CN113834667A - Doubling method based on heuristic evaluation strategy in high-density virtual traffic flow - Google Patents
Doubling method based on heuristic evaluation strategy in high-density virtual traffic flow Download PDFInfo
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Abstract
The invention relates to the field of vehicle testing, in particular to a doubling method based on a heuristic evaluation strategy in a high-density virtual traffic flow, which comprises the steps of constructing a following vehicle fleet model; generating a following motorcade model on a side lane of the test vehicle by applying an automatic driving control algorithm, and injecting the following motorcade model into the test vehicle for testing through an RSU (remote navigation Unit); the test vehicle sends a doubling request to a following motorcade, detects and identifies head time distance feedback in the following motorcade, and performs doubling operation when a safe doubling opportunity occurs; and evaluating the parallel operation on a physical engine of the virtual simulation platform, so that after the parallel test based on a heuristic evaluation strategy can be performed in the simulated high-density traffic flow, the motor vehicle has the capability of driving in the high-density traffic flow under the real driving environment to finish the parallel operation.
Description
Technical Field
The invention relates to the field of vehicle testing, in particular to a doubling method based on a heuristic evaluation strategy in a high-density virtual traffic flow.
Background
At present, the doubling test of the internet automobiles is limited to be carried out in low-density traffic, the test vehicles only need to detect a plurality of peripheral parallel vehicles, and the doubling operation is carried out after the safe distance is selected to be accelerated and pulled away or the safe distance is reserved after the safe distance is decelerated.
The parallel line behavior test of the networked vehicles in the low-density traffic flow has great limitation, and cannot cover the parallel line behavior after the high-density following traffic flow is formed, which is common in the real driving scene. After the vehicle passes through a simple parallel behavior test, the vehicle still cannot cope with a real driving scene.
Disclosure of Invention
The invention aims to provide a doubling method based on a heuristic evaluation strategy in a high-density virtual traffic flow, and aims to construct a simulation high-density traffic flow based on a real internet vehicle test field and a virtual simulation technology, apply the heuristic evaluation strategy based on the background of the simulation traffic flow, perform vehicle doubling behavior test in the high-density traffic flow, and finally form the doubling method so as to be applied in a real driving scene.
In order to achieve the aim, the invention provides a doubling method based on a heuristic evaluation strategy in a high-density virtual traffic flow, which comprises the steps of constructing a following vehicle fleet model;
generating a following motorcade model on a side lane of the test vehicle by applying an automatic driving control algorithm, and injecting the following motorcade model into the test vehicle for testing through an RSU (remote navigation Unit);
the test vehicle sends a doubling request to a following motorcade, detects and identifies head time distance feedback in the following motorcade, and performs doubling operation when a safe doubling opportunity occurs;
and evaluating the parallel operation on a physical engine of the virtual simulation platform.
The following motorcade model building method comprises the following specific steps:
establishing a driving style model;
a following fleet model is generated based on a plurality of vehicles of different driving style models.
The specific steps of establishing the driving style model are as follows:
constructing a sensitivity coefficient formula;
and generating a plurality of driving styles based on the sensitivity coefficient formula.
The specific way for generating the following fleet model based on the vehicles with different driving style models is as follows:
when the following vehicle finds that the target vehicle is accelerated in response, the time interval between the following vehicle and the front vehicle is in a first interval;
when the following vehicle finds that the target vehicle responds to deceleration, the time interval between the following vehicle and the front vehicle is in a second interval;
when the following vehicle finds that the target vehicle reacts to keep the original speed, the time distance between the following vehicle and the front vehicle is in a third interval:
the first interval is smaller than a third interval, and the third interval is smaller than the second interval.
The specific way of generating the following fleet model based on the vehicles with different driving style models further comprises the following steps: when the test target vehicle doubling request disappears, the headway of the following vehicle is kept in the third interval.
The method comprises the following steps that a test vehicle sends a doubling request to a following motorcade, the head time distance feedback in the following motorcade is detected and identified, and when a safe doubling opportunity occurs, the doubling operation is carried out according to the specific steps:
the test vehicle preliminarily selects a doubling position according to the headway time of the fleet;
keeping the front vehicle at a position with a time interval of 1.5 seconds from the vehicle head, and turning on a steering lamp;
evaluating the behavior of the rear vehicle, and searching a new doubling position if the rear vehicle does not decelerate;
and if the rear vehicle has a deceleration behavior, starting steering and merging when the headway time is in the second interval.
