CN117994985B - Intelligent automobile driving planning system based on mixed driving environment - Google Patents
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Abstract
The invention belongs to the technical field of automobile driving supervision, in particular to an intelligent automobile driving planning system based on a mixed driving environment, which comprises a supervision platform, a vehicle sensing module, a vehicle behavior analysis module, a road right distribution management and control module, a road time-sharing evaluation module and a remote terminal, wherein the road right distribution management and control module is used for monitoring the driving environment of an automobile; according to the road traffic management and control system, the vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicle and utilizing the machine learning algorithm and the behavior recognition technology, the road right management and control module is used for marking the corresponding vehicle as an high-road right vehicle or a low-road right vehicle based on all the behaviors required to be managed and analyzed, different management measures are adopted for the high-road right vehicle and the low-road right vehicle, the vehicle behavior is analyzed in real time, the road right of the vehicle is reasonably distributed and controlled, the road traffic efficiency and the road traffic safety are effectively improved, the intelligent degree is high, the road traffic management difficulty is remarkably reduced, and the management effect is improved.
Description
Technical Field
The invention relates to the technical field of automobile driving supervision, in particular to an intelligent automobile driving planning system based on a mixed driving environment.
Background
Along with the acceleration of the urban process, the road traffic pressure is increasingly increased, the mixed driving environment is increasingly common, and at present, when road vehicles in the mixed driving environment are monitored, corresponding roads can be monitored only through cameras so as to provide a basic traffic monitoring function;
In the actual application process, real-time analysis of vehicle behaviors cannot be realized, road right distribution and control of vehicles cannot be reasonably performed, the improvement of road traffic efficiency and safety is not facilitated, the problems of traffic jam, accident risk and the like are frequently caused, the intelligent degree is low, and the road supervision difficulty is increased;
In view of the above technical drawbacks, a solution is now proposed.
Disclosure of Invention
The invention aims to provide an intelligent automobile driving planning system based on a mixed driving environment, which solves the problems that the prior art cannot realize real-time analysis of vehicle behaviors and reasonably carry out road right distribution control of vehicles, has low intelligent degree, increases road supervision difficulty and is difficult to improve traffic efficiency and safety.
In order to achieve the above purpose, the present invention provides the following technical solutions:
An intelligent automobile driving planning system based on a mixed driving environment comprises a supervision platform, a vehicle perception module, a vehicle behavior analysis module, a road right distribution management and control module, a road time-sharing evaluation module and a remote terminal; the monitoring platform acquires a road to be monitored and marks the road as a monitored road, the vehicle sensing module is used for acquiring the running information of the vehicle on the monitored road, and the running information of the vehicle is sent to the vehicle behavior analysis module through the monitoring platform;
The vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicle and utilizing a machine learning algorithm and a behavior recognition technology, capturing the behavior to be controlled of the corresponding vehicle, and transmitting the behavior to be controlled of the corresponding vehicle to the road right management and control module; wherein, the behavior to be controlled comprises overspeed, lane changing and deceleration; the road right management and control module dynamically adjusts the driving right and speed limit of the corresponding vehicle on the monitored road based on all the vehicles to be managed and controlled and through analysis to mark the corresponding vehicle as an expressway right vehicle or an expressway right vehicle, and sends the marking information of the corresponding vehicle to the remote terminal through the supervision platform;
The method comprises the steps that when speed limit adjustment is carried out, the speed upper limit threshold value of a low-road-weight vehicle is smaller than the speed upper limit threshold value of an high-road-weight vehicle, when driving permission adjustment is carried out, an evaluation period with the number of days being Y1 is set through a road time-division evaluation module, a plurality of passing time periods are set every day, the duration of each passing time period is the same, the corresponding passing time period is marked as a blocking time period or an easy time period through time-division road monitoring analysis, marking information of the corresponding passing time period is sent to a road-weight distribution management module and a remote terminal through a supervision platform, and the road-weight distribution management module prohibits part of the low-road-weight vehicle from entering a monitored road in the blocking time period.
Further, the specific operation process of the road right distribution management and control module comprises the following steps:
Setting a road right evaluation period with the number of days of L1, collecting the total duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the total duration as a speed overtime detection value, collecting the single duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the single duration as a speed overtime value, comparing the speed overtime value with the preset speed overtime time threshold value, marking the corresponding speed overtime value as a speed overtime table value if the speed overtime value exceeds the preset speed overtime threshold value, and marking the number of the speed overtime table values of the corresponding vehicle in the road right evaluation period as a speed overtime frequency table value;
The road weight evaluation value is obtained by carrying out numerical calculation on the speed overtime detection value, the speed overtime table value, the road change evaluation value and the speed reduction supervision value of the corresponding vehicle, the running total duration of the corresponding vehicle on the monitored road in the road weight evaluation period of the corresponding vehicle is obtained, and the ratio of the road weight evaluation value to the running total duration is marked as the road weight occupation evaluation value;
respectively carrying out numerical comparison on the road right evaluation value and the road right occupation evaluation value and a preset road right evaluation threshold value and a preset road right occupation evaluation threshold value, and marking the corresponding vehicle as a low-road-weight vehicle for monitoring the road if the road right evaluation value or the road right occupation evaluation value exceeds the corresponding preset threshold value; and if the road right evaluation value and the road right occupation value do not exceed the corresponding preset threshold values, marking the corresponding vehicle as an expressway right vehicle for monitoring the road.
