-car), ρ C-B (C-bus). The penetration rate relationship between different vehicle types can be expressed by the following formula:

[0087] ρ H-C +ρ H-B +ρ A-C +ρ A-B +ρ C-C +ρ C-B =1 (Formula Six)

[0088] Where, ρ H-C ρ represents the market penetration rate of traditional manned cars. H-B For the market penetration rate of traditional manned buses, ρ A-C For the market penetration rate of non-connected autonomous vehicles, ρ A-B For the market penetration rate of non-connected autonomous buses, ρ C-C For the market penetration rate of connected autonomous vehicles, ρ C-B This is to increase the market penetration rate of connected autonomous buses.

[0089] Meanwhile, in the traditional manned passenger car (H-car) segment, including single-passenger cars (Dan-car) and multi-passenger cars (Duo-car), the market penetration rate can be expressed by the following formula:

[0090] ρ H-C =ρ Dan-car +ρ Duo-car (Formula 7)

[0091] Where, ρ Dan-car ρ represents the market penetration rate of traditional single-occupancy passenger cars. Duo-car This represents the market penetration rate of traditional manned multi-passenger cars.

[0092] The headway of various vehicle types can be obtained in the following ways:

[0093] 1) If this vehicle is a traditional manned car (H-car), regardless of the type of vehicle in front, the headway is T. H-car .

[0094] 2) If this vehicle is a traditional manned bus (H-bus), the headway of the preceding vehicle, regardless of its type, is T. H-bus .

[0095] 3) If this vehicle is a non-connected autonomous driving car (A-car), it mainly relies on its own vehicle equipment such as sensors for perception, decision-making, and control. Therefore, regardless of the model of the vehicle in front, the headway is T. A-car .

[0096] 4) If this vehicle is a non-connected autonomous driving bus (A-bus), it mainly relies on its own vehicle equipment such as sensors for perception, decision-making, and control. Therefore, regardless of the type of vehicle in front, the headway is always T. A-bus .

[0097] 5) If this vehicle is a connected autonomous driving car (C-car), it primarily relies on its own vehicle equipment, such as sensors, for perception, decision-making, and control. Simultaneously, it needs to utilize connected infrastructure to achieve full-domain perception. In this case, the vehicle in front must also be a connected autonomous driving vehicle (C-car or C-bus), with a headway of T. C-car Otherwise, this vehicle will automatically revert to a non-connected autonomous driving vehicle, with a headway of T. A-car .

[0098] 6) If this vehicle is a connected autonomous bus (C-bus), it primarily relies on its own vehicle equipment, such as sensors, for perception, decision-making, and control. Simultaneously, it needs to utilize connected infrastructure to achieve full-area perception. In this case, the preceding vehicle must also be a connected autonomous vehicle (C-car or C-bus), with a headway of T. C-busOtherwise, this vehicle will automatically revert to a non-connected autonomous driving vehicle, with a headway of T. A-bus .

[0099] 7) Among traditional manned cars, some vehicles may have the characteristics of multi-occupant (2 or more people, including the driver), i.e., Duo-cars. In this case, their technical characteristics and headway are the same as those of traditional manned cars, and the only difference is the access mechanism when there is a multi-occupant lane.

[0100] The above are just examples illustrating headway distances between a few vehicle types. Headway distances between other vehicle types can also be obtained in this way. Alternatively, headway distances for the required vehicle type can be obtained through market research, manufacturer consultation, etc., without further limitations. Furthermore, manually driven vehicles, non-connected autonomous vehicles, and connected autonomous vehicles may all have different headway distances set depending on the type of vehicle preceding them; adjustments should be made according to the actual situation.

[0101] Market penetration rates for each vehicle type can also be obtained through observation, research, and other methods. Of course, these are not the only methods available; the appropriate method should be chosen based on the specific circumstances.

[0102] Step 140: Based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane, obtain the average headway of the m-th lane.

[0103] Specifically, in an optional embodiment, the average headway of the m-th lane is obtained based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane. This specifically includes, for example: Figure 2 The steps shown are as follows:

[0104] Step 210: Based on the market penetration rate corresponding to the vehicle type of the i-th vehicle, the probability of a vehicle of the i-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type among all vehicle types and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, obtain the probability that the i-th vehicle appears in the m-th lane.

[0105] Specifically, the market penetration rate ρ corresponding to the vehicle type of the i-th vehicle. i The probability γ of a vehicle of the i-th vehicle type choosing the m-th lane type.i The product of ρ and ρ, representing the market penetration rate ρ of each vehicle type allowed to travel in the m-th lane. c The probability γ of a vehicle of this type choosing the m-th lane. c The proportion of the product of the products in the set is the probability k of the i-th vehicle appearing in that lane. i The formula is shown below:

[0106]

[0107] Step 220: Based on the market penetration rate corresponding to the vehicle type of the j-th vehicle, the probability of the vehicle of the j-th vehicle choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of each vehicle type choosing the lane type of the m-th lane, obtain the probability of the j-th vehicle appearing in the m-th lane.

[0108] Specifically, the probability k of the j-th vehicle appearing in the m-th lane can be determined using the method in Formula 8. j As shown in the formula below:

[0109]

[0110] Where, γ j The probability ρ of selecting the m-th lane type for a vehicle of the j-th vehicle type. j Let be the market penetration rate of the vehicle type for the j-th vehicle.

[0111] Step 230: Based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles will appear in the m-th lane, obtain the average headway of the m-th lane.

[0112] Specifically, the headway between any two adjacent vehicles in the m-th lane includes the headway between the i-th and j-th vehicles. The probability of each of the two adjacent vehicles appearing in the m-th lane is given by the probability of the i-th vehicle appearing in the m-th lane and the probability of the j-th vehicle appearing in the m-th lane. The average headway in the m-th lane can then be obtained using the following formula:

[0113]

[0114] Step 150: Determine the total capacity of the road segment to be measured based on the average headway for each lane in all lanes.

[0115] Specifically, the method for calculating the traffic capacity of a road with m lanes is as follows:

[0116]

[0117] Among them, C hun For road capacity, T m Let be the average headway of the m-th lane.

[0118] This method determines the permitted vehicle types in each lane based on the lane type of the road segment to be measured. It then determines the headway between adjacent vehicles based on their vehicle types. Furthermore, by obtaining the market penetration rate of each vehicle type and the probability of that vehicle type choosing a lane type, it determines the average headway for each lane. Finally, it determines the total capacity of the road segment to be measured based on the average headway for each lane. In this method, regardless of whether the vehicles are autonomous or traditionally driven, as long as the headway, market penetration rate, and probability of lane type selection of vehicles in each lane are determined, the capacity of the road segment to be measured can be accurately calculated. This solves the problem of inaccurate road capacity calculations caused by the addition of autonomous vehicles to the road in existing methods, providing strong data support for subsequent road decision-making.

