Intelligent traffic flow line optimization driving behavior adjustment method and system

Abstract

The invention is suitable for the technical field of intelligent driving regulation, and provides an intelligent traffic flow line optimized driving behavior regulation method and system, and the method comprises the steps: continuously collecting the behavior characteristic data of the following distance, lane changing frequency, accelerator stability and the like of a driver, and generating aggressive or prudent driving style DNA tags; in combination with vehicle navigation destinations and routes, a temporary motorcade containing one aggressive leader vehicle and two cautious following vehicles is established in the vehicles sharing the main road path; sending a team establishment application through the Internet of Vehicles, establishing a temporary collaborative team after confirmation of all the members, and planning an exclusive collaborative route; the leader vehicle broadcasts control instructions such as lane changing and speed changing, a vehicle team is regarded as a whole to calculate a cooperative safety space, instruction transmission intervals are dynamically set, and a unified driving strategy is generated. According to the invention, vehicle complementation and cooperation are realized, the traffic flow line is optimized, the driving behavior is adjusted, and the traffic efficiency and safety are improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the technical field of intelligent driving regulation, and particularly relates to an intelligent traffic flow line optimization driving behavior regulation method and system. BACKGROUND

[0002] With the rapid development of intelligent traffic technology, Internet of Vehicles, big data analysis and driving behavior recognition technology have been gradually applied to the field of traffic management, aiming to solve the problems of urban traffic congestion, low traffic efficiency and frequent traffic accidents. At present, the traffic system is transforming from "individual vehicle independent driving" to "multi-vehicle cooperative driving", and collecting vehicle driving data and analyzing the driving habits of drivers to provide data support for traffic flow optimization has become a development trend in the industry. However, the driving styles of different drivers are significantly different, and such differences are easy to cause operation conflicts between vehicles, and then cause traffic flow disorder, affecting the overall traffic efficiency. How to realize the complementation of driving styles through technical means has become a key research direction of intelligent traffic flow line optimization.

[0003] The existing technology has insufficient granularity in classifying driving styles, and it is difficult to accurately distinguish the operation preferences of different drivers, which leads to the inability to provide targeted behavior regulation guidance for drivers according to driving characteristics, and easy to appear the situation that the operation rhythm of the driver is not consistent with the overall traffic flow; in the multi-vehicle driving scene, there is a lack of coordination and control of driving behaviors between vehicles, and independent decision-making of each vehicle is easy to cause operation conflicts, such as frequent lane changing of some vehicles and slow following of some vehicles, which further disrupts the order of traffic flow and affects the overall traffic efficiency; route planning is mostly focused on the shortest distance or shortest time requirements of a single vehicle, and does not combine the traffic preferences of vehicles with different driving characteristics, making it difficult to balance the driving needs of various vehicles and easy to cause congestion of vehicle flow in local sections. SUMMARY

[0004] The purpose of the present application is to provide an intelligent traffic flow line optimization driving behavior regulation method, which aims to solve the technical problems existing in the prior art identified in the background.

[0005] The present application is implemented as follows: an intelligent traffic flow line optimization driving behavior regulation method, the method comprising: continuously collecting behavior characteristic data of the driver, including following distance, lane changing frequency and throttle smoothness, and generating a driving style DNA tag for each driver based on the behavior characteristic data, the driving style DNA tag being used to represent the driving style type of the driver, including aggressive type and cautious type; According to the driving style DNA tag, in combination with the navigation destination and navigation route of the vehicle that has set navigation, a temporary vehicle team is dynamically initiated among vehicles sharing the same trunk path, the temporary vehicle team including a vehicle of aggressive driving style as a leading vehicle and two vehicles of cautious driving style as following vehicles; A temporary team building application is sent to the drivers of the leading vehicle and the following vehicles through the Internet of Vehicles, and after all confirmations are obtained, a temporary cooperative team is established, and an exclusive cooperative route is planned for the temporary cooperative team; The leading vehicle broadcasts real-time operation instructions to the following vehicles through the Internet of Vehicles, the operation instructions including lane changing instructions, speed change instructions and brake instructions, while regarding the leading vehicle and the following vehicles as a whole virtual buffer area, the temporary cooperative team calculates a cooperative safety space, sets a transmission interval of the operation instructions based on the cooperative safety space, and generates a unified driving strategy.

[0006] As a further scheme of the present application, the driving style DNA tag of each driver is generated based on the behavior characteristic data, specifically including: For each vehicle, follow-up distance data, vehicle lane changing frequency data and throttle smoothness data are continuously collected; The collected follow-up distance data, lane changing frequency data and throttle smoothness data are preprocessed, including data cleaning, outlier filtering and data standardization, to obtain a standardized behavior characteristic data set; Based on the standardized behavior characteristic data set, a pre-trained driving style classification model is input, the driving style classification model being obtained based on historical behavior characteristic data, and outputting a driving style DNA tag for the current vehicle, the driving style DNA tag including an aggressive tag and a cautious tag.

[0007] As a further scheme of the present application, the temporary vehicle team is dynamically initiated, specifically including: Current navigation data of each vehicle is shared in the cloud, including navigation data collected from a vehicle machine and navigation data collected from a mobile terminal; navigation destination and navigation route data of the vehicle that has set navigation are obtained, and a candidate vehicle set is established in combination with the driving style DNA tag; For the candidate vehicle set, path overlap degrees among each vehicle in the candidate vehicle set are calculated, and vehicles sharing the same trunk path are selected from the candidate vehicle set; According to the driving style DNA tag, the vehicles sharing the same trunk path are grouped and matched, a vehicle of aggressive driving style is dynamically selected as a leading vehicle candidate, and two vehicles of cautious driving style are selected as following vehicle candidates, to form a temporary vehicle team building scheme.

