CN114283594B - Special vehicle path optimization method with dynamic adjustment - Google Patents
Special vehicle path optimization method with dynamic adjustment Download PDFInfo
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Abstract
The invention discloses a dynamically-adjusted special vehicle path optimization method, which is realized by a vehicle machine module and a terminal module, and particularly, the running position of a special vehicle is detected, and the green light timing of a traffic signal lamp is adjusted, so that all intersections passed by the special vehicle can be unblocked during the special task execution period; namely, when the special vehicle executes a task, the real-time position information and the navigation information are sent, and the terminal module adjusts the green light timing of the traffic intersection signal lamps which are about to pass according to the special vehicle information. According to the invention, the time for the special vehicle to adjust the signal lamp timing is detected, so that the running time of the special vehicle is reduced, and the requirement for the special vehicle to execute the task is met.
Description
Technical Field
The invention relates to a special vehicle path optimization method in the traffic field, in particular to a dynamically adjusted special vehicle path optimization method.
Background
With the development of the automobile industry and the popularization of vehicles, the automobile keeping amount is increasing. Traffic congestion also becomes a ubiquitous phenomenon, and affects the estimated time of drivers and passengers. For some special vehicles, such as ambulances, fire engines and other special vehicles, the time is life. If the destination is not reached in time to implement effective rescue, irreparable loss can be caused.
In the process that an existing special vehicle executes a task, when the special vehicle executing the task moves to a destination and a traffic signal lamp is a red light, the special vehicle often cannot move to the destination in time due to the influence of traffic flow and the like in a road. This is a non-negligible drag factor for the efficiency with which a particular vehicle performs its task.
In the prior art, a method of assisting guidance of vehicle driving and spontaneous lane giving or emergency lane passing of a driver by traffic managers is generally used for providing conditions for smooth driving of special vehicles, but certain problems exist, for example, certain time is needed for the traffic managers to assist in guiding the vehicles to each intersection, and sometimes, advance planning or advance deployment of a large amount of manpower is needed, so that the time is long and inconvenient; drivers give way by a spontaneous '45-degree way giving method', vehicles on two lanes obliquely give way by 45 degrees towards opposite directions at the same time, but not every driver can make such a decision, so that the requirement of smooth passing of special vehicles cannot be met.
Secondly, when the lane is not used, the lane can be occupied by irrelevant vehicles, so that the special vehicles cannot pass smoothly when passing; and some roads are not necessarily equipped with emergency lanes to allow special vehicles to quickly pass through the traffic intersection. Meanwhile, in case of violating the order of traffic lights, traffic accidents may be caused by rapid traffic.
Moreover, a large amount of manpower and material resources can be called when the special vehicle executes a task, and the accuracy and precision of judgment can be influenced by artificial interference, so that a plurality of special vehicles cannot be scheduled in a large-range and long-span manner at the same time; in some cases, the special vehicle supplies are met by a distribution center and a transfer center in a multi-source mode, and the requirement of the multi-department coordination work on efficiency is stricter; one significant difference from conventional vehicle path optimization is that special vehicle path optimization focuses more on timeliness and accuracy.
Therefore, how to adjust the route optimization of the special vehicle becomes a technical problem which needs to be solved urgently.
Disclosure of Invention
The purpose of the invention is as follows: aiming at the defects in the prior art, the invention provides a dynamically-adjusted special vehicle path optimization method to solve the problem that the special vehicle executing the task cannot be dredged in time in the prior art.
The technical scheme is as follows: the invention discloses a path optimization method for a dynamically adjusted special vehicle, which is realized by a vehicle machine module and a terminal module, and comprises the following steps:
(1) Acquiring position information and a path of the special vehicle; the specific process is as follows:
(1.1) the special vehicle receives a special task execution command;
(1.2) the vehicle machine module sends license plate information E1;
(1.3) the terminal module receives license plate information E1 and inputs the license plate information into a database;
(1.4) the vehicle-mounted machine module sends the information E2 of the origin and the destination;
(1.5) the terminal module receives the information E2 of the origin and the destination;
(1.6) planning a terminal module path, and sending a special vehicle driving path;
(1.7) navigating the vehicle machine module path to guide a special vehicle to run;
(1.8) the special vehicle sends GPS information E3 every n seconds;
(1.9) the terminal module identifies license plate information and assists in judging the position of a special vehicle;
(1.10) the car machine module sends destination arrival information E4;
(2) And judging the timing state of the passing traffic signal lamp.
