Intelligent network connection vehicle dynamic control method for unsteady state communication environment

Abstract

The invention discloses an unsteady-state communication environment-oriented intelligent network connection vehicle dynamic control method, relates to the technical field of vehicle networking and intelligent network connection vehicle control, and aims to solve the problem of real-time control of an intelligent network connection vehicle team in an unsteady-state communication environment. The method specifically comprises the following steps: acquiring communication link data and vehicle state data in real time, accurately monitoring unsteady communication parameters such as communication transmission delay and packet loss rate, acquiring vehicle state data such as speed, acceleration and longitudinal position of each vehicle in a motorcade, analyzing communication stability in real time through a multi-dimensional communication environment evaluation index, and determining the state of the vehicle in the motorcade. And finally, according to unsteady state communication environment monitoring and vehicle safety risk assessment results, a dynamic control strategy is adopted to adjust a vehicle control mode, and it is ensured that a motorcade keeps efficient and stable operation in the unsteady state communication environment. By means of the innovative vehicle dynamic control method, the safety and the operation efficiency of the intelligent network connection vehicle team in the unsteady state communication environment are effectively improved.

Description

Technical Field

[0001] The present invention relates to the field of vehicle networking and intelligent networked vehicle control technology, and in particular to a dynamic control method for an intelligent networked vehicle in a non-steady-state communication environment. Background Art

[0002] With the rapid development of information communication and artificial intelligence technologies, intelligent connected vehicles have become a key component of the next generation of transportation systems, driving the transportation system towards a safer, more efficient and sustainable direction. In recent years, the application of autonomous driving technology has gradually deepened, especially the collaborative adaptive cruise control system has performed outstandingly in assisted driving systems. The collaborative adaptive cruise control system enables intelligent connected vehicles to autonomously form a fleet and drive on the road in a coordinated manner, improving the overall efficiency and safety of traffic flow.

[0003] However, with the widespread application of intelligent network technology, there are still some challenges that need to be solved. Among them, the transmission of real-time traffic information in vehicle network communication is one of the key obstacles to the implementation of practical applications. Under normal circumstances, vehicle network communication is in a state of low packet loss rate and low communication transmission delay. However, due to various interference factors, non-steady-state communication environment may still occur. For example, open communication systems are vulnerable to various network attacks, which can endanger the lives of drivers and passengers. In addition, in real road environments, vehicle network communication is still affected by unfavorable factors such as communication hardware, obstacle obstruction and network congestion, which will cause intelligent connected vehicles to be in a non-steady-state communication environment. Therefore, adopting the correct vehicle control strategy in a non-steady-state communication environment is crucial to maintaining the stability of vehicle operation. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the shortcomings of the prior art and provide a dynamic control method for intelligent connected vehicles in a non-steady-state communication environment, further enhance the collaborative ability of intelligent connected vehicles in a complex communication environment, ensure that they can still operate stably under various communication interferences, and improve the overall efficiency and safety of the fleet operation.

[0005] The present invention adopts the following technical solutions to solve the above technical problems:

[0006] According to a method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment proposed by the present invention, in a potential non-steady-state communication environment, based on the communication link data and vehicle status data of each vehicle in the intelligent connected vehicle fleet, at a preset time interval Δt, each vehicle in the intelligent connected vehicle fleet periodically performs the following process:

[0007] Collect communication link data: Every certain time interval Δt, the nth vehicle Veh nReal-time collection of Veh of the mth vehicle connected to it m Communication link data, where Veh n is the target vehicle, Veh m For Veh n The preceding vehicle, n and m are vehicle numbers, m∈{1,2,...,n-1} and nm≤S-1, S is the maximum length of the intelligent networked vehicle fleet;

[0008] Obtain vehicle status data: collect Veh in real time at a certain time interval Δt n The vehicle status data is collected and communicated with Veh in real time through the Internet of Vehicles communication technology. n Veh for communication connection m Vehicle status data;

