CN114743369A - Intelligent vehicle formation method based on path contact ratio - Google Patents
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/20—Monitoring the location of vehicles belonging to a group, e.g. fleet of vehicles, countable or determined number of vehicles
- G08G1/202—Dispatching vehicles on the basis of a location, e.g. taxi dispatching
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/22—Platooning, i.e. convoy of communicating vehicles
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
- H04L67/00—Network arrangements or protocols for supporting network services or applications
- H04L67/01—Protocols
- H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
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- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/40—Services specially adapted for particular environments, situations or purposes for vehicles, e.g. vehicle-to-pedestrians [V2P]
Abstract
An intelligent vehicle formation method based on path contact ratio belongs to the technical field of vehicle-road cooperation, and is characterized in that proper vehicles are screened out to run in a formation mode according to the contact ratio of different vehicle paths, so that the fuel economy of a vehicle formation is improved; the condition that vehicles are frequently grouped and are separated due to the fact that the coincident path is short is avoided, and the safety and the driving stability of the vehicle queue are improved. According to the method, the proper vehicles are screened out to run in a queue according to the overlap ratio of different vehicle paths, the problem that the vehicle formation is too long under the condition that the vehicles are not screened out to enter the queue is solved, and the road traffic capacity is improved.
Description
Technical Field
The invention belongs to the technical field of vehicle-road cooperation, and particularly relates to an intelligent formation method for trucks under the background of an expressway.
Background
The vehicle-road cooperation technology is a new generation internet technology for effectively interacting real-time information between vehicles and roads through wireless communication and internet technologies. The traffic safety can be better guaranteed, and the road traffic capacity is improved. The vehicle-road cooperation provides a foundation for safe and reliable in-line running under the condition that the distance between vehicles is small. The vehicle can receive surrounding vehicles and road condition information in real time through a vehicle-road cooperation technology, and the distance between the vehicles is shortened on the premise of ensuring the driving safety, so that a plurality of vehicles can be formed to drive. Since 85% of the aerodynamic resistance comes from the differential pressure resistance, when the vehicle keeps driving with a short following distance, the tail pressure of the front vehicle is increased, the head pressure of the rear vehicle is reduced, and the front-rear and vehicle alignment aerodynamic resistance is reduced. The trucks can save energy consumption and reduce exhaust emission by reducing aerodynamic resistance when running in a queue on a highway.
The existing vehicle formation method mainly focuses on realizing formation driving and control of vehicles through vehicles and communication equipment on roads, does not consider the influence of the ratio of the common driving mileage of the vehicles in a queue to the total driving mileage of each vehicle on fuel consumption, and has relatively poor fuel saving effect in the queue. Meanwhile, the conventional vehicle formation method does not consider the negative influence of too long formation on the queue running and road traffic capacity, has relatively simple functions and is difficult to deal with a relatively complex traffic environment.
Disclosure of Invention
The technical problem to be solved by the invention is as follows: the method comprises the steps of providing an intelligent vehicle formation method based on path contact ratio, and solving the problem that the ratio of the common driving mileage of the vehicles in a queue to the total driving mileage of each vehicle has no influence on the fuel consumption; the fuel economy, the stability and the road traffic capacity of the queue are reduced; the method can adapt to more complex traffic environment, improve the utilization rate of traffic roads, and improve the safety, stability, fuel economy and road traffic capacity of the queue.