In the step (2), the step of judging the route traffic signal lamp timing state comprises the following steps:
(2.1) the terminal module receives the GPS information E3 in the step (1.8);
(2.2) the terminal module calculates the speed v of the special vehicle;
(2.3) detecting road traffic information by the terminal module, and calculating a traffic influence factor alpha;
(2.4) judging whether the next traffic light is a green light when the special vehicle passes by;
(2.5) if the judgment result is yes, not carrying out the next operation;
(2.6) if the judgment result is no, adjusting the timing of the signal lamp to meet the requirement that the special vehicle is green when passing;
(2.7) the terminal module receives the GPS information to know that the special vehicle passes through the regulated traffic light, and the regulated traffic light is recovered.
And (2.8) the terminal module receives the destination arrival information E4 and ends the work.
The judgment process of the step (2.2) is as follows:
wherein V represents vehicle speed, x m Geographical position, x, of the current time of the particular vehicle n The geographical position of the special vehicle at the time, and d is the time interval of the vehicle sending the GPS information.
The calculation process of the step (2.3) is as follows:
α＝η·∑num (2)
in the formula (2), num is the number of vehicles on the road, and η is the conversion parameter. When there is one vehicle on the road, α is increased by η seconds.
The judgment process of the green light in the step (2.4) is as follows:
A n ≤t≤A n+1 (4)
A n+1 -A n ＝T (5)
in the formula (3), x is the distance from the special vehicle to the next signal lamp, t is the time when the special vehicle reaches the traffic light, and v is the speed of the special vehicle.
In the formulae (4) and (5), A n The predicted time point of changing the traffic signal lamp is A 1 I.e. A 1 To initiate a change of lamp time point, A n+1 The next lamp change time point.
When A is 1 When the green light starting time is reached and n is an odd number, judging that the special vehicle passes through the traffic signal light; and when n is an even number, judging that the traffic signal lamp cannot pass through. When A is 1 When the time is the red light starting time and n is an even number, judging that the special vehicle passes through the traffic signal lamp; and when n is an odd number, judging that the special vehicle does not pass through the traffic signal lamp.
When A is 1 When the time is the starting time of the green light, when n is an odd number, T is the duration of the green light; when n is an even number, T is the red light duration; when A is 1 When the time is the red light starting time, when n is an even number, T is the green light duration; when n is an odd number, T is the red light duration.
The adjusting process of the step (2.6) comprises the following steps:
in formula (6), TE 1 The time TE when the special vehicle starts to emit red light or green light when the special vehicle arrives at the traffic signal light n+1 The time when the next special vehicle reaches the traffic signal lamp and the red light or the green light starts; t is the time when the special vehicle reaches the traffic signal lamp, alpha is the influence factor of the traffic flow, and epsilon is the allowable error.
The working principle is as follows: in the invention, under the environment of the Internet of vehicles, the running position of the special vehicle is detected, and the green light timing of the traffic signal lamp is adjusted, so that all the intersections passed by the special vehicle can be unblocked when the special vehicle executes a special task; namely, when the special vehicle executes a task, real-time position information and navigation information are sent; and the terminal module adjusts the green light timing of the traffic intersection signal lamps to be passed according to the special vehicle information.
Has the advantages that: compared with the prior art, the invention has the following advantages:
(1) The invention directly adjusts the state of the traffic signal lamp through the position and the path of the special vehicle which executes the task, is convenient for dredging the road in advance, and ensures that the special vehicle is green when passing.
(2) According to the invention, the time for the special vehicle to adjust the signal lamp timing is detected, so that the running time of the special vehicle is reduced, the requirement of the special vehicle for executing the task is met, and the task execution efficiency of the special vehicle is improved.
Drawings
FIG. 1 is a flow chart of the present invention for dynamically adjusting route optimization of a specialty vehicle;
FIG. 2 is a schematic diagram of an embodiment of the present invention;
fig. 3 is a timing diagram of a traffic signal lamp according to the present invention.
Detailed Description
As shown in fig. 1, the method for optimizing the path of the dynamically adjusted special vehicle of the present invention uses a dynamic adjustment system to perform the determination, wherein the dynamic adjustment system includes a vehicle machine module and a terminal module; the vehicle-mounted device module comprises a GPS positioning module, a vehicle-mounted device interaction module, a navigation module and a signal sending module; the terminal module comprises a signal receiving module, a path planning module, a signal lamp judging module, a video detecting module and a signal lamp adjusting module.
