CN114882705B - Freight vehicle interactive game lane change decision method based on lane change decision system - Google Patents
Freight vehicle interactive game lane change decision method based on lane change decision system Download PDFInfo
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- CN114882705B CN114882705B CN202210596647.XA CN202210596647A CN114882705B CN 114882705 B CN114882705 B CN 114882705B CN 202210596647 A CN202210596647 A CN 202210596647A CN 114882705 B CN114882705 B CN 114882705B
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- 238000011156 evaluation Methods 0.000 claims abstract description 37
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- 230000001133 acceleration Effects 0.000 claims abstract description 25
- 238000004458 analytical method Methods 0.000 claims abstract description 8
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/01—Detecting movement of traffic to be counted or controlled
- G08G1/052—Detecting movement of traffic to be counted or controlled with provision for determining speed or overspeed
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/09—Arrangements for giving variable traffic instructions
- G08G1/0962—Arrangements for giving variable traffic instructions having an indicator mounted inside the vehicle, e.g. giving voice messages
- G08G1/0967—Systems involving transmission of highway information, e.g. weather, speed limits
- G08G1/096708—Systems involving transmission of highway information, e.g. weather, speed limits where the received information might be used to generate an automatic action on the vehicle control
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Abstract
The invention provides a freight vehicle interactive game lane change decision method based on a lane change decision system. The invention comprises a lane change decision system. The vehicle networking information platform acquires state information data of an automatic driving vehicle and surrounding vehicles in real time, preprocesses the speed of the vehicle to obtain the speed of the preprocessed vehicle, and simultaneously obtains the position information of the vehicle; judging whether the lane change of the automatic driving vehicle meets the minimum safe distance condition or not according to the acquired state information; establishing a utility evaluation function of the vehicle; the method comprises the steps that through interaction behavior game analysis of an automatic driving vehicle and surrounding vehicles, a balanced behavior solution is obtained based on a stackelberg game; and judging whether the speed meets the constraint condition, and then adopting the obtained acceleration to change the track or giving up the change of the track. The invention reduces the occurrence rate of traffic safety accidents caused by dangerous lane change behavior and improves the transportation benefit.
Description
Technical Field
The invention relates to the field of intelligent traffic control, in particular to a freight vehicle interactive game lane change decision method based on a lane change decision system.
Background
In a complex environment of man-driven/unmanned hybrid driving formed by interactive permeation of intelligent network vehicles and manual driving vehicles, the driving vehicles have independence, restriction and transmissibility; the intelligent automatic driving and internet connection communication technologies enable the internet connection automobile to have the characteristics of high-precision sensing, high-speed communication and ultra-fast reaction, and compared with the traditional manual driving automobile, the intelligent automatic driving and internet connection communication technology has the advantage that sensing and reaction time is greatly shortened. Intelligent networking technology has been the focus of research in the field of intelligent transportation, and in recent years, with the increasing prominence of problems such as urban pollution, traffic jams, traffic accidents, etc., the research of intelligent networking technology has become particularly important. The Society of Automotive Engineers (SAE) classifies intelligent vehicles into six classes according to the degree of vehicle intelligence: and the system is free of automation, driving support, partial automation, conditional automation, high automation and full automation. While research into intelligent networked autonomous vehicles has been initiated since the last century, during which countless difficulties have been overcome, the popularity of truly fully automated autonomous vehicles has also required long research experimentation, and human-driven traditional vehicles remain. Thus, for a long time in the future, there will be a mixed traffic environment where a conventional Human Vehicle (HV) and an intelligent networked automatic driving vehicle (Connected autonomous vehicle, CAV) coexist. CAV driving behavior research needs to fully consider urban environments and traffic scenes with higher requirements such as real-time and reliable information, controllable driving assistance and the like. The characteristics of different vehicle types, various cargo carrying forms, coexistence of traditional power and new energy, and the like of the freight vehicle group exist for a long time in the future, and the conventional freight vehicle lane change key theory and method have the problems of vehicle homogenization, time, space, task constraint idealization, and the like, so that the running safety and the transportation efficiency of the vehicle are difficult to realize optimal solution.
Disclosure of Invention
In order to solve the technical problems, the invention provides a freight vehicle interactive game lane change decision method based on a lane change decision system.