Further, the specific analysis process of the lane change detection analysis is as follows:
Setting a plurality of detection time periods in the running process of the corresponding vehicle corresponding to the monitored road, collecting the times of changing the road of the corresponding vehicle in the detection time periods, marking the times as changing road frequency, comparing the changing road frequency with a preset changing road frequency threshold value, and marking the corresponding detection time periods as changing road risk time periods if the changing road frequency exceeds the preset changing road frequency threshold value; and acquiring all lane change risk periods of the corresponding vehicles on the monitored road in the road right evaluation period, and marking the number of the lane change risk periods as a lane change evaluation value.
Further, the specific analysis process of the deceleration full-flow supervision analysis is as follows:
Acquiring all deceleration states of the corresponding vehicles on the monitored road in the road right evaluation period, calculating the time difference between the ending time and the starting time of the corresponding deceleration states to obtain deceleration duration, acquiring the speed reduction value of the corresponding vehicles in the deceleration duration, and marking the ratio of the speed reduction value to the deceleration duration as a deceleration risk measurement value; comparing the deceleration risk measurement value with a preset deceleration risk measurement threshold value in a numerical mode, and marking the corresponding deceleration state as a sudden-falling state if the deceleration risk measurement value exceeds the preset deceleration risk measurement threshold value;
If the deceleration risk measurement value does not exceed the preset deceleration risk measurement threshold value, acquiring a speed curve of a corresponding vehicle in the deceleration duration, and placing the speed curve into a rectangular coordinate system positioned in a first quadrant, wherein an X axis of the rectangular coordinate system is time, and a Y axis of the rectangular coordinate system is vehicle speed; all turning points on a speed curve are obtained, line segments connecting two adjacent groups of turning points are marked as falling table line segments, a horizontal straight line which is parallel to an X axis and intersects with the falling table line segments is made in a rectangular coordinate system and marked as a transverse table straight line, and an acute angle formed between the transverse table straight line and the corresponding falling table line segments is marked as a vehicle falling table value;
The vehicle condition reduction value is obtained through mean value calculation of all vehicle condition reduction values in corresponding deceleration states, the vehicle condition reduction value with the largest value is marked as a vehicle condition reduction value, the vehicle condition reduction value and the vehicle condition reduction value are respectively compared with a preset vehicle condition reduction threshold value and a preset vehicle condition reduction threshold value, and if the vehicle condition reduction value or the vehicle condition reduction value exceeds the corresponding preset threshold value, the corresponding deceleration state is marked as a sudden drop state; the total number of times of the corresponding vehicle in the road right evaluation period in the sudden drop state on the monitored road is obtained and marked as a deceleration supervision value.
Further, the specific analysis process of the time-division road monitoring analysis is as follows:
The method comprises the steps of collecting the number of the congestion road sections of a monitoring road at a detection time point, marking the number of the congestion road sections as a congestion number detection value, carrying out summation calculation on the congestion lengths of all the congestion road sections to obtain a congestion distance detection value, and carrying out numerical calculation on the congestion number detection value and the congestion distance detection value to obtain a congestion coefficient; acquiring the congestion coefficients of all detection points of the monitoring road in the corresponding passing time period of the corresponding date, establishing a congestion set, carrying out mean value calculation and variance calculation on the congestion set to obtain a congestion representation value and a congestion difference value, respectively carrying out numerical comparison on the congestion representation value and the congestion difference value with a preset congestion representation value and a preset congestion difference threshold value, and judging that the monitoring road is in a high-congestion state in the corresponding passing time period of the corresponding date if the congestion representation value exceeds the preset congestion representation threshold value and the congestion difference value does not exceed the preset congestion difference threshold value; if the congestion representation value does not exceed the preset congestion representation threshold value and the congestion difference value does not exceed the preset congestion difference threshold value, judging that the monitored road is in a low-congestion state in a corresponding passing period of the corresponding date;
Otherwise, marking the ratio of the subset number exceeding the preset congestion coefficient threshold value in the congestion set as an over-congestion detection value, carrying out numerical calculation on the over-congestion detection value and the congestion representation value to obtain a congestion judgment value, carrying out numerical comparison on the congestion judgment value and a preset congestion judgment value range, and judging that the monitored road is in a high-congestion state in a corresponding passing period of the corresponding date if the congestion judgment value exceeds the maximum value of the preset congestion judgment value range; if the jam judgment value does not exceed the minimum value of the range of the preset jam judgment value, judging that the monitored road is in a low-jam state in the corresponding passing period of the corresponding date; if the blocking judgment value is within the preset blocking judgment value range, judging that the monitored road is in a medium blocking state in the passing period corresponding to the corresponding date.
Further, after judging that the monitored road is in a high-blocking state, a medium-blocking state or a low-blocking state in a corresponding passing period of a corresponding date, acquiring the number of days of the monitored road in the high-blocking state, the number of days of the monitored road in the medium-blocking state and the number of days of the monitored road in the low-blocking state in the corresponding passing period in an evaluation period, marking the days as a high-blocking condition table value, a medium-blocking condition table value and a low-blocking condition table value respectively, and carrying out numerical calculation on the high-blocking condition table value, the medium-blocking condition table value and the low-blocking condition table value to obtain a blocking analysis value;
comparing the blocking value with a preset blocking threshold value, and marking the corresponding passing time period as a blocking causing time period if the blocking value exceeds the preset blocking threshold value; if the blocking value does not exceed the preset blocking threshold value, marking the corresponding passing time period as an easy-to-operate time period.
