Microscopic simulation method for mixed traffic flow of large vehicles with cooperative adaptive cruise control

Abstract

The present invention discloses a method for microscopic simulation of mixed traffic flow of large vehicles with cooperative adaptive cruise control. The method completes the microscopic simulation of CACC mixed traffic flow of four types of vehicles, namely, CACC large vehicles, CACC small vehicles, traditional large vehicles and traditional small vehicles, by constructing a CACC large vehicle mixed traffic flow microscopic model. The steps for constructing the CACC large vehicle mixed traffic flow microscopic model are as follows: Step 1: Determine the vehicle type and state judgment logic; Step 2: Determine the CACC vehicle queue state judgment logic; Step 3: Determine the vehicle lane change control logic; Step 4: Determine the vehicle speed control logic. The present invention provides a complete set of methods for microscopic simulation of CACC large vehicle mixed traffic flow, and considers the application of the method in the future transportation field, providing a basis for related research on CACC mixed traffic flow considering vehicle type differences.

Description

Technical Field

[0001] The invention relates to a microscopic simulation method for a large vehicle mixed traffic flow under cooperative adaptive cruise control, and belongs to the technical field of traffic flow microscopic simulation. Background Art

[0002] The Cooperative Adaptive Cruise Control (CACC) system retains the on-board sensors of the adaptive cruise control system and introduces the Internet and vehicle-to-vehicle communication technology. Vehicles can share information and obtain basic information such as the speed, acceleration, and position of the vehicle in front. It can accurately and actively control the distance between vehicles in the fleet, so that multiple following vehicles can be linked together to drive in coordination and form a vehicle queue, thereby making the distance between vehicles more reasonable. By shortening the distance between vehicles and stabilizing vehicle speeds, it can better adapt to changes in traffic flow, help reduce traffic congestion and accident risks, improve road use efficiency, and reduce energy consumption.

[0003] In the study of CACC mixed traffic flow, until the development level of autonomous driving reaches the stage of fully autonomous driving, the situation of CACC large vehicles mixed with other types of vehicles will exist for a long time. Due to the differences in the structure and power performance of large vehicles, there are great differences in speed distribution, acceleration and deceleration range and driving behavior between large vehicles and small vehicles, and they will consume more road time and space resources.

[0004] In the study of CACC mixed traffic flow, considering the difficulty and complexity of observing actual vehicle test data, it is necessary to establish a complete set of CACC mixed traffic flow micro-simulation methods and conduct in-depth research on the impact of CACC large vehicles on other types of vehicles and traffic flow. Summary of the invention

[0005] In response to the shortcomings of existing technologies, this study constructs a complete set of methods for the microscopic simulation of mixed traffic flows, including CACC large vehicles, CACC small vehicles, traditional large vehicles and traditional small vehicles. The methods involve vehicle type and state judgment, CACC vehicle queue state judgment, vehicle lane change control, and vehicle speed control.

[0006] To achieve the above objectives, the present invention specifically adopts the following steps to establish a CACC mixed traffic flow microscopic model considering large vehicles and complete the CACC mixed traffic flow microscopic simulation:

[0007] Step 1: Determine the vehicle type and state judgment logic;

[0008] Step 2: Determine the CACC vehicle queue status judgment logic;

[0009] Step 3: Determine the vehicle lane change control logic;

[0010] Step 4: Determine the vehicle speed control logic.

[0011] Furthermore, the vehicle type and state judgment logic in step 1 includes:

[0012] 1) Determine the vehicle type of the target vehicle, which is divided into vehicle control mode and vehicle model structure:

[0013] T=T control +T structure

[0014]

[0015]

[0016] 2) If the target vehicle is controlled by traditional manual driving, platooning is not adopted;

[0017] 3) If the target vehicle is controlled in CACC mode, based on the premise that CACC vehicles of the same type can form a vehicle platoon, the CACC vehicle status is further determined:

[0018] 4) If the target vehicle and the preceding vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the preceding convoy is not full, then the target vehicle can be identified as a convoy member vehicle:

[0019] S i =2

[0020]

[0021] 5) If the relationship between the target vehicle and the preceding vehicle does not meet the conditions for being a convoy member vehicle, the target vehicle and the following vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the following convoy is not full, then the vehicle can be identified as the convoy leader:

[0022] S i =1

[0023]

[0024] 6) If the target vehicle does not meet the conditions to become a team member vehicle or a team leader vehicle, then the vehicle can be identified as a CACC non-team free vehicle. i =0.