The lane change decision system comprises: the system comprises a cloud server, an automobile microcomputer controller, a distance sensor, a speed sensor, a vehicle-mounted display, a roadbed signal receiver, a roadbed signal transmitter, a cloud wireless transmission module and an Internet of vehicles information platform;
the automobile microcomputer controller is respectively connected with the distance sensor, the speed sensor, the vehicle-mounted display, the roadbed signal receiver and the cloud wireless transmission module in sequence; the cloud wireless transmission module is connected with the cloud server in a wireless communication mode; the roadbed signal receiver is connected with the roadbed signal transmitter in a wireless communication mode; the Internet of vehicles information platform is connected with the cloud server in a wireless communication mode.
The method for making the lane change decision in the vehicle-carrying interactive game comprises the following steps:
Step 1: the vehicle networking information platform acquires state information data of an automatic driving vehicle and surrounding vehicles in real time, preprocesses the speed of the vehicle to obtain the speed of the preprocessed vehicle, and simultaneously obtains the position information of the vehicle;
step 2: judging whether the lane change of the automatic driving vehicle meets the minimum safe distance condition or not according to the acquired state information;
Step 3: establishing a utility evaluation function of the vehicle;
step 4: the method comprises the steps that through interaction behavior game analysis of an automatic driving vehicle and surrounding vehicles, a balanced behavior solution is obtained based on a stackelberg game;
step 5: judging whether the speed meets the constraint condition or not, and then adopting the obtained acceleration to change the track or abandon the track;
preferably, in the step 1, the speed of the vehicle is collected by the speed sensor, and the speed of the vehicle is uploaded to the cloud server by the cloud wireless transmission module; the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are acquired through the distance sensor, and the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are uploaded to the cloud server through the cloud wireless transmission module;
The real-time acquisition of the speed of the automatic driving vehicle in the step 1 is as follows:
the speed of the vehicle is: v i, i e [1, N ], N being the number of sampling instants, v i representing the vehicle speed at the i-th sampling instant;
The preprocessing of the speed of the vehicle in step 1 is as follows:
Processing invalid value of the speed of the vehicle by a data preprocessing mode, and if v i is null or missing, making
vi＝0；
Wherein i epsilon [1, N ], N is the number of sampling moments, v i represents the vehicle speed at the ith sampling moment;
The speed of the pretreated vehicle in the step 1 is as follows: v i, i e [1, N ], N is the number of sampling moments, V i represents the vehicle speed at the ith sampling moment;
in the daily running of the vehicle, the roadbed signal receiver receives the road type w transmitted by the roadbed signal transmitter, and the vehicle microcomputer controller collects the data and uploads the data to the cloud server through the cloud wireless transmission module, so that the cloud server counts the distance between the vehicle and the distance sensor under the road type w according to the running data of the vehicle.
Preferably, in the step 2, the determining whether the lane change of the freight vehicle meets the minimum safe distance condition specifically includes:
S(0)＝Δx-L
Wherein S (0) is the actual distance between the freight vehicle and the front vehicle of the original lane
Δx is the distance from the front right sensor of the freight vehicle to the front vehicle of the original lane
L is the length of the body of the freight vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
V 1 is the initial speed of the freight vehicle
A y max is the transverse maximum acceleration of the freight vehicle during transverse lane change
A x max is the maximum acceleration of the longitudinal acceleration of the freight vehicle
W is the transverse distance from the right side of the freight vehicle to the lane intersection line
T L is the time for the freight vehicle to reach the intersection of the primary lane and the target lane when changing lanes
D is the width of the lane
Wherein, the calculation mode of t L is as follows:
Based on sine function lateral acceleration model
Order the
Then when y=0, t L =arg (y)
Wherein C is the width of the freight vehicle
If S MSD is less than or equal to S (0), the channel switching can be carried out, and if not, the channel switching is abandoned.
