Multi-vehicle cooperative road changing right arbitration method in intelligent network connection mixed traffic scene

Abstract

The invention discloses a multi-vehicle cooperative road changing right arbitration method in an intelligent network connection mixed traffic scene. The method comprises the following steps: S1, judging whether a main vehicle meets a lane changing condition or not; if yes, entering the step S2; s2, judging whether the right of road of adjacent lanes is sufficient or not; if yes, entering the step S3; if not, the right of way is arbitrated as the front space of the lane; s3, whether multi-vehicle cooperative lane changing exists or not is judged; if yes, entering the step S4; if not, arbitrating the right of way as the space in front of the target lane, and changing the lane; s4, judging whether road right conflicts exist or not; if yes, the right of way is arbitrated as the front space of the lane; and if not, performing road right arbitration according to the priority, performing road right arbitration as a space-time position corresponding to the target lane, and performing lane changing. According to the method, safe and efficient driving of vehicles in complex scenes of interlaced areas such as urban intersections and high-speed ramps can be guaranteed, and technical support is provided for passing efficiency, safety, comfort and the like in the multi-vehicle collaborative lane changing process.

Description

Technical Field

[0001] The present invention relates to the field of intelligent transportation, and in particular to an arbitration method for multi-vehicle cooperative right-of-way change in an intelligent networked hybrid traffic scenario. Background Art

[0002] For situations where traffic conflicts are complex and lane-changing risks are prominent in intelligent connected mixed traffic scenarios, consider conducting right-of-way arbitration for multi-vehicle coordinated lane changing from a roadside perspective, helping connected autonomous driving vehicles (CAV) and manually driven vehicles (HDV) to make safe decisions at the driving safety level, and using advanced means to improve situations such as overall low traffic flow efficiency, insufficient reliability of driving decisions, and lack of refined traffic safety reminders and guidance.

[0003] There are many advanced technologies supporting lane-changing models at home and abroad, which can calculate and analyze different lane-changing methods to help drivers make the best choice. However, for heterogeneous traffic flow scenarios, driver behavior is an unstable factor in traffic flow. At the same time, different smart car penetration rates will interfere with driver behavior and thus affect lane-changing decisions. Existing research basically revolves around the impact of different penetration rates on factors such as traffic capacity, speed, and flow, and also studies the driving safety of mixed driving from many aspects. However, most of the current research is only focused on the following behavior of vehicles in a single lane, and the analysis of vehicle lane-changing behavior is not comprehensive. There is little research on the coordinated lane-changing of CAV vehicles and HDV vehicles, and the research on lateral behaviors such as lane changes is far less comprehensive than the research on longitudinal driving behavior.

[0004] Therefore, a method for arbitration of right of way for multi-vehicle collaborative lane change in intelligent connected mixed traffic scenarios is needed, which can ensure safe and efficient driving of vehicles in complex scenarios such as urban intersections and highway ramps, and provide technical support for traffic efficiency, safety and comfort during multi-vehicle collaborative lane change. Summary of the invention

[0005] In view of this, the purpose of the present invention is to overcome the defects in the prior art and provide a method for arbitration of right of way for multi-vehicle collaborative lane change in intelligent connected mixed traffic scenarios, which can ensure safe and efficient driving of vehicles in complex scenarios such as urban intersections and highway ramps, and provide technical support for traffic efficiency, safety and comfort in the process of multi-vehicle collaborative lane change.

[0006] The multi-vehicle cooperative right-of-way arbitration method for intelligent networked hybrid traffic scenarios of the present invention comprises:

[0007] S1. Determine whether the host vehicle meets the lane change conditions; if so, proceed to step S2; if not, continue to step S1;

[0008] S2. Determine whether the adjacent lane has sufficient right of way; if so, proceed to step S3; if not, the right of way arbitration is the space in front of the lane, take the following action, and return to step S1;

[0009] S3. Determine whether there is a coordinated lane change of multiple vehicles; if so, proceed to step S4; if not, the right of way arbitration is the space in front of the target lane, and the lane change is performed. If the lane change is completed, the lateral right of way decision of the current lane is cleared, otherwise, return to step S2;

[0010] S4. Determine whether there is a right of way conflict; if so, the right of way arbitration is the space in front of the lane, follow the car, and return to step S1; if not, right of way arbitration is performed according to priority, the right of way arbitration is the time and space position corresponding to the target lane, and lane change is performed. If the lane change is completed, the lateral right of way decision of the current lane is cleared, otherwise, return to step S2.