The invention relates to a doubling method based on a heuristic evaluation strategy in a high-density virtual traffic flow, which comprises the steps of constructing a following vehicle fleet model; generating a following motorcade model on a side lane of the test vehicle by applying an automatic driving control algorithm, and injecting the following motorcade model into the test vehicle for testing through an RSU (remote navigation Unit); the test vehicle sends a doubling request to a following motorcade, detects and identifies head time distance feedback in the following motorcade, and performs doubling operation when a safe doubling opportunity occurs; and evaluating the parallel operation on a physical engine of the virtual simulation platform, so that after the parallel test based on a heuristic evaluation strategy can be performed in the simulated high-density traffic flow, the motor vehicle has the capability of driving in the high-density traffic flow under the real driving environment to finish the parallel operation.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart of a method of merging based on heuristics to evaluate policies in high density virtual traffic according to the present invention;
FIG. 2 is a flow chart of the present invention for constructing a following fleet model;
FIG. 3 is a flow chart of the present invention for building a driving style model;
fig. 4 is a flowchart of the present invention for a test vehicle to send a parallel connection request to a following motorcade, detect and identify a head time distance feedback in the following motorcade, and perform parallel connection operation when a safe parallel connection opportunity occurs.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the drawings are illustrative and intended to be illustrative of the invention and are not to be construed as limiting the invention.
Referring to fig. 1 to 4, the present invention provides a merging method based on heuristic evaluation strategy in high-density virtual traffic, including:
s101, constructing a following motorcade model;
the common doubling behavior in actual driving can be divided into two types, one type is doubling in low-density traffic flow, and the doubling behavior can be generally simplified into two-vehicle interaction of a main test vehicle and an interference vehicle in a target lane; the other is the merging in high density traffic flow, which can be understood as the interaction of the main test vehicle with a target fleet of vehicles that are closely following in the target lane. The invention aims to solve the problem of testing the parallel behavior in the high-density traffic flow.
The core of the parallel behavior test in the high-density traffic flow is that the driving behavior of a following motorcade in a target lane is simulated, the following motorcade is fixed in the target lane to run, the transverse control of vehicles can be omitted, the head time interval and the head distance of the vehicles in the motorcade are controlled by using an automatic driving longitudinal control algorithm, the vehicles with different driving styles of aggressiveness, peace and the like are reasonably configured in the motorcade, the driving styles of the vehicles are adjusted through longitudinal control algorithm parameters, the driving styles are mainly embodied in the following time interval and the following distance, the adjustment of the following distance and the like after the parallel intention of the target vehicles is identified.
When the test vehicle is subjected to the parallel testing, a multi-lane road with the length of more than 200 meters is selected for carrying out secondary development on the virtual simulation platform, a following motorcade is generated on a nearby lane by applying an automatic driving control algorithm, and the following motorcade is injected into the test vehicle through the RSU for testing. And the test vehicle sends out a doubling request, detects and identifies vehicle feedback in the following motorcade, and performs doubling operation when a safe doubling opportunity occurs.
And evaluating the safety and comfort of the parallel on the basis of the physical engine of the virtual simulation platform.
A tightly followed fleet of vehicles is generated using an autonomous longitudinal control algorithm and responds to a test vehicle merge request. The longitudinal control algorithm controls the vehicles in the motorcade, and the acceleration of the vehicle is adjusted according to constant variables such as time distance from the front vehicle, speed difference, reaction time of a driver and the like to jointly form a tight following motorcade.