[0119] As can be seen from the above formula, the key to calculating traffic capacity is to determine the average headway for each lane.

[0120] Optionally, the total capacity of the road segment to be measured is determined based on the average headway for each lane in all lanes, including:

[0121] The lane capacity of the m-th lane is determined based on the average headway of the m-th lane.

[0122] The total capacity of the road segment to be measured is determined based on the lane capacity of all lanes.

[0123] Specifically, the lane capacity of the m-th lane can be obtained by the following formula:

[0124]

[0125] Among them, C dan Let T be the lane capacity of the m-th lane. m Let be the average headway of the m-th lane.

[0126] As can be seen from Formulas 11 and 12, the total capacity of a road segment is the sum of the capacity of all lanes in the road segment to be measured.

[0127] Optionally, when the road segment to be measured includes two lane types, and the two lane types are separated by a preset isolation method, the method may also include, for example... Figure 3 The method steps shown are as follows:

[0128] Step 310: Obtain the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second lane type, and the second probability of vehicles of the second lane type choosing the second lane type in the road segment to be measured.

[0129] Specifically, the first vehicle type is any vehicle type permitted in the first lane type, and the second vehicle type is any vehicle type permitted in both the first and second lane types. Preset isolation methods include non-physical isolation methods such as lane markings and signs, which can be called soft isolation methods. The first lane type can be a regular lane type, i.e., a lane type without a set road traffic policy, meaning all types of vehicles can pass. The second lane type can be a special lane type, i.e., a lane type with one or more road traffic policies. The market penetration rate and the probability of vehicles of that vehicle type choosing that lane type are determined for each vehicle type in the first lane type. Similarly, based on the traffic policy of the second lane type, the market penetration rate and the probability of vehicles of that vehicle type choosing that lane type are determined for each vehicle type in the second lane type.

[0130] In one optional example, the two lane types can include special lanes and regular lanes. Lanes with traffic control policies can be uniformly classified as special lanes, such as bus lanes and high-occupancy vehicle lanes, while lanes without traffic control policies can be uniformly classified as regular lanes. Furthermore, special lanes may have multiple traffic control policies, such as... Figure 4 As shown, Figure 4 Several common access strategies are illustrated below:

[0131] 1) Scenario 1: Mandatory automated driving special lane based on bus lane

[0132] It is mandatory for autonomous vehicles to use existing bus lanes to minimize the risk impact of autonomous vehicles (limited to local areas). Buses are free to use either bus lanes or regular lanes.

[0133] 2) Scenario 2: Autonomous driving special lane based on bus lane

[0134] Allowing autonomous vehicles to use existing bus lanes, meaning autonomous vehicles can freely choose between special lanes and regular lanes, is intended to improve traffic efficiency for autonomous vehicles and attract more people to choose them.

[0135] 3) Scenario 3: Mandatory Automated Driving Special Lanes Based on Multi-Occupant Lanes

[0136] It mandates that autonomous vehicles must use existing multi-occupant lanes in order to minimize the risk impact of autonomous vehicles (limited to local areas).

[0137] 4) Scenario 4: Autonomous driving special lanes based on multi-occupant lanes

[0138] Allowing autonomous vehicles to use existing multi-occupant lanes, meaning autonomous vehicles can freely choose between special lanes and regular lanes, can improve traffic efficiency for autonomous vehicles and attract more people to choose autonomous vehicles.

[0139] 5) Scenario 5: Mandatory Automated Driving Special Lanes Based on Dedicated Automated Driving Lanes

[0140] New dedicated lanes for autonomous vehicles will be constructed and their use will be mandatory to ensure that autonomous vehicles are not disturbed and to reduce their potential impact on normal traffic. Other vehicles will be prohibited from using these dedicated lanes.

[0141] 6) Scenario Six: Autonomous Automated Driving Special Lanes Based on Dedicated Automated Driving Lanes

[0142] New dedicated lanes for autonomous vehicles will be constructed, allowing only autonomous vehicles to use them. Autonomous vehicles can freely choose between the dedicated lanes and regular lanes. Other vehicles will be prohibited from using these lanes. This policy grants autonomous vehicles maximum access rights, facilitating their rapid deployment.

[0143] In each strategy scenario, we can obtain the number of first lanes in the first lane type (regular lane type) and the number of second lanes in the second lane type (special lane type) for both lane types, as well as the isolation form between the first and second lane types. Furthermore, based on the vehicle types allowed to pass in each lane type, we can determine the first market penetration rate (i.e., the set of market penetration rates corresponding to each vehicle type allowed to pass in the first lane type, which can also be determined by other mathematical methods that are more in line with reality) and the first probability of vehicles of the allowed vehicle types in the first lane type choosing the first lane type (by determining the probability of each vehicle type allowed to pass in the first lane type choosing that lane type, we can determine the probability of all allowed vehicle types in the first lane type choosing the first lane type). Similarly, we can determine the second market penetration rate of the allowed vehicle types in the second lane type and the second probability of vehicles of the allowed vehicle types in the second lane type choosing the second lane type.

[0144] Step 320: Based on the number of first lanes, the first market penetration rate, the first probability, the number of second lanes, the second market penetration rate, and the second probability, obtain the first weight of the first lane type and the second weight of the second lane type.

[0145] Specifically, in an optional example, the first lane type is a regular lane type, the second lane type is a special lane type, and the isolation between the first lane type and the second lane type is a soft isolation type. Based on the number of first lanes, the first market penetration rate, the first probability, the number of second lanes, the second market penetration rate, and the second probability, the relationship between the capacity of the first lane type and the capacity of the second lane type can be proposed as follows:

[0146]

[0147] Where, k f Given the first weight of the first lane type (regular lane type), the second weight of the second lane type (special lane type) can be expressed as: p is the set of vehicle types permitted to travel in both regular and special lanes, s is the set of vehicle types permitted to travel only in the current lane, and S is the set of vehicle types permitted to travel only in the current lane, where s∈S, ρ p It represents the market penetration rate of vehicle type p. It represents the probability of vehicle type p choosing a conventional lane. Let be the probability of vehicle type p choosing a special lane, s-GL be the vehicle types that can only travel in regular lanes, and S-GL be the set of vehicle types that can only travel in regular lanes. GL ∈S GL s ML It is a vehicle type that can only travel in special lanes, S ML It is a collection of vehicle types that can only travel in special lanes, s ML ∈S ML , ρ s-GL It is vehicle type s GL Market penetration rate, ρ s-ML It is vehicle type s ML Market penetration rate, n GL This refers to the number of regular lanes, n. ML It refers to the number of special lanes.

[0148] Step 330: Obtain the total traffic capacity of the road segment to be measured based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of first lanes, the first weight, the second average headway corresponding to the second lane type, the number of second lanes, and the second weight.