Preferably, the utility evaluation function of the vehicle in step 3 is:
U＝Usafe+Up+UV
Wherein U is the utility evaluation function of the vehicle
U safe is a safety benefit function of the vehicle
U p is a lane change success rate profit function of the vehicle
U V is a running benefit function of the vehicle
The benefit evaluation function comprises three benefit indexes of safety benefit, channel changing success rate benefit and running benefit;
Wherein U safe is a safety benefit function of the vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
Wherein a is the acceleration adopted by the freight vehicle, v * is the updated speed of the target lane vehicle
Wherein U V is the time-dependent benefit;
v 1 is the initial speed of the freight vehicle;
v 2 is the average speed of the target lane;
Preferably, in the step 4, the analysis of the interaction behavior game between the automatically driven vehicle and the surrounding vehicles is performed, and the equilibrium behavior solution is obtained based on the stackelberg game, which specifically includes:
when the lane change freight vehicle is the leader and the target lane vehicle is the follower, it can be known that
Wherein U lv is the leader's utility evaluation function
U fv is the utility evaluation function of the follower
The acceleration of the freight vehicle when the deviation is 0 according to the return evaluation function of the lane change vehicle, namelyThen getWill/>Substituting, and obtaining the updated speed of the target lane vehicle when the partial derivative is 0 according to the vehicle gain evaluation function behind the target lane, namely/>Then get/>Simultaneously, a (a lv,v*) can be obtained;
Preferably, in step 5, by determining whether the speed meets the constraint condition, the acceleration is obtained to change the track or give up the change of the track, which specifically includes:
When (when) And when the lane change vehicle gives up lane change.
When (when)When the lane changing vehicle changes lanes;
wherein, Is a utility evaluation function of the leader before lane change;
is a utility evaluation function of a track change follower;
U lv is the leader's utility evaluation function;
u fv is the utility evaluation function of the follower.
The beneficial effects of the invention are as follows: the invention provides a method and a system for deciding a traffic safety accident caused by the interactive game of a freight vehicle in a complex environment, which aim to reduce the occurrence rate of the traffic safety accident caused by dangerous lane changing, so that the vehicle can execute safer lane changing, the transportation benefit is improved under the condition of ensuring the safety benefit, and meanwhile, the vehicle running data recorded by a cloud network also provides data support for accident cause analysis and responsibility judgment after the traffic accident occurs.
Drawings
Fig. 1: a flow chart of a method of an embodiment of the invention;
fig. 2: the driving channel change scene graph provided by the 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.
The following describes embodiments of the present invention with reference to fig. 1 to 2:
fig. 1 is a schematic diagram of a system structure of the present invention, which is a method for making a lane change decision for a freight vehicle interactive game based on a lane change decision system.
The lane change decision system comprises: the system comprises a cloud server, an automobile microcomputer controller, a distance sensor, a speed sensor, a vehicle-mounted display, a roadbed signal receiver, a roadbed signal transmitter, a cloud wireless transmission module and an Internet of vehicles information platform;
the automobile microcomputer controller is respectively connected with the distance sensor, the speed sensor, the vehicle-mounted display, the roadbed signal receiver and the cloud wireless transmission module in sequence; the cloud wireless transmission module is connected with the cloud server in a wireless communication mode; the roadbed signal receiver is connected with the roadbed signal transmitter in a wireless communication mode; the Internet of vehicles information platform is connected with the cloud server in a wireless communication mode.
The automobile microcomputer controller is arranged on a vehicle and used for integrating information acquired from the speed sensor, the distance sensor and the roadbed signal receiver, reading instructions sent by the cloud server and executing the instructions;
the cloud server is used for storing, sharing and collecting real-time running data of the vehicle, which are acquired from the distance sensor, the speed sensor and the roadbed signal receiver on the vehicle, and comprehensively processing and analyzing the collected real-time running data of the vehicle to obtain habit and inertia running data of the vehicle under different road types, wherein the accident response time of a driver and the braking time and the braking distance of the vehicle under different roads; judging whether the running of the vehicle is threatened according to the current collected real-time running data of the vehicle, prompting and warning a driver, and assisting the vehicle to run more safely;
The cloud wireless transmission module is arranged on the vehicle and used for uploading vehicle driving data to the cloud server and receiving data and instructions of the cloud server;
The distance sensor is arranged at the middle bumper of the front end of the vehicle and is used for detecting the following distance of the vehicle;
The speed sensor is arranged on the transmission output shaft and used for acquiring the running speed of the vehicle;
the vehicle-mounted display is arranged in the middle of the automobile center console, is used for providing information for a driver, and is in the form of sound and text images;
the roadbed signal transmitter is arranged on a road and paved along the road and is used for providing road types for vehicles;
The roadbed signal receiver is arranged at the upper parts of left and right searchlights in front of the vehicle and is used for receiving the road type provided by the roadbed signal transmitter;
the road type is: curves, crossroads, speed-limiting road sections, congestion road sections, accident-prone areas, landslide road sections and the like.