[0025] Where T is the vehicle type, T control is the vehicle control type, T structureis the vehicle structure type, lenth and width are the length and width of the vehicle; i is the target vehicle number, i-1 is the number of the vehicle in front of the target vehicle, and i+1 is the number of the vehicle behind the target vehicle; S is the CACC vehicle status, 0 represents a CACC non-convoy free vehicle, 1 represents a CACC convoy pilot vehicle, and 2 represents a CACC convoy member vehicle; L is the lane number of the vehicle; x is the position of the vehicle head, D max is the maximum allowable headway; N is the number of vehicles in the convoy, N max is the maximum number of vehicles in the convoy.

[0026] Furthermore, the CACC vehicle queue state judgment in step 2 is based on the vehicle type and state judgment, and completes the vehicle queue initialization, free vehicle joining the fleet and vehicle queue reorganization:

[0027] 1) Two adjacent CACC free vehicles, i.e. the front vehicle and the rear vehicle, can be grouped to form a new convoy if the distance between them meets the distance condition for platooning and they are in the same lane or the rear vehicle meets the lane change condition. At this time, the front vehicle will become the CACC convoy leader vehicle, and the rear vehicle will become a convoy member vehicle, thus initializing the vehicle convoy formation;

[0028] 2) When a CACC free car approaches the front convoy and the front convoy has not reached the maximum length limit, the car will join the convoy from the rear by accelerating or changing lanes;

[0029] 3) When the vehicle at the rear of the convoy encounters a situation where the convoy in front is not full, the leader vehicle of the rear convoy may change lanes or accelerate to join the convoy in front under certain conditions, thereby changing its vehicle status from a CACC leader vehicle to a CACC member vehicle; when the member vehicles in the convoy need to change lanes to leave the current convoy and enter the target lane due to route changes, they will perform mandatory lane change behavior, and the vehicle status will become a CACC free vehicle. This state change is accompanied by the reorganization of the original convoy.

[0030] Furthermore, the vehicle lane changing control in step 3 performs lane changing control on the vehicle based on the LC2013 lane changing model. Both CACC vehicles and traditional vehicles use the same lane changing control logic, including four lane changing motivations: strategic lane changing, cooperative lane changing, tactical lane changing, and regulated lane changing.

[0031] Further, the vehicle speed control in step 4 is differentiated according to the vehicle control mode, including traditional vehicle speed control and CACC vehicle speed control.

[0032] Furthermore, the conventional vehicle speed control in step 4 is based on the safety distance theory, and the target vehicle is a conventional vehicle, and there are:

[0033]

[0034] v h,des,t =min[v h,safe,t ,v h,t-1 +a h,acc ,v h,max ]

[0035] v h,t =max[0,rand[v h,des,t -η,v h,des,t ]]

[0036] Among them, v h,safe,t is the safe speed of the target vehicle at time t, v l,t is the speed of the preceding vehicle at time t, g t is the distance between the rear of the preceding vehicle and the front of the target vehicle at time t, v h,t is the target vehicle speed at time t, τ is the target vehicle driver reaction time, a h,dec is the maximum deceleration of the target vehicle, v h,des,t is the target vehicle’s expected speed at time t, a h,acc is the maximum acceleration of the target vehicle, v h,max is the maximum speed of the target vehicle, and η is the speed deviation caused by the vehicle's mechanical performance and the driver's operating error and intention.

[0037] Furthermore, the CACC vehicle speed control in step 4 is specifically divided into four modes: speed control mode, gap control mode, gap closing control mode and collision avoidance control mode:

[0038] 1) When there is no platooning vehicle in front of the CACC vehicle within the vehicle-to-vehicle communication range or the headway between the vehicle and the platooning vehicle is greater than 2s, the speed control mode is enabled, with:

[0039] v i,t =v i,t-1 +k0·(v i,des -v i,t-1 )

[0040] 2) When the actual distance between the CACC member vehicle and the preceding vehicle deviates from the expected distance by 0-0.2m and the actual vehicle speed deviation is less than 0.1m / s, the gap control mode is enabled, with:

[0041]