[0149] Optionally, the total capacity of the road segment to be measured is obtained based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of first lanes, the first weight, the second average headway corresponding to the second lane type, the number of second lanes, and the second weight, including:

[0150] Based on the first average headway of the first lane type, the first number of lanes, and the first weight, the first traffic capacity of the first lane type is obtained;

[0151] Based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of second lanes, and the second weight, the second traffic capacity of the second lane type is obtained.

[0152] The total capacity of the road segment to be measured is obtained based on the first and second capacity.

[0153] The first average headway for lanes of the first lane type and the second average headway for lanes of the second lane type can both be obtained using the methods in steps 210 to 230, only the first lane type and the second lane type need to be distinguished. The specific formulas are as follows:

[0154]

[0155] Where i represents the vehicle type of this vehicle, j represents the vehicle type of the vehicle preceding i, and T ij ρ is the headway when the vehicle type of this vehicle is i and the vehicle type of the vehicle in front is j. i ρ represents the market penetration rate of vehicle type i. j ρ represents the market penetration rate of vehicle type j. p It is the market penetration rate of vehicle type p, γ i γ is the probability of vehicle type i choosing the current lane. j γ is the probability of vehicle type j choosing the current lane. p It represents the probability of vehicle type p choosing the current lane. It represents the probability of vehicle type p choosing a conventional lane. It represents the probability of vehicle type p choosing a specific lane. It represents the probability of vehicle type i choosing a conventional lane; It is the probability of vehicle type i choosing a special lane; It is the probability of vehicle type j choosing a conventional lane; This represents the probability of vehicle type j choosing a special lane; when the current lane type is a regular lane type... T m This refers to the first average headway for a regular lane type. When the current lane is a special lane... T m The second average headway is the lane headway corresponding to a lane of a special lane type.

[0156] and The sum of the probabilities of a vehicle choosing a special lane and a regular lane is equal to 1, as shown in the following formula:

[0157]

[0158] When the separation between the first lane type and the second lane type is soft, the traffic capacity of all lanes of the first lane type is as follows:

[0159]

[0160] The capacity of all lanes in the second lane type is as follows:

[0161]

[0162] When the first lane type and the second lane type are physically separated, there is no need to consider the interaction between the two vehicle types. The interaction can be determined based on the number of lanes in each lane type and the average headway of each lane.

[0163] For example, the capacity of all lanes in the first lane type is determined as follows:

[0164]

[0165] The capacity of all lanes in the second lane type is as follows:

[0166]

[0167] Finally, the road capacity calculation method based on the two lane types is as follows:

[0168] C hun =C GL +C ML (Formula 20)

[0169] Among them, C hun To determine the road capacity of the section to be measured, T GLIt is the average headway of vehicles in the regular lanes of this road section, T ML It is the average headway of the special lanes on this road section, n GL n represents the number of regular lanes on this road section. ML k represents the number of special lanes on this road section. f As the first weight for the regular lane type, The second weight for special lane types.

[0170] In this way, when there are two lane types, the market penetration rate of the vehicle types allowed to pass through each lane type, the probability of vehicles of each vehicle type choosing a lane type, can be used to obtain the traffic capacity relationship (first weight and second weight) between the two types. Based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the isolation type between the two lane types, and the traffic capacity relationship between the two lane types, the total traffic capacity of the road segment to be measured can be determined. This method is more accurate than simply summing the traffic capacity of each lane to obtain the total traffic capacity of the entire road segment to be measured.

[0171] To facilitate application in practical traffic strategies, specific calculation methods for road capacity in multiple scenarios are provided below:

[0172] First, clarify the meaning of each parameter:

[0173] 1) Traditional manned cars (H-car);

[0174] 2) Traditional manned buses (H-bus);

[0175] 3) Non-connected autonomous driving vehicles (A-car);

[0176] 4) Non-connected automated driving buses (A-bus);

[0177] 5) Connected autonomous driving cars (C-car);

[0178] 6) Connected autonomous driving buses (C-bus);

[0179] The groups of vehicles involved in different lanes are as follows:

[0180] Z represents the set of all vehicles that may appear on the road during the current period (including special lanes and regular lanes);

[0181] P is the set of vehicle types that are allowed to travel in both regular lanes and special lanes.

[0182] I is the set of vehicle types permitted to travel in the current lane, where I GLIt is the set of vehicle types that are permitted to travel in regular lanes, I ML It is the set of vehicle types that are permitted to travel in special lanes;

[0183] K is the set of vehicle types prohibited from entering the current lane, where K GL It is the set of vehicle types that are prohibited from driving in regular lanes, K ML It is a collection of vehicle types that are prohibited from driving in special lanes;

[0184] S is the set of vehicle types that can only travel in the current lane, where S GL It is a collection of vehicle types that can only travel in ordinary lanes, S ML It is a collection of vehicle types that can only travel in special lanes.

[0185] The relationships between the parameters are shown below.

[0186] I GL ∪K GL =I ML ∪K ML =Z (Formula 21)

[0187] The above formula indicates that the union of all vehicle types that can travel in regular lanes and all vehicle types that are prohibited from traveling in regular lanes is the total number of vehicle types in this scenario, and it is also the union of all vehicle types that can travel in special lanes and all vehicle types that are prohibited from traveling in special lanes.

[0188] P = I GL ∩I ML (Formula 22)

[0189] The above formula indicates that the types of vehicles that can travel in both regular lanes and special lanes are the intersection of the types of vehicles that can travel in regular lanes and the types of vehicles that can travel in special lanes.

[0190] S GL ∪P=I GL (Formula 23)

[0191] The above formula indicates that the union of vehicle types that can only travel in regular lanes and vehicle types that can travel in both regular lanes and special lanes is the total number of vehicle types that can travel in regular lanes.

[0192] S ML ∪P=I ML (Formula 24)

[0193] The above formula indicates that the union of the types of vehicles that can only travel in special lanes and the types of vehicles that can travel in both regular lanes and special lanes is the total number of vehicle types that can travel in special lanes.

[0194] K GL =S ML (Formula 25)

[0195] The above formula indicates that the types of vehicles prohibited from driving in regular lanes are the same types of vehicles that can only drive in special lanes.

[0196] K ML =S GL (Formula 26)

[0197] The above formula indicates that the types of vehicles prohibited from driving in special lanes are the same types of vehicles that can only drive in regular lanes.