Further, the supervision platform is in communication connection with the traffic insurance detection module, the traffic insurance detection module acquires all vehicles on the monitored road, the corresponding vehicles are marked as i, and i is a natural number larger than 1; the running high risk signal or the running low risk signal of the vehicle i is generated through running risk detection analysis, the running high risk signal is sent to the vehicle-mounted terminal of the vehicle i through the supervision platform, and corresponding early warning is sent out when the vehicle-mounted terminal of the vehicle i receives the running high risk signal.
Further, the specific analysis process of the risk detection analysis is as follows:
collecting a distance value of the vehicle i from a vehicle in front of the vehicle i, marking the distance value as a short-distance value, collecting a distance reduction speed of the vehicle i and the vehicle in front of the vehicle i as a distance reduction value, marking a ratio of the short-distance value to the distance reduction value as a speed insurance value, comparing the speed insurance value with a preset speed insurance threshold value, and generating a running high insurance signal of the vehicle i if the speed insurance value does not exceed the preset speed insurance threshold value;
If the speed risk value exceeds a preset speed risk threshold, collecting the shaking amplitude of the vehicle i, marking the shaking amplitude as a driving shaking detection value, collecting the visibility data of the environment where the vehicle i is located, marking the minimum distance value of the vehicle i compared with the side line of the lane where the vehicle i is located as a side distance detection value, carrying out numerical calculation on the speed risk value, the driving shaking detection value, the visibility data and the side distance detection value of the vehicle i to obtain a running risk evaluation value, carrying out numerical comparison on the running risk evaluation value and the preset running risk evaluation threshold, and if the running risk evaluation value exceeds the preset running risk evaluation threshold, generating a driving high risk signal of the vehicle i; and if the running risk evaluation value does not exceed the preset running risk evaluation threshold value, generating a running low risk signal of the vehicle i.
Compared with the prior art, the invention has the beneficial effects that:
1. According to the invention, the vehicle perception module is used for acquiring the running information of the vehicle on the monitored road, the vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicle, the road right distribution management module is used for marking the corresponding vehicle as an expressway right vehicle or an expressway right vehicle through analysis, the speed upper limit threshold value of the expressway right vehicle is smaller than the speed upper limit threshold value of the expressway right vehicle when the speed limit adjustment is carried out, and part of the expressway right vehicle is forbidden to enter the monitored road in the blocking period, and the road right is reasonably distributed and controlled through real-time analysis of the vehicle behavior, so that the road traffic efficiency and the road traffic safety are improved, the intelligent degree is high, the road traffic monitoring difficulty is remarkably reduced, and the management effect is improved;
2. According to the invention, all vehicles on a monitored road are acquired through the traffic risk detection module, the traffic risk detection analysis is performed to generate the traffic risk signals or the traffic risk signals of the corresponding vehicles, the traffic risk signals are sent to the vehicle-mounted terminals of the corresponding vehicles through the supervision platform, and the vehicle-mounted terminals of the corresponding vehicles send corresponding early warning when receiving the traffic risk signals, so that corresponding drivers are timely reminded to make reasonable adjustment measures, the traffic safety of the corresponding vehicles is effectively ensured, and the traffic risk of the road is further reduced.
Drawings
For the convenience of those skilled in the art, the present invention will be further described with reference to the accompanying drawings;
FIG. 1 is a system block diagram of a first embodiment of the present invention;
fig. 2 is a system block diagram of a second embodiment of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made clearly and completely with reference to the accompanying drawings, in which it is apparent that the embodiments described are only some embodiments of the present invention, but not all embodiments. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
Embodiment one: as shown in fig. 1, the intelligent automobile driving planning system based on the hybrid driving environment provided by the invention comprises a supervision platform, a vehicle sensing module, a vehicle behavior analysis module, a road right distribution management and control module, a road time-sharing evaluation module and a remote terminal, wherein the supervision platform is in communication connection with the vehicle sensing module, the vehicle behavior analysis module, the road right distribution management and control module, the road time-sharing evaluation module and the remote terminal; the hybrid driving environment refers to a running environment where an autonomous vehicle and a manual vehicle coexist;
The monitoring platform acquires a road to be monitored and marks the road as a monitored road, the vehicle sensing module is used for acquiring running information of a vehicle on the monitored road, the running information comprises information such as the position, the speed and the acceleration of the vehicle, and the running information of the vehicle is sent to the vehicle behavior analysis module through the monitoring platform; the vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicle and utilizing a machine learning algorithm and a behavior recognition technology, capturing the behavior to be controlled of the corresponding vehicle, and sending the behavior to be controlled of the corresponding vehicle to the road right management and control module, wherein the vehicle behavior analysis module can realize real-time monitoring and analysis of the vehicle behavior and provide data support for subsequent road right distribution; wherein, the behavior to be controlled comprises overspeed, lane changing, deceleration and the like;
The road right management and control module dynamically adjusts the driving right and speed limit of the corresponding vehicle on the monitored road based on all the required management and control behaviors of the vehicle and through analysis to mark the corresponding vehicle as an expressway right vehicle or an expressway right vehicle, namely, the system can reduce the road right of the expressway right vehicle so as to reduce the interference of the expressway right vehicle on other vehicles, give higher road right to the expressway right vehicle so as to improve the passing efficiency, and the marking information of the corresponding vehicle is sent to a remote terminal through a supervision platform; the specific operation process of the road right distribution control module is as follows:
Setting a road right evaluation period with the number of days of L1, wherein L1 is preferably ten days; collecting the total duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the total duration as a speed overtime detection value, collecting the single duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the single duration as a speed overtime value, comparing the speed overtime value with a preset speed overtime time threshold value, marking the corresponding speed overtime value as a speed overtime table value if the speed overtime value exceeds the preset speed overtime time threshold value, and marking the number of the speed overtime table values of the corresponding vehicle in the road right evaluation period as a speed overtime table value;
And obtaining a lane change evaluation value of the corresponding vehicle through lane change detection analysis, specifically: setting a plurality of detection time periods in the running process of the corresponding vehicle corresponding to the monitored road, collecting the times of changing the road of the corresponding vehicle in the detection time periods, marking the times as the changing frequency, comparing the changing frequency with a preset changing frequency threshold value, and marking the corresponding detection time periods as changing risk time periods if the changing frequency exceeds the preset changing frequency threshold value, which indicates that the corresponding vehicle in the corresponding detection time periods frequently changes the road in the monitored road and the risk is large; acquiring all lane change risk periods of the corresponding vehicles on the monitored road in the road right evaluation period, and marking the number of the lane change risk periods as a lane change evaluation value;
And the deceleration supervision value of the corresponding vehicle is obtained through deceleration full-flow supervision analysis, specifically: acquiring all deceleration states of the corresponding vehicles on the monitored road in the road right evaluation period, calculating the time difference between the ending time and the starting time of the corresponding deceleration states to obtain deceleration duration, acquiring the speed reduction value of the corresponding vehicles in the deceleration duration, and marking the ratio of the speed reduction value to the deceleration duration as a deceleration risk measurement value; the larger the value of the deceleration risk measurement is, the more abrupt the deceleration action of the vehicle is, and the greater the safety risk is brought; comparing the deceleration risk measurement value with a preset deceleration risk measurement threshold value in a numerical mode, and marking the corresponding deceleration state as a sudden-falling state if the deceleration risk measurement value exceeds the preset deceleration risk measurement threshold value;
If the deceleration risk measurement value does not exceed the preset deceleration risk measurement threshold value, acquiring a speed curve of a corresponding vehicle in the deceleration duration, and placing the speed curve into a rectangular coordinate system positioned in a first quadrant, wherein an X axis of the rectangular coordinate system is time, and a Y axis of the rectangular coordinate system is vehicle speed; all turning points on a speed curve are obtained, line segments connecting two adjacent groups of turning points are marked as falling table line segments, a horizontal straight line which is parallel to an X axis and intersects with the falling table line segments is made in a rectangular coordinate system and marked as a transverse table straight line, and an acute angle formed between the transverse table straight line and the corresponding falling table line segments is marked as a vehicle falling table value; the larger the value of the vehicle drop rate value is, the faster the speed of the corresponding vehicle drops in the interval duration between two adjacent turning points is indicated;
The vehicle condition reduction value is obtained through mean value calculation of all vehicle condition reduction values in corresponding deceleration states, the vehicle condition reduction value with the largest value is marked as a vehicle condition reduction value, the vehicle condition reduction value and the vehicle condition reduction value are respectively compared with a preset vehicle condition reduction threshold value and a preset vehicle condition reduction threshold value, and if the vehicle condition reduction value or the vehicle condition reduction value exceeds the corresponding preset threshold value, the corresponding deceleration state is marked as a sudden drop state, the safety risk caused by the corresponding deceleration state is indicated to be larger; acquiring the total times of the sudden drop states of the corresponding vehicles on the monitored road in the road right evaluation period and marking the total times as a deceleration supervision value;
By the formula Carrying out numerical calculation on a speed overtime detection value QD, a speed overtime table value QY, a lane change evaluation value QL and a speed reduction supervision value QS of a corresponding vehicle to obtain a road weight evaluation value QX, wherein, the values of the w1, the w2, the w3 and the w4 are preset proportion coefficients, and the values of the w1, the w2, the w3 and the w4 are positive numbers; and, the larger the value of the road right evaluation value QX is, the larger the adverse effect of the corresponding vehicle on the safety traffic of the monitored road in the road right evaluation period is, and the more the management and control of the corresponding vehicle on the monitored road are required to be enhanced; acquiring the total running duration of the corresponding vehicle on the monitored road in the corresponding vehicle road right evaluation period, and marking the ratio of the road right evaluation value to the total running duration as a road right occupation evaluation value; the larger the road weight estimated value is, the more the corresponding vehicle is required to be managed and controlled on the monitored road;
Respectively carrying out numerical comparison on the road right evaluation value and the road right occupation evaluation value and a preset road right evaluation threshold value and a preset road right occupation evaluation threshold value, and marking the corresponding vehicle as a low-road-right vehicle of the monitored road if the road right evaluation value or the road right occupation evaluation value exceeds the corresponding preset threshold value, which indicates that the adverse effect of the corresponding vehicle on the safe passing of the monitored road is larger and the management and control of the corresponding vehicle on the monitored road are required to be enhanced; if the road right evaluation value and the road right occupation value do not exceed the corresponding preset threshold values, the adverse effect of the corresponding vehicle on the safety traffic of the monitored road is smaller, and the management and control of the corresponding vehicle on the monitored road are not required to be enhanced, and the corresponding vehicle is marked as the high-road right vehicle of the monitored road.