The automobile microcomputer controller is selected as a CP80617; the roadbed signal receiver selects BF-686; the roadbed signal emitters are selected from 25-0571-0059; the speed sensor is selected from Bi5-M18-AZ3X; the distance sensor is TF02; the vehicle-mounted display is SPD-043-AIO; the cloud wireless transmission module is 82C250.
The method for making the lane change decision in the vehicle-carrying interactive game comprises the following steps:
The method for making the lane change decision in the vehicle-carrying interactive game comprises the following steps:
Step 1: the vehicle networking information platform acquires state information data of an automatic driving vehicle and surrounding vehicles in real time, preprocesses the speed of the vehicle to obtain the speed of the preprocessed vehicle, and simultaneously obtains the position information of the vehicle;
In the step 1, the speed of the vehicle is collected through the speed sensor, and the speed of the vehicle is uploaded to the cloud server through the cloud wireless transmission module; the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are acquired through the distance sensor, and the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are uploaded to the cloud server through the cloud wireless transmission module;
The real-time acquisition of the speed of the automatic driving vehicle in the step 1 is as follows:
The speed of the vehicle is: v i, i e [1, N ], n=1024 is the number of sampling instants, v i represents the vehicle speed at the i-th sampling instant;
The preprocessing of the speed of the vehicle in step 1 is as follows:
Processing invalid value of the speed of the vehicle by a data preprocessing mode, and if v i is null or missing, making
vi＝0；
Wherein i epsilon [1, N ], N is the number of sampling moments, v i represents the vehicle speed at the ith sampling moment;
The speed of the pretreated vehicle in the step 1 is as follows: v i, i e1, N, n=1024 is the number of sampling instants, V i represents the vehicle speed at the i-th sampling instant;
in the daily running of the vehicle, the roadbed signal receiver receives the road type w transmitted by the roadbed signal transmitter, and the vehicle microcomputer controller collects the data and uploads the data to the cloud server through the cloud wireless transmission module, so that the cloud server counts the distance between the vehicle and the distance sensor under the road type w according to the running data of the vehicle.
Step 2: judging whether the lane change of the automatic driving vehicle meets the minimum safe distance condition or not according to the acquired state information;
in the step 2, whether the change of the freight vehicle meets the minimum safe distance condition is determined specifically as follows:
S(0)＝Δx-L
Wherein S (0) is the actual distance between the freight vehicle and the front vehicle of the original lane
Δx is the distance from the front right sensor of the freight vehicle to the front vehicle of the original lane
L is the length of the body of the freight vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
V 1 is the initial speed of the freight vehicle
A y max is the transverse maximum acceleration of the freight vehicle during transverse lane change
A x max is the maximum acceleration of the longitudinal acceleration of the freight vehicle
W is the transverse distance from the right side of the freight vehicle to the lane intersection line
T L is the time for the freight vehicle to reach the intersection of the primary lane and the target lane when changing lanes
D is the width of the lane
Wherein, the calculation mode of t L is as follows:
Based on sine function lateral acceleration model
Order the
Then when y=0, t L =arg (y)
Wherein C is the width of the freight vehicle
If S MSD is less than or equal to S (0), the channel switching can be carried out, and if not, the channel switching is abandoned.