[0011] Further, judging whether the host vehicle meets the lane change conditions includes:

[0012] Calculate the lane change expectation λ of the main vehicle hv :

[0013] λ hv =U hv pq+U hv (1-p)q+U hv p(1-q)+U hv (1-p)(1-q);

[0014] Among them, U hv is the comprehensive lane-changing intention determination index of the main vehicle; q is the probability of the main vehicle changing lanes, 1-q is the probability of the main vehicle not changing lanes, p is the probability of the vehicles affected by the lane change accepting the lane change of the main vehicle, and 1-p is the probability of the vehicles affected by the lane change not accepting the lane change of the main vehicle;

[0015] Using the lane change expectation λ of the host vehicle hv Derivative the probability q, set its derivative to 0, and obtain the value of the probability q. If the value of the probability q is greater than the threshold q0, the host vehicle meets the lane changing condition; otherwise, the host vehicle meets the lane changing condition.

[0016] Further, the comprehensive lane-changing intention determination index U of the host vehicle is determined according to the following formula: hv :

[0017]

[0018] in, fp is the penalty function; It is a safety distance indicator; is the vehicle speed indicator; is the comfort index; ω1 and ω2 are penalty parameters; a0 is the initial acceleration of the vehicle; t1 is the lane change time; a is the current acceleration of the vehicle; t is the current time; v is the lane change target speed; v i，j (t) is the speed of vehicle j in lane i at time t, and the host vehicle is vehicle j in lane i;

[0019]

[0020] S i，j is the required safety distance of vehicle j in lane i; S i，j+1 is the required safety distance of vehicle j+1 in lane i; α is the vehicle reaction time; β is 1 / 2 of the inverse of the vehicle's maximum deceleration; l is the vehicle length; d i,j+1 is the distance between vehicles j and j+1 on lane i;

[0021]

[0022] v i，j (t+t1) is the speed of vehicle j after changing lanes to the target lane; v i，j (t+t1)=(v i，j (t)+a s t1)cosθ, θ is the maximum rotation angle, a s is the acceleration of the vehicle;

[0023]

[0024] is the vehicle space occupancy rate of lane i; L is the total length of the observation section; l j is the length of the jth vehicle; n is the number of vehicles in the observation section.

[0025] Further, determine whether the adjacent lane has sufficient right of way, including:

[0026] Calculate the inherent right of way of the lane; the inherent right of way of the lane includes the inherent right of way of the vehicle in front of the main vehicle, the inherent right of way of the vehicle behind the adjacent lane, and the inherent right of way of the vehicle in front of the adjacent lane;

[0027] If the actual right of way of the lane environment where the host vehicle is located is greater than the inherent right of way of the lane, the right of way of the adjacent lane is sufficient; otherwise, the right of way of the adjacent lane is insufficient.

[0028] Furthermore, the inherent right of way of the vehicle ahead of the main vehicle is determined according to the following formula:

[0029]

[0030] in, v hvis the speed of the main vehicle; ρ is the reaction lag time of the autonomous driving vehicle; a hv，brake is the deceleration of the main vehicle; a max，brake is the maximum deceleration of the vehicle; a min，brake is the minimum deceleration of the vehicle; v max is the maximum speed limit of the lane, v l1 is the speed of the vehicle in front of the main vehicle;

[0031] The inherent right of way of the vehicle behind in the adjacent lane is determined according to the following formula:

[0032]

[0033] in, v f2 is the speed of the vehicle behind in the adjacent lane; ρ human The reaction lag time of human drivers;

[0034] The inherent right of way of the vehicle ahead in the adjacent lane is determined according to the following formula

[0035]

[0036] in,

[0037] Furthermore, right of way arbitration is conducted based on priority, including:

[0038] Compared with the manually driven vehicle HDV, the connected autonomous vehicle CAV has the right of way;

[0039] Among several CAV vehicles, the one with the best efficiency will arbitrate the right of way, and the one with the best efficiency will have the right of way first. Among them, when the efficiency is the same, the first-come-first-served basis will get the road priority.