[0198] For ease of explanation, the parameters that may be used in the various implementation scenarios illustrated below are explained as follows:

[0199] ρ H-bus The market penetration rate of the H-bus vehicle type;

[0200] ρ H-car The market penetration rate of H-car, a vehicle type;

[0201] ρ A-car Market penetration rate for vehicle type A-car;

[0202] ρ A-bus The market penetration rate of vehicle type A-bus;

[0203] ρ C-car The market penetration rate of the C-car vehicle type;

[0204] ρ C-bus The market penetration rate of the C-bus vehicle type;

[0205] The probability of vehicle type H-bus selecting a conventional lane;

[0206] The probability of H-bus vehicle type selecting a special lane;

[0207] The probability of H-car vehicles choosing a conventional lane;

[0208] The probability of H-car vehicles selecting a special lane;

[0209] The probability of vehicle type A-car choosing a conventional lane;

[0210] The probability of vehicle type A-car selecting a special lane;

[0211] The probability of vehicle type A-bus choosing a conventional lane;

[0212] The probability of vehicle type A-bus selecting a special lane;

[0213] The probability of a vehicle type C-car choosing a conventional lane;

[0214] The probability of a vehicle type C-car selecting a special lane;

[0215] The probability of vehicle type C-bus choosing a conventional lane;

[0216] The probability of C-bus vehicle type selecting a special lane;

[0217] T H-bus|H-bus The headway between vehicles of type H-bus in front and type H-bus behind;

[0218] T H-bus|A-bus The headway between vehicles with an H-bus type vehicle ahead and an A-bus type vehicle behind.

[0219] T H-bus|A-car The headway when the preceding vehicle is an H-bus and the following vehicle is an A-car;

[0220] T H-bus|A-bus The headway is when the preceding vehicle is an H-bus and the following vehicle is an A-bus.

[0221] T H-bus|C-car The headway when the preceding vehicle is an H-bus and the following vehicle is a C-car;

[0222] T H-bus|C-bus The headway when the preceding vehicle is an H-bus and the following vehicle is a C-bus;

[0223] T A-car|H-bus The headway when the preceding vehicle is an A-car and the following vehicle is an H-bus;

[0224] T A-car|A-carThe headway when both the preceding and following vehicles are A-cars.

[0225] T A-car|A-bus The headway when the preceding vehicle is an A-car and the following vehicle is an A-bus;

[0226] T A-car|C-car The headway when the preceding vehicle is an A-car and the following vehicle is a C-car;

[0227] T A-car|C-bus The headway when the preceding vehicle is an A-car and the following vehicle is a C-bus;

[0228] T A-bus|H-bus The headway when the preceding vehicle is an A-bus and the following vehicle is an H-bus;

[0229] T A-bus|A-car The headway when the preceding vehicle is an A-bus and the following vehicle is an A-car;

[0230] T A-bus|A-bus The headway when both the preceding and following vehicles are of type A-bus.

[0231] T A-bus|C-car The headway when the preceding vehicle is an A-bus and the following vehicle is a C-car;

[0232] T A-bus|C-bus The headway when the preceding vehicle is an A-bus and the following vehicle is a C-bus;

[0233] T C-car|H-bus The headway when the preceding vehicle is a C-car and the following vehicle is an H-bus;

[0234] T C-car|A-car The headway when the preceding vehicle is a C-car and the following vehicle is an A-car;

[0235] T C-car|A-bus The headway when the preceding vehicle is a C-car and the following vehicle is an A-bus;

[0236] T C-car|C-car The headway when both the preceding and following vehicles are C-cars.

[0237] T C-car|C-bus The headway when the preceding vehicle is a C-car and the following vehicle is a C-bus;

[0238] T C-bus|H-bus The headway is when the preceding vehicle is a C-bus and the following vehicle is an HD-bus.

[0239] T C-bus|A-car The headway when the preceding vehicle is a C-bus and the following vehicle is an A-car;

[0240] T C-bus|A-bus The headway when the preceding vehicle is a C-bus and the following vehicle is an A-bus;

[0241] T C-bus|C-car The headway when the preceding vehicle is a C-bus and the following vehicle is a C-car;

[0242] T C-bus|CACC-bus The headway when both the preceding and following vehicles are C-bus types;

[0243] T H-bus The headway is the distance between the following vehicle and the vehicle type H-bus, regardless of the type of the preceding vehicle.

[0244] T H-car The headway of the following vehicle is an H-car regardless of the type of the preceding vehicle.

[0245] T A-car The headway of the following vehicle is an A-car regardless of the type of the vehicle in front.

[0246] T A-bus The headway is for vehicles of type A-bus, regardless of the type of vehicle in front.

[0247] T C-car The headway of the following vehicle is a C-car regardless of the type of the vehicle in front.

[0248] T C-bus The headway is the distance between the following vehicle and the vehicle type C-bus, regardless of the type of the preceding vehicle.

[0249] In a specific embodiment, such as scenario one: the capacity calculation method for a special lane for mandatory automated driving based on a bus lane is as follows:

[0250] In this scenario, the relevant parameters are as follows:

[0251] Z={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0252] P = {H-bus}

[0253] Special lanes:

[0254] I = I ML ={H-bus,A-car,A-bus,C-car,C-bus}

[0255] K = K ML ={H-car}

[0256] S = S ML ={A-car,A-bus,C-car,C-bus}

[0257] Regular lane:

[0258] I = I GL ={H-car,H-bus}

[0259] K = K GL ={A-car,A-bus,C-car,C-bus}

[0260] S = S GL ={H-car}

[0261] Therefore, the average headway T in special lanes 1-ML for:

[0262]

[0263] Except for connected autonomous vehicles, the headway of other vehicles does not change regardless of the type of vehicle in front, such as T H-bus =T H-bus|H-bus =T H-bus|A-car .

[0264] When a connected autonomous vehicle is driving, if another connected autonomous vehicle is ahead of it, the headway is T. C (T C-car or T C-bus If the vehicle ahead is neither a connected autonomous vehicle nor a traditional manually driven vehicle, the headway is T. A (T A-car or T A-bus This means that the vehicle automatically degrades into a non-connected autonomous driving vehicle.

[0265] Therefore, the above equation can be simplified to:

[0266]

[0267] Simplifying again, we get:

[0268]

[0269] Simplifying again, we get:

[0270]

[0271] Average headway T in conventional lanes 1-GL for:

[0272]

[0273] Simplifying, we get:

[0274]

[0275] When using soft barriers such as traffic markings, the ratio of traffic flow between regular lanes and special lanes, k f1 as follows:

[0276]

[0277] The average headway T in this scenario for special lanes 1-ML The average headway T in a regular lane 1-GL The ratio of traffic flow between regular lanes and special lanes, k f1 Substituting the number of special lanes and regular lanes into Formulas 16, 17, and 20, we can determine the road capacity (soft isolation) of special lanes for mandatory automated driving based on bus lanes in Scenario 1.

[0278] The average headway T in this scenario for special lanes 1-ML The average headway T in a regular lane 1-GL Substituting the number of special lanes and regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of special lanes for mandatory automated driving based on bus lanes in scenario 1.