When the speed limit adjustment is carried out, the speed upper limit threshold value of the low-road-weight vehicle is smaller than the speed upper limit threshold value of the high-road-weight vehicle, and when the driving permission adjustment is carried out, the evaluation period with the number of days being Y1 is set through the road time-interval evaluation module, preferably, Y1 is twenty-five days; setting a plurality of traffic time periods every day, wherein the duration of each traffic time period is the same, marking the corresponding traffic time period as a blocking time period or an easy time period through time period road monitoring analysis, and sending marking information of the corresponding traffic time period to a road right distribution management and control module and a remote terminal through a supervision platform, wherein the road right distribution management and control module prohibits part of low road right vehicles from entering a monitored road in the blocking time period, provides data support for road right distribution and control of the monitored road, and is beneficial to traffic management of the monitored road; the specific analysis process of the time-interval road monitoring analysis is as follows:
the method comprises the steps of collecting the number of the congestion road sections of a monitoring road at a detection time point, marking the number of the congestion road sections as a congestion number detection value, carrying out summation calculation on the congestion lengths of all the congestion road sections to obtain a congestion distance detection value, and carrying out numerical calculation on the congestion number detection value RS and the congestion distance detection value RL through a formula RK=kp1xRS+kp2xRL to obtain a congestion coefficient RK; wherein kp1 and kp2 are preset weight coefficients, and kp1 is more than kp2 is more than 0; and, the larger the value of the congestion coefficient RK is, the worse the traffic condition of the corresponding detection time point monitoring road is; acquiring congestion coefficients of all detection time points of a monitoring road in a passing period corresponding to a corresponding date, establishing a congestion set, and carrying out mean value calculation and variance calculation on the congestion set to obtain a congestion representation value and a congestion difference value;
Respectively carrying out numerical comparison on the congestion representation value and the congestion difference value and a preset congestion representation value and a preset congestion difference threshold value, and judging that the monitored road is in a high-congestion state in the corresponding traffic period of the corresponding date if the congestion representation value exceeds the preset congestion representation threshold value and the congestion difference value does not exceed the preset congestion difference threshold value, which indicates that the traffic representation of the monitored road in the corresponding traffic period of the corresponding date is extremely poor as a whole; if the congestion representation value does not exceed the preset congestion representation threshold value and the congestion difference value does not exceed the preset congestion difference threshold value, indicating that the traffic performance of the monitored road in the corresponding traffic time period on the corresponding date is good as a whole, judging that the monitored road is in a low-congestion state in the corresponding traffic time period on the corresponding date;
Otherwise, marking the ratio of the subset number exceeding the preset congestion coefficient threshold value in the congestion set as an over-congestion detection value, and carrying out numerical calculation on the over-congestion detection value WY and the congestion expression value WL through a formula WX=ty 1 xWY+ty 2 xWL/(ty 1+0.682) to obtain a congestion judgment value WX, wherein ty1 and ty2 are preset proportionality coefficients, and ty1 > ty2 > 0; and, the larger the value of the jam evaluation value WX is, the worse the traffic performance of the monitored road in the corresponding passing period of the corresponding date is indicated;
Comparing the blocking judgment value WX with a preset blocking judgment value range in a numerical mode, and judging that the monitored road is in a high blocking state in a corresponding passing period of the corresponding date if the blocking judgment value WX exceeds the maximum value of the preset blocking judgment value range, which indicates that the traffic performance of the monitored road in the corresponding passing period of the corresponding date is extremely poor as a whole; if the jam judging value WX does not exceed the minimum value of the preset jam judging value range, indicating that the traffic performance of the monitored road in the corresponding passing time period on the corresponding date is good as a whole, judging that the monitored road is in a low-jam state in the corresponding passing time period on the corresponding date; if the jam evaluation value WX is within the preset jam evaluation value range, which indicates that the traffic performance of the monitored road in the traffic period corresponding to the corresponding date is poor as a whole, the monitored road is judged to be in a medium jam state in the traffic period corresponding to the corresponding date.
Further, after judging that the monitored road is in a high-blocking state, a medium-blocking state or a low-blocking state in the corresponding passing time period of the corresponding date, acquiring the number of days of the monitored road in the high-blocking state, the number of days of the medium-blocking state and the number of days of the low-blocking state in the corresponding passing time period in the evaluation period, and marking the days as a high-blocking state table value, a medium-blocking state table value and a low-blocking state table value respectively, wherein the number of days of the high-blocking state, the number of days of the medium-blocking state and the number of days of the low-blocking state in the corresponding passing time period in the evaluation period are obtained, and the high-blocking state table value, the medium-blocking state table value and the low-blocking state table value are represented by the formulaCarrying out numerical calculation on the high-blockage-condition table value DY, the medium-blockage-condition table value DZ and the low-blockage-condition table value DK to obtain a blockage analysis value DX;
It should be noted that f1, f2, f3 are preset proportionality coefficients, f1 > f2 > f3 > 0; and the larger the value of the blocking value DX is, the more serious the traffic jam condition of the monitored road in the corresponding traffic period in the evaluation period is; comparing the blocking value DX with a preset blocking threshold value, and marking the corresponding passing time period as a blocking causing time period if the blocking value DX exceeds the preset blocking threshold value, which indicates that the corresponding passing time period of the monitored road is easy to be blocked in the evaluation period; if the blockage analysis value DX does not exceed the preset blockage analysis threshold value, the condition that the corresponding traffic time period of the monitored road is difficult to be jammed in the evaluation period is indicated, the traffic of the monitored road is smooth, and the corresponding traffic time period is marked as an easy time period.