[0009] Monitoring non-steady-state communication environment: Veh n and Veh m Communication transmission delay between Bit error rate in time T1 and packet loss rate The communication indicators are normalized and weights are assigned to each normalized communication indicator to construct a comprehensive evaluation indicator of the communication environment. When Veh n With any car in front of Veh m of When , it is determined to be a non-steady-state communication environment; otherwise, it is determined to be a steady-state communication environment; where E * A comprehensive evaluation index for the communication environment The threshold value of

[0010] Assessing vehicle safety risk: Using the modified collision time MTTC as a vehicle safety risk assessment indicator, when the vehicle status data is collected at the time t n Veh n Corrected collision time MTTC n (t n )>MTTC * When Veh n is in a security risk; otherwise, Veh n Not in a security risk; and count the distance t n Moment Veh in the time frame n Number of security risks Among them, MTTC * To correct the threshold of collision time MTTC, The time range for counting the number of security risks;

[0011] Adjust vehicle dynamic control: All intelligent connected vehicles on the road section will make different vehicle dynamic control adjustments based on the results of non-steady-state communication environment monitoring and vehicle safety risk assessment.

[0012] As a further optimization scheme of the intelligent connected vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the time interval Δt∈{10ms, 20ms, 50ms, 100ms}.

[0013] As a further optimization scheme of the intelligent connected vehicle dynamic control method for non-steady-state communication environment described in the present invention, the communication link data includes Veh n and Veh m The communication link between the data collection time t n,m , communication transmission delay Bit error rate within T1 time and packet loss rate

[0014] As a further optimization scheme of the intelligent connected vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the Veh n The vehicle status data includes Veh n The vehicle status data collection time t n , Veh n Speed Veh n Acceleration Veh n Vertical position Veh n Vehicle length L n , Veh of the vehicle immediately ahead obtained through the vehicle-mounted sensor n-1 Speed Acceleration Veh n The car next to it, Veh n-1 The distance between Veh m The vehicle status data includes Veh n Receive Veh m The time t of vehicle status data m , Veh m Speed Veh m Acceleration Veh m Vertical position and Veh m Vehicle length L m .

[0015] As a further optimization scheme of the intelligent connected vehicle dynamic control method for non-steady-state communication environment described in the present invention, a comprehensive evaluation index of the communication environment is constructed The details are as follows:

[0016] (1) The normalization process of each communication index, the specific calculation formula is as follows:

[0017]

[0018]

[0019]

[0020] in, Delay in communication transmission The normalized result of * is the communication transmission delay threshold, is the bit error rate within T1 time The normalized result, BER * is the bit error rate threshold within T1 time, is the packet loss rate within T1 The normalized result, PLR * is the packet loss rate threshold within T1 time;

[0021] (2) Assign weights to each normalized indicator to construct a comprehensive evaluation index for the communication environment The specific formula is as follows:

[0022]

[0023] Among them, ω1 is The weight coefficient, ω2 is The weight coefficient of The weight coefficient of .

[0024] As a further optimization scheme of the intelligent connected vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the Veh n In t n Corrected time to collision MTTC n (t n ), the specific calculation formula is as follows:

[0025]

[0026]

[0027]

[0028] Among them, MTTC1 n(t n ) is Veh n In t n The first corrected collision time calculation result at the moment, MTTC2 n (t n ) is Veh n In t n The second corrected collision time calculation result at time.

[0029] As a further optimization scheme of the intelligent connected vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the modified collision time MTTC is used as a vehicle safety risk assessment indicator. n Moment Veh n The modified collision time MTTC n (t n )>MTTC * When Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, Veh n Not at risk of security and will n Safe switching variables at all times Recorded as 0.

[0030] As a further optimization scheme of the intelligent networked vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the The calculation formula is as follows:

[0031]

[0032] Among them, t i A specific time node in the time series of statistical security risk counts. t i Safe switching variables at all times.

