A dynamic control method for intelligent connected vehicles in non-steady-state communication environments

Abstract

The present invention discloses a dynamic control method for intelligent connected vehicles in a non-steady-state communication environment, which relates to the field of vehicle networking and intelligent connected vehicle control technology, and aims to solve the real-time control problem of intelligent connected vehicle fleets in non-steady-state communication environments. The specific method is as follows: by collecting communication link data and vehicle status data in real time, accurately monitoring non-steady-state communication parameters such as communication transmission delay and packet loss rate, and simultaneously obtaining vehicle status data such as speed, acceleration, and longitudinal position of each vehicle in the fleet, analyzing communication stability in real time through multi-dimensional communication environment evaluation indicators, and dynamically evaluating vehicle safety risks. Finally, based on the results of non-steady-state communication environment monitoring and vehicle safety risk assessment, a dynamic control strategy is used to adjust the vehicle control mode to ensure that the fleet maintains efficient and stable operation in a non-steady-state communication environment. The present invention effectively improves the safety and operating efficiency of intelligent connected vehicle fleets in non-steady-state communication environments through innovative vehicle dynamic control methods.

Description

Technical Field

[0001] The present invention relates to the field of vehicle networking and intelligent connected vehicle control technology, and in particular to a dynamic control method for an intelligent connected 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 (ICVs) have become a key component of the next-generation transportation system, driving it towards a safer, more efficient, and more sustainable future. In recent years, the application of autonomous driving technology has steadily deepened, with cooperative adaptive cruise control (ACS) in particular demonstrating its prominence in assisted driving systems. ACS enables ICVs to autonomously form convoys and navigate the road in a coordinated manner, improving the overall efficiency and safety of traffic flow.

[0003] However, with the widespread adoption of intelligent connected technologies, several challenges remain to be addressed. Among them, the transmission of real-time traffic information in connected vehicle communications is a key obstacle to practical application. Under normal circumstances, connected vehicle communications experience low packet loss and low transmission latency. However, various interference factors can still lead to unstable communication environments. For example, open communication systems are vulnerable to various cyberattacks, which can endanger the lives of drivers and passengers. Furthermore, in real-world road environments, connected vehicle communications still face adverse factors such as communication hardware, obstruction by obstacles, and network congestion. These factors can lead to unstable communication environments for connected vehicles. Therefore, implementing appropriate vehicle control strategies in these unstable communication environments is crucial to maintaining vehicle stability. Summary of the Invention

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

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

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

[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 For 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 connected vehicle fleet;

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

[0009] Monitoring of 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 index of the communication environment. When Veh n With any preceding vehicle Veh m of When , it is determined to be a non-steady communication environment; otherwise, it is determined to be a steady communication environment; where E * Comprehensive evaluation index for communication environment threshold value;

[0010] Assessing vehicle safety risk: Using the modified time to collision (MTTC) as a vehicle safety risk assessment indicator, when the vehicle status data is collected at time t n Veh n Corrected collision time MTTC n (t n )>MTTC * When Veh n In security risk; otherwise, determine Veh n Not in a security risk; and calculate the distance t n Moment Veh in the timeframe 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 dynamic control method of an intelligent connected vehicle 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 method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment described in the present invention, the communication link data includes Veh n and Veh m Communication link 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 dynamic control method of intelligent connected vehicles in 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 Its immediate front car Veh n-1 The distance between Said 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 dynamic control method of intelligent connected vehicles 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 indicator, the specific calculation formula is as follows:

[0017]

[0018]

[0019]

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

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

[0022]

[0023] Among them, ω1 is The weight coefficient, ω2 is The weight coefficient, ω3 is The weight coefficient of .

[0024] As a further optimization scheme of the dynamic control method of intelligent connected vehicles in 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 dynamic control method of intelligent connected vehicles in a non-steady-state communication environment described in the present invention, the modified time to collision (MTTC) is used as a vehicle safety risk assessment indicator. When t n Moment Veh n Modified time to collision (MTTC) n (t n )>MTTC * When Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, determine Veh n Not at risk of security and n Safe switching variables at all times Recorded as 0.