The method comprises the following specific steps:
s201, establishing a driving style model;
the method comprises the following specific steps:
s301, constructing a sensitivity coefficient formula;
3. the motorcade consists of three driving style vehicles which are distributed in equal proportion, and the driving style is embodied in two aspects, namely controlling the reaction intensity (sensitivity coefficient) of the vehicles; and secondly, identifying the tight, neglect and courtesy behaviors after the doubling intention of the test target vehicle is recognized, wherein the behaviors are realized by adjusting the time interval target with the head of the front vehicle. The reaction behaviors of the group A vehicles are set to be tight, the group B vehicles are set to be courtesy, and the group C vehicles are set to be ignored.
xFront side(t),xRear end(t) respectively represents the positions of the front vehicle and the following vehicle at the time t,
representing the first derivative of displacement to the event, i.e. the vehicle speed of the front and rear vehicles;
representing the second derivative of displacement with respect to time, i.e. the front and rear vehicle acceleration. T represents the reaction time of the driver. λ is the coefficient of sensitivity: i.e. the intensity of the driver's reaction to the speed difference.
In the formula: a isl,mIs constant, usually determined by simulation experiments; l is more than or equal to 0 and m is more than or equal to 0 as parameters:
s302, a plurality of driving styles are generated based on the sensitivity coefficient formula.
Sensitivity coefficient when driving style is A
al,m＝0.6,l＝0.1,m＝2.5
Sensitivity coefficient when driving style is B
al,m＝0.8,l＝0.7,m＝2.5
Coefficient of sensitivity for driving style C
al,m＝0.1,l＝0.3,m＝2.7
S202 generates a following fleet model based on a plurality of vehicles of different driving style models.
The following model that satisfies the condition is:
the specific mode is as follows:
when the following vehicle finds that the target vehicle is accelerated in response, the headway of the following vehicle and the headway of the front vehicle are in a first interval. When the following vehicle finds that the reaction of the target vehicle is acceleration, namely the driving style is A, the head time distance between the following vehicle and the front vehicle is reduced: the above models need to be satisfied simultaneously
When the following vehicle finds that the target vehicle responds to deceleration, the time interval between the following vehicle and the front vehicle is in a second interval; when the following vehicle finds that the target vehicle reacts to be decelerated, namely the driving style is B, the time interval between the following vehicle and the front vehicle is increased: the above models need to be satisfied simultaneously
When the following vehicle finds that the target vehicle reacts to keep the original speed, the time distance between the following vehicle and the front vehicle is in a third interval:
when the following vehicle finds that the target vehicle reacts to keep the original speed and the driving style is C: the above models need to be satisfied at the same time
The first interval is smaller than a third interval, and the third interval is smaller than the second interval.
When the test target vehicle doubling request disappears, the headway of the following vehicle is kept in the third interval.
When the test target vehicle doubling request disappears, the following vehicle recovers the original driving behavior, namely
When the test target vehicle starts the doubling action, and part of the vehicle body enters the lane, the following vehicle regards the test target vehicle as a front vehicle and calculates according to the original driving behavior, namely, the following vehicle meets the following requirements:
s102, generating a following motorcade model on a side lane of the test vehicle by applying an automatic driving control algorithm, and injecting the following motorcade model into the test vehicle for testing through an RSU (remote navigation Unit);
the RSU is an english abbreviation of Road Side Unit, and the interpretation is the meaning of a roadside Unit, and is a device which is installed in the roadside in the ETC system, and communicates with an On Board Unit (OBU) by using a dsrc (dedicated Short Range communication) technology to realize vehicle identification and electronic deduction. In the management of expressways and parking lots, RSUs are installed on the road sides, and unattended fast special lanes are established. The RSU is designed according to the national standard GB20851, and the communication frequency is 5.8 GHz. The RSU consists of a high-gain directional beam control read-write antenna and a radio frequency controller. The high-gain directional beam control read-write antenna is a microwave transceiver module and is responsible for transmitting/receiving, modulating/demodulating, coding/decoding, encrypting/decrypting signals and data; the radio frequency controller is a module for controlling data transmission and reception and processing information transmission and reception to an upper computer. An RSU typically has 4 PSAM card sockets. In the management of highways and parking lots, the DSRC technology is adopted to realize the non-stop fast lane. From 2013, all military vehicles are provided with OBUs, and vehicle identity recognition is achieved through the DSRC technology.
S103, the test vehicle sends a wire-doubling request to a following motorcade, detects and identifies head time distance feedback in the following motorcade, and performs wire-doubling operation when a safe wire-doubling opportunity occurs;
the method comprises the following specific steps:
s401, preliminarily selecting a merging position by a test vehicle according to the headway of a fleet;
s402, keeping the front vehicle at a position with a time interval of 1.5 seconds from the vehicle head, and turning on a steering lamp;
s403, evaluating the behavior of the rear vehicle, and if the rear vehicle does not decelerate, searching a new doubling position;
and S404, if the rear vehicle has a deceleration behavior, starting steering and merging when the headway time is in a second interval.