[0033] As a further optimization scheme of the intelligent connected vehicle dynamic control method for a non-steady-state communication environment described in the present invention, the vehicle dynamic control adjustment includes the definition of the vehicle dynamic control strategy and the vehicle dynamic control adjustment, which are as follows:

[0034] The vehicle dynamic control strategy includes the first to third control strategies, wherein:

[0035] First control strategy A: When Veh n When a packet is received, it immediately replaces the corresponding previous packet; the number of packets required to adjust the driving state is equal to Veh n The number of connected vehicles; the first control strategy A is based on the detected communication environment comprehensive evaluation index Dynamically adjust Veh n To Veh m The weight coefficient of the vehicle status data packet, and when the communication environment comprehensive evaluation index More than E * When the corresponding Veh m The vehicle status data packet weight coefficient will be set to zero;

[0036] Second control strategy B: for the vehicle immediately ahead Veh n-1 Vehicle status data acquisition, target vehicle Veh n Will switch to vehicle sensor-based detection to obtain Veh n-1 Vehicle status data; at the same time, Veh n Continue to use the same method as the first control strategy A to process the n-1 Other than the previous car Veh m Vehicle status data packet;

[0037] The third control strategy C: take emergency measures such as manual takeover and active collision avoidance system intervention;

[0038] The delineation of vehicle dynamic control adjustments is specifically divided into the following situations:

[0039] (1) When ① is satisfied ② When one of these two conditions is met, that is, when ① the target vehicle Veh n Number of security risks Less than or equal to ② Target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Less than or equal to E * , when one of the two conditions is met, the target vehicle Veh n The first control strategy A is adopted, in which, is the threshold of the number of security risks;

[0040] (2) When ① ② and When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the front car Veh m of Less than or equal to E * And the target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Greater than E * , under the two conditions, the target vehicle Veh n Adopt the second control strategy B;

[0041] (3) When ① ② When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When the target vehicle Veh n and any car in front of it m of Greater than E * , under the two conditions, the target vehicle Veh n The third control strategy C is adopted.

[0042] As a further optimization scheme of the dynamic control method of an intelligent connected vehicle in a non-steady-state communication environment described in the present invention, in the first control strategy A, Veh is dynamically adjusted. n To Veh m The weight coefficient of the vehicle status data packet specifically includes the following steps:

[0043] Step A1: Calculate the weight coefficient of each vehicle status data packet after attenuation The specific formula is as follows:

[0044]

[0045] in, Veh is the target vehicle after considering the attenuation of the non-steady-state communication effect n Veh m The weight coefficient of the vehicle status data packet, The target vehicle Veh n Veh m Initial weight coefficient of vehicle status data packet, Δ d is the attenuation parameter to consider the impact of non-steady-state communication;

[0046] Step A2: Calculate the final weight coefficient of each vehicle status data packet after normalization of the total weight coefficient The specific formula is as follows:

[0047]

[0048] in, The target vehicle Veh n Veh m The final weight coefficient of the vehicle status data packet.

[0049] Compared with the prior art, the present invention adopts the above technical solution and has the following technical effects:

[0050] (1) First, through the communication module of the intelligent connected vehicle, the data transmission status of the vehicle network communication link is collected in real time, including communication transmission delay, packet loss rate and bit error rate, so as to accurately capture the unstable factors in the communication link; secondly, this method can continuously obtain and update the vehicle status data in a non-steady-state communication environment, such as speed, acceleration, location information and the relative distance between vehicles; in addition, this method establishes a monitoring mechanism for the non-steady-state communication environment, and constructs a multi-dimensional comprehensive evaluation index for the communication environment. To analyze the stability of the communication environment in real time, a certain amount of monitoring data redundancy is set to ensure the reliability of the results, providing a basis for the adjustment of vehicle dynamic control. Based on the collected communication link data and vehicle status data, this method can dynamically evaluate the safety risks of vehicles in non-steady-state communication environments and provide a reference for control decisions. Finally, this method designs three dynamic control strategies that can adaptively adjust the vehicle control mode to ensure the stable operation and safety of the fleet, especially in complex non-steady-state communication environments, and still maintain high traffic efficiency and vehicle stability.