Step 3: establishing a utility evaluation function of the vehicle;
the utility evaluation function of the vehicle in step3 is:
U＝Usafe+Up+UV
Wherein U is the utility evaluation function of the vehicle
U safe is a safety benefit function of the vehicle
U p is a lane change success rate profit function of the vehicle
U V is a running benefit function of the vehicle
The benefit evaluation function comprises three benefit indexes of safety benefit, channel changing success rate benefit and running benefit;
Wherein U safe is a safety benefit function of the vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
Wherein a is the acceleration adopted by the freight vehicle, v * is the updated speed of the target lane vehicle
Wherein U V is the time-dependent benefit;
v 1 is the initial speed of the freight vehicle;
v 2 is the average speed of the target lane;
step 4: the method comprises the steps that through interaction behavior game analysis of an automatic driving vehicle and surrounding vehicles, a balanced behavior solution is obtained based on a stackelberg game;
and step 4, obtaining a balanced behavior solution based on a stackelberg game through interaction behavior game analysis of the automatic driving vehicle and surrounding vehicles, wherein the balanced behavior solution specifically comprises the following steps:
when the lane change freight vehicle is the leader and the target lane vehicle is the follower, it can be known that
Wherein U lv is the leader's utility evaluation function
U fv is the utility evaluation function of the follower
The acceleration of the freight vehicle when the deviation is 0 according to the return evaluation function of the lane change vehicle, namelyThen getWill/>Substituting, and obtaining the updated speed of the target lane vehicle when the partial derivative is 0 according to the vehicle gain evaluation function behind the target lane, namely/>Then get/>Simultaneously, a (a lv,v*) can be obtained;
step 5: judging whether the speed meets the constraint condition or not, and then adopting the obtained acceleration to change the track or abandon the track;
In the step 5, judging whether the speed meets the constraint condition, and adopting the obtained acceleration to change the track or give up the change of the track, specifically:
When (when) And when the lane change vehicle gives up lane change.
When (when)When the lane changing vehicle changes lanes;
wherein, Is a utility evaluation function of the leader before lane change;
is a utility evaluation function of a track change follower;
U lv is the leader's utility evaluation function;
u fv is the utility evaluation function of the follower.
It should be understood that parts of the specification not specifically set forth herein are all prior art.
Although terms such as cloud server, car microcomputer controller, distance sensor, speed sensor, on-board display, roadbed signal receiver, roadbed signal transmitter, cloud wireless transmission module are used more herein, the possibility of using other terms is not excluded. These terms are only used to facilitate a more complete description of the nature of the invention and should be construed as requiring no additional limitations whatsoever.
It should be understood that the foregoing description of the preferred embodiments is not intended to limit the scope of the invention, but rather to limit the scope of the claims, and that those skilled in the art can make substitutions or modifications without departing from the scope of the invention as set forth in the appended claims.
Claims (2)
1. A freight vehicle interactive game lane change decision method based on a lane change decision system is characterized in that,
The lane change decision system comprises: the system comprises a cloud server, an automobile microcomputer controller, a distance sensor, a speed sensor, a vehicle-mounted display, a roadbed signal receiver, a roadbed signal transmitter, a cloud wireless transmission module and an Internet of vehicles information platform;
The automobile microcomputer controller is respectively connected with the distance sensor, the speed sensor, the vehicle-mounted display, the roadbed signal receiver and the cloud wireless transmission module in sequence; the cloud wireless transmission module is connected with the cloud server in a wireless communication mode; the roadbed signal receiver is connected with the roadbed signal transmitter in a wireless communication mode; the Internet of vehicles information platform is connected with the cloud server in a wireless communication mode;
the method for deciding the interactive game lane change of the freight vehicle comprises the following steps:
Step 1: the vehicle networking information platform acquires state information data of an automatic driving vehicle and surrounding vehicles in real time, preprocesses the speed of the vehicle to obtain the speed of the preprocessed vehicle, and simultaneously obtains the position information of the vehicle;
step 2: judging whether the lane change of the automatic driving vehicle meets the minimum safe distance condition or not according to the acquired state information;
Step 3: establishing a utility evaluation function of the vehicle;
step 4: the method comprises the steps that through interaction behavior game analysis of an automatic driving vehicle and surrounding vehicles, a balanced behavior solution is obtained based on a stackelberg game;
step 5: judging whether the speed meets the constraint condition or not, and then adopting the obtained acceleration to change the track or abandon the track;