[0008] As a further scheme of the present application, the temporary cooperative vehicle team is established and the exclusive cooperative route is planned for the temporary cooperative vehicle team, specifically comprising: The temporary vehicle team formation application is sent to the vehicle-mounted terminals of the lead vehicle candidate and the following vehicle candidate through the Internet of Vehicles communication, and the temporary vehicle team formation application information is displayed on the vehicle-mounted terminals of the lead vehicle candidate and the following vehicle candidate, including the vehicle team member role assignment and the expected driving route; The confirmation responses of the lead vehicle candidate and the following vehicle candidate are received and verified, and when all the confirmation responses are agreed, the temporary cooperative vehicle team is established; When there is any confirmation response that is not agreed, the corresponding vehicle that meets the driving style DNA label is supplemented from the candidate vehicle set as a new candidate based on the number of confirmation responses that are not agreed, the temporary vehicle team formation application is re-sent, and the verification process is repeated until all the confirmation responses are agreed, and the temporary cooperative vehicle team is established; Based on the shared main road path and real-time road condition information, an exclusive cooperative route is planned for the temporary cooperative vehicle team, and the exclusive cooperative route considers the overall traffic efficiency of the temporary cooperative vehicle team.

[0009] As a further scheme of the present application, the transmission interval of the operation instruction based on the cooperative safety space is set, and a unified driving strategy is generated, specifically comprising: Based on the real-time position and motion state of the lead vehicle and the following vehicle, the cooperative safety space of the virtual buffer area considering the three vehicles as a whole is calculated; Based on the cooperative safety space and the exclusive cooperative route, a unified driving strategy is generated, which is simultaneously issued to the lead vehicle and the following vehicle; The operation instruction data of the lead vehicle is collected in real time, the operation instruction data includes lane changing instruction, speed change instruction and brake instruction, and the transmission interval of the operation instruction in the Internet of Vehicles is set according to the size and dynamic change of the cooperative safety space.

[0010] As a further scheme of the present application, the unified driving strategy is generated, specifically: Based on the size and shape of the cooperative safety space, the available traffic area range of the vehicle team as a whole is determined, and the potential traffic conflict points in the traffic area range are identified; Combined with the path planning of the exclusive cooperative route and the real-time road condition information, the geometric characteristics and traffic flow state of the front road are analyzed, and the optimal traffic opportunity and traffic path are identified; According to the dynamic change of the cooperative safety space and the navigation requirements of the exclusive cooperative route, a coordinated operation scheme containing unified lane changing instruction, unified speed adjustment instruction and unified following distance control is formulated.

[0011] Another object of the present application is to provide an intelligent traffic flow line optimization driving behavior adjustment system, which comprises: behavior characteristic data collection module, configured to continuously collect behavior characteristic data of the drivers, including a following distance, a lane changing frequency and an accelerator smoothness, and generate a driving style DNA label of each driver based on the behavior characteristic data, the driving style DNA label being used to represent a driving style type of the driver, including an aggressive type and a cautious type; temporary vehicle team forming module, configured to dynamically initiate forming a temporary vehicle team in vehicles sharing a same trunk path according to the driving style DNA label and in combination with a navigation destination and a navigation route of the vehicle having set the navigation, the temporary vehicle team including one vehicle of the aggressive type as a leading vehicle and two vehicles of the cautious type as following vehicles; vehicle team application sending module, configured to send a temporary vehicle team forming application to drivers of the leading vehicle and the following vehicles through the Internet of Vehicles, and establish a temporary cooperative vehicle team after obtaining all confirmations, and plan an exclusive cooperative route for the temporary cooperative vehicle team; real-time operation instruction broadcasting module, configured to broadcast real-time operation instructions to the following vehicles by the leading vehicle through the Internet of Vehicles, the operation instructions including a lane changing instruction, a speed changing instruction and a brake instruction, and the leading vehicle and the following vehicles are regarded as a virtual buffer area as a whole, the temporary cooperative vehicle team calculates a cooperative safety space, sets a transmission interval of the operation instructions based on the cooperative safety space, and generates a unified driving strategy.

[0012] As a further scheme of the present application, the temporary vehicle team forming module includes: candidate vehicle set establishing unit, configured to share current navigation data of each vehicle in the cloud, including navigation data collected from a vehicle machine and navigation data collected from a mobile terminal, obtain navigation destination and navigation route data of the vehicle having set the navigation, and establish a candidate vehicle set in combination with the driving style DNA label; path overlap degree calculation unit, configured to calculate a path overlap degree between each vehicle in the candidate vehicle set for the candidate vehicle set, and screen vehicles sharing a same trunk path from the candidate vehicle set; forming scheme generation unit, configured to group and match the screened vehicles sharing the same trunk path according to the driving style DNA label, dynamically select one vehicle of the aggressive type as a leading vehicle candidate and select two vehicles of the cautious type as following vehicle candidates, and form a temporary vehicle team forming scheme.

[0013] As a further scheme of the present application, the vehicle team application sending module includes: The application further comprises a temporary team formation application sending unit, which is configured to send a temporary team formation application to the candidate leading vehicle and the candidate following vehicle through V2V communication, and display the temporary team formation application information on the candidate leading vehicle and the candidate following vehicle, including team member role allocation and expected driving route. The application further comprises a response receiving and verifying unit, which is configured to receive and verify the confirmation responses of the candidate leading vehicle and the candidate following vehicle, and establish a temporary cooperative team when all the confirmation responses are in agreement. The application further comprises a candidate vehicle supplement unit, which is configured to supplement a vehicle with a driving style DNA label from the candidate vehicle set as a new candidate when there is any confirmation response in disagreement, resend the temporary team formation application, and repeat the verification process until all the confirmation responses are in agreement, so as to establish a temporary cooperative team. The application further comprises a cooperative route planning unit, which is configured to plan a dedicated cooperative route for the temporary cooperative team based on the shared trunk path and real-time traffic information, and the dedicated cooperative route takes into account the overall traffic efficiency of the temporary cooperative team.