[0040] Furthermore, the total speed change TotalΔv of the affected vehicles during the interaction is taken as the efficiency corresponding to the CAV vehicle; where, Δ vi =v i,after -v i,before , Δ vi is the speed change of the i-th vehicle, v i,before is the speed before the interaction, v i,after is the speed after the interaction; n is the total number of vehicles affected during the interaction.

[0041] Furthermore, when the efficiency is consistent, in the scenario of uniform motion or uniform acceleration, the time it takes for the lane-changing vehicle to reach the right-of-way arbitration area is:

[0042]

[0043] Among them, v i is the initial speed of the vehicle; v f is the expected speed of the vehicle at the target position; a is the average acceleration of the vehicle; d is the distance from the vehicle to the road right arbitration area;

[0044] In the motion scenario where the vehicle speed changes unsteadily, Kalman filtering is used to estimate the arrival time of the vehicle.

[0045] The beneficial effects of the present invention are as follows: the present invention discloses a method for arbitration of right of way for collaborative lane changing of multiple vehicles in an intelligent connected mixed traffic scenario, which takes into account the safety and comfort of collaborative lane changing of multiple vehicles in a connected traffic environment; from the perspective of roadside guidance and control of intelligent connected vehicles, a dynamic method for arbitration of right of way for collaborative lane changing of multiple vehicles is proposed; and the realization of safe and efficient lane changing of collaborative lane changing of multiple vehicles is of great significance for solving the traffic capacity of interweaving areas and the overall traffic efficiency of road sections in a connected mixed traffic environment, and as the penetration rate of intelligent connected vehicles continues to increase, the superiority of this method becomes higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] The present invention will be further described below in conjunction with the accompanying drawings and embodiments:

[0047] Figure 1 A schematic diagram of a three-lane multi-vehicle coordinated lane-changing scenario of the present invention;

[0048] Figure 2 A schematic diagram of the lane-changing safety distance of the present invention;

[0049] Figure 3 A vehicle right-of-way distribution diagram for a lane-changing scenario of the present invention;

[0050] Figure 4 It is a schematic diagram of the multi-vehicle cooperative right-of-way arbitration simulation of the present invention;

[0051] Figure 5 It is a schematic diagram of the overall process of multi-vehicle cooperative right-of-way arbitration of the present invention. DETAILED DESCRIPTION

[0052] The present invention is further described below in conjunction with the accompanying drawings, as shown in the drawings:

[0053] This embodiment discloses a method for arbitrating the right of way of multiple vehicles in a coordinated intelligent network hybrid traffic scenario, including the following steps:

[0054] S1. Determine whether the host vehicle meets the lane change conditions; if so, proceed to step S2; if not, continue to step S1;

[0055] S2. Determine whether the adjacent lane has sufficient right of way; if so, proceed to step S3; if not, the right of way arbitration is the space in front of the lane, keep driving in the lane, take the following action, and return to step S1;

[0056] S3. Determine whether there is a coordinated lane change of multiple vehicles; if so, proceed to step S4; if not, the right of way arbitration is the space in front of the target lane, and the lane change is performed. If the lane change is completed, the lateral right of way decision of the current lane is cleared, otherwise, return to step S2;

[0057] S4. Determine whether there is a conflict in right of way; if so, the right of way arbitration is the space in front of the lane, keep driving in the lane, take the following action, and return to step S1; if not, right of way arbitration is performed according to priority, the right of way arbitration is the time and space position corresponding to the target lane, and change lanes. If the lane change behavior is completed, the lateral right of way decision of the current lane is cleared, otherwise, return to step S2.