[0279] In a specific embodiment, such as scenario two: the road capacity calculation method for autonomous driving special lanes based on bus lanes is as follows:

[0280] In this scenario, the relevant parameters are as follows:

[0281] Z={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0282] P={H-bus,A-car,A-bus,C-car,C-bus}

[0283] Special lanes:

[0284] I = I ML={H-bus,A-car,A-bus,C-car,C-bus}

[0285] K = K ML ={HD-car}

[0286]

[0287] Regular lane:

[0288] I = I GL ={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0289]

[0290] S = S GL ={H-car}

[0291] Average headway T in special lanes 2-ML for:

[0292]

[0293] The average headway in a conventional lane is T 2-GL :

[0294]

[0295] When using soft barriers such as traffic markings, the ratio of traffic flow between regular lanes and special lanes, k f2 as follows:

[0296]

[0297] The average headway T in this scenario for special lanes 2-ML The average headway T in a conventional lane 2-GL The ratio of traffic flow between regular lanes and special lanes, k f2 Substituting the number of special lanes and the number of regular lanes into formulas sixteen, seventeen, and twenty, we can determine the road capacity of special lanes for autonomous driving based on bus lanes in scenario two (soft isolation).

[0298] The average headway T in this scenario for special lanes 2-ML The average headway T in a conventional lane 2-GL Substituting the number of special lanes and the number of regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of special lanes for autonomous driving based on bus lanes in scenario 2.

[0299] In a specific embodiment, such as scenario three: the road capacity calculation method for special lanes for mandatory automated driving based on multi-occupant lanes is as follows:

[0300] In multi-occupant lane scenarios, traditional manned cars (H-cars) include single-occupant cars (Dan-cars) and multi-occupant cars (Duo-cars), ρ dan ρ is the proportion of single-person driven cars among all cars. Duo It is the proportion of multi-occupant cars among all cars, and satisfies ρ Dan +ρ Duo =ρ H-car .

[0301] In this scenario, the relevant parameters are as follows, where H-car is divided into Dan-car and Duo-car.

[0302] Z={Dan-car,Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0303] P = {Duo-car, H-bus}

[0304] Special lanes:

[0305] I = I ML ={Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0306] K = K ML ={Dan-car}

[0307] S = S ML ={A-car,A-bus,C-car,C-bus}

[0308] Regular lane:

[0309] I = I GL ={Dan-car,Duo-car,H-bus}

[0310] K = K GL ={A-car,A-bus,C-car,C-bus}

[0311] S = S GL ={Dan-car}

[0312] Average headway T in special lanes 3-ML for:

[0313]

[0314] Average headway T in conventional lanes 3-GL for:

[0315]

[0316] When using soft barriers such as traffic markings, the ratio of traffic flow between regular lanes and special lanes, k f3 as follows:

[0317]

[0318] The average headway T in this scenario for special lanes 3-ML The average headway T in a conventional lane 3-GL The ratio of traffic flow between regular lanes and special lanes, k f3 Substituting the number of special lanes and the number of regular lanes into formulas sixteen, seventeen, and twenty, we can determine the road capacity (soft isolation) of special lanes for mandatory autonomous driving based on multi-occupant lanes in scenario three.

[0319] The average headway T in this scenario for special lanes 3-ML The average headway T in a conventional lane 3-GL Substituting the number of special lanes and the number of regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of special lanes for mandatory autonomous driving based on multi-occupant lanes in scenario 3.

[0320] In a specific embodiment, such as scenario four: the road capacity calculation method for autonomous driving special lanes based on multi-occupant lanes is as follows:

[0321] In this scenario, the relevant parameters are as follows:

[0322] Z={Dan-car,Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0323] P={Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0324] Special lanes:

[0325] I = I ML ={Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0326] K = K ML ={Dan-car}

[0327]

[0328] Regular lane:

[0329] I = I GL ={Dan-car,Duo-car,H-bus,A-car,A-bus,C-car,C-bus}

[0330] K = K GL ={A-car,A-bus,C-car,C-bus}

[0331]

[0332] Average headway T in special lanes 4-ML for:

[0333]

[0334] Average headway T in conventional lanes 4-GL for:

[0335]

[0336] When using soft barriers such as traffic markings, the ratio of traffic flow between regular lanes and special lanes, k f4 as follows:

[0337]

[0338] The average headway T in this scenario for special lanes 4-ML The average headway T in a conventional lane 4-GL The ratio of traffic flow between regular lanes and special lanes, k f4 Substituting the number of special lanes and the number of regular lanes into formulas sixteen, seventeen, and twenty, we can determine the road capacity (soft isolation) of special lanes for autonomous driving based on multi-occupant lanes in scenario four.

[0339] The average headway T in this scenario for special lanes 4-ML The average headway T in a conventional lane 4-GL Substituting the number of special lanes and the number of regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of special lanes for autonomous driving based on multi-occupant lanes in scenario 4.

[0340] In a specific embodiment, such as scenario five: the road capacity calculation method for a mandatory autonomous driving special lane based on an autonomous driving dedicated lane is as follows:

[0341] In this scenario, the relevant parameters are as follows:

[0342] Z={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0343]

[0344] Special lane vehicle types:

[0345] I = I ML ={A-car,A-bus,C-car,C-bus}

[0346] K = K ML ={H-car,H-bus}

[0347] S = S ML ={A-car,A-bus,C-car,C-bus}

[0348] Vehicle types in regular lanes:

[0349] I = I GL ={H-car,H-bus}

[0350] K = K GL ={A-car,A-bus,C-car,C-bus}

[0351] S = S GL ={H-car,H-bus}

[0352] When using soft barriers such as traffic markings for separation, the average headway T of special lanes 5-ML Represented as:

[0353]

[0354] Average headway T in conventional lanes 5-GL for:

[0355]

[0356] Traffic flow ratio k between regular lanes and special lanes f5 as follows:

[0357]

[0358] The average headway T in this scenario for special lanes 5-ML The average headway T in a conventional lane 5-GL The ratio of traffic flow between regular lanes and special lanes, k f5Substituting the number of special lanes and the number of regular lanes into formulas sixteen, seventeen, and twenty, we can determine the road capacity (soft isolation) of the mandatory autonomous driving special lane based on the autonomous driving dedicated lane for scenario five.

[0359] The average headway T in this scenario for special lanes 5-ML The average headway T in a conventional lane 5-GL Substituting the number of special lanes and the number of regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of the mandatory autonomous driving special lane based on the autonomous driving dedicated lane for scenario 5.