Embodiment two: as shown in fig. 2, the difference between the present embodiment and embodiment 1 is that the supervision platform is in communication connection with the traffic risk detection module, the traffic risk detection module obtains all vehicles on the monitored road, and marks the corresponding vehicles as i, where i is a natural number greater than 1; generating a high-risk signal or a low-risk signal of the vehicle i through running risk detection analysis, transmitting the high-risk signal to a vehicle-mounted terminal of the vehicle i through a supervision platform, and sending out corresponding early warning when the vehicle-mounted terminal of the vehicle i receives the high-risk signal, so as to remind a corresponding driver to properly reduce the running speed or take other adjustment measures in time, thereby effectively ensuring the running safety of the vehicle i; the specific analysis process of the risk detection analysis is as follows:
Collecting a distance value of a vehicle i from a vehicle in front of the vehicle i, marking the distance value as a short-distance value, collecting a distance reduction speed of the vehicle i from the vehicle in front of the vehicle i, marking the distance reduction speed as a distance reduction value, and marking the ratio of the short-distance value to the distance reduction value as a speed risk value, wherein the smaller the value of the speed risk value is, the greater the probability that the vehicle i collides with the vehicle in front of the vehicle is, and the greater the running risk is; comparing the speed risk value with a preset speed risk threshold value, and if the speed risk value does not exceed the preset speed risk threshold value, indicating that the probability that the vehicle i is about to collide with the vehicle in front of the vehicle is high, generating a running high risk signal of the vehicle i;
If the speed risk value exceeds a preset speed risk threshold value, acquiring the shaking amplitude of the vehicle i, marking the shaking amplitude as a driving shaking detection value, acquiring the visibility data of the environment where the vehicle i is located, marking the minimum distance value of the vehicle i compared with the side line of the lane where the vehicle i is located (namely the lateral lines on two sides of the lane) as a side distance detection value, and carrying out numerical calculation on the speed risk value XS, the driving shaking detection value XR, the visibility data XW and the side distance detection value XK of the vehicle i through a formula XP=a2×XR/(a1×XS+a3×a4×XK) to obtain a speed risk evaluation value XP;
it should be noted that a1, a2, a3, a4 are preset proportionality coefficients, and values of a1, a2, a3, a4 are positive numbers; and, the larger the number of the risk evaluation value XP is, the larger the current running risk of the vehicle i is; comparing the running risk evaluation value XP with a preset running risk evaluation threshold value, and generating a running high risk signal of the vehicle i if the running risk evaluation value XP exceeds the preset running risk evaluation threshold value, which indicates that the current running risk of the vehicle i is large; if the running risk evaluation value XP does not exceed the preset running risk evaluation threshold value, and the current running risk of the vehicle i is smaller, a running low risk signal of the vehicle i is generated.
The working principle of the invention is as follows: when the road traffic monitoring system is used, the vehicle perception module is used for acquiring the running information of the vehicles on the monitored road, the vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicles and utilizing the machine learning algorithm and the behavior recognition technology, the road right distribution control module is used for capturing the behavior required to be controlled of the corresponding vehicles, the road right distribution control module is used for marking the corresponding vehicles as high-road right vehicles or low-road right vehicles based on all the behavior required to be controlled of the vehicles through analysis, the speed upper limit threshold value of the low-road right vehicles is smaller than the speed upper limit threshold value of the high-road right vehicles when the speed limit adjustment is carried out, the road evaluation module is used for carrying out time-interval road evaluation analysis when the driving right adjustment is carried out so as to mark the corresponding passing time interval as a blocking time interval or an easy time interval, and the road right distribution control module is used for prohibiting part of the low-road right vehicles from entering the monitored road during the blocking time interval and carrying out reasonable distribution control on the road right of the vehicles through real-time analysis, the road passing efficiency and the safety are improved, the intelligent degree is high, the road traffic difficulty is obviously reduced, and the management effect is improved.
The above formulas are all formulas with dimensions removed and numerical values calculated, the formulas are formulas with a large amount of data collected for software simulation to obtain the latest real situation, and preset parameters in the formulas are set by those skilled in the art according to the actual situation. The preferred embodiments of the invention disclosed above are intended only to assist in the explanation of the invention. The preferred embodiments are not intended to be exhaustive or to limit the invention to the precise form disclosed. Obviously, many modifications and variations are possible in light of the above teaching. The embodiments were chosen and described in order to best explain the principles of the invention and the practical application, to thereby enable others skilled in the art to best understand and utilize the invention. The invention is limited only by the claims and the full scope and equivalents thereof.