[0058] Among them, if multiple controllable connected vehicles initiate lane change requests in the same area at the same time, then there is a multi-vehicle coordinated lane change. As for whether the lane change behavior is completed, when driving from one lane to another, the lane change behavior is completed when the lateral acceleration remains unchanged or changes very little. The lateral right of way decision of the current lane is reset, which means that the lateral decision of the main vehicle's lane change has been completed or canceled, so the lateral right of way decision is reset. Whether there is a conflict in right of way refers to the situation where multiple vehicles occupy the same place or area at the same time. The existing road-side collaborative control unit can be used to monitor the speed and position of multiple vehicles to determine whether there is a conflict in right of way.

[0059] In addition, the time and space position corresponding to the target lane can be determined by the roadside collaborative control unit. The roadside collaborative control unit collects the position, speed and other information of all vehicles, calculates the time and space distribution of different vehicles, and determines the time and space position of the free driving right, which is the time and space position corresponding to the target lane, that is, the lane change area.

[0060] In this embodiment, the present invention takes a three-lane three-vehicle coordinated lane change scenario as an example. Figure 1 As shown. The scenario involved in the present invention is a one-way three-lane basic road section, where the lane lines are all dotted lines, and there are no restrictions on lane changing between vehicles, and vehicles can change lanes freely. Vehicle types are divided into: connected autonomous driving vehicles CAV (vehicles with arrows) and manually driven vehicles HDV (vehicles without arrows). Intelligent connected vehicles can report their own operating status information in real time and receive guidance and control information issued by the roadside collaborative control unit to assist the vehicle in making lateral lane change decisions. Among them, the roadside collaborative control unit adopts the existing roadside vehicle and traffic monitoring system, which will not be repeated here.

[0061] On the one hand, the driver's lane-changing decision enables the driver to gain an advantage in speed or following distance at a higher proportion; on the other hand, when the driving conditions do not allow the driver to maintain or increase the speed, the driver will make a lane-changing decision in most cases. Therefore, the decision on lane-changing intention in this method is analyzed using three indicators: safety distance index, speed index and comfort index.

[0062] (1) Safety distance indicator

[0063]

[0064]

[0065] In the formula, Figure 2 As shown, i and j are lane and vehicle numbers respectively; S i,j is the required safety distance of vehicle j in lane i, m; α is the vehicle reaction time, s; β is 1 / 2 of the inverse of the vehicle's maximum deceleration, m / s 2 ; l is the length of the vehicle, m; v i,j (t) is the speed of vehicle j in lane i at time t, m / s; d i,j+1 is the distance between vehicles j and j+1 on lane i, m.

[0066] (2) Speed ​​index

[0067] ①.Host Vehicle (HV) speed index

[0068]

[0069] In the formula, v i,j (t+t1) is the speed of vehicle j after changing lanes to the target lane, m / s; t1 is the lane changing time, s.

[0070] v i,j (t+t1)=(v i,j (t)+a s t1)cosθ(1-4)

[0071] In the formula, θ is the maximum rotation angle, a s is the acceleration of the vehicle;

[0072] ②. Putative Following Vehicle (PFV) speed indicator of the vehicle behind the target lane

[0073] Where: d i+1,j+1represents the distance between vehicles j and j+1 in lane i+1; T is the safe headway, s; b is the braking deceleration of the lane-changing vehicle at time t, m / s 2 ; b p is the maximum braking deceleration of the vehicle behind the target lane, m / s 2 ;v p (t) is the safe lane-changing speed of the vehicle behind the target lane, m / s. Wherein, headway = distance between two vehicles / vehicle speed;

[0074] That is, the PFV speed index of the vehicle behind the target lane is obtained

[0075]

[0076] Where: v i+1,j+1 (t) represents the speed of vehicle j+1 in lane i+1 at time t;

[0077] (3) Comfort index

[0078]

[0079] Where: is the vehicle space occupancy rate of lane i.