[0360] In a specific embodiment, such as scenario six: the road capacity calculation method for autonomous driving special lanes based on dedicated autonomous driving lanes is as follows:

[0361] In this scenario, the relevant parameters are as follows:

[0362] Z={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0363] P = {A-car, A-bus, C-car, C-bus}

[0364] Vehicle types for special lanes:

[0365] I = I ML ={A-car,A-bus,C-car,C-bus}

[0366] K = K ML ={H-car,H-bus}

[0367]

[0368] Vehicle types in regular lanes:

[0369] I = I GL ={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0370]

[0371] S = S GL ={H-car,H-bus}

[0372] Average headway T in special lanes 6-ML for:

[0373]

[0374] Average headway T in conventional lanes 6-GL for:

[0375]

[0376] When using soft barriers such as traffic markings, the ratio of traffic flow between regular lanes and special lanes, k f6 as follows:

[0377]

[0378] The average headway T in this scenario for special lanes 6-ML The average headway T in a conventional lane 6-GL The ratio of traffic flow between regular lanes and special lanes, k f6 Substituting the number of special lanes and the number of regular lanes into formulas sixteen, seventeen, and twenty, we can determine the road capacity (soft isolation) of the autonomous driving special lane based on the dedicated autonomous driving lane for scenario six.

[0379] The average headway T in this scenario for special lanes 6-ML The average headway T in a conventional lane 6-GL Substituting the number of special lanes and the number of regular lanes into formulas 18, 19 and 20, we can determine the road capacity (hard isolation) of the autonomous driving special lane based on the dedicated autonomous driving lane for scenario six.

[0380] In one specific embodiment, for example, a method for calculating the road capacity in a special scenario where all lanes are conventional lanes:

[0381] In this scenario, the relevant parameters are as follows:

[0382] Z=P=S=I={H-car,H-bus,A-car,A-bus,C-car,C-bus}

[0383]

[0384] Average headway T in the lane G1 for:

[0385]

[0386] The road capacity of each lane can be determined by the average headway of each lane, and the sum of the lane capacities of all lanes is the road capacity in this scenario.

[0387] In one specific embodiment, for example in a special scenario where all lanes are conventional lanes and there are no connected vehicles, the lane capacity calculation method is as follows:

[0388] In this scenario, the relevant parameters are as follows:

[0389] Z=P=S=I={H-car,HD-bus,A-car,A-bus}

[0390]

[0391] Average headway T in the lane G2 for:

[0392]

[0393] The road capacity of each lane can be determined by the average headway of each lane, and the sum of the lane capacities of all lanes is the road capacity in this scenario.

[0394] In one specific embodiment, for example, in a special scenario where all lanes are regular lanes with no connected vehicles and no distinction is made between buses and cars, the road capacity is calculated as follows:

[0395] In this scenario, the relevant parameters are as follows:

[0396] Z = P = S = I = {H-car, A-car}

[0397]

[0398] Average headway T in the lane G3 for

[0399]

[0400] The road capacity of each lane can be determined by the average headway of each lane, and the sum of the lane capacities of all lanes is the road capacity in this scenario.

[0401] The above are specific embodiments of the road capacity calculation method of the present invention in several specific scenarios.

[0402] This application fully considers the possible future development trends of autonomous vehicles (i.e., non-connected autonomous vehicles and connected autonomous vehicles), traffic characteristics of multiple vehicles coexisting, differences in car-following behavior among different vehicles, possible special lane forms under different demand orientations, isolation forms between special lanes and regular lanes, and the influence relationship between vehicles, and reserves room for improvement.

[0403] Meanwhile, due to differences in the stage of technological development and the degree of application, the characteristics of vehicle composition vary across different times and spaces. This application fully considers these differences, including the ratio of autonomous vehicles to manually driven vehicles, the ratio of non-connected to connected vehicles, the ratio of multi-occupant vehicles to single-driver vehicles, and the ratio of buses to cars.

[0404] Furthermore, with the development of technology, the actual characteristics of vehicles may change to some extent (cathode distance, vehicle lane selection probability, etc.), and this change can be captured by this method.

[0405] In a specific embodiment, for example Figure 5 The diagram illustrating the impact of autonomous driving market penetration and the proportion of non-connected autonomous driving on traffic capacity sets the ratio of buses to cars at 2.5%:97.5%, the isolation method at Soft Isolation, and the ratio of multi-occupant vehicles to single-occupant vehicles at 10%:90%. The expected headway for different vehicles is shown in the table below.

[0406]

[0407] (Table 1)

[0408] With a 90% willingness rate for different vehicles to choose special lanes, the results show the characteristics of traffic capacity variation in Scenario 1. Overall, traffic capacity gradually increases with the increase in autonomous driving market penetration, peaking when the market penetration rate reaches 0.7. When the autonomous driving market penetration rate is low (0-0.6), the proportion of non-connected autonomous vehicles has almost no impact on traffic capacity. When the autonomous driving market penetration rate is high (0.6-1.0), as the proportion of non-connected autonomous vehicles increases, traffic capacity shows a downward trend at the same autonomous driving market penetration rate.

[0409] To make the process of this invention clearer, this method also provides a flowchart of a specific embodiment of the road capacity calculation method, as shown below. Figure 6 As shown:

[0410] First, the specific lane types and lane management strategies for new types of vehicles are clearly defined (i.e., the characteristics and proportions of vehicle types within each lane type, such as mandatory automated driving lanes based on bus lanes, autonomous automated driving lanes based on bus lanes, etc., and the isolation methods between lanes, which can be replaced or added / removed according to local conditions). Next, the composition of mixed traffic flow is clearly defined (traditional manned cars, traditional manned buses, etc.). Then, the implementation type of the special lanes for automated driving vehicles is determined (including lane types, i.e., mandatory and autonomous use by the target vehicles, the number of lanes, and the isolation methods between lanes). Relevant parameters are then determined (such as the market penetration rate of vehicle types and the probability of vehicles of a particular type choosing a specific lane). Lane-level capacity and the relationship between traffic flow between lanes are calculated separately, and then the multi-lane mixed traffic capacity is measured.

[0411] The method proposed in this application fully considers the two development directions of autonomous vehicles (non-connected and connected), the differences in car-following among different vehicles, the different design forms and purposes of special lanes, and the forms of lane isolation. It proposes a method for calculating road capacity, and further optimizes the capacity calculation method by considering the mutual influence between vehicles in different lanes and the different lane selection intentions of different vehicles in different special lane scenarios. It also considers the impact of market penetration rates of different vehicles (large vehicles represented by buses and small vehicles represented by cars, single-driver vehicles and multi-driver vehicles, etc.) on the results. This method provides predictive research on traffic flow changes as autonomous driving gradually integrates into the traffic environment. Based on this method, other vehicle types such as trucks can be integrated to calculate the capacity of new autonomous vehicles under the gradual integration of autonomous driving in the local area. Furthermore, this method has low testing costs, requiring only short-term observation surveys of the road section under study, combined with questionnaires to vehicle owners and the acquisition of relevant parameters from vehicle manufacturers.

[0412] The above are embodiments of the road capacity calculation method provided in this application. Other embodiments of the road capacity calculation method provided in this application will be described below. Please refer to the following for details.