[0030] As a further optimization scheme of the dynamic control method of intelligent connected vehicles in 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 delineation of the vehicle dynamic control strategy and the vehicle dynamic control adjustment, which are specifically as follows:

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

[0035] The first control strategy A: When Veh n When a data packet is received, it immediately replaces the corresponding previous data packet; the number of data 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 comprehensive evaluation index of the detected communication environment 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 detection based on vehicle sensors 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 divided into the following situations:

[0039] (1) When ① 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 ②Target vehicle Veh n and 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, namely, ① target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the preceding car Veh m of Less than or equal to E * And the target vehicle Veh n and 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, namely, ① 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 intelligent connected vehicles in a non-steady-state communication environment described in the present invention, in the first control strategy A, the dynamic adjustment of Veh 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 considering 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. This method uses real-time analysis of the stability of the communication environment and incorporates a certain level of monitoring data redundancy to ensure the reliability of the results, providing a basis for adjusting vehicle dynamic control. Based on collected communication link data and vehicle status data, this method dynamically assesses vehicle safety risks in non-steady-state communication environments, providing a reference for control decisions. Finally, the method designs three dynamic control strategies that adaptively adjust vehicle control modes to ensure stable operation and safety of the fleet, particularly in complex non-steady-state communication environments, while maintaining high traffic efficiency and vehicle stability.

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

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

[0053] Figure 2 Schematic diagram of the fleet arrangement and communication topology in the implementation example of the present invention; wherein, (a) is a dual-front vehicle communication topology, (b) is a leader-dual-front vehicle communication topology, and (c) is a multi-vehicle front communication topology. 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 based on typical embodiments only, and the present invention is not limited to the scope of the embodiments described. Combinations of different embodiments, replacement of certain technical features in different embodiments, and replacement of certain technical features in the embodiments with the same or similar prior art methods are also within the scope of the present invention.

[0056] This embodiment provides a dynamic control method for intelligent connected vehicles in a non-steady-state communication environment. Figure 1 As shown in the figure, facing a potential non-steady-state communication environment, based on the communication link data and vehicle status data of each vehicle in the intelligent connected fleet, at a preset time interval Δt, each vehicle in the intelligent connected 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 For 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 network vehicle fleet, and the time interval Δt is 100ms; the communication link data includes Veh n and Veh m Communication link 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 connected vehicle fleet is 6 vehicles, and the value of T1 is 5s;

[0058] Figure 2 The three fleet arrangement and communication topologies presented in the text 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 the figure is a multi-vehicle front communication topology. For further explanation, in this embodiment, a fleet of 6 intelligent connected vehicles will be selected and the following Figure 2The multi-vehicle communication topology shown in (c) in the figure. Considering 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, the control strategy of intelligent connected vehicles is dynamically changed to better ensure the stable operation and safety of the fleet. Therefore, the communication link data and vehicle status data of each vehicle under 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 at the same time (50s-51s); ③ severe non-steady-state communication environment and vehicle safety risk occur at the same time (110s-111s). At the same time, select Figure 2 Veh5 in the example is the research object of this embodiment. Therefore, the data presented in this embodiment are the communication link data and vehicle status data obtained by Veh5. The communication link data of Veh5 are shown in Tables 1, 2, and 3.

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

[0060]

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

[0062]

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

[0064]

[0065]

[0066] Step 2. Obtain vehicle status data: collect Veh in real time at a certain time interval Δt n Vehicle status data is collected and communicated with Veh in real time through vehicle network 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 Its immediate front car Veh n-1 The distance between Said 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; the speed, acceleration, and longitudinal position data of each vehicle in the intelligent connected fleet received by Veh5 are shown in Tables 4, 5, and 6. The null values ​​in the tables indicate data packet loss. The status data of the vehicle immediately preceding Veh4 obtained by Veh5 through the onboard lidar 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 connected fleet received by Veh5 (unit: ms) 2 )

[0070]

[0071] Table 6 Longitudinal position data of each vehicle in the intelligent connected 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 index of the communication environment. When Veh n With any preceding vehicle Veh m of When , it is determined to be a non-steady communication environment; otherwise, it is determined to be a steady communication environment; where E * Comprehensive evaluation index for communication environment The threshold value of * The value of is 5;

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

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

[0078]

[0079]

[0080]

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

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

[0083]

[0084] Among them, ω1 is The weight coefficient, ω2 is The weight coefficient, ω3 is 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 The results are shown in Table 8.