[0042] e i,t =x i-1,t-1 -x i,t-1 -L i-1 -t des ·v i,t-1 -d0

[0043] 3) When the headway is between 1.5s and 2s, the CACC vehicle retains the control mode used at the last moment. When the CACC vehicle approaches the platooning vehicle and the headway is less than 1.5s, the gap closing control mode is activated, with:

[0044]

[0045] 4) When the actual distance between the CACC vehicle and the vehicle ahead is less than the expected distance and the deviation is greater than 0.2m, and the actual speed deviation is greater than 0.1m / s, the collision avoidance control mode is enabled, with:

[0046]

[0047] Among them, v i,t is the speed of the target vehicle i at time t, v i,des is the expected speed of target vehicle i associated with the vehicle type, e i,t is the deviation between the actual distance between the target vehicle i and the preceding vehicle i-1 at time t and the expected distance, x i,t is the position of the target vehicle i at the front of the vehicle at time t, L i-1 is the body length of the preceding vehicle i-1, t des is the expected headway time of target vehicle i related to vehicle type, d0 is the headway safety margin related to the speed of target vehicle i at time t-1, k0 and k v is the speed control feedback gain factor related to the speed deviation, k s It is the speed control feedback gain factor related to the pitch deviation.

[0048] Based on the above technical means, the microscopic simulation method of large-vehicle mixed traffic flow under cooperative adaptive cruise control proposed in this invention can be applied to the research of CACC mixed traffic flow and the research of traffic management strategy:

[0049] 1. Research on CACCC mixed traffic flow

[0050] At present, the research on CACC system mainly focuses on homogeneous flow and mixed flow of the same type of vehicles, and there is less research on the mixed traffic flow of CACC large and small vehicles and traditional large and small vehicles. Based on the CACC mixed traffic flow micro-simulation method proposed in the present invention, the influence of CACC large vehicles on the mixed traffic flow characteristics is studied, and a targeted model is constructed, which is conducive to quantifying the effect of CACC large vehicles on the mixed traffic flow characteristics, and is conducive to the further promotion and application of CACC technology, so that it has a more complete theoretical support.

[0051] 2. Research on traffic management strategies

[0052] The emergence of intelligent driving technology has fundamentally changed the control mode of traditional cars. With the continuous development of big data, the Internet of Things, and cloud computing, the performance of driverless cars will be more perfect, and traffic management strategies will also be improved and perfected accordingly. Based on the CACC mixed traffic flow micro-simulation method proposed in this invention, the influence of CACC large vehicles on the characteristics of mixed traffic flow is studied, which can not only provide reference for mixed traffic management on highways, provide a theoretical basis for alleviating traffic congestion, improving road service levels and traffic capacity, but also promote the good development of intelligent driving technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] Figure 1 is a microscopic simulation flow chart of a large vehicle mixed traffic flow in a cooperative adaptive cruise control according to an embodiment of the present invention;

[0054] Figure 2 is a schematic diagram of the logic of judging the vehicle type in a mixed traffic flow in an embodiment of the present invention;

[0055] Figure 3 is a schematic diagram of a CACC vehicle state in an embodiment of the present invention;

[0056] Figure 4 is a CACC vehicle state judgment flow chart in an embodiment of the present invention;

[0057] Figure 5 is a schematic diagram of vehicle queue initialization in the CACC vehicle queue state in an embodiment of the present invention;

[0058] Figure 6 Schematic diagram of a self-owned vehicle joining a vehicle fleet in a CACC vehicle queue state in an embodiment of the present invention;

[0059] Figure 7 1 is a schematic diagram of the reorganization of a vehicle platoon in a CACC vehicle platoon state in an embodiment of the present invention, wherein (a) is a leading vehicle in a rear platoon joining a front platoon, and (b) is a member vehicle leaving the platoon;

[0060] Figure 8 is a schematic diagram of vehicle lane change control logic in an embodiment of the present invention;

[0061] Fig. 9 is a schematic diagram of a conventional vehicle speed control logic in an embodiment of the present invention;

[0062] Fig.10 It is a schematic diagram of the CACC vehicle speed control logic in an embodiment of the present invention. DETAILED DESCRIPTION

[0063] In order to make the above-mentioned objectives, technical solutions and advantages of the invention clearer, the technical solutions proposed in the present invention are described more clearly and completely in conjunction with the accompanying drawings and specific embodiments below.