[0051] (2) By collecting the communication link data and vehicle status data of each vehicle in the intelligent networked vehicle fleet in real time, non-steady-state communication environment monitoring and vehicle safety risk assessment are performed based on these data, and real-time dynamic control of intelligent networked vehicles is performed according to different non-steady-state communication environment monitoring and vehicle safety risk assessment results to improve the overall safety and stability of the operation of the intelligent networked vehicle fleet; effectively solve the problem of real-time dynamic control of the intelligent networked vehicle fleet in a possible non-steady-state communication environment to ensure that it can still operate stably under poor communication interference. The present invention provides strong support for the safe and efficient operation of intelligent networked vehicles and lays a solid foundation for their wide application. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 It is a flow chart of a method for dynamic control of an intelligent networked vehicle in a non-steady-state communication environment according to the present invention;

[0053] Figure 2 It is a schematic diagram of the vehicle fleet arrangement and communication topology structure in the implementation example of the present invention; wherein, (a) is a dual front vehicle communication topology structure, (b) is a leader-dual front vehicle communication topology structure, and (c) is a multi-vehicle front communication topology structure. DETAILED DESCRIPTION

[0054] In order to further understand the present invention, preferred embodiments of the present invention are described below in conjunction with examples. However, it should be understood that these descriptions are only for further illustrating the features and advantages of the present invention, rather than limiting the claims of the present invention.

[0055] The description in this section is only for typical embodiments, and the present invention is not limited to the scope of the embodiments. The combination of different embodiments, the mutual replacement of some technical features in different embodiments, and the mutual replacement of the same or similar prior art means with some technical features in the embodiments are also within the scope of the description and protection of the present invention.

[0056] This embodiment provides a method for dynamic control of an intelligent connected vehicle in a non-steady-state communication environment. Figure 1 As shown, facing the potential non-steady-state communication environment, based on the communication link data and vehicle status data of each vehicle in the intelligent networked fleet, at a preset time interval Δt, each vehicle in the intelligent networked fleet periodically performs the following process:

[0057] Step 1. Collect communication link data: Every certain time interval Δt, the nth vehicle Veh n Real-time collection of Veh of the mth vehicle connected to it m Communication link data, where Veh n is the target vehicle, Veh m For Veh n The preceding vehicle, n and m are vehicle numbers, m∈{1,2,...,n-1} and nm≤S-1, S is the maximum length of the intelligent networked vehicle fleet, and the time interval Δt is 100ms; the communication link data includes Veh n and Veh m The communication link between the data collection time t n,m , communication transmission delay Bit error rate within T1 time and packet loss rate Preferably, the maximum length S of the intelligent networked vehicle fleet is 6 vehicles, and the value of T1 is 5s;

[0058] Figure 2 The three fleet scheduling and communication topologies presented in are all applicable to the present invention. Figure 2 (a) is a dual front vehicle communication topology. Figure 2 (b) is the leader-two-vehicle front communication topology. Figure 2 (c) in FIG. 1 is a multi-vehicle front communication topology. For further explanation, in this embodiment, a fleet of 6 intelligent networked vehicles is selected and the following Figure 2The multi-vehicle communication topology shown in (c) in the figure. Taking into account that the present invention focuses on the dynamic control changes of intelligent connected vehicles, that is, facing different non-steady-state communication environments and vehicle safety risks, dynamically changing the control strategy of intelligent connected vehicles to better ensure the stable operation and safety of the fleet, the communication link data and vehicle status data of each vehicle in three possible situations will be presented one by one to present the dynamic change process of the control strategy. The three situations are: ① Stable communication environment and no vehicle safety risk (10s-11s); ② Slight non-steady-state communication environment and vehicle safety risk occur simultaneously (50s-51s); ③ Severe non-steady-state communication environment and vehicle safety risk occur simultaneously (110s-111s). At the same time, select Figure 2 Veh5 in the embodiment is taken as the research object of this embodiment, so the data presented in this embodiment are the communication link data and vehicle status data acquired by Veh5. The communication link data of Veh5 are shown in Table 1, Table 2 and Table 3.