[0014] As a further scheme of the application, the real-time operation instruction broadcasting module comprises: The application further comprises a safety space calculation unit, which is configured to calculate a cooperative safety space of a virtual buffer area of the three vehicles as a whole based on the real-time positions and motion states of the leading vehicle and the following vehicle. The application further comprises a driving strategy generation unit, which is configured to generate a unified driving strategy based on the cooperative safety space and the dedicated cooperative route, and the unified driving strategy is simultaneously issued to the leading vehicle and the following vehicle. The application further comprises a transmission interval setting unit, which is configured to collect operation instruction data of the leading vehicle in real time, the operation instruction data comprises lane changing instruction, speed change instruction and brake instruction, and set a transmission interval of the operation instruction in V2V communication according to the size and dynamic change of the cooperative safety space.

[0015] The application has the following advantages: The application realizes intelligent traffic flow line optimization and driving behavior adjustment from micro-vehicle cooperation to macro-traffic flow optimization, and significantly improves traffic efficiency and safety. By continuously collecting behavior data such as following distance, lane changing frequency and throttle smoothness, and analyzing the data through a preprocessing and classification model to generate a precise driving style DNA label, the application provides a scientific basis for the complementary formation of a temporary team, and avoids traffic disorder caused by driving style conflicts. The dynamically formed temporary team can take advantage of the sharp judgment and rapid decision-making of aggressive drivers to explore roads and find efficient traffic paths, and rely on the stable following operation and smooth operation habits of cautious drivers to smooth the traffic ripple effect caused by aggressive operation of the leading vehicle, and reduce congestion causes. The team building application containing role assignment and expected route is sent to the driver through the Internet of Vehicles, full voluntary participation is guaranteed to improve the cooperation degree, the candidate vehicle replacement mechanism is cooperated, the team building failure caused by individual vehicle refusal is effectively avoided, and the continuous coverage of the cooperative vehicle team on the main road section during the peak period is ensured; A dedicated cooperative route is planned for the vehicle team, the path section suitable for the whole team driving is preferentially selected in combination with the real-time road condition, invalid lane changing and congestion section occupation are reduced, and the traffic efficiency is further improved; in addition, the lead vehicle and the following vehicle are regarded as a whole to build a virtual buffer area and a cooperative safety space, the interference of external vehicles is reduced, the formation is maintained, the control instruction transmission interval is dynamically adjusted based on the safety space, the driving safety and efficiency are balanced, and the problems caused by instruction delay or over-density are avoided; The lead vehicle broadcasts the control instruction and generates a unified driving strategy, the operation of the vehicle team is synchronized, the aggressive driver is indirectly guided to make standard decisions, the cautious driver improves driving confidence, the behaviors of drivers with different styles are made the most of and shortcomings are avoided, traffic congestion is effectively relieved, traffic accident risk is reduced, and the efficient operation of the intelligent traffic system is promoted. BRIEF DESCRIPTION OF DRAWINGS

[0016] Figure 1 A flowchart of an intelligent traffic flow line optimization driving behavior adjustment method provided by the embodiment of the present application is provided; Figure 2 A flowchart of generating the driving style DNA tag of each driver provided by the embodiment of the present application is provided; Figure 3 A flowchart of dynamically initiating the establishment of a temporary vehicle team provided by the embodiment of the present application is provided; Figure 4 A flowchart of establishing a temporary cooperative vehicle team and planning a dedicated cooperative route for the temporary cooperative vehicle team provided by the embodiment of the present application is provided; Figure 5 A flowchart of generating a unified driving strategy provided by the embodiment of the present application is provided; Figure 6 A structural block diagram of an intelligent traffic flow line optimization driving behavior adjustment system provided by the embodiment of the present application is provided; Figure 7 A structural block diagram of a temporary vehicle team establishment module provided by the embodiment of the present application is provided; Figure 8 A structural block diagram of a vehicle team application sending module provided by the embodiment of the present application is provided; Figure 9 A structural block diagram of a real-time control instruction broadcasting module provided by the embodiment of the present application is provided. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical scheme and advantages of the present application clearer, the present application will be further described in detail below in combination with the drawings and examples. It should be understood that the specific examples described herein are only used to explain the present application and not to limit the present application.

[0018] Figure 1 A flow chart of an intelligent traffic flow line optimization driving behavior adjustment method provided by an embodiment of the present application is shown in Figure 1 The method comprises the following steps: S100, continuously collecting behavior characteristic data of a driver, including a following distance, a lane changing frequency and an accelerator smoothness, and generating a driving style DNA tag of each driver based on the behavior characteristic data, the driving style DNA tag being used to represent a driving style type of the driver, including an aggressive type and a cautious type; In a whole driving cycle of a vehicle, core behavior characteristic data reflecting an operation habit of a driver is obtained in real time by relying on hardware devices such as a vehicle-mounted millimeter wave radar, a front camera and a vehicle body CAN bus. The following distance data not only records an absolute distance value, but also captures a dynamic change trend of the following distance of the vehicle in combination with a driving state of a preceding vehicle. Only a lane changing operation actively initiated by the driver is counted, and vehicle speed, a steering angle and other auxiliary data at the time of lane changing are associated to distinguish smooth lane changing from abrupt lane changing. The accelerator smoothness data is obtained by collecting a change rate, a duration and a feedback engine power output curve of an accelerator pedal opening degree through the CAN bus. For example, a frequency ratio of a rapid accelerator pedal (a pedal opening degree jumps from 30% to 90% in less than 1.5 seconds) and a slow accelerator pedal (a same opening degree change takes more than 4 seconds) is used to accurately depict an aggressive degree of the driver to the vehicle power control.

[0019] The standardized behavior characteristic data set is input into a pre-trained driving style classification model. The model is iteratively optimized based on a large amount of historical behavior data in combination with traffic risk coefficients corresponding to different driving styles (for example, a scraping risk of aggressive driving on a congested road section and a passing efficiency of cautious driving on a high-speed road section). Finally, a precise driving style DNA tag is output.