[0064] The embodiment of the present invention completes the microscopic simulation of Cooperative Adaptive Cruise Control (CACC) mixed traffic flow by establishing a microscopic model of large-scale mixed traffic flow of Cooperative Adaptive Cruise Control. The establishment of the CACC mixed traffic flow model is as follows: Figure 1 As shown, it specifically includes the following 4 steps:

[0065] Step 1: Determine vehicle type and status judgment logic

[0066] In this step, considering the large vehicle cooperative adaptive cruise control mixed traffic flow, there are four types of vehicles, according to the vehicle control mode and vehicle model structure, such as Figure 2 As shown, including CACC large vehicles, CACC small vehicles, traditional large vehicles and traditional small vehicles.

[0067] Further, such as Figure 3 As shown, the CACC vehicle status can be divided into three categories: CACC fleet leader vehicle, CACC fleet member vehicle and CACC non-fleet free vehicle. The leader vehicle is the vehicle in the CACC vehicle queue that leads the vehicle queue to accelerate, decelerate, change lanes, etc. It is at the front of the vehicle queue, and is usually judged whether it is a leader vehicle based on the type of the front and rear vehicles and the distance to the front and rear vehicles. The member vehicle is the subsequent vehicle in the CACC vehicle queue, and its own speed will be adjusted according to the distance to the front vehicle and the speed of the front vehicle. It is also judged based on the type of the front and rear vehicles and the distance between vehicles. Free vehicles are CACC vehicles that have not been organized into a fleet, and are similar to the driving status of traditional vehicles. Specifically:

[0068] 1) Determine the vehicle type of the target vehicle, which is divided into vehicle control mode and vehicle model structure:

[0069] T=T control +T structure

[0070]

[0071]

[0072] 2) If the target vehicle is controlled by traditional manual driving, platooning is not adopted;

[0073] 3) If the target vehicle control mode is CACC, based on the premise that CACC vehicles of the same type can form a vehicle platoon, further determine the CACC vehicle status, such as Figure 4 As shown;

[0074] 4) If the target vehicle and the preceding vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the preceding convoy is not full, then the target vehicle can be identified as a convoy member vehicle:

[0075] S i =2

[0076]

[0077] 5) If the relationship between the target vehicle and the preceding vehicle does not meet the conditions for being a convoy member vehicle, the target vehicle and the following vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the following convoy is not full, then the vehicle can be identified as the convoy leader:

[0078] S i =1

[0079]

[0080] 6) If the target vehicle does not meet the conditions to become a team member vehicle or a team leader vehicle, then the vehicle can be identified as a CACC non-team free vehicle. i =0.

[0081] Where T is the vehicle type, T control is the vehicle control type, T structure is the vehicle structure type, lenth and width are the length and width of the vehicle; i is the target vehicle number, i-1 is the number of the vehicle in front of the target vehicle, and i+1 is the number of the vehicle behind the target vehicle; S is the CACC vehicle status, 0 represents a CACC non-convoy free vehicle, 1 represents a CACC convoy pilot vehicle, and 2 represents a CACC convoy member vehicle; L is the lane number of the vehicle; x is the position of the vehicle head, D maxx is the maximum allowable headway; N is the number of vehicles in the convoy, N max is the maximum number of vehicles in the convoy.

[0082] Step 2: Determine the CACC vehicle queue status judgment logic

[0083] In this step, CACC vehicle queue status judgment is based on vehicle type and status judgment. According to the situation of the fleet formation, the vehicle lane changing behavior can be further considered to judge the vehicle queue status for various situations encountered during the platoon driving.

[0084] Furthermore, Figures 5 to 7 The three states of the CACC vehicle queue are shown, including vehicle queue initialization, free vehicle joining the fleet, and vehicle queue reorganization:

[0085] 1) If Figure 5 As shown in the figure, two adjacent CACC free vehicles, i.e. the front vehicle and the rear vehicle, can be grouped to form a new convoy if the distance between the vehicles meets the distance condition for allowing vehicles to platoon and they are in the same lane or the rear vehicle meets the lane change condition. At this time, the front vehicle will become the CACC convoy leader vehicle, and the rear vehicle will become a convoy member vehicle, thus realizing the initialization of the vehicle convoy formation;

[0086] 2) If Figure 6 As shown, when the CACC free car approaches the front convoy and the front convoy has not reached the maximum length limit, the vehicle will join the convoy from the rear by accelerating or changing lanes;

[0087] 3) If Figure 7 As shown in the figure, when the rear full convoy encounters the front underfull convoy, the rear convoy leader vehicle will change lanes or accelerate to join the front convoy under the premise of ensuring safety in order to improve road utilization and driving efficiency, thereby changing its vehicle status from a CACC leader vehicle to a CACC member vehicle; when the member vehicles in the convoy need to change lanes to leave the current convoy and enter the target lane due to route changes, they will perform mandatory lane change behavior, and the vehicle status will become a CACC free vehicle. This state change is accompanied by the reorganization of the original convoy.