[0413] Figure 7 A road capacity calculation device provided in this embodiment of the invention includes: an acquisition module 701, a determination module 702, and a processing module 703;

[0414] The acquisition module 701 is used to acquire the lane type of each lane in the road segment to be measured;

[0415] The determination module 702 is used to determine, based on the lane type, at least one type of vehicle allowed to pass in each lane;

[0416] The acquisition module 701 is also used to acquire the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each vehicle type in at least one vehicle type, and the probability of each vehicle type choosing the lane type of the m-th lane. Here, the m-th lane is any lane in the road segment to be measured, the i-th vehicle and the j-th vehicle are two adjacent vehicles, and m, i and j are all positive integers.

[0417] The processing module 703 is used to obtain the average headway of the m-th lane based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th vehicle and the j-th vehicle in the m-th lane; and to determine the total traffic capacity of the road segment to be measured based on the average headway of each lane in all lanes.

[0418] Optionally, the device includes:

[0419] The processing module 703 is further configured to: obtain the probability that the i-th vehicle appears in the m-th lane based on the market penetration rate corresponding to the vehicle type of the i-th vehicle, the probability that vehicles of the i-th vehicle's vehicle type choose the lane type of the m-th lane, and the market penetration rate of each vehicle type among all vehicle types and the probability that vehicles of each vehicle type among all vehicle types choose the lane type of the m-th lane; obtain the probability that the j-th vehicle appears in the m-th lane based on the market penetration rate corresponding to the vehicle type of the j-th vehicle, the probability that vehicles of the j-th vehicle's vehicle type choose the lane type of the m-th lane, and the market penetration rate of each vehicle type among all vehicle types and the probability that vehicles of each vehicle type among all vehicle types choose the lane type of the m-th lane; and obtain the average headway of the m-th lane based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles appears in the m-th lane.

[0420] Optionally, the device includes:

[0421] The determination module 702 is also used to determine the lane capacity of the m-th lane based on the average headway of the m-th lane; and to determine the total capacity of the road segment to be measured based on the lane capacity of all lanes.

[0422] Optionally, the device includes:

[0423] The acquisition module 701 is also used to acquire the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second lane type, and the second probability of vehicles of the second lane type choosing the second lane type in the road segment to be measured, wherein the first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in the first lane type and the second lane type;

[0424] The processing module 703 is further configured to obtain a first weight for the first lane type and a second weight for the second lane type based on the first number of lanes, a first market penetration rate, a first probability, a second number of lanes, a second market penetration rate, and a second probability; and to obtain the total traffic capacity of the road segment to be measured based on the first average headway corresponding to the lanes of the first lane type, the second average headway corresponding to the lanes of the second lane type, the first number of lanes, the first weight, the second average headway corresponding to the lanes of the second lane type, the second number of lanes, and the second weight.

[0425] Optionally, the device includes:

[0426] The processing module 703 is further configured to obtain the first capacity of the first lane type based on the first average headway, the number of lanes, and the first weight; obtain the second capacity of the second lane type based on the first average headway corresponding to the lanes of the first lane type, the second average headway corresponding to the lanes of the second lane type, the number of lanes, and the second weight; and obtain the total capacity of the road segment to be measured based on the first capacity and the second capacity.

[0427] The functions performed by each component in the road capacity calculation device provided in this embodiment have been described in detail in any of the above method embodiments, and therefore will not be repeated here.

[0428] This invention provides a road capacity measurement device that obtains the lane type of each lane in a road segment to be measured; determines at least one vehicle type allowed to pass in each lane based on the lane type; obtains the headway between the i-th and j-th vehicles in the m-th lane, the market penetration rate of each of the at least one vehicle type, and the probability of each vehicle type choosing the m-th lane, where the m-th lane is any lane in the road segment to be measured, the i-th and j-th vehicles are two adjacent vehicles, and m, i, and j are all positive integers; obtains the average headway of the m-th lane based on the market penetration rate of each of the at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane; and determines the total capacity of the road segment to be measured based on the average headway of each lane. This method determines the permitted vehicle types in each lane based on the lane type of the road segment to be measured. It then determines the headway between adjacent vehicles based on their vehicle types. Furthermore, by obtaining the market penetration rate of each vehicle type and the probability of that vehicle type choosing a lane type, it determines the average headway for each lane. Finally, it determines the total capacity of the road segment to be measured based on the average headway for each lane. In this method, regardless of whether the vehicles are autonomous or traditionally driven, as long as the headway, market penetration rate, and probability of lane type selection of vehicles in each lane are determined, the capacity of the road segment to be measured can be accurately calculated. This solves the problem of inaccurate road capacity calculations caused by the addition of autonomous vehicles to the road in existing methods, providing strong data support for subsequent road decision-making.

[0429] like Figure 8 As shown, this application provides an electronic device including a processor 111, a communication interface 112, a memory 113, and a communication bus 114, wherein the processor 111, the communication interface 112, and the memory 113 communicate with each other through the communication bus 114.

[0430] Memory 113 is used to store computer programs;

[0431] In one embodiment of this application, the processor 111, when executing a program stored in the memory 113, implements the road capacity calculation method provided in any of the foregoing method embodiments, including:

[0432] Obtain the lane type for each lane in the road segment to be measured;

[0433] Based on the lane type, determine at least one type of vehicle that is allowed to travel in each lane;

[0434] Get the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each vehicle type in at least one vehicle type, and the probability of each vehicle type choosing the m-th lane. The m-th lane is any lane in the road segment to be tested, the i-th vehicle and the j-th vehicle are two adjacent vehicles, and m, i and j are all positive integers.

[0435] Based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane, the average headway of the m-th lane is obtained.

[0436] The total capacity of the road segment to be measured is determined based on the average headway for each lane in all lanes.

[0437] Optionally, based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane, the average headway of the m-th lane is obtained, specifically including:

[0438] Based on the market penetration rate of the vehicle type of the i-th vehicle, the probability of a vehicle of the i-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the i-th vehicle appearing in the m-th lane is obtained.

[0439] Based on the market penetration rate of the vehicle type of the j-th vehicle, the probability of a vehicle of the j-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the j-th vehicle appearing in the m-th lane is obtained.

[0440] The average headway of the m-th lane is obtained based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles appears in the m-th lane.

[0441] Optionally, the total capacity of the road segment to be measured is determined based on the average headway for each lane in all lanes, including:

[0442] The lane capacity of the m-th lane is determined based on the average headway of the m-th lane.

[0443] The total capacity of the road segment to be measured is determined based on the lane capacity of all lanes.

[0444] Optionally, the road segment to be measured includes two lane types, and the two lane types are separated by a preset isolation method. The method also includes:

[0445] The method obtains the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second lane type, and the second probability of vehicles of the second lane type choosing the second lane type in the road segment to be measured. Here, the first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in the first lane type and the second lane type.