[0020] S200, according to the driving style DNA tag and in combination with a navigation destination and a navigation route of a vehicle that has set the navigation, a temporary vehicle platoon is dynamically initiated and formed among vehicles sharing a same trunk path, the temporary vehicle platoon including one vehicle with an aggressive driving style as a leading vehicle and two vehicles with a cautious driving style as following vehicles; The integration and sharing of multi-source navigation data are realized by relying on a cloud platform. Not only navigation data of a vehicle-mounted terminal are collected, but also data of a navigation application of a driver mobile terminal are synchronously accessed. Route misjudgment caused by inconsistency between the vehicle-mounted terminal and the mobile terminal navigation is eliminated. It is ensured that navigation information of each vehicle obtained can truly reflect an actual driving intention thereof.

[0021] On this basis, combined with the generated driving style DNA label, a candidate set covering all set navigation vehicles is established, the key of this step is to narrow the range for subsequent screening, to avoid invalid calculation on vehicles without navigation targets and random driving routes, so as to improve the team efficiency.

[0022] The path overlap calculation is carried out for the vehicles in the candidate set, and the intelligent traffic flow line optimization focuses on relieving the congestion of the main road section, because the main road is the aorta of the urban traffic network, and its traffic efficiency directly determines the overall traffic condition. If the vehicles with no main road overlap in the driving route are grouped, the team will quickly disintegrate because of the diversion in the middle, and cannot realize continuous cooperation. Therefore, the length of the main road section overlapped by each vehicle in the navigation route and the proportion of the driving time of the overlapped section are analyzed, and the vehicles sharing the same main road path are screened out.

[0023] Each vehicle is grouped and matched to determine a team structure of 1 aggressive lead vehicle + 2 cautious following vehicles. By using the complementarity of driving style, the traffic efficiency and driving stability are balanced: aggressive drivers are usually more sensitive to road gaps and more decisive in lane changing decisions, so they can serve as lead vehicles to actively explore efficient traffic paths on main roads and avoid the dilemma of following cars at a slow speed. Cautious drivers are better at maintaining stable distances and smooth vehicle control, so they can effectively buffer the traffic ripple effects caused by aggressive operations of lead vehicles to ensure smooth overall driving trajectories of the team.

[0024] S300, through the Internet of Vehicles, sends a temporary team formation application to the drivers of the lead vehicle and the following vehicle, and after obtaining all confirmations, establishes a temporary cooperative team and plans a dedicated cooperative route for the temporary cooperative team; Through the Internet of Vehicles, complete information including team member role allocation (clearly indicating which vehicle is the lead vehicle and which two vehicles are the following vehicles) and expected driving route (annotating the specific direction of the shared main road section and key nodes such as interchanges or exit locations) is synchronously pushed to the vehicle terminal of the lead vehicle candidate and the following vehicle candidate. The driver can clearly know whether the operation responsibility and driving path after joining the team are consistent with their own navigation needs, to avoid misjudgment or resistance caused by ambiguous information. After all, only when the driver recognizes the role and route will he actively cooperate in the subsequent cooperative process, reducing the operation disconnection caused by passive participation.

[0025] In response to receiving and verifying the link, the real-time collection of each candidate vehicle confirmation response, and all agree to establish a temporary cooperative team as the only standard, if there is any vehicle refused, forced to form may lead to the vehicle in the subsequent driving may not cooperate operation, but become a hidden danger of interference traffic flow. Therefore, when there is a response to disagree, the system will immediately start the candidate vehicle replacement mechanism: according to the number of vehicles that disagree, from the candidate vehicle set established in the early stage, filter the vehicles that completely match the DNA tag of the rejected vehicle driving style and meet the path overlap degree as new candidates, resend the formation application containing complete information, until all candidate vehicles confirm to agree, avoid the path overlap analysis and style matching work in the early stage due to the refusal of individual vehicles, ensure that there is enough temporary cooperative team on the main road section with dense traffic flow to form successfully, maintain the continuity of cooperative driving, avoid the local disorder of traffic flow caused by team fault.

[0026] With the core goal of optimizing the overall traffic efficiency of the team, on the basis of sharing the main road path, combined with real-time traffic information for fine path customization. The exclusive cooperative route pays more attention to the overall driving of the team. In the case of dense left lane traffic and flat middle lane traffic on the main road, the system will plan the driving path mainly in the middle lane to avoid conflicts between the team and other social vehicles caused by frequent lane changes; if there is an interchange in front, the system will mark "the team needs to start merging to the rightmost lane after x kilometers" in the route to reserve sufficient merging time for the team, avoiding temporary emergency braking or continuous lane changes.

[0027] S400, the lead vehicle broadcasts real-time control instructions to the follower vehicles through the Internet of Vehicles, including lane change instructions, speed change instructions, and brake instructions, while considering the lead vehicle and follower vehicles as a whole virtual buffer area, the temporary cooperative team calculates the cooperative safety space, sets the transmission interval of the control instructions based on the cooperative safety space, and generates a unified driving strategy.

[0028] The real-time instruction output is mainly led by the lead vehicle. Such drivers are more sensitive to changes in road environment and respond more quickly to decisions. The lane change, speed change, and brake instructions generated by them can ensure the timeliness of the team's response to road conditions and avoid missing the optimal traffic opportunity due to delayed decisions. At the same time, the instructions are broadcast in real time to the two follower vehicles through the Internet of Vehicles, with the lead vehicle's decision basis, allowing the follower vehicle drivers to understand the road condition logic behind the instructions and reducing the hesitation caused by information asymmetry. This transmission method can significantly improve the synchronization of follower vehicle operations and avoid the disconnection of the team caused by delayed lane changes by follower vehicles after the lead vehicle changes lanes.

[0029] In a complex traffic environment, a single vehicle is easily inserted by other social vehicles, causing the original orderly following relationship to be broken. The setting of the virtual buffer area is essentially to define three vehicles as an indivisible driving unit at the system level. Based on the real-time positions, vehicle body sizes and trajectories of the three vehicles, the system marks a virtual boundary covering the three vehicles on the electronic map. This boundary is not only used for position reference of the internal team members, but also indirectly synchronized to the vehicle terminal of the surrounding social vehicles through the Internet of Vehicles, reducing the interference of external vehicles on the team from a spatial level. Once the team is inserted by external vehicles, the subsequent unified driving strategy cannot be executed, and the coordination effect will be instantly lost. The virtual buffer area can effectively reduce the probability of insertion and ensure that the team always participates in the traffic flow in the form of a whole.