[0080]

[0081] Where L is the total length of the observation section, m; l j is the length of the jth vehicle, m; n is the number of vehicles in the observation section.

[0082] Finally, the comprehensive lane-changing intention judgment index U is obtained

[0083]

[0084] Where: fp is the penalty function; v * is the expected speed of the vehicle, m / s; ω1 and ω2 are penalty parameters, both of which have a default value of 0.5; a0 is the initial acceleration of the vehicle, m / s 2 t1 is the lane change time, s; a is the current acceleration of the vehicle, m / s 2 , t is the current time, s; v is the lane change target speed m / s. For the main vehicle HV, v in formula (1-9) * for U for U hv ; For the PFV of the vehicle behind the target lane, v in equation (1-9) * for U for U PFv .

[0085] Taking the real-time operating status data of the vehicle as input, by calculating the safety distance index, speed index and comfort index between the vehicle and surrounding vehicles, and then calculating the comprehensive lane change intention judgment index, the optimal driving lane and lane change intention of the intelligent connected vehicle are comprehensively decided.

[0086] Specifically, for the participant HV in the game, there are two strategies: {change lanes, do not change lanes}. The probability of choosing a lane change is q, and the probability of staying in the current lane without changing lanes is 1-q. Similarly, when the participant PFV encounters a lane change decision of HV, there are two strategies: {accept, do not accept}. The vehicle PFV affected by the lane change accepts the lane change of the main vehicle p, and 1-p is the probability that the vehicle PFV affected by the lane change does not accept the lane change of the main vehicle. If the HV chooses not to change lanes, the PFV can choose to maintain its current operating state or change lanes. The expectations of the main vehicle and the vehicle behind the target lane are obtained as λ respectively. hv With λ PFv :

[0087]

[0088] In the formula, in the case of acceptance or not and lane change or not, U hv and U PFv The corresponding parameter values ​​in the same formula (1-9) will be different (such as lane change time, current vehicle acceleration, etc.), making U hv and U PFv The calculation results are different and will not be repeated here.

[0089] The expected pair q or p of the host vehicle and the target lane rear vehicle in equation (11) and equation (12) are derived respectively, and their derivatives are set to 0, and the lane change probability q or p is obtained respectively. The lane change principle of the target vehicle and other adjacent lane vehicles is similar. Therefore, when the lane change probability q is greater than 0.5 or the probability of accepting lane change p is greater than 0.5, the vehicle lane change behavior can be executed.

[0090] In this embodiment, determining whether the adjacent lane has sufficient right of way specifically includes:

[0091] Calculate the inherent right of way of the lane; the inherent right of way of the lane includes the inherent right of way of the vehicle in front of the main vehicle, the inherent right of way of the vehicle behind the adjacent lane, and the inherent right of way of the vehicle in front of the adjacent lane;

[0092] If the actual right of way of the lane environment where the host vehicle is located is greater than the inherent right of way of the lane, the right of way of the adjacent lane is sufficient; otherwise, the right of way of the adjacent lane is insufficient.

[0093] Specifically, each vehicle on the road has its inherent safety space, which is called inherent right of way. During the lane change process of the host vehicle (hv), the vehicles in front of the host lane, the vehicles in front of the target lane, and the vehicles behind the target lane are mainly affected. Therefore, in the single-vehicle lane change scenario, the inherent right of way of the vehicle can be seen in Figure 3 , where the adjacent lane is the left lane.

[0094] (1) The vehicle ahead of the main vehicle has the inherent right of way

[0095]

[0096] Where: v hv is the speed of the host vehicle (hv) (m / s), ρ is the reaction lag time of the autonomous driving vehicle (s), and the reaction time of the autonomous driving vehicle can generally be 0s; a hv,brake The deceleration of the main vehicle (m / s 2 );a max,brake is the maximum deceleration of the vehicle (m / s 2 ),a min,brake is the minimum deceleration of the vehicle (m / s 2 ), v max is the maximum speed limit of the lane (m / s), v l1 The speed of the vehicle in front of the main vehicle (m / s).