An intelligent vehicle formation method based on path contact ratio is characterized in that: comprises the following steps which are sequentially carried out,
firstly, vehicles with a queuing intention send a queuing running instruction through an internet-of-vehicles communication module, a running path is planned by a vehicle environment sensing module and the internet-of-vehicles communication module, queuing running vehicles are screened by taking the path contact ratio as an index, and the vehicle with the largest expected running mileage is selected as a queue running pilot vehicle;
secondly, numbering the vehicles by a decision control module of the pilot vehicle according to the sequence of the predicted driving mileage of the vehicles from large to small, and driving in line according to the sequence of the vehicle numbers;
thirdly, real-time monitoring of the queue predicted running road conditions is carried out through a piloting vehicle environment sensing module and an internet of vehicles communication module, the queue real-time vehicle speed is decided according to road information monitored by the piloting vehicle, state parameters of all vehicles are shared in real time through the internet of vehicles communication module, and all vehicle decision control modules finish control over the speed of a fleet of vehicles;
fourthly, the distances between the vehicle-mounted radars of the other vehicle environment sensing modules and the front vehicle are monitored in real time except for the pilot vehicle in the queue, and are compared with the preset distance calculated by the vehicle decision control module according to the vehicle speed and the vehicle type, the real-time distance is greater than the preset distance, acceleration control is carried out, and when the real-time distance is smaller than the preset distance, deceleration control is carried out;
fifthly, the pilot vehicle monitors the information of the rest vehicles in real time through the internet of vehicles communication module, the rest vehicles send out an enqueue application, the vehicles are screened according to the coincidence degree of the predicted driving path of the vehicle to be added and the predicted driving path of the pilot vehicle, the predicted driving mileage of the vehicle to be added is compared with the predicted driving mileage of other vehicles of the fleet and is numbered, and the vehicles are driven in a team according to the newly generated number;
step six, the piloted vehicles are monitored in real time through the internet of vehicles communication module, if the vehicles arrive at the destination or the vehicles leave the queue, the vehicle numbers of the vehicles are deleted, and the rear vehicles of the vehicles leaving the queue are numbered again through the piloted vehicle decision control module; stopping formation until the pilot vehicle reaches the destination;
therefore, the intelligent vehicle formation method based on the path contact ratio is completed.
The method for calculating the coincidence degree of the paths in the first step and the fifth step comprises the steps of calculating repeated parts in the predicted driving paths of the vehicles through a vehicle decision control module, and comparing the mileage of the coincident paths with the corresponding mileage, wherein the method specifically comprises the steps that the vehicles are not in line with one another and the beta is d/max { a, b }
Formed fleet β ═ d/max { b, c }
Wherein beta represents the coincidence degree of the paths, d represents the mileage of the coincident paths calculated by the vehicle decision control module, a represents the mileage of the paths of the vehicles added into the fleet, b represents the mileage of the paths of the vehicles added into the fleet, and c represents the mileage of the paths of the piloting vehicles of the fleet.
The vehicle networking communication module has the function of transmitting information among vehicles, other vehicles and roads in real time; the environment sensing module realizes the functions of monitoring and collecting the surrounding environment information of the vehicle through sensors such as a vehicle-mounted laser radar, a millimeter wave radar and the like; the decision control module collects information obtained by the internet of vehicles communication module and the environment sensing module, and completes vehicle screening to be enqueued, vehicle sequencing and running of the queue, and control of queue distance and vehicle speed.
Through the design scheme, the invention can bring the following beneficial effects: an intelligent vehicle formation method based on path overlap ratio screens out proper vehicles to run in a formation according to the sizes of different vehicle path overlap ratios, and is beneficial to improving the fuel economy of a vehicle formation; the condition of frequent vehicle formation and departure caused by short coincident paths is avoided, and the safety and the driving stability of the vehicle queue are improved.
Furthermore, proper vehicles are screened out to run in a queue according to the contact ratio of different vehicle paths, the problem of overlong vehicle formation under the condition that the vehicles are not screened out in a queue is avoided, and the road traffic capacity is improved.
The vehicles are arranged in formation to run according to the sequence of the predicted running mileage of the vehicles from large to small, so that the influence of the vehicles in the queue reaching the destination can be reduced, and the running stability of the vehicle queue can be improved.
Because the fuel-saving effect of the pilot vehicles is poorer than that of other vehicles when the vehicles are formed into a formation to run, the fuel-saving road sections of the pilot vehicles can be ensured to be longest according to the sequential formation running of the predicted running mileage of the vehicles from large to small, and the fuel-saving effect of each vehicle in the formation is relatively balanced.
Drawings
The invention is further described with reference to the following figures and detailed description:
FIG. 1 is a schematic block diagram of a process of an intelligent vehicle formation method based on path contact ratio.