Claims (3)
1. The intelligent automobile driving planning system based on the mixed driving environment is characterized by comprising a supervision platform, a vehicle sensing module, a vehicle behavior analysis module, a road right distribution management module, a road time-sharing evaluation module and a remote terminal; the monitoring platform acquires a road to be monitored and marks the road as a monitored road, the vehicle sensing module is used for acquiring the running information of the vehicle on the monitored road, and the running information of the vehicle is sent to the vehicle behavior analysis module through the monitoring platform;
The vehicle behavior analysis module is used for analyzing the vehicle behavior based on the running information of the vehicle and utilizing a machine learning algorithm and a behavior recognition technology, capturing the behavior to be controlled of the corresponding vehicle, and transmitting the behavior to be controlled of the corresponding vehicle to the road right management and control module; wherein, the behavior to be controlled comprises overspeed, lane changing and deceleration; the road right management and control module dynamically adjusts the driving right and speed limit of the corresponding vehicle on the monitored road based on all the vehicles to be managed and controlled and through analysis to mark the corresponding vehicle as an expressway right vehicle or an expressway right vehicle, and sends the marking information of the corresponding vehicle to the remote terminal through the supervision platform;
When the speed limit adjustment is carried out, the speed upper limit threshold value of the low-road-weight vehicle is smaller than the speed upper limit threshold value of the high-road-weight vehicle, when the driving permission adjustment is carried out, the evaluation period with the number of days being Y1 is set through the road time-division evaluation module, a plurality of passing time periods are set every day, the duration of each passing time period is the same, the corresponding passing time period is marked as a blocking time period or an easy-to-operate time period through time-division road monitoring analysis, marking information of the corresponding passing time period is sent to the road-weight distribution management module and the remote terminal through the supervision platform, and the road-weight distribution management module prohibits part of the low-road-weight vehicle from entering a monitored road in the blocking time period;
The specific operation process of the road right distribution control module comprises the following steps:
Setting a road right evaluation period with the number of days of L1, collecting the total duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the total duration as a speed overtime detection value, collecting the single duration that the running speed of the corresponding vehicle on the monitored road exceeds the preset running speed threshold value of the corresponding vehicle in the road right evaluation period, marking the corresponding speed overtime value as a speed overtime table value if the speed overtime value exceeds the preset speed overtime time threshold value, and marking the number of the speed overtime table values of the corresponding vehicle in the road right evaluation period as a speed overtime table value;
The lane change evaluation value of the corresponding vehicle is obtained through lane change detection analysis, and the deceleration supervision value of the corresponding vehicle is obtained through deceleration full-flow supervision analysis;
By the formula Carrying out numerical calculation on a speed overtime detection value QD, a speed overtime table value QY, a lane change evaluation value QL and a speed reduction supervision value QS of a corresponding vehicle to obtain a road weight evaluation value QX, wherein, the values of the w1, the w2, the w3 and the w4 are preset proportion coefficients, and the values of the w1, the w2, the w3 and the w4 are positive numbers; acquiring the total running duration of the corresponding vehicle on the monitored road in the corresponding vehicle road right evaluation period, and marking the ratio of the road right evaluation value to the total running duration as a road right occupation evaluation value;
If the road right evaluation value or the road right occupation value exceeds a corresponding preset threshold value, marking the corresponding vehicle as a low-road-right vehicle for monitoring the road; if the road right evaluation value and the road right occupation value do not exceed the corresponding preset threshold values, marking the corresponding vehicle as an expressway right vehicle for monitoring the road;
The specific analysis process of the lane change detection analysis is as follows:
Setting a plurality of detection time periods in the running process of the corresponding vehicle corresponding to the monitored road, collecting the times of changing the road of the corresponding vehicle in the detection time periods, marking the times as the frequency of changing the road, and marking the corresponding detection time periods as the risk time periods of changing the road if the frequency of changing the road exceeds a preset frequency threshold value of changing the road; acquiring all lane change risk periods of the corresponding vehicles on the monitored road in the road right evaluation period, and marking the number of the lane change risk periods as a lane change evaluation value;
the specific analysis process of the deceleration full-flow supervision analysis is as follows:
Acquiring all deceleration states of the corresponding vehicles on the monitored road in the road right evaluation period, calculating the time difference between the ending time and the starting time of the corresponding deceleration states to obtain deceleration duration, acquiring the speed reduction value of the corresponding vehicles in the deceleration duration, and marking the ratio of the speed reduction value to the deceleration duration as a deceleration risk measurement value; if the deceleration risk measurement exceeds a preset deceleration risk measurement threshold, marking the corresponding deceleration state as a sudden drop state;
If the deceleration risk measurement value does not exceed the preset deceleration risk measurement threshold value, acquiring a speed curve of a corresponding vehicle in the deceleration duration, and placing the speed curve into a rectangular coordinate system positioned in a first quadrant, wherein an X axis of the rectangular coordinate system is time, and a Y axis of the rectangular coordinate system is vehicle speed; all turning points on a speed curve are obtained, line segments connecting two adjacent groups of turning points are marked as falling table line segments, a horizontal straight line which is parallel to an X axis and intersects with the falling table line segments is made in a rectangular coordinate system and marked as a transverse table straight line, and an acute angle formed between the transverse table straight line and the corresponding falling table line segments is marked as a vehicle falling table value;