[0097] (2) The vehicle behind you has the right of way

[0098]

[0099] Where: v f2 is the speed of the left rear vehicle (m / s), ρ human is the reaction lag time of human drivers (s), usually 2s. Other parameters are the same as above.

[0100] (3) The vehicle behind you has the right of way and negotiable right of way

[0101]

[0102] In the formula, a max,accel is the maximum acceleration of the vehicle (m / s 2 );

[0103] (4) The vehicle in front of you has the inherent right of way

[0104]

[0105] When the actual right of way of the vehicle in front of the main vehicle is greater than the inherent right of way of the vehicle in front of the main vehicle, the actual right of way of the vehicle behind the adjacent lane is greater than the inherent right of way of the vehicle behind the adjacent lane, and the actual right of way of the vehicle in front of the adjacent lane is greater than the inherent right of way of the vehicle in front of the adjacent lane, then the adjacent lane has sufficient right of way; otherwise, the adjacent lane has insufficient right of way.

[0106] In this embodiment, based on the above-mentioned vehicle lane change intention decision and the calculation results of the inherent right of way of a single vehicle, the roadside collaborative control unit is used as the calculation carrier to analyze the dynamic distribution of the real-time right of way of multiple vehicles in real time. Then, the global spatiotemporal right of way arbitration of the road can be carried out according to the vehicle priority principle and first-come, first-served rule.

[0107] Road right arbitration is carried out according to priority, including:

[0108] ①Compared with CAV and HDV, HDV has priority;

[0109] ② When CAV vehicles conflict with each other, road right arbitration is carried out based on the principle of optimal efficiency, and the party with the best efficiency has the right of way. When the efficiency is consistent, the road priority of existing traffic regulations is implemented, and the judgment condition is first come first served.

[0110] Efficiency is calculated using the average speed change under different interaction strategies. The smaller the index is, the smaller the impact of the action on surrounding vehicles is, and the smoother the lane change process is, which is not only efficient but also safer.

[0111] Δ vi =v i,after -v i,before (1-20)

[0112] In the formula, Δ vi is the speed change of the i-th vehicle, v i,before is the speed before the interaction (m / s), v i,after is the speed after the interaction (m / s);

[0113]

[0114] TotalΔv is the overall speed change of the affected vehicles during the interaction process. The smaller the value of TotalΔv, the better the efficiency.

[0115] When the efficiency is basically the same, the principle of first come first served is adopted. Specifically, based on the current movement state of the vehicle, the predicted time of occupying the right of way in the future is given priority to the vehicle that arrives the earliest to occupy the right of way in the current state.

[0116] I. In the case of uniform motion or uniform acceleration, the time it takes for a lane-changing vehicle to reach the right-of-way arbitration area can be calculated using the following formula:

[0117]

[0118] Where: v i is the initial speed of the vehicle (m / s); v fis the expected speed of the vehicle at the target position (m / s); a is the average acceleration of the vehicle (m / s2); d is the distance from the vehicle to the road right arbitration area, m.

[0119] II. When the speed changes unsteadily, this method uses the Kalman filter method to estimate the time when the vehicle arrives. The specific process is as follows:

[0120] (1) System Modeling

[0121] First, define the state model of vehicle motion, including position and velocity:

[0122] State vector x: contains the vehicle's position p and velocity v information

[0123] Control vector u: contains the vehicle's acceleration a information

[0124] The state update equation can be expressed as:

[0125] x k+1 =Fx k +Bu k +w k (1-23)

[0126] Where: x k+1 and x k are the states of the next moment and the current moment respectively, F is the state transfer matrix, which describes how the state is transferred from one moment to the next. B is the control input matrix, which describes how the control vector (such as acceleration) affects the state, u k is the control vector, representing acceleration, etc., w k is the process noise, taking into account the uncertainty in the model.