Detailed Description
An intelligent vehicle formation method based on the coincidence degree of the paths, as shown in figure 1, comprises the following steps,
the method comprises the following steps: vehicle drivers put forward the in-line driving demands through the vehicle networking communication module, the optimal driving path is planned by each vehicle environment sensing module and the vehicle networking communication module, proper in-line driving vehicles are screened out by taking the path contact ratio as an index, and the vehicle with the largest expected driving mileage is selected out to serve as a queue piloting vehicle;
step two: the piloted vehicle decision control module numbers the vehicles according to the sequence of the predicted driving mileage of the vehicles from large to small, and the vehicles are driven in a queue according to the sequence of the vehicle numbers;
step three: the real-time monitoring of the conditions of the queue predicted running road is completed by a piloting vehicle environment sensing module and an internet of vehicles communication module, the real-time ideal vehicle speed of the queue is decided by a piloting vehicle according to road information, the state parameters of all vehicles are shared in real time by the internet of vehicles communication module, and the speed of a fleet is controlled by all vehicle decision control modules;
step four: the vehicle-mounted radars of the environment sensing modules of other vehicles except the pilot vehicle in the queue measure the distances between the vehicle-mounted radars and the front vehicle, the distances are compared with the preset distances calculated by the vehicle decision control module according to the vehicle speed, when the real-time distance is greater than the preset distance, acceleration control is carried out on the vehicle-mounted radars, and when the real-time distance is less than the preset distance, deceleration control is carried out on the vehicle-mounted radars;
step five: the method comprises the following steps that a piloting vehicle monitors whether a vehicle needs to be added into a motorcade or not in real time through a vehicle networking communication module, when the vehicle needs to be added into the motorcade, the vehicle is screened according to the coincidence degree of a predicted driving path of the added vehicle and a predicted driving path of the piloting vehicle, the predicted driving mileage of the added vehicle is compared with the predicted driving mileage of other vehicles of the motorcade and numbered, and the vehicle drives in a team according to a new number;
step six: the piloting vehicle monitors whether a vehicle arrives at a destination or applies for leaving the queue in real time, and when the vehicle arrives at the destination or applies for leaving the queue, the vehicle number of the piloting vehicle is deleted, and the rear vehicle of the piloting vehicle is renumbered;
step seven: and (5) stopping formation when the pilot vehicle reaches the destination.
The vehicle networking communication module is used for transmitting information among vehicles, other vehicles and roads in real time; the environment sensing module is used for monitoring and collecting the surrounding environment information of the vehicle through a vehicle-mounted laser radar sensor and a millimeter wave radar sensor; the decision control module is used for collecting information obtained by the internet of vehicles communication module and the environment sensing module, and finishing vehicle screening to be enqueued, queue vehicle sequencing running, and queue distance and vehicle speed control.
The first specific implementation way is as follows: the method for calculating the contact ratio of the paths in the first step and the fifth step specifically comprises the following steps: the repeated part in the predicted running path of each vehicle is calculated through a vehicle decision control module, and the mileage of the overlapped path is compared with the corresponding mileage, wherein the specific calculation method comprises the following steps:
β ═ d/max { a, b } vehicles are not in-line
Formed fleet of vehicles
Wherein beta represents the coincidence degree of the path, d represents the mileage of the coincident path calculated by the vehicle decision control module,
a represents the mileage of the route of the added vehicle, b represents the mileage of the route of the added vehicle of the motorcade, and c represents the mileage of the route of the piloting vehicle of the motorcade;
the second embodiment is as follows: the first difference between the present embodiment and the specific embodiment is: screening out proper in-line running vehicles by taking the path contact ratio as an index in the first step and the fifth step; the specific process is as follows: the accepted route overlap ratio sequence of the enqueue vehicles is reasonably adjusted according to different numbers of vehicles in the current queue, and a specific adjusting method is shown in a table I. Selecting vehicles with high path coincidence degree to be preferentially enqueued from the enqueued vehicles meeting the requirement of the table I at the same time;
TABLE 1 Path overlap ratio screening method
| Number of vehicles in queue (i) | Accepting vehicle route overlap ratio (beta) |
| i≤2 | β＞60％ |
| 2＜i≤4 | β＞70％ |
| 4＜i≤7 | β＞80％ |
| 7＜i≤10 | β＞90％ |
| i＞10 | Stopping accepting vehicle enqueues |
In particular, when the number of vehicles in the queue is more than 10, in order to prevent the influence on the stability of the queue and the road traffic capacity due to overlong queue, the queue does not receive enqueue application of other vehicles.