[0088] Step 3: Determine the vehicle lane change control logic

[0089] The vehicle lane changing model established in the present invention is based on the LC2013 lane changing model to control the lane changing of the vehicle. The present invention assumes that CACC vehicles cannot form a convoy by autonomous lane changing, and the lane changing behavior is taken over by the driver. CACC vehicles and traditional vehicles use the same lane changing control logic, including four lane changing motivations: strategic lane changing, collaborative lane changing, tactical lane changing, and regulated lane changing.

[0090] 1) Strategic lane change means that when there is no available connection between the current lane and the next section of the planned route, the vehicle must change lanes to reach the next section in order to complete the lane change behavior according to the planned route. The decision on whether to make a strategic lane change is made based on the urgency of the lane change demand, and deadlock is avoided during the lane change process, that is:

[0091] L d -o <v p ·n·f

[0092] Among them, L dis the distance from the target vehicle to the end of the current road section, o is the distance reduction related to the traffic flow density; v p is the expected speed of the vehicle when it reaches the end of the current section; n is the number of lane changes from the current section lane to the target lane; f is the time coefficient for the vehicle to successfully change lanes, which is 10 for changing lanes to the left and 20 for changing lanes to the right.

[0093] 2) Cooperative lane changing is a lane changing behavior performed by a vehicle in certain traffic conditions to help the vehicle in the adjacent lane to free up space in the current lane. The vehicle uses the turn signal of the vehicle in front of the adjacent lane to determine whether the vehicle in front has a strategic lane changing intention, and thus determines whether a cooperative lane change is needed. If there is no strategic reason to oppose the lane changing behavior, the vehicle intending to change lanes will make a cooperative lane change to the target lane in the possible direction to free up space in the current lane for the vehicle in front of the adjacent lane, and assist the vehicle in front to complete the strategic lane change. When the conditions at the current moment are not sufficient to implement a cooperative lane change, the vehicle intending to change lanes will adjust its speed to increase the probability of a successful subsequent lane change.

[0094] 3) Tactical lane change is the behavior of a vehicle changing lanes to avoid being blocked by a slower vehicle ahead. It is necessary to strike a balance between the expected speed gain of the lane change and the input of the lane change process and keeping the overtaking lane clear. The decision on whether to make a tactical lane change is based on the evaluation of the expected speed gain, that is:

[0095]

[0096] Among them, g s,t is the speed gain parameter at time t; D is the coefficient of lane change direction, -1 means changing lanes to the right, 1 means changing lanes to the left; v is the vehicle speed of the intended lane change; v l is the speed of the vehicle ahead.

[0097] 4) Regulated lane change refers to the lane change behavior in which the left lane of the vehicle's driving direction is used as the overtaking lane under the right lane driving rule. Based on the relevant requirements of laws and regulations, the driver is obliged to return to the right lane after completing overtaking in the left lane. Whether to perform a regulated lane change is determined based on the evaluation of the right lane change parameters, namely:

[0098]

[0099] Among them, p r,t is the lane-changing parameter of the vehicle intending to change lanes at time t; C R is the adjustment urgency factor for lane change based on regulatory requirements; t p v is the estimated time that the lane-changing vehicle can travel at full speed in the right lane based on the distance and speed of the vehicle in front of it; des is the expected speed of the vehicle intending to change lanes; v L is the maximum speed limit of the right target lane; v is the speed of the vehicle intending to change lanes.

[0100] like Figure 8 As shown, when the strategic lane change demand is urgent and deadlock will not occur, a strategic lane change is performed; when a vehicle causes an obstruction to the vehicle ahead that is performing a strategic lane change, a cooperative lane change is performed; when the expected speed gain brought by the lane change is greater than a threshold, a tactical lane change is performed; when the right lane change parameter is less than a threshold, a regulated lane change is performed.