[0030] Based on the real-time positions and motion states of the lead vehicle and the following vehicles, the coordinated safety space is dynamically calculated, which not only includes the safety distance within the team, but also includes the safety margin of the team and external vehicles. When the coordinated safety space is dynamically adjusted due to road condition changes, the system will simultaneously optimize the transmission interval of the control instructions: if the safety space is sufficient, the transmission interval can be appropriately extended to avoid excessive instructions interfering with the driver's operation; if the safety space is reduced, the transmission interval will be shortened to ensure that the emergency instructions of the lead vehicle can be quickly received and executed by the following vehicles, preventing rear-end accidents. This not only avoids safety risks caused by instruction delays, but also prevents driving fatigue caused by excessive instructions, allowing the team to maintain a stable driving state under different road conditions.

[0031] Based on the size and shape of the coordinated safety space, the range of the whole team's passable area is determined, and potential traffic conflict points within the range are identified. Then, combined with the path direction of the exclusive coordinated route and the real-time road conditions, the optimal passing time and path are analyzed. Finally, a coordinated operation scheme including unified lane changing instructions, unified speed adjustment instructions, and unified following distance control is developed and simultaneously issued to the lead vehicle and the following vehicles.

[0032] As shown in Figure 2 The generating, based on the behavior feature data, of the driving style DNA label of each driver specifically includes: S110, for each vehicle, continuously collecting following distance data, vehicle lane changing frequency data, and throttle smoothness data; S120, preprocessing the collected following distance data, lane changing frequency data, and throttle smoothness data, including data cleaning, outlier filtering, and data standardization, to obtain a standardized behavior feature data set; S130, input a pre-trained driving style classification model based on the standardized behavior feature dataset, the driving style classification model is obtained based on historical behavior feature data, and output a driving style DNA label for the current vehicle, the driving style DNA label includes an aggressive label and a cautious label.

[0033] Specifically: The following three core feature dimensions in the dataset are input into the K-Means clustering model: following distance, lane changing frequency, and accelerator smoothness. The rule engine interprets the center point features of each cluster: When the standardized following distance data of the vehicle is less than the 30th percentile of the historical data distribution, the standardized lane changing frequency data is greater than the 70th percentile of the historical data distribution, and the standardized accelerator smoothness data is greater than the 70th percentile of the historical data distribution, output the aggressive label; When the standardized following distance data of the vehicle is greater than the 70th percentile of the historical data distribution, the standardized lane changing frequency data is less than the 30th percentile of the historical data distribution, and the standardized accelerator smoothness data is less than the 30th percentile of the historical data distribution, output the cautious label; Other cases are classified into aggressive or cautious labels according to the nearest neighbor principle; Finally, the system outputs the corresponding "aggressive" or "cautious" driving style DNA label according to the cluster to which the behavior data of the current driver belongs.

[0034] As shown in Figure 3 The dynamic initiation group forms a temporary vehicle team, specifically including: S210, share the current navigation data of each vehicle in the cloud, including navigation data collected from the car machine and navigation data collected from the mobile terminal; obtain the navigation destination and navigation route data of the vehicle that has set the navigation, and establish a candidate vehicle set in combination with the driving style DNA label; S220, for the candidate vehicle set, calculate the path overlap degree between each vehicle in the candidate vehicle set, and select vehicles that share the same trunk path from the candidate vehicle set; S230, group and match the selected vehicles that share the same trunk path according to the driving style DNA label, dynamically select an aggressive driving style vehicle as a lead vehicle candidate, and select two cautious driving style vehicles as following vehicles candidates, forming a temporary vehicle team formation scheme.

[0035] The aggressive driver is usually better at finding and using road gaps for lane changing and overtaking, and as the lead car, can fully exert its ability to explore the road and find a more efficient path for the entire team. At the same time, the two cautious vehicles as the following cars can form a stable team, effectively smoothing the ripple effect caused by the aggressive driving behavior of the lead car in the traffic flow, thereby improving the stability of the traffic flow at the micro level.

[0036] This configuration assigns the lead task, which requires frequent decision-making, to the driver who enjoys or is accustomed to this style, and allows the cautious driver, who prefers stability and avoids risks, to benefit from following without having to make independent complex path decisions and intense maneuvers, thereby significantly reducing their driving decision-making pressure and improving driving comfort and safety.

[0037] As shown in Figure 4 The temporary cooperative team is established and a dedicated cooperative route is planned for the temporary cooperative team, specifically including: S310, sending a temporary team formation application to the vehicle-mounted terminals of the lead car candidate and the following car candidate through vehicle networking communication, and displaying the temporary team formation application information on the vehicle-mounted terminals of the lead car candidate and the following car candidate, including team member role assignment and expected driving route; S320, receiving and verifying the confirmation responses of the lead car candidate and the following car candidate, and establishing a temporary cooperative team when all confirmation responses are in agreement; S330, when there is any confirmation response that is not in agreement, supplementing a vehicle that meets the driving style DNA label as a new candidate from the candidate vehicle set based on the number of confirmation responses that are not in agreement, re-sending the temporary team formation application and repeating the verification process until all agreements are obtained, and establishing a temporary cooperative team; S340, planning a dedicated cooperative route for the temporary cooperative team based on the shared trunk path and real-time traffic information, which considers the overall traffic efficiency of the temporary cooperative team.

[0038] The navigation destination of all members of the temporary cooperative team is constrained, and the shortest overall travel time and the smoothest travel of the team are the primary optimization targets. The specific process is: Based on real-time traffic information systems and road geometry data, the shared trunk path is refined. Preferably, a path segment that can provide continuous and smooth driving conditions for a micro team of three vehicles is selected, and specific cooperative lane changing opportunities and lanes may be dynamically reserved or recommended for such teams.