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

[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 Modified time to collision (MTTC) n (t n )>MTTC * When it is determined to be Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, determine Veh n Not at risk of security and n Safe switching variables at all times Recorded as 0; and statistical 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 statistical safety risk count; preferably, MTTC * The value is 1.5s, The value of is 5s; the security risk assessment results of Veh5 are shown in Table 9;

[0089] Said 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] described 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 modified 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 based on the obtained non-steady-state communication environment monitoring and vehicle safety risk assessment results. The specific vehicle dynamic control adjustments for Veh5 are 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] The first control strategy A: When Veh n When a data packet is received, it immediately replaces the corresponding previous data packet; the number of data 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 comprehensive evaluation index of the detected communication environment 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 detection based on vehicle sensors 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 divided into the following situations:

[0115] (1) When ① 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 ②Target vehicle Veh n and 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 value 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, namely, ① target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the preceding car Veh m of Less than or equal to E * And the target vehicle Veh n and 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, namely, ① 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 adjustments for Veh5

[0119]

[0120]

[0121] The description and application of the present invention here are illustrative and are not intended to limit the scope of the present invention to the above-mentioned embodiments. The relevant descriptions of 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 relevant descriptions of the effects or advantages are not used to limit the scope of the invention. Variations and changes to the embodiments disclosed here are possible, and the replacement of the embodiments and various equivalent components are well known to those of ordinary skill in the art. It should be clear to those skilled in the art that, without departing from the spirit or essential characteristics of the present invention, the present invention can be implemented in other forms, structures, arrangements, proportions, and with other components, materials and parts. Without departing from the scope and spirit of the present invention, other variations and changes can be made to the embodiments disclosed here.

Claims

1. A dynamic control method for intelligent connected vehicles in a non-steady-state communication environment, characterized in that: In a potentially non-steady-state communication environment, based on the communication link data and vehicle status data of each vehicle in the intelligent connected fleet, each vehicle in the intelligent connected 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 For 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 connected vehicle fleet; Obtain vehicle status data: collect Veh in real time at a certain time interval Δt n Vehicle status data is collected and communicated with Veh in real time through vehicle network 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 index of the communication environment. When Veh n With any preceding vehicle Veh m of When , it is determined to be a non-steady communication environment; otherwise, it is determined to be a steady communication environment; where E * Comprehensive evaluation index for communication environment threshold value; Assessing vehicle safety risk: Using the modified time to collision (MTTC) as a vehicle safety risk assessment indicator, when the vehicle status data is collected at time t n Veh n Corrected collision time MTTC n (t n )>MTTC * When Veh n In security risk; otherwise, determine Veh n Not in a security risk; and calculate the distance t n Moment Veh in the timeframe 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; Constructing comprehensive evaluation indicators for communication environment The details are as follows: (1) The normalization process of each communication indicator, the specific calculation formula is as follows: in, Communication transmission delay The normalized result of τ * is the communication transmission delay threshold, is the bit error rate within T1 The normalized processing result, BER * is the bit error rate threshold within T1 time, is the packet loss rate within T1 The normalized processing result, PLR * The packet loss rate threshold within T1 time; (2) Assign weights to each normalized indicator to construct a comprehensive evaluation index of the communication environment The specific formula is as follows: Among them, ω1 is The weight coefficient, ω2 is The weight coefficient, ω3 is The weight coefficient of .

2. The method for dynamic control of intelligent connected vehicles 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 Communication link 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: Said 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 Its immediate front car Veh n-1 The distance between Said 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 4, characterized in that: Said 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.

6. 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 Modified time to collision (MTTC) n (t n )>MTTC * When Veh n At risk of security and n Safe switching variables at all times Recorded as 1; otherwise, determine Veh n Not in a security risk and will n Safe switching variables at all times Recorded as 0.

7. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 1, characterized in that: described 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.

8. The method for dynamic control of intelligent connected vehicles 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: The first control strategy A: When Veh n When a data packet is received, it immediately replaces the corresponding previous data packet; the number of data 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 comprehensive evaluation index of the detected communication environment 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 detection based on vehicle sensors 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 divided into the following situations: (1) When ① 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 ②Target vehicle Veh n and 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, namely, ① target vehicle Veh n Number of security risks Greater than ②When there is a target vehicle Veh n and the preceding car Veh m of Less than or equal to E * And the target vehicle Veh n and 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, namely, ① 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.

9. The method for dynamic control of intelligent connected vehicles in a non-steady-state communication environment according to claim 8, 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 considering 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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