[0101] Step 4: Determine the vehicle speed control logic

[0102] The present invention proposes to differentiate vehicle speed control according to vehicle control modes, including traditional vehicle speed control and CACC vehicle speed control.

[0103] Further, such as Fig. 9 As shown in the figure, the traditional vehicle speed control is based on the safety distance theory, and the target vehicle is a traditional vehicle, with:

[0104]

[0105] v h,des,t =min[v h,safe,t ,v h,t-1 +a h,acc ,v h,max ]

[0106] v h,t =max[0,rand[v h,des,t -η,v h,des,t ]]

[0107] Among them, v h,safe,t is the safe speed of the target vehicle at time t, v l,t is the speed of the preceding vehicle at time t, g t is the distance between the rear of the preceding vehicle and the front of the target vehicle at time t, v h,t is the target vehicle speed at time t, τ is the target vehicle driver reaction time, a h,dec is the maximum deceleration of the target vehicle, v h,des,t is the target vehicle’s expected speed at time t, a h,acc is the maximum acceleration of the target vehicle, v h,max is the maximum speed of the target vehicle, and η is the speed deviation caused by the vehicle's mechanical performance and the driver's operating error and intention.

[0108] Further, such as Fig.10 As shown in the figure, CACC vehicle speed control is divided into four modes: speed control mode, gap control mode, gap closing control mode and collision avoidance control mode:

[0109] 1) When there is no platooning vehicle in front of the CACC vehicle within the vehicle-to-vehicle communication range or the headway between the vehicle and the platooning vehicle is greater than 2s, the speed control mode is enabled, with:

[0110] v i,t =v i,t-1 +k0·(v i,des -v i,t-1 )

[0111] 2) When the actual distance between the CACC member vehicle and the preceding vehicle deviates from the expected distance by 0-0.2m and the actual vehicle speed deviation is less than 0.1m / s, the gap control mode is enabled, with:

[0112]

[0113] e i,t =x i-1,t-1 -x i,t-1 -L i-1 -t des ·v i,t-1 -d0

[0114] 3) When the headway is between 1.5s and 2s, the CACC vehicle retains the control mode used at the last moment. When the CACC vehicle approaches the platooning vehicle and the headway is less than 1.5s, the gap closing control mode is activated, with:

[0115]

[0116] 4) When the actual distance between the CACC vehicle and the vehicle ahead is less than the expected distance and the deviation is greater than 0.2m, and the actual speed deviation is greater than 0.1m / s, the collision avoidance control mode is enabled, with:

[0117]

[0118] Among them, v i,t is the speed of the target vehicle i at time t, v i,des is the expected speed of target vehicle i associated with the vehicle type, e i,t is the deviation between the actual distance between the target vehicle i and the preceding vehicle i-1 at time t and the expected distance, x i,t is the position of the target vehicle i at the front of the vehicle at time t, L i-1 is the body length of the preceding vehicle i-1, t des is the expected headway time of target vehicle i related to vehicle type, d0 is the headway safety margin related to the speed of target vehicle i at time t-1, k0 and k v is the speed control feedback gain factor related to the speed deviation, k s It is the speed control feedback gain factor related to the pitch deviation.

[0119] The above four steps complete the microscopic simulation of large-vehicle mixed traffic flow under cooperative adaptive cruise control, which is only a description of the specific implementation of the present invention through preferred implementation. The protection scope of the present invention is not limited to the above embodiments. All technical solutions under the concept of the present invention belong to the protection scope of the present invention. For ordinary technicians in this technical field, several improvements and modifications to the principles of the present invention without creative work should be regarded as the protection scope of the present invention.