in the step 2, whether the change of the freight vehicle meets the minimum safe distance condition is determined specifically as follows:
S(0)＝Δx-L
Wherein S (0) is the actual distance between the freight vehicle and the front vehicle of the original lane
Δx is the distance from the front right sensor of the freight vehicle to the front vehicle of the original lane
L is the length of the body of the freight vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
V 1 is the initial speed of the freight vehicle
A y max is the transverse maximum acceleration of the freight vehicle during transverse lane change
A x max is the maximum acceleration of the longitudinal acceleration of the freight vehicle
W is the transverse distance from the right side of the freight vehicle to the lane intersection line
T L is the time for the freight vehicle to reach the intersection of the primary lane and the target lane when changing lanes
D is the width of the lane
Wherein, the calculation mode of t L is as follows:
Based on sine function lateral acceleration model
Order the
Then when y=0, t L =arg (y)
Wherein C is the width of the freight vehicle
When S MSD is less than or equal to S (0) and is established, the channel switching can be carried out, and if not, the channel switching is abandoned;
the utility evaluation function of the vehicle in step3 is:
U＝Usafe+Up+UV
Wherein U is a utility evaluation function of the vehicle;
U safe is a safety benefit function for the vehicle;
u p is a lane change success rate profit function of the vehicle;
u V is a travel benefit function of the vehicle;
The utility evaluation function comprises three benefit indexes of safety benefit, channel changing success rate benefit and running benefit;
Wherein U safe is a safety benefit function of the vehicle
S MSD is the minimum safety distance between the freight vehicle and the front vehicle of the original lane when changing lanes
Wherein a is the acceleration adopted by the freight vehicle, v * is the updated speed of the target lane vehicle
Wherein U V is the time-dependent benefit;
v 1 is the initial speed of the freight vehicle;
v 2 is the average speed of the target lane;
and step 4, obtaining a balanced behavior solution based on a stackelberg game through interaction behavior game analysis of the automatic driving vehicle and surrounding vehicles, wherein the balanced behavior solution specifically comprises the following steps:
when the lane change freight vehicle is the leader and the target lane vehicle is the follower, it can be known that
Wherein U lv is the leader's utility evaluation function
U fv is the utility evaluation function of the follower
The acceleration of the freight vehicle when the deviation is 0 according to the return evaluation function of the lane change vehicle, namelyThen getWill/>Substituting, and obtaining the updated speed of the target lane vehicle when the partial derivative is 0 according to the vehicle gain evaluation function behind the target lane, namely/>Then get/>Simultaneously, a (a lv,v*) can be obtained;
In the step 5, judging whether the speed meets the constraint condition, and adopting the obtained acceleration to change the track or give up the change of the track, specifically:
When (when) When the lane change vehicle gives up lane change;
When (when) When the lane changing vehicle changes lanes;
wherein, Is a utility evaluation function of the leader before lane change;
is a utility evaluation function of a track change follower;
U lv is the leader's utility evaluation function;
u fv is the utility evaluation function of the follower.
2. The lane change decision system-based interactive game lane change decision method for the freight vehicle according to claim 1, wherein in the step 1, the speed of the vehicle is collected by the speed sensor and uploaded to the cloud server by the cloud wireless transmission module; the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are acquired through the distance sensor, and the distance between the front vehicle and the lane intersection line and the transverse distance between the front vehicle and the lane intersection line are uploaded to the cloud server through the cloud wireless transmission module;
The real-time acquisition of the speed of the automatic driving vehicle in the step 1 is as follows:
The speed of the vehicle is: v i, i e [1, N ], N being the number of sampling instants, v i representing the vehicle speed at the i-th sampling instant;
The preprocessing of the speed of the vehicle in step 1 is as follows:
Performing invalid value processing on the speed of the vehicle by a data preprocessing mode, and if v i is a null value or is missing, making v i =0;
Wherein i epsilon [1, N ], N is the number of sampling moments, v i represents the vehicle speed at the ith sampling moment;
the speed of the pretreated vehicle in the step 1 is as follows: v i, i e [1, N ], N is the number of sampling moments, V i represents the vehicle speed at the ith sampling moment;
In the daily running of the vehicle, the roadbed signal receiver receives the road type w transmitted by the roadbed signal transmitter, and the vehicle microcomputer controller collects the data and uploads the data to the cloud server through the cloud wireless transmission module, so that the cloud server counts the distance between the vehicle and the distance sensor under the road type w according to the running data of the vehicle.
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