The present invention may be embodied in other specific forms without departing from the spirit or essential attributes thereof, and it should be understood that various changes and modifications can be effected therein by one skilled in the art without departing from the spirit and scope of the invention as defined in the appended claims.
Claims (3)
1. An intelligent vehicle formation method based on path contact ratio is characterized in that: comprises the following steps which are sequentially carried out,
firstly, vehicles with a queuing intention send a queuing running instruction through an internet-of-vehicles communication module, a running path is planned by a vehicle environment sensing module and the internet-of-vehicles communication module, queuing running vehicles are screened by taking the path contact ratio as an index, and the vehicle with the largest expected running mileage is selected as a queue running pilot vehicle;
secondly, numbering the vehicles by a decision control module of the pilot vehicle according to the sequence of the predicted driving mileage of the vehicles from large to small, and driving in line according to the sequence of the vehicle numbers;
thirdly, real-time monitoring of the queue predicted running road conditions is carried out through a piloting vehicle environment sensing module and an internet of vehicles communication module, the queue real-time vehicle speed is decided according to road information monitored by the piloting vehicle, state parameters of all vehicles are shared in real time through the internet of vehicles communication module, and all vehicle decision control modules finish control over the speed of a fleet of vehicles;
fourthly, the distances between the vehicle-mounted radars of the other vehicle environment sensing modules and the front vehicle are monitored in real time except for the pilot vehicle in the queue, and are compared with the preset distance calculated by the vehicle decision control module according to the vehicle speed and the vehicle type, the real-time distance is greater than the preset distance, acceleration control is carried out, and when the real-time distance is smaller than the preset distance, deceleration control is carried out;
fifthly, the pilot vehicle monitors the information of the rest vehicles in real time through the internet of vehicles communication module, the rest vehicles send out an enqueue application, the vehicles are screened according to the coincidence degree of the predicted driving path of the vehicle to be added and the predicted driving path of the pilot vehicle, the predicted driving mileage of the vehicle to be added is compared with the predicted driving mileage of other vehicles of the fleet and is numbered, and the vehicles are driven in a team according to the newly generated number;
step six, the piloted vehicles are monitored in real time through the internet of vehicles communication module, if the vehicles arrive at the destination or the vehicles leave the queue, the vehicle numbers of the vehicles are deleted, and the rear vehicles of the vehicles leaving the queue are numbered again through the piloted vehicle decision control module; stopping formation until the pilot vehicle reaches the destination;
therefore, the intelligent vehicle formation method based on the path contact ratio is completed.
2. The intelligent vehicle formation method based on the path coincidence degree as claimed in claim 1, wherein: the method for calculating the coincidence degree of the paths in the first step and the fifth step comprises the steps of calculating repeated parts in the predicted driving paths of the vehicles through a vehicle decision control module, and comparing the mileage of the coincident paths with the corresponding mileage, wherein the method specifically comprises the steps that the vehicles are not in line with one another and the beta is d/max { a, b }
Formed fleet β ═ d/max { b, c }
Wherein, beta represents the coincidence degree of the route, d represents the mileage of the coincident route calculated by the vehicle decision control module, a represents the mileage of the route of the added vehicle, b represents the mileage of the route of the added vehicle of the motorcade, and c represents the mileage of the route of the piloting vehicle of the motorcade.
3. The intelligent vehicle formation method based on the path coincidence degree as claimed in claim 1, wherein: the vehicle networking communication module is used for transmitting information among vehicles, other vehicles and roads in real time; the environment sensing module is used for monitoring and collecting the surrounding environment information of the vehicle through a vehicle-mounted laser radar sensor and a millimeter wave radar sensor; and the decision control module is used for collecting information obtained by the Internet of vehicles communication module and the environment sensing module, and finishing vehicle screening to be enqueued, queue vehicle sequencing and running, and queue distance and vehicle speed control.
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