[0446] Based on the number of first lanes, the first market penetration rate, the first probability, the number of second lanes, the second market penetration rate, and the second probability, obtain the first weight of the first lane type and the second weight of the second lane type;

[0447] The total traffic capacity of the road segment to be measured is obtained based on the first average headway for lanes of the first lane type, the second average headway for lanes of the second lane type, the number of lanes of the first lane, the first weight, the second average headway for lanes of the second lane type, the number of lanes of the second lane, and the second weight.

[0448] Optionally, the total capacity of the road segment to be measured is obtained based on the first average headway, the number of lanes, and the first weight for the first lane type, and the second average headway, the number of lanes, and the second weight for the lanes of the second lane type. This includes:

[0449] Based on the first average headway of the first lane type, the first number of lanes, and the first weight, the first traffic capacity of the first lane type is obtained;

[0450] Based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of second lanes, and the second weight, the second traffic capacity of the second lane type is obtained.

[0451] The total capacity of the road segment to be measured is obtained based on the first and second capacity.

[0452] This application also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the road capacity calculation method provided in any of the foregoing method embodiments.

[0453] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes the element.

[0454] The above are merely specific embodiments of the present invention, enabling those skilled in the art to understand or implement the invention. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of the invention. Therefore, the present invention is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for calculating road capacity for autonomous driving, characterized in that, The method includes: Obtain the lane type for each lane in the road segment to be measured; Based on the lane type, determine at least one type of vehicle permitted to travel in each lane; The headway between the i-th and j-th vehicles in the m-th lane is obtained, as well as the market penetration rate of each of the at least one vehicle types and the probability of each vehicle type choosing the m-th lane. The m-th lane is any lane in the road segment to be measured, the i-th and j-th vehicles are two adjacent vehicles, and m, i, and j are all positive integers. The average headway of the m-th lane is obtained based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th vehicle and the j-th vehicle in the m-th lane. The total capacity of the road segment to be measured is determined based on the average headway for each lane in all lanes. When the road segment to be measured includes two lane types, and the two lane types are separated by a preset isolation method, the method further includes: The method obtains the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second vehicle type, and the second probability of vehicles of the second vehicle type choosing the second lane type in the road segment to be measured. The first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in both the first lane type and the second lane type. Based on the first number of lanes, the first market penetration rate, the first probability, the second number of lanes, the second market penetration rate, and the second probability, obtain the first weight of the first lane type and the second weight of the second lane type; The total traffic capacity of the road segment to be measured is obtained based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of the first lanes, the first weight, the number of the second lanes, and the second weight.

2. The method according to claim 1, characterized in that, The step of obtaining the average headway of the m-th lane based on the market penetration rate of each vehicle type in at least one vehicle type in the m-th lane, the probability of vehicles of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane, specifically includes: Based on the market penetration rate corresponding to the vehicle type of the i-th vehicle, the probability of a vehicle of the i-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the i-th vehicle appearing in the m-th lane is obtained. Based on the market penetration rate corresponding to the vehicle type of the j-th vehicle, the probability of a vehicle of the j-th vehicle type choosing the lane type of the m-th lane, and the market penetration rate of each vehicle type and the probability of a vehicle of each vehicle type choosing the lane type of the m-th lane, the probability of the j-th vehicle appearing in the m-th lane is obtained. The average headway of the m-th lane is obtained based on the headway between each pair of adjacent vehicles in the m-th lane and the probability that each of the two adjacent vehicles appears in the m-th lane.

3. The method according to claim 1, characterized in that, The determination of the total capacity of the road segment to be measured based on the average headway for each lane in all lanes includes: Based on the average headway of the m-th lane, the lane capacity of the m-th lane is determined. The total capacity of the road segment to be measured is determined based on the lane capacity of all lanes.

4. The method according to claim 1, characterized in that, The step of obtaining the total capacity of the road segment to be measured based on the first average headway corresponding to the first lane type, the second average headway corresponding to the second lane type, the number of the first lanes, the first weight, the second average headway corresponding to the second lane type, the second number of lanes, and the second weight includes: Based on the first average headway of the first lane type, the number of the first lanes, and the first weight, the first traffic capacity of the first lane type is obtained. Based on the first average headway corresponding to the lane of the first lane type, the second average headway corresponding to the lane of the second lane type, the number of lanes, and the second weight, the second traffic capacity of the second lane type is obtained. The total capacity of the road segment to be measured is obtained based on the first capacity and the second capacity.

5. A road capacity calculation device, characterized in that, The device includes: The first acquisition module is used to acquire the lane type of each lane in the road segment to be measured; The determining module is configured to determine, based on the lane type, at least one type of vehicle permitted to pass in each lane; The first acquisition module is further configured to acquire the headway between the i-th vehicle and the j-th vehicle in the m-th lane, the market penetration rate of each of the at least one vehicle types, and the probability that each vehicle type selects the lane type of the m-th lane, wherein the m-th lane is any lane in the road segment to be measured, the i-th vehicle and the j-th vehicle are two adjacent vehicles, and m, i and j are all positive integers; The processing module is used to obtain the average headway of the m-th lane based on the market penetration rate of each of the at least one vehicle type in the m-th lane, the probability of each vehicle type choosing the lane type of the m-th lane, and the headway between the i-th and j-th vehicles in the m-th lane; and to determine the total capacity of the road segment to be measured based on the average headway of each lane in all lanes. When the road segment to be measured includes two lane types, and the two lane types are separated by a preset isolation method, the device further includes: The second acquisition module is used to acquire the number of first lanes belonging to the first lane type, the number of second lanes belonging to the second lane type, the first market penetration rate corresponding to the first vehicle type, the first probability of vehicles of the first vehicle type choosing the first lane type, the second market penetration rate corresponding to the second vehicle type, and the second probability of vehicles of the second vehicle type choosing the second lane type in the road segment to be measured, wherein the first vehicle type is any vehicle type allowed to pass in the first lane type, and the second vehicle type is any vehicle type allowed to pass in the first lane type and the second lane type; The third acquisition module is used to acquire a first weight of the first lane type and a second weight of the second lane type based on the first number of lanes, the first market penetration rate, the first probability, the second number of lanes, the second market penetration rate, and the second probability. The fourth acquisition module is used to acquire the total traffic capacity of the road segment to be measured based on the first average headway corresponding to the lane of the first lane type, the second average headway corresponding to the lane of the second lane type, the number of the first lanes, the first weight, the number of the second lanes, and the second weight.

6. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; The memory is used to store computer programs; When the processor executes the program stored in the memory, it implements the steps of the road capacity calculation method according to any one of claims 1-4.

7. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the steps of the road capacity calculation method as described in any one of claims 1-4.

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