[0039] The role of the exclusive collaborative route is to convert three independent vehicles into a collaborative whole, and it is a route specially designed for this vehicle team to ensure that the team can run in a coordinated, efficient and smooth mode from start to finish, avoiding the disintegration of the team and the decline in efficiency caused by internal vehicle path conflicts or external traffic interference.

[0040] As shown in Figure 5 , the transmission interval of the operation instruction based on the collaborative safety space setting generates a unified driving strategy, which specifically includes: S410, based on the real-time position and motion state of the lead vehicle and the following vehicle, the collaborative safety space of the virtual buffer area considering the three vehicles as a whole is calculated; The collaborative safety space can be conceptualized as an elliptical area covering the three vehicles with the geometric center of the team as the center. Its range is dynamically determined by the following formula: ; Where: is the minimum longitudinal length of the collaborative safety space required by the temporary collaborative team as a whole, which directly defines the range of the passing area occupied by the team on the road.

[0041] is the team collaborative safety coefficient ( >1), considering that there may be a slight delay in collaborative braking for a temporary collaborative team consisting of one lead vehicle and two following vehicles, this coefficient is used to enlarge the safety margin.

[0042] is the real-time speed of the aggressive driving style vehicle of the lead vehicle.

[0043] is the real-time speed of the last cautious driving style vehicle in the following vehicle queue.

[0044] is the total reaction time of the temporary collaborative team, including the total time from the lead vehicle issuing operation instructions, transmission through the vehicle network, processing by the assisted driving system of the following vehicle, and finally execution.

[0045] is the preset maximum safety deceleration of the team, which is a negative acceleration value that guarantees ride comfort and safety.

[0046] is the static buffer length, which is the sum of the physical length of the lead vehicle and the two following vehicles and the minimum static safety gap required to maintain the formation.

[0047] S420, generate a unified driving strategy based on the cooperative safety space and the exclusive cooperative route, which is issued to both the lead vehicle and the following vehicle; S430, collect the operation instruction data of the lead vehicle in real time, which includes lane change instruction, speed change instruction and brake instruction, and set the transmission interval of the operation instruction in the Internet of Vehicles according to the size and dynamic change of the cooperative safety space.

[0048] In this step, the generation of the unified driving strategy is specifically: Based on the size and shape of the cooperative safety space, determine the range of the available traffic area for the whole vehicle group, and identify the potential traffic conflict points in the traffic area range; Combine the path planning of the exclusive cooperative route with the real-time traffic information to analyze the geometric characteristics and traffic flow state of the front road, and identify the optimal traffic opportunity and traffic path; The identification of the optimal traffic opportunity and traffic path is realized by a multi-factor weighted scoring model, which calculates a comprehensive score for each potential traffic option, and the highest score is the optimal choice.

[0049] ; Among them, The comprehensive suitability score of a certain path or opportunity is used to identify the optimal choice.

[0050] is the quality score of the distance between the front and rear vehicles in the target lane, which is calculated according to the distance and relative speed between the front and rear vehicles in the target lane. The farther the distance and the higher the speed matching degree, the higher the score.

[0051] is the real-time traffic density of the target path segment, which is provided by the roadside unit or the cloud traffic big data platform. The lower the density, the higher the score of this contribution.

[0052] is the degree of fit between the operation and the exclusive cooperative route. The operation that completely conforms to the predetermined route gets the highest score, and the deviation gets a low score.

[0053] is the urgency of the operation. The higher the urgency, the lower the score of this item. The system will tend to make early and gentle decisions.

[0054] is the weight coefficient, which is pre-set according to the optimization target during system design.

[0055] According to the dynamic change of the cooperative safety space and the navigation requirements of the exclusive cooperative route, develop a coordinated operation scheme including unified lane change instruction, unified speed adjustment instruction and unified following distance control.

[0056] Figure 6 The structural block diagram of an intelligent traffic flow line optimization driving behavior adjustment system provided for an embodiment of the present application is shown in Figure 6 The system comprises: A behavior characteristic data collection module 100 is configured to continuously collect behavior characteristic data of drivers, including following distance, lane changing frequency and throttle smoothness, and generate a driving style DNA tag for each driver based on the behavior characteristic data, the driving style DNA tag being used to represent a driving style type of the driver, including aggressive type and cautious type. A temporary vehicle team formation module 200 is configured to dynamically initiate formation of a temporary vehicle team in vehicles sharing a same trunk path according to the driving style DNA tag and in combination with a navigation destination and a navigation route of a vehicle having set navigation, the temporary vehicle team comprising one vehicle of aggressive driving style as a leading vehicle and two vehicles of cautious driving style as following vehicles. A team application sending module 300 is configured to send a temporary vehicle team formation application to drivers of the leading vehicle and the following vehicles through vehicle networking, and establish a temporary cooperative team after obtaining all confirmations, and plan an exclusive cooperative route for the temporary cooperative team. A real-time control instruction broadcasting module 400 is configured to broadcast real-time control instructions to the following vehicles by the leading vehicle through vehicle networking, the control instructions including lane changing instructions, speed change instructions and brake instructions, and simultaneously regarding the leading vehicle and the following vehicles as a whole virtual buffer area, the temporary cooperative team calculating a cooperative safety space, setting a transmission interval of the control instructions based on the cooperative safety space, and generating a unified driving strategy.

[0057] As shown in Figure 7 The temporary vehicle team formation module 200 comprises: A candidate vehicle set establishment unit 210 is configured to share current navigation data of each vehicle in the cloud, including navigation data collected from a vehicle machine and navigation data collected from a mobile terminal, obtain navigation destination and navigation route data of a vehicle having set navigation, and establish a candidate vehicle set in combination with the driving style DNA tag. A path overlap degree calculation unit 220 is configured to calculate path overlap degrees between each vehicle in the candidate vehicle set for the candidate vehicle set, and screen vehicles sharing a same trunk path from the candidate vehicle set. A formation scheme generation unit 230 is configured to group and match the screened vehicles sharing a same trunk path according to the driving style DNA tag, dynamically select one vehicle of aggressive driving style as a leading vehicle candidate and select two vehicles of cautious driving style as following vehicle candidates, and form a temporary vehicle team formation scheme.