Claims

1. A method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control, characterized in that: The method completes the CACC mixed traffic flow micro-simulation of four types of vehicles, namely, CACC large vehicles, CACC small vehicles, traditional large vehicles and traditional small vehicles, by constructing a CACC large vehicle mixed traffic flow micro-model. The steps of constructing the CACC large vehicle mixed traffic flow micro-model are as follows: Step 1: Determine the vehicle type and state judgment logic; Step 2: Determine the CACC vehicle queue status judgment logic; Step 3: Determine the vehicle lane change control logic; Step 4: Determine the vehicle speed control logic; The vehicle type and state judgment logic in step 1 includes: 1) Determine the vehicle type of the target vehicle, which is divided into vehicle control mode and vehicle model structure: 2) If the target vehicle is controlled by traditional manual driving, platooning is not adopted; 3) If the target vehicle is controlled in CACC mode, based on the premise that CACC vehicles of the same type can form a vehicle platoon, further determine the CACC vehicle status: 4) If the target vehicle and the preceding vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the preceding convoy is not full, then the target vehicle is identified as a convoy member vehicle: 5) If the relationship between the target vehicle and the preceding vehicle does not meet the conditions for being a convoy member vehicle, the target vehicle and the following vehicle are of the same type, are not in the process of changing lanes and are in the same lane, meet the vehicle spacing determination conditions and the following convoy is not full, then the vehicle is identified as the convoy leader: 6) If the target vehicle does not meet the conditions to become a team member vehicle or a team leader vehicle, the vehicle is considered a CACC non-team free vehicle. ; in, is the vehicle type, is the vehicle control type, Is the vehicle structure type, and is the vehicle length and width; is the target vehicle number, is the target vehicle's preceding vehicle number, is the target vehicle's rear vehicle number; is the CACC vehicle status, 0 represents a CACC non-team free vehicle, 1 represents a CACC team leader vehicle, and 2 represents a CACC team member vehicle; is the lane number of the vehicle; It is the position of the front of the vehicle. is the maximum allowable headway; is the number of vehicles in the vehicle's fleet, is the maximum number of vehicles in the convoy.

2. The method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control as claimed in claim 1, characterized in that: The CACC vehicle queue state judgment in step 2 is based on vehicle type and state judgment, and the completion includes vehicle queue initialization, free vehicle joining the fleet and vehicle queue reorganization: 1) Two adjacent CACC free vehicles, i.e. the front vehicle and the rear vehicle, are grouped to form a new convoy if the distance between them meets the distance condition for platooning and they are in the same lane or the rear vehicle meets the lane change condition. At this time, the front vehicle will become the CACC convoy leader and the rear vehicle will become a convoy member, thus initializing the convoy formation. 2) When a CACC free car approaches the convoy ahead and the convoy ahead has not reached the maximum length limit, the car will join the convoy from the rear by accelerating or changing lanes; 3) When a full convoy at the rear encounters an underfilled convoy at the front, the leading vehicle at the rear will, in order to improve road utilization and driving efficiency, change lanes or accelerate to join the convoy in front while ensuring safety, thereby changing its vehicle status from a CACC leading vehicle to a CACC member vehicle; when a member vehicle in the convoy needs to change lanes to leave the current convoy and enter the target lane due to route changes, a mandatory lane change is performed, and the vehicle status becomes a CACC free vehicle. This status change is accompanied by the reorganization of the original convoy.