The vehicle drop condition value is obtained by carrying out average calculation on all the vehicle drop values in the corresponding deceleration state, the vehicle drop value with the largest value is marked as the vehicle drop value, and if the vehicle drop condition value or the vehicle drop value exceeds the corresponding preset threshold value, the corresponding deceleration state is marked as the emergency drop state; acquiring the total times of the sudden drop states of the corresponding vehicles on the monitored road in the road right evaluation period and marking the total times as a deceleration supervision value;
the specific analysis process of the time-interval road monitoring analysis is as follows:
The method comprises the steps of collecting the number of the congestion road sections of a monitoring road at a detection time point, marking the number of the congestion road sections as a congestion number detection value, carrying out summation calculation on the congestion lengths of all the congestion road sections to obtain a congestion distance detection value, and carrying out numerical calculation on the congestion number detection value RS and the congestion distance detection value RL through a formula RK=kp1xRS+kp2xRL to obtain a congestion coefficient RK; wherein kp1 and kp2 are preset weight coefficients, and kp1 is more than kp2 is more than 0; acquiring the congestion coefficients of all detection time points of the monitoring road in the corresponding passing time period of the corresponding date, establishing a congestion set, carrying out mean value calculation and variance calculation on the congestion set to obtain a congestion expression value and a congestion difference value, and judging that the monitoring road is in a high-congestion state in the corresponding passing time period of the corresponding date if the congestion expression value exceeds a preset congestion expression threshold value and the congestion difference value does not exceed the preset congestion difference threshold value; if the congestion representation value does not exceed the preset congestion representation threshold value and the congestion difference value does not exceed the preset congestion difference threshold value, judging that the monitored road is in a low-congestion state in a corresponding passing period of the corresponding date;
Otherwise, marking the ratio of the subset number exceeding the preset congestion coefficient threshold value in the congestion set as an over-congestion detection value, and carrying out numerical calculation on the over-congestion detection value WY and the congestion expression value WL through a formula WX=ty 1 xWY+ty 2 xWL/(ty 1+0.682) to obtain a congestion judgment value WX, wherein ty1 and ty2 are preset proportionality coefficients, and ty 1> ty2 > 0; if the jam judgment value exceeds the maximum value of the preset jam judgment value range, judging that the monitored road is in a high jam state in the passing period corresponding to the corresponding date; if the jam judgment value does not exceed the minimum value of the range of the preset jam judgment value, judging that the monitored road is in a low-jam state in the corresponding passing period of the corresponding date; if the blocking judgment value is within the preset blocking judgment value range, judging that the monitored road is in a medium blocking state in the passing period corresponding to the corresponding date;
After judging that the monitored road is in a high-blocking state, a medium-blocking state or a low-blocking state in a corresponding passing period of corresponding dates, acquiring the number of days in the high-blocking state, the number of days in the medium-blocking state and the number of days in the low-blocking state in the corresponding passing period of the monitored road in an evaluation period, marking the days as a high-blocking condition table value, a medium-blocking condition table value and a low-blocking condition table value respectively, and determining the number of days in the high-blocking state, the medium-blocking condition table value and the low-blocking condition table value according to the formula Carrying out numerical calculation on the high-blockage-condition table value DY, the medium-blockage-condition table value DZ and the low-blockage-condition table value DK to obtain a blockage analysis value DX; it should be noted that f1, f2, f3 are preset proportionality coefficients, f1 > f2 > f3 > 0;
if the blocking value exceeds the preset blocking threshold value, marking the corresponding passing time period as a blocking time period; if the blocking value does not exceed the preset blocking threshold value, marking the corresponding passing time period as an easy-to-operate time period.
2. The intelligent automobile driving planning system based on the mixed driving environment according to claim 1, wherein the supervision platform is in communication connection with a traffic insurance module, the traffic insurance module acquires all vehicles on a monitored road, the corresponding vehicles are marked as i, and i is a natural number larger than 1; the running high risk signal or the running low risk signal of the vehicle i is generated through running risk detection analysis, the running high risk signal is sent to the vehicle-mounted terminal of the vehicle i through the supervision platform, and corresponding early warning is sent out when the vehicle-mounted terminal of the vehicle i receives the running high risk signal.
3. The intelligent automobile driving planning system based on the mixed driving environment according to claim 2, wherein the specific analysis process of the driving risk detection analysis is as follows:
Collecting a distance value of the vehicle i from a vehicle in front of the vehicle i, marking the distance value as a short-distance value, collecting a distance reduction speed of the vehicle i and the vehicle in front of the vehicle i as a distance reduction value, marking a ratio of the short-distance value to the distance reduction value as a speed insurance value, and generating a driving high insurance signal of the vehicle i if the speed insurance value does not exceed a preset speed insurance threshold value;
If the speed risk value exceeds a preset speed risk threshold, acquiring the shaking amplitude of the vehicle i, marking the shaking amplitude as a running shaking detection value, acquiring the visibility data of the environment where the vehicle i is located, marking the minimum distance value of the vehicle i compared with the boundary of the lane where the vehicle i is located as a boundary detection value, and carrying out numerical calculation on the speed risk value, the running shaking detection value, the visibility data and the boundary detection value of the vehicle i to obtain a running risk evaluation value, and if the running risk evaluation value exceeds the preset running risk evaluation threshold, generating a running high risk signal of the vehicle i; and if the running risk evaluation value does not exceed the preset running risk evaluation threshold value, generating a running low risk signal of the vehicle i.
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