[0059] Table 1 Communication transmission delay between Veh5 and other vehicles in the convoy (Unit: s)

[0060]

[0061] Table 2 Bit error rate during T1 between Veh5 and other vehicles in the fleet (unit:%)

[0062]

[0063] Table 3 Packet loss rate between Veh5 and other vehicles in the convoy during T1 period (unit:%)

[0064]

[0065]

[0066] Step 2. Obtain vehicle status data: collect Veh in real time at a certain time interval Δt n The vehicle status data is collected and communicated with Veh in real time through the Internet of Vehicles communication technology. n Veh for communication connection m Vehicle status data; the Veh n The vehicle status data includes Veh n The vehicle status data collection time t n , Veh n Speed Veh n Acceleration Veh n Vertical position Veh n Vehicle length L n , Veh of the vehicle immediately ahead obtained through the vehicle-mounted sensor n-1 Speed Acceleration Veh n The car next to it, Veh n-1 The distance between Veh m The vehicle status data includes Veh n Receive Veh m The time t of vehicle status data m , Veh m Speed Veh m Acceleration Veh m Vertical position and Veh m Vehicle length L m In this embodiment, t n =t m , and the length of all vehicles is 5m, that is, L n =L m =5m; Among them, the speed, acceleration, and longitudinal position data of each vehicle in the intelligent networked fleet received by Veh5 are shown in Table 4, Table 5, and Table 6. The null value in the table indicates that there is a data packet loss. The vehicle status data of the adjacent preceding vehicle Veh4 obtained by Veh5 through the vehicle-mounted laser radar is shown in Table 7;

[0067] Table 4 Speed ​​data of each vehicle in the intelligent connected fleet received by Veh5 (unit: ms)

[0068]

[0069] Table 5 Acceleration data of each vehicle in the intelligent networked fleet received by Veh5 (unit: ms) 2 )

[0070]

[0071] Table 6 Longitudinal position data of each vehicle in the intelligent networked fleet received by Veh5 (unit: m)

[0072]

[0073] Table 7. Vehicle status data of the vehicle immediately preceding Veh4 obtained by Veh5 through the vehicle-mounted laser radar

[0074]

[0075] Step 3. Monitor the non-steady-state communication environment: n and Veh m Communication transmission delay between Bit error rate in time T1 and packet loss rate The communication indicators are normalized and weights are assigned to each normalized communication indicator to construct a comprehensive evaluation indicator of the communication environment. When Veh n With any car in front of Veh m of When , it is determined to be a non-steady-state communication environment; otherwise, it is determined to be a steady-state communication environment; where E * A comprehensive evaluation index for the communication environment Preferably, E * The value of is 5;

[0076] Constructing comprehensive evaluation indicators of communication environment The details are as follows:

[0077] (1) The normalization process of each communication index, the specific calculation formula is as follows:

[0078]

[0079]

[0080]

[0081] in, Delay in communication transmission The normalized result of * is the communication transmission delay threshold, is the bit error rate within T1 time The normalized result, BER * is the bit error rate threshold within T1 time, is the packet loss rate within T1 The normalized result, PLR * is the packet loss rate threshold within T1; preferably, τ * The value of is 0.4s, BER * The value of PLR is 20%, * The value of is 60%;

[0082] (2) Assign weights to each normalized indicator to construct a comprehensive evaluation index for the communication environment The specific formula is as follows:

[0083]

[0084] Among them, ω1 is The weight coefficient, ω2 is The weight coefficient of The specific values ​​of the weight coefficients ω1, ω2, and ω3 can be set according to actual application requirements; preferably, the value of ω1 is The value of ω2 is The value of ω3 is Among them, the comprehensive evaluation index of the communication environment between Veh5 and other vehicles in the fleet is The results are shown in Table 8.