3. The method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control as claimed in claim 1, characterized in that: The vehicle lane change control in step 3 is based on the LC2013 lane change model to control the vehicle's lane change. Both CACC vehicles and traditional vehicles use the same lane change control logic, including four lane change motivations: strategic lane change, cooperative lane change, tactical lane change, and regulated lane change: 1) Strategic lane change means that when there is no available connection between the current lane and the next section of the planned route, the vehicle must change lanes to reach the next section in order to complete the lane change behavior according to the planned route. The decision on whether to make a strategic lane change is made based on the urgency of the lane change demand, and deadlock is avoided during the lane change process, that is: in, is the distance from the target vehicle to the end point of the current road section, is the distance reduction related to traffic flow density; is the expected speed of the vehicle when it reaches the end of the current road segment; is the number of lane changes from the current lane to the target lane; is the time coefficient for the vehicle to successfully change lanes, which is 10 for changing lanes to the left and 20 for changing lanes to the right; 2) Cooperative lane changing is a lane changing behavior performed by a vehicle in certain traffic conditions to help the vehicle in the adjacent lane to free up space in the current lane. The vehicle uses the turn signal of the vehicle in front of the adjacent lane to determine whether the vehicle in front has a strategic lane changing intention, and thus determines whether a cooperative lane change is needed. If there is no strategic reason against the lane changing behavior, the vehicle intending to change lanes will make a cooperative lane change to the target lane in the possible direction to free up space in the current lane for the vehicle in front of the adjacent lane, and assist the vehicle in front to complete the strategic lane change. When the conditions at the current moment are not sufficient to implement a cooperative lane change, the vehicle intending to change lanes will adjust its speed to increase the probability of a successful subsequent lane change. 3) Tactical lane change is the behavior of a vehicle changing lanes to avoid being blocked by a slower vehicle ahead. It is necessary to strike a balance between the expected speed gain of the lane change and the input of the lane change process and keeping the overtaking lane clear. The decision on whether to make a tactical lane change is based on the evaluation of the expected speed gain, that is: in, yes Moment speed gain parameter; is the coefficient of lane change direction, -1 means changing lanes to the right, 1 means changing lanes to the left; is the speed of the vehicle intending to change lanes; is the speed of the preceding vehicle; 4) Regulated lane change refers to the lane change behavior in which the left lane of the vehicle's driving direction is used as the overtaking lane under the right lane driving rule. Based on the relevant requirements of laws and regulations, the driver is obliged to return to the right lane after completing overtaking in the left lane. Whether to perform a regulated lane change is determined based on the evaluation of the right lane change parameters, namely: in, yes Lane changing parameters of vehicles intending to change lanes at any moment; is the adjustment urgency factor for lane changes based on regulatory requirements; It is the estimated time that the lane-changing vehicle can travel at full speed in the right lane based on the distance and speed to the vehicle ahead in the right lane; is the expected speed of the vehicle intending to change lanes; is the maximum speed limit of the right target lane; Speed ​​of vehicle intending to change lanes; When the strategic lane change demand is urgent and deadlock will not occur, a strategic lane change is performed; when a vehicle causes an obstruction to the vehicle ahead that is performing a strategic lane change, a collaborative lane change is performed; when the expected speed gain brought by the lane change is greater than a threshold, a tactical lane change is performed; when the right lane change parameter is less than a threshold, a regulated lane change is performed.

4. The method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control as claimed in claim 1, characterized in that: The vehicle speed control in step 4 is differentiated according to the vehicle control mode, including traditional vehicle speed control and CACC vehicle speed control.

5. The method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control as claimed in claim 4, characterized in that: The conventional vehicle speed control in step 4 is based on the safety distance theory, and the target vehicle is a conventional vehicle, and there are: in, yes The safe speed of the target vehicle at all times, yes The speed of the preceding vehicle at that moment, yes The distance between the rear of the preceding vehicle and the front of the target vehicle at the moment, yes The target vehicle speed at the moment, is the target vehicle driver reaction time, is the maximum deceleration of the target vehicle, yes The expected speed of the target vehicle at time is the maximum acceleration of the target vehicle, is the maximum speed of the target vehicle, It is the speed deviation caused by the vehicle's mechanical performance and the driver's operating errors and intentions.

6. The method for simulating mixed traffic flow of large vehicles with cooperative adaptive cruise control as claimed in claim 5, wherein the CACC vehicle speed control in step 4 is specifically divided into four modes: speed control mode, gap control mode, gap closing control mode and collision avoidance control mode: 1) When there is no platooning vehicle ahead within the CACC vehicle-to-vehicle communication range or the headway between the vehicle and the platooning vehicle ahead is greater than 2s, the speed control mode is enabled, with: 2) When the actual distance between the CACC member vehicle and the preceding vehicle deviates from the expected distance by 0-0.2m and the actual vehicle speed deviation is less than 0.1m / s, the gap control mode is enabled, with: 3) When the headway is between 1.5s and 2s, the CACC vehicle retains the control mode used at the last moment. When the CACC vehicle approaches the platooning vehicle and the headway is less than 1.5s, the gap closing control mode is enabled, with: 4) When the actual distance between the CACC vehicle and the vehicle ahead is less than the expected distance and the deviation is greater than 0.2m, and the actual speed deviation is greater than 0.1m / s, the collision avoidance control mode is enabled, with: in, yes Time target vehicle speed, Is the target vehicle associated with the vehicle type The expected speed, yes Time target vehicle With the front car The deviation between the actual spacing and the expected spacing, yes Time target vehicle At the front of the car, It's the front car The length of the body, Is the target vehicle associated with the vehicle type The expected headway time, The target vehicle exist The speed-dependent spacing safety margin at each moment, and is the speed control feedback gain coefficient related to the speed deviation, It is the speed control feedback gain factor related to the pitch deviation.

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