[0127] (2) Observation model

[0128] Define how to update the state estimate using observations:

[0129] z k =Hx k +v k (1-24)

[0130] z k is the observation vector, including the position and velocity measured by the sensor; H is the observation matrix, describing how the state vector is observed; v k is the observation noise.

[0131] (3) Kalman filter implementation

[0132] The steps to implement the Kalman filter include initialization, prediction, and update:

[0133] Initialization: Setting the initial state estimate and the initial error covariance P0

[0134] ① Prediction:

[0135] Predict the next state:

[0136]

[0137] Forecast error covariance:

[0138] P k+1|k =FP k F T +Q(1-26)

[0139] ②Update:

[0140] Calculate the Kalman gain:

[0141] K k =P k|k-1 H T (HP k|k-1 H T +R) -1 (1-27)

[0142] Update the state estimate:

[0143]

[0144] Update the error covariance:

[0145] P_{k|k}=(I-K_k H)P_{k|k-1}(1-29)

[0146] 4. Time prediction

[0147] Using the filtered position and velocity estimates, calculate the target position p target Prediction time:

[0148]

[0149] where p current and v current The Kalman filter calculates the latest position and speed after the update. The Kalman filter calculation process not only provides the best estimate of the vehicle's position and speed, but also adapts to changes in vehicle behavior through continuous updates, thereby accurately predicting the arrival time.

[0150] The present invention can be applied to relatively complex intersections, highway ramps and other sections with frequent weaving conflicts. It uses the roadside collaborative control unit to perform global vehicle state perception, make behavioral decisions for dispatchable connected vehicles, and conduct road right arbitration for multi-vehicle collaborative lane changing based on the results of the behavioral decisions. A single-vehicle inherent road right calculation method and a multi-vehicle dynamic road right arbitration method are established, thereby improving the traffic efficiency and safety of weaving sections. It is of great significance to improving the overall traffic capacity of roads, reducing traffic congestion and preventing safety accidents. In addition, the method is more effective when the penetration rate of intelligent connected vehicles increases. In the context of the continuous development of vehicle-road collaboration, it has a very broad application prospect.

[0151] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solution of the present invention can be modified or replaced by equivalents without departing from the purpose and scope of the technical solution of the present invention, which should be included in the scope of the claims of the present invention.

Claims

1. A method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario, characterized in that: include: S1. Determine whether the host vehicle meets the lane change conditions; If yes, proceed to step S2; if no, continue to step S1; S2. Determine whether the adjacent lane has sufficient right of way; if so, proceed to step S3; if not, the right of way arbitration is the space in front of the lane, take the following action, and return to step S1; S3. Determine whether there is a coordinated lane change of multiple vehicles; if so, proceed to step S4; if not, the right of way arbitration is the space in front of the target lane, and the lane change is performed. If the lane change is completed, the lateral right of way decision of the current lane is cleared, otherwise, return to step S2; S4. Determine whether there is a conflict in road rights; If so, the right of way arbitration is the space in front of this lane, the following behavior is taken, and the process returns to step S1; if not, the right of way arbitration is performed according to the priority, the right of way arbitration is the time and space position corresponding to the target lane, and the lane change is performed. If the lane change behavior is completed, the lateral right of way decision of the current lane is cleared, otherwise, the process returns to step S2.

2. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 1 is characterized by: Determine whether the host vehicle meets the lane change conditions, including: Calculate the lane change expectation λ of the main vehicle hv : λ hv =U hv pq+U hv (1-p)q+U hv p(1-q)+U hv (1-p)(1-q); Among them, U hv is the comprehensive lane-changing intention determination index of the main vehicle; q is the probability of the main vehicle changing lanes, 1-q is the probability of the main vehicle not changing lanes, p is the probability of the vehicles affected by the lane change accepting the lane change of the main vehicle, and 1-p is the probability of the vehicles affected by the lane change not accepting the lane change of the main vehicle; Using the lane change expectation λ of the host vehicle hv Derivative the probability q, set its derivative to 0, and obtain the value of the probability q. If the value of the probability q is greater than the threshold q0, the host vehicle meets the lane changing condition; otherwise, the host vehicle meets the lane changing condition.

3. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 2 is characterized by: The comprehensive lane-changing intention determination index U of the host vehicle is determined according to the following formula: hv : in, fp is the penalty function; It is a safety distance indicator; is the vehicle speed indicator; is the comfort index; ω1 and ω2 are penalty parameters; a0 is the initial acceleration of the vehicle; t1 is the lane change time; a is the current acceleration of the vehicle; t is the current time; v is the lane change target speed; v i,j (t) is the speed of vehicle j in lane i at time t, and the host vehicle is vehicle j in lane i; S i,j is the required safety distance of vehicle j in lane i; S i,j+1 is the required safety distance of vehicle j+1 in lane i; α is the vehicle reaction time; β is 1 / 2 of the inverse of the vehicle's maximum deceleration; l is the vehicle length; d i,j+1 is the distance between vehicles j and j+1 on lane i; v i,j (t+t1) is the speed of vehicle j after changing lanes to the target lane; v i,j (t+t1)=(v i,j (t)+a s t1)cosθ, θ is the maximum rotation angle, a s is the acceleration of the vehicle; is the vehicle space occupancy rate of lane i; L is the total length of the observation section; l j is the length of the jth vehicle; n is the number of vehicles in the observation section.

4. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 1 is characterized by: Determine whether the adjacent lane has sufficient right of way, including: Calculate the inherent right of way of the lane; the inherent right of way of the lane includes the inherent right of way of the vehicle in front of the main vehicle, the inherent right of way of the vehicle behind the adjacent lane, and the inherent right of way of the vehicle in front of the adjacent lane; If the actual right of way of the lane environment where the host vehicle is located is greater than the inherent right of way of the lane, the right of way of the adjacent lane is sufficient; otherwise, the right of way of the adjacent lane is insufficient.

5. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 4 is characterized by: The inherent right of way of the vehicle ahead of the host vehicle is determined according to the following formula in, v hv is the speed of the main vehicle; ρ is the reaction lag time of the autonomous driving vehicle; a hv,brake is the deceleration of the main vehicle; a max,brake is the maximum deceleration of the vehicle; a min,brake is the minimum deceleration of the vehicle; v max is the maximum speed limit of the lane, v l1 is the speed of the vehicle in front of the main vehicle; The inherent right of way of the vehicle behind in the adjacent lane is determined according to the following formula: in, v f2 is the speed of the vehicle behind in the adjacent lane; ρ human The reaction lag time of human drivers; The inherent right of way of the vehicle ahead in the adjacent lane is determined according to the following formula in, 6. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 1 is characterized by: Road right arbitration is carried out according to priority, including: Compared with the manually driven vehicle HDV, the connected autonomous vehicle CAV has the right of way; Among several CAV vehicles, the one with the best efficiency will arbitrate the right of way, and the one with the best efficiency will have the right of way first. Among them, when the efficiency is the same, the first-come-first-served basis will get the road priority.

7. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 6 is characterized by: The total speed change TotalΔv of the affected vehicles during the interaction is taken as the efficiency of the CAV vehicle; where, Δ vi =v i,after -v i,before , Δ vi is the speed change of the i-th vehicle, v i,before is the speed before the interaction, v i,after is the speed after the interaction; n is the total number of vehicles affected during the interaction.

8. The method for arbitrating the right of way of multiple vehicles in a coordinated intelligent networked mixed traffic scenario according to claim 6 is characterized by: When the efficiency is consistent, in a uniform motion or uniform acceleration scenario, the time it takes for a lane-changing vehicle to reach the right-of-way arbitration area is: Among them, v i is the initial velocity of the vehicle; v f is the expected speed of the vehicle at the target position; a is the average acceleration of the vehicle; d is the distance from the vehicle to the road right arbitration area; In the motion scenario where the vehicle speed changes unsteadily, Kalman filtering is used to estimate the arrival time of the vehicle.

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