[0085] Table 8 Comprehensive evaluation indicators of the communication environment between Veh5 and other vehicles in the convoy

[0086]

[0087]

[0088] Step 4. Evaluate vehicle safety risk: Use Modified Time to Collision (MTTC) as the vehicle safety risk assessment indicator. n Time target vehicle Veh n The modified collision time MTTC n (t n )>MTTC * When Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, Veh n Not at risk of security and will n Safe switching variables at all times Record as 0; and count the distance t n Moment Target vehicle Veh within the time range n Number of security risks Among them, MTTC * To correct the threshold of collision time MTTC, The time range for counting the number of security risks; preferably, MTTC * The value of is 1.5s. The value of is 5s; the safety risk assessment results of Veh5 are shown in Table 9;

[0089] Veh n In t n Corrected time to collision MTTC n (t n), the specific calculation formula is as follows:

[0090]

[0091]

[0092]

[0093] Among them, MTTC1 n (t n ) is Veh n In t n The first corrected collision time calculation result at the moment, MTTC2 n (t n ) is Veh n In t n The second corrected collision time calculation result at time.

[0094] Said The calculation formula is as follows:

[0095]

[0096] Among them, t i A specific time node in the time series of statistical security risk counts. t i Safe switching variables at all times.

[0097] Table 9 Security risk assessment results of Veh5

[0098]

[0099]

[0100] Among them, the corrected collision time MTTC of Veh5 in Table 9 is n The "-" in the column represents MTTC n The value is too large, and Veh5 is in a very safe state.

[0101] Step 5. Adjust vehicle dynamic control: All intelligent connected vehicles in the road section perform different vehicle dynamic control adjustments according to the obtained non-steady-state communication environment monitoring and vehicle safety risk assessment results. The specific vehicle dynamic control adjustment of Veh5 is shown in Table 10;

[0102] The vehicle dynamic control adjustment includes the definition of the vehicle dynamic control strategy and the vehicle dynamic control adjustment, which are as follows:

[0103] The vehicle dynamic control strategy includes the first to third control strategies, wherein:

[0104] First control strategy A: When Veh n When a packet is received, it immediately replaces the corresponding previous packet; the number of packets required to adjust the driving state is equal to Veh n The number of connected vehicles; the first control strategy A is based on the detected communication environment comprehensive evaluation index Dynamically adjust Veh n To Veh m The weight coefficient of the vehicle status data packet, and when the communication environment comprehensive evaluation index More than E * When the corresponding Veh m The vehicle status data packet weight coefficient will be set to zero;

[0105] In the first control strategy A, Veh is dynamically adjusted n To Veh m The weight coefficient of the vehicle status data packet specifically includes the following steps:

[0106] Step A1: Calculate the weight coefficient of each vehicle status data packet after attenuation The specific formula is as follows:

[0107]

[0108] in, Veh is the target vehicle after considering the attenuation of the non-steady-state communication effect n Veh m The weight coefficient of the vehicle status data packet, The target vehicle Veh n Veh m The initial weight coefficient of the vehicle status data packet, α d is the attenuation parameter considering the influence of non-steady-state communication. Preferably, α d The value of is 0.7;

[0109] Step A2: Calculate the final weight coefficient of each vehicle status data packet after normalization of the total weight coefficient The specific formula is as follows:

[0110]

[0111] in, The target vehicle Veh n Veh m The final weight coefficient of the vehicle status data packet.

[0112] Second control strategy B: for the vehicle immediately ahead Veh n-1 Vehicle status data acquisition, target vehicle Veh nWill switch to vehicle sensor-based detection to obtain Veh n-1 Vehicle status data; at the same time, Veh n Continue to use the same method as the first control strategy A to process the n-1 Other than the previous car Veh m Vehicle status data packet;

[0113] The third control strategy C: take emergency measures such as manual takeover and active collision avoidance system intervention;

[0114] The delineation of vehicle dynamic control adjustments is specifically divided into the following situations:

[0115] (1) When ① is satisfied ② When one of these two conditions is met, that is, when ① the target vehicle Veh n Number of security risks Less than or equal to ② Target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Less than or equal to E * , when one of the two conditions is met, the target vehicle Veh n The first control strategy A is adopted, in which, is the threshold of the number of security risks; preferably, The value of is 5 times.

[0116] (2) When ① ② and When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the front car Veh m of Less than or equal to E * And the target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Greater than E * , under the two conditions, the target vehicle Veh n Adopt the second control strategy B;

[0117] (3) When ① ② When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When the target vehicle Vehn and any car in front of it m of Greater than E * , under the two conditions, the target vehicle Veh n The third control strategy C is adopted.