[0058] As Figure 8 shown, the vehicle team application sending module 300 includes: The team application sending unit 310 is configured to send the temporary vehicle team formation application to the corresponding lead vehicle candidate and following vehicle candidate through the vehicle networking communication, and display the temporary vehicle team formation application information on the lead vehicle candidate and following vehicle candidate, including the vehicle team member role allocation and the expected driving route. The response receiving and verifying unit 320 is configured to receive and verify the confirmation responses of the lead vehicle candidate and following vehicle candidate, and establish the temporary cooperative vehicle team when all the confirmation responses are in agreement. The candidate vehicle supplement unit 330 is configured to supplement the vehicle with the same driving style DNA label as the new candidate from the candidate vehicle set based on the number of confirmation responses in disagreement when there is any confirmation response in disagreement, resend the temporary vehicle team formation application and repeat the verification process until all the confirmation responses are in agreement, and establish the temporary cooperative vehicle team. The cooperative route planning unit 340 is configured to plan the exclusive cooperative route for the temporary cooperative vehicle team based on the shared trunk path and real-time traffic information, and the exclusive cooperative route considers the overall traffic efficiency of the temporary cooperative vehicle team.

[0059] As Figure 9 shown, the real-time operation instruction broadcasting module 400 includes: The safety space calculation unit 410 is configured to calculate the cooperative safety space of the virtual buffer area considering the three vehicles as a whole based on the real-time position and motion state of the lead vehicle and following vehicle. The driving strategy generation unit 420 is configured to generate the unified driving strategy based on the cooperative safety space and the exclusive cooperative route, and the unified driving strategy is simultaneously issued to the lead vehicle and following vehicle. The transmission interval setting unit 430 is configured to collect the operation instruction data of the lead vehicle in real time, the operation instruction data includes the lane change instruction, the speed change instruction and the brake instruction, and set the transmission interval of the operation instruction in the vehicle networking according to the size and dynamic change of the cooperative safety space.

[0060] The technical features of the above-described embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above-described embodiments are described, however, as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present disclosure.

[0061] The above embodiments only express several implementation manners of the present application, which are described in a more specific and detailed manner, but should not be understood as a limitation on the patent scope of the present application. It should be noted that, for ordinary skilled persons in the art, several modifications and improvements can be made without departing from the concept of the present application, which are all within the protection scope of the present application. Therefore, the protection scope of the patent of the present application should be subject to the appended claims.

[0062] The above only describes the preferred embodiments of the present application and should not be used to limit the present application. Any modification, equivalent replacement and improvement made within the spirit and principle of the present application should be included in the protection scope of the present application.

Claims

1. A method for optimizing driving behavior in intelligent traffic flow, characterized in that, The method includes: The system continuously collects driver behavior data, including following distance, lane change frequency, and throttle smoothness, and generates a driving style DNA tag for each driver based on the behavior data. The driving style DNA tag is used to characterize the driver's driving style type, including aggressive and cautious. Based on the driving style DNA tag, and combined with the navigation destination and navigation route of the vehicle with the pre-set navigation, a temporary convoy is dynamically initiated among vehicles sharing the same main road route. The temporary convoy includes one vehicle with an aggressive driving style as the lead car and two vehicles with a cautious driving style as follow cars. The vehicle network sends a temporary fleet formation application to the drivers of the lead vehicle and the following vehicle, and after receiving full confirmation, establishes a temporary collaborative fleet and plans a dedicated collaborative route for the temporary collaborative fleet. The lead vehicle broadcasts real-time control commands to the following vehicles via the vehicle network. The control commands include lane change commands, speed change commands, and braking commands. At the same time, the lead vehicle and the following vehicles are regarded as a whole virtual buffer zone. The temporary cooperative vehicle fleet calculates the cooperative safety space, sets the transmission interval of control commands based on the cooperative safety space, and generates a unified driving strategy.

2. The method according to claim 1, characterized in that, The process of generating a driving style DNA tag for each driver based on the behavioral feature data specifically includes: For each vehicle, continuously collect data on following distance, lane change frequency, and throttle smoothness. The collected following distance data, lane change frequency data, and throttle smoothness data are preprocessed, including data cleaning, outlier filtering, and data standardization, to obtain a standardized behavioral feature dataset. Based on a standardized behavioral feature dataset, a pre-trained driving style classification model is input. The driving style classification model is obtained based on historical behavioral feature data and outputs a driving style DNA label for the current vehicle. The driving style DNA label includes an aggressive label and a cautious label.

3. The method according to claim 2, characterized in that, The dynamic initiation of the formation of temporary vehicle fleets specifically includes: Share the current navigation data of each vehicle in the cloud, including navigation data collected from the vehicle's infotainment system and navigation data collected from mobile devices; obtain the navigation destination and navigation route data of vehicles with set navigation, and combine them with the driving style DNA tags to build a candidate vehicle set; For a candidate vehicle set, calculate the path overlap between each vehicle in the candidate vehicle set, and filter out vehicles that share the same main road path from the candidate vehicle set; Based on driving style DNA tags, vehicles sharing the same main road route are grouped and matched. One vehicle with an aggressive driving style is dynamically selected as the lead vehicle candidate, and two vehicles with a cautious driving style are selected as the follower vehicle candidates, forming a temporary convoy formation plan.