And S104, evaluating the parallel operation on the physical engine of the virtual simulation platform.
The test vehicle preliminarily selects a doubling position according to the headway time of the motorcade (>2.5 seconds), keeps the position of the headway time 1.5 seconds with the front vehicle, turns on the steering lamp, starts to evaluate the behavior of the rear vehicle, searches for a new doubling position through acceleration and deceleration if the rear vehicle has no courtesy action (the headway time is reduced), and starts to turn to the doubling when the headway time is >3.5 seconds if the rear vehicle has the deceleration behavior.
After the parallel-line test based on the heuristic evaluation strategy is carried out in the simulated high-density traffic flow, the motor vehicles partially have the capability of driving in the high-density traffic flow under the real driving environment to finish the parallel-line operation. And the method is different from the accelerating and decelerating merging operation in a simple scene, uses a turn signal lamp to express the turning intention, evaluates the courtesy behavior of a merging entry point vehicle, and selects a proper time to perform the merging operation, so that the method is more suitable for a real scene.
While the invention has been described with reference to a preferred embodiment, it will be understood by those skilled in the art that various changes in form and detail may be made therein without departing from the spirit and scope of the invention as defined by the appended claims.
Claims (6)
1. A merging method based on a heuristic evaluation strategy in a high-density virtual traffic flow is characterized in that,
the method comprises the following steps: constructing a following motorcade model;
generating a following motorcade model on a side lane of the test vehicle by applying an automatic driving control algorithm, and injecting the following motorcade model into the test vehicle for testing through an RSU (remote navigation Unit);
the test vehicle sends a doubling request to a following motorcade, detects and identifies head time distance feedback in the following motorcade, and performs doubling operation when a safe doubling opportunity occurs;
and evaluating the parallel operation on a physical engine of the virtual simulation platform.
2. The merging method for evaluating policy based on heuristics in high-density virtual traffic streams according to claim 1,
the specific steps of constructing the following motorcade model are as follows:
establishing a driving style model;
a following fleet model is generated based on a plurality of vehicles of different driving style models.
3. The merging method for evaluating policy based on heuristics in high-density virtual traffic flow according to claim 2,
the specific steps for establishing the driving style model are as follows:
constructing a sensitivity coefficient formula;
and generating a plurality of driving styles based on the sensitivity coefficient formula.
4. The merging method for evaluating policy based on heuristics in high-density virtual traffic flow according to claim 2,
the specific way for generating the following fleet model based on the vehicles with different driving style models is as follows:
when the following vehicle finds that the target vehicle is accelerated in response, the time interval between the following vehicle and the front vehicle is in a first interval;
when the following vehicle finds that the target vehicle responds to deceleration, the time interval between the following vehicle and the front vehicle is in a second interval;
when the following vehicle finds that the target vehicle reacts to keep the original speed, the time distance between the following vehicle and the front vehicle is in a third interval:
the first interval is smaller than a third interval, and the third interval is smaller than the second interval.
5. The merging method for evaluating strategies based on heuristics in high-density virtual traffic streams as recited in claim 4,
the specific way of generating the following fleet model based on the vehicles with different driving style models further comprises the following steps: when the test target vehicle doubling request disappears, the headway of the following vehicle is kept in the third interval.
6. The merging method for evaluating policy based on heuristics in high-density virtual traffic streams according to claim 1,
the test vehicle sends a doubling request to a following motorcade, detects and identifies the head time distance feedback in the following motorcade, and when a safe doubling opportunity occurs, the concrete steps of doubling operation are as follows:
the test vehicle preliminarily selects a doubling position according to the headway time of the fleet;
keeping the front vehicle at a position with a time interval of 1.5 seconds from the vehicle head, and turning on a steering lamp;
evaluating the behavior of the rear vehicle, and searching a new doubling position if the rear vehicle does not decelerate;
and if the rear vehicle has a deceleration behavior, starting steering and merging when the headway time is in the second interval.
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Patent Citations (5)
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