[0118] Table 10 Vehicle dynamic control adjustment of Veh5

[0119]

[0120]

[0121] The description and application of the present invention here are illustrative, and it is not intended to limit the scope of the present invention to the above-mentioned embodiments. The effects or advantages involved in the specification may not be reflected in the actual experimental examples due to the uncertainty of specific condition parameters or other factors, and the effects or advantages are not used to limit the scope of the invention. The deformation and change of the embodiments disclosed here are possible, and the replacement of the embodiments and the various equivalent parts are well known to those of ordinary skill in the art. It should be clear to those skilled in the art that the present invention can be implemented in other forms, structures, arrangements, proportions, and with other components, materials and parts without departing from the spirit or essential features of the present invention. Other deformations and changes can be made to the embodiments disclosed here without departing from the scope and spirit of the present invention.

Claims

1. A dynamic control method for an intelligent connected vehicle in a non-steady-state communication environment, characterized in that: Facing the potential non-steady-state communication environment, based on the communication link data and vehicle status data of each vehicle in the intelligent networked fleet, each vehicle in the intelligent networked fleet periodically performs the following process at a preset time interval Δt: Collect communication link data: Every certain time interval Δt, the nth vehicle Veh n Real-time collection of Veh of the mth vehicle connected to it m Communication link data, where Veh n is the target vehicle, Veh m For Veh n The preceding vehicle, n and m are vehicle numbers, m∈{1,2,...,n-1} and nm≤S-1, S is the maximum length of the intelligent networked vehicle fleet; Obtain vehicle status data: collect Veh in real time at a certain time interval Δt n The vehicle status data is collected and communicated with Veh in real time through the Internet of Vehicles communication technology. n Veh for communication connection m Vehicle status data; Monitoring non-steady-state communication environment: Veh n and Veh m Communication transmission delay between Bit error rate in time T1 and packet loss rate The communication indicators are normalized and weights are assigned to each normalized communication indicator to construct a comprehensive evaluation indicator of the communication environment. When Veh n With any car in front of Veh m of When , it is determined to be a non-steady-state communication environment; otherwise, it is determined to be a steady-state communication environment; where E * A comprehensive evaluation index for the communication environment The threshold value of Assessing vehicle safety risk: Using the modified collision time MTTC as a vehicle safety risk assessment indicator, when the vehicle status data is collected at the time t n Veh n Corrected collision time MTTC n (t n )>MTTC * When Veh n is in a security risk; otherwise, Veh n Not in a security risk; and count the distance t n Moment Veh in the time frame n Number of security risks Among them, MTTC * To correct the threshold of collision time MTTC, The time range for counting the number of security risks; Adjust vehicle dynamic control: All intelligent connected vehicles on the road section will make different vehicle dynamic control adjustments based on the results of non-steady-state communication environment monitoring and vehicle safety risk assessment.

2. The method for dynamic control of an intelligent connected vehicle in a non-steady-state communication environment according to claim 1, characterized in that: The time interval Δt∈{10ms, 20ms, 50ms, 100ms}.

3. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: The communication link data includes Veh n and Veh m The communication link between the data collection time t n,m , communication transmission delay Bit error rate within T1 time and packet loss rate 4. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: Veh n The vehicle status data includes Veh n The vehicle status data collection time t n , Veh n Speed Veh n Acceleration Veh n Vertical position Veh n Vehicle length L n , Veh of the vehicle immediately ahead obtained through the vehicle-mounted sensor n-1 Speed Acceleration Veh n The car next to it, Veh n-1 The distance between Veh m The vehicle status data includes Veh n Receive Veh m The time t of vehicle status data m , Veh m Speed Veh m Acceleration Veh m Vertical position and Veh m Vehicle length L m .

5. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: Constructing comprehensive evaluation indicators of communication environment The details are as follows: (1) The normalization process of each communication index, the specific calculation formula is as follows: in, Delay in communication transmission The normalized result of * is the communication transmission delay threshold, is the bit error rate within T1 time The normalized result, BER * is the bit error rate threshold within T1 time, is the packet loss rate within T1 The normalized result, PLR * is the packet loss rate threshold within T1 time; (2) Assign weights to each normalized indicator to construct a comprehensive evaluation index for the communication environment The specific formula is as follows: Among them, ω1 is The weight coefficient, ω2 is The weight coefficient of The weight coefficient of .

6. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 4, characterized in that: Veh n In t n Corrected time to collision MTTC n (t n ), the specific calculation formula is as follows: Among them, MTTC1 n (t n ) is Veh n In t n The first corrected collision time calculation result at the moment, MTTC2 n (t n ) is Veh n In t n The second corrected collision time calculation result at time.

7. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: The modified collision time MTTC is used as the vehicle safety risk assessment indicator. n Moment Veh n The modified collision time MTTC n (t n )>MTTC * When Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, Veh n Not at risk of security and will n Safe switching variables at all times Recorded as 0.

8. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: Said The calculation formula is as follows: Among them, t i A specific time node in the time series of statistical security risk counts. t i Safe switching variables at all times.

9. The method for dynamic control of an intelligent connected vehicle in a non-steady-state communication environment according to claim 1, characterized in that: The vehicle dynamic control adjustment includes the definition of the vehicle dynamic control strategy and the vehicle dynamic control adjustment, which are as follows: The vehicle dynamic control strategy includes the first to third control strategies, wherein: First control strategy A: When Veh n When a packet is received, it immediately replaces the corresponding previous packet; the number of packets required to adjust the driving state is equal to Veh n The number of connected vehicles; the first control strategy A is based on the detected communication environment comprehensive evaluation index Dynamically adjust Veh n To Veh m The weight coefficient of the vehicle status data packet, and when the communication environment comprehensive evaluation index More than E * When the corresponding Veh m The vehicle status data packet weight coefficient will be set to zero; Second control strategy B: for the vehicle immediately ahead Veh n-1 Vehicle status data acquisition, target vehicle Veh n Will switch to vehicle sensor-based detection to obtain Veh n-1 Vehicle status data; at the same time, Veh n Continue to use the same method as the first control strategy A to process the n-1 Other than the previous car Veh m Vehicle status data packet; The third control strategy C: take emergency measures such as manual takeover and active collision avoidance system intervention; The delineation of vehicle dynamic control adjustments is specifically divided into the following situations: (1) When ① is satisfied ② When one of these two conditions is met, that is, when ① the target vehicle Veh n Number of security risks Less than or equal to ② Target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Less than or equal to E * , when one of the two conditions is met, the target vehicle Veh n The first control strategy A is adopted, in which, is the threshold of the number of security risks; (2) When ① ② and When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the front car Veh m of Less than or equal to E * And the target vehicle Veh n With the vehicle immediately ahead, Veh n-1 of Greater than E * , under the two conditions, the target vehicle Veh n Adopt the second control strategy B; (3) When ① ② When two conditions are met at the same time, that is, when ① the target vehicle Veh n Number of security risks Greater than ②When the target vehicle Veh n and any car in front of it m of Greater than E * , under the two conditions, the target vehicle Veh n The third control strategy C is adopted.

10. The method for dynamic control of an intelligent connected vehicle in a non-steady-state communication environment according to claim 9, characterized in that: In the first control strategy A, Veh is dynamically adjusted n To Veh m The weight coefficient of the vehicle status data packet specifically includes the following steps: Step A1: Calculate the weight coefficient of each vehicle status data packet after attenuation The specific formula is as follows: in, Veh is the target vehicle after considering the attenuation of the non-steady-state communication effect n Veh m The weight coefficient of the vehicle status data packet, The target vehicle Veh n Veh m The initial weight coefficient of the vehicle status data packet, α d is the attenuation parameter to consider the impact of non-steady-state communication; Step A2: Calculate the final weight coefficient of each vehicle status data packet after normalization of the total weight coefficient The specific formula is as follows: in, The target vehicle Veh n Veh m The final weight coefficient of the vehicle status data packet.

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