4. The method according to claim 3, characterized in that, The establishment of a temporary collaborative vehicle fleet and the planning of dedicated collaborative routes for the temporary collaborative vehicle fleet specifically include: The application for forming a temporary convoy is sent to the in-vehicle terminals of the corresponding lead vehicle candidate and follow vehicle candidate via vehicle-to-everything (V2X) communication. The application information for forming a temporary convoy, including the role assignment of convoy members and the expected driving route, is displayed on the in-vehicle terminals of the lead vehicle candidate and follow vehicle candidate. Receive and verify the confirmation responses from the lead vehicle candidate and the following vehicle candidate. When all confirmation responses are in agreement, establish a temporary collaborative fleet. If any confirmation response is "disagree", a vehicle matching the driving style DNA tag is added from the candidate vehicle set based on the number of disagreeing confirmation responses. The temporary fleet formation application is resent and the verification process is repeated until all consents are obtained, and a temporary collaborative fleet is established. Based on shared main road routes and real-time traffic information, dedicated collaborative routes are planned for temporary collaborative vehicle fleets, taking into account the overall traffic efficiency of the temporary collaborative vehicle fleets.

5. The method according to claim 4, characterized in that, The method of setting the transmission interval of control commands based on the collaborative safety space to generate a unified driving strategy specifically includes: Based on the real-time position and motion status of the lead vehicle and the following vehicle, the collaborative safety space of the virtual buffer zone that treats the three vehicles as a whole is calculated. Based on the collaborative safety space and dedicated collaborative routes, a unified driving strategy is generated, which is simultaneously distributed to the lead vehicle and the following vehicle. The system collects control command data from the lead vehicle in real time. The control command data includes lane change commands, speed change commands, and braking commands. The transmission interval of the control commands in the vehicle network is set according to the size and dynamic changes of the cooperative safety space.

6. The method according to claim 5, characterized in that, The generation of a unified driving strategy specifically includes: Based on the size and shape of the collaborative safety space, the overall usable passage area of ​​the convoy is determined, and potential traffic conflict points within the passage area are identified. By combining route planning with real-time traffic information from dedicated collaborative routes, the geometric features and traffic flow status of the road ahead are analyzed to identify the optimal travel time and route. Based on the dynamic changes in the collaborative safety space and the navigation requirements of the dedicated collaborative route, a coordinated operation plan is formulated, which includes unified lane change instructions, unified speed adjustment instructions, and unified following distance control.

7. An intelligent traffic flow optimization driving behavior adjustment system, characterized in that, The system includes: The behavioral characteristic data acquisition module is used to continuously collect the driver's behavioral characteristic data, including following distance, lane change frequency and throttle smoothness, and generate a driving style DNA tag for each driver based on the behavioral characteristic data. The driving style DNA tag is used to characterize the driver's driving style type, including aggressive and cautious. The temporary convoy formation module is used to dynamically initiate the formation of a temporary convoy among vehicles sharing the same main road route, based on the driving style DNA tag and in combination with the navigation destination and navigation route of the vehicles with pre-set navigation. The temporary convoy includes one vehicle with an aggressive driving style as the lead vehicle and two vehicles with a cautious driving style as follow vehicles. The fleet application sending module is used to send temporary fleet formation applications to the drivers of the lead vehicle and the following vehicle via the vehicle network, and after receiving full confirmation, establish a temporary collaborative fleet and plan a dedicated collaborative route for the temporary collaborative fleet. The real-time control command broadcasting module is used by the lead vehicle to broadcast real-time control commands to the following vehicles via the vehicle network. The control commands include lane change commands, speed change commands, and braking commands. At the same time, the lead vehicle and the following vehicles are regarded as a whole virtual buffer zone. The temporary cooperative vehicle fleet calculates the cooperative safety space, sets the transmission interval of control commands based on the cooperative safety space, and generates a unified driving strategy.

8. The system according to claim 7, characterized in that, The temporary convoy assembly module includes: The candidate vehicle set establishment unit is used to share the current navigation data of each vehicle in the cloud, including navigation data collected from the vehicle's infotainment system and navigation data collected from the mobile device; obtain the navigation destination and navigation route data of vehicles with set navigation, and establish a candidate vehicle set in combination with the driving style DNA tag; The path overlap calculation unit is used to calculate the path overlap between each vehicle in the candidate vehicle set and to filter vehicles that share the same main road path from the candidate vehicle set. The vehicle formation unit is used to group and match vehicles that share the same main road route based on driving style DNA tags, dynamically select one vehicle with an aggressive driving style as a lead vehicle candidate, and select two vehicles with a cautious driving style as follower vehicle candidates to form a temporary vehicle formation scheme.

9. The system according to claim 8, characterized in that, The fleet application sending module includes: The application sending unit is used to send the application for temporary fleet formation to the on-board terminals of the corresponding lead vehicle candidate and follow vehicle candidate via vehicle-to-everything (V2X) communication. The on-board terminals of the lead vehicle candidate and follow vehicle candidate display the application information for temporary fleet formation, including the role assignment of fleet members and the expected driving route. The response receiving and verification unit is used to receive and verify the confirmation responses of the lead vehicle candidate and the following vehicle candidate. When all confirmation responses are in agreement, a temporary cooperative fleet is established. The candidate vehicle replacement unit is used to replace any vehicle that matches the driving style DNA tag with a new candidate from the candidate vehicle set based on the number of dissenting confirmation responses when any confirmation response is disagreed. The temporary fleet formation application is then resent and the verification process is repeated until all consents are obtained, and a temporary collaborative fleet is established. The collaborative route planning unit is used to plan a dedicated collaborative route for temporary collaborative vehicle fleets based on shared main road routes and real-time traffic information. The dedicated collaborative route takes into account the overall traffic efficiency of the temporary collaborative vehicle fleet.

10. The system according to claim 9, characterized in that, The real-time control command broadcasting module includes: The safety space calculation unit is used to calculate the collaborative safety space of a virtual buffer zone that treats the three vehicles as a whole, based on the real-time position and motion status of the lead vehicle and the following vehicle. The driving strategy generation unit is used to generate a unified driving strategy based on the collaborative safety space and the exclusive collaborative route. The unified driving strategy is simultaneously distributed to the lead vehicle and the following vehicle. The transmission interval setting unit is used to collect the control command data of the lead vehicle in real time. The control command data includes lane change command, speed change command and braking command. Based on the size and dynamic changes of the cooperative safety space, the transmission interval of the control command in the vehicle network is set.

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