The invention discloses a dynamically-adjusted special vehicle path optimization method, which comprises the following steps:
(1) Acquiring position information and a path of the special vehicle; the step of obtaining the position information and the path of the special vehicle comprises the following steps:
(1.1) the special vehicle receives a special task execution command;
(1.2) the vehicle machine module sends license plate information E1;
(1.3) the terminal module receives license plate information E1 and inputs the license plate information into a database;
(1.4) the vehicle-mounted machine module sends the information E2 of the origin and the destination;
(1.5) the terminal module receives the information E2 of the origin and the destination;
(1.6) planning a path by the terminal module, and sending a running path of the special vehicle;
(1.7) the vehicle machine module conducts path navigation and guides the special vehicle to run;
(1.8) in the embodiment, the special vehicle sends the GPS information E3 every 2 seconds;
(1.9) the terminal module identifies license plate information and assists in judging the position of the special vehicle;
(1.10) the car machine module sends destination arrival information E4.
(2) Judging the timing state of the approach traffic signal lamp, wherein the step of judging the timing state of the approach traffic signal lamp comprises the following steps:
(2.1) the terminal module receives the GPS information E3 in the step (1.8);
(2.2) the terminal module calculates the speed v of the special vehicle;
(2.3) the terminal module detects road traffic information and calculates a traffic influence factor alpha;
(2.4) judging whether the next traffic light is a green light when the special vehicle passes by;
(2.5) if the judgment result is yes, not carrying out the next operation;
(2.6) if the judgment result is no, adjusting the timing of the signal lamp to meet the requirement that the special vehicle is green when passing;
(2.7) the terminal module receives the GPS information to know that the special vehicle passes through the regulated traffic light, and the regulated traffic light is recovered;
and (2.8) the terminal module receives the destination arrival information E4 and ends the work.
The judgment process of the step (2.2) is as follows:
wherein v represents vehicle speed, x m Geographical position, x, of the current time of the particular vehicle n The geographical position of the special vehicle at the time, and d is the time interval of the vehicle sending the GPS information.
The calculation process of the step (2.3) is as follows:
α＝η·∑num (2)
in the formula (2), num is the number of vehicles on the road, and η is a conversion parameter. When one vehicle is added to the road, α is increased by η seconds.
The judgment process of the green light in the step (2.4) is as follows:
A n ≤t≤A n+1 (4)
A n+1 -A n ＝T (5)
in the formula (3), x is the distance from the special vehicle to the next signal lamp, t is the time when the special vehicle reaches the traffic light, and v is the speed of the special vehicle.
In the formulae (4) and (5), A n The predicted time point of changing the traffic signal lamp is A 1 . Namely A 1 To initiate a change of lamp time point, A n+1 The next lamp change time point.
When A is 1 When the green light starting time is reached and n is an odd number, judging that the special vehicle passes through the traffic signal light; and when n is an even number, judging that the traffic signal lamp cannot pass through. When A is 1 When the time is the red light starting time and n is an even number, judging that the special vehicle can pass through the traffic signal lamp; and when n is an odd number, judging that the special vehicle cannot pass through the traffic signal lamp.
When A is 1 When the green light starts, n is oddWhen the time is several, T is the duration of green light; when n is an even number, T is the red light duration; when A is 1 When the time is the red light starting time, when n is an even number, T is the green light duration; when n is an odd number, T is the red light duration.
The adjusting process of the step (2.6) comprises the following steps:
in formula (6), TE 1 TE is the time when the special vehicle reaches the red light or the green light when the traffic signal light is started n+1 The time when the next special vehicle reaches the traffic signal lamp and the red light or the green light starts; t is the time when the special vehicle reaches the traffic signal lamp, alpha is the influence factor of the traffic flow, and epsilon is the allowable error.
As shown in FIG. 2, the method for dynamically adjusting the special vehicle path optimization system of the invention comprises the following steps:
setting a special vehicle at 8 am: 00 receives the task and starts to drive, the distance between the special vehicle and the first traffic signal lamp S1 is 300 meters, the distance between the S1 and the S2 is 800 meters, and the distance between the S2 and the destination is 200 meters. The green time of the traffic signal lamp is 15 seconds, and the red time is 30 seconds. There are 20 other vehicles on the road between the special vehicle and the next intersection. When 8 a.m.: at 00, S1 is green for 5 seconds, and 10 seconds remain to jump to red, where A1=0, A2=15, A3=45, and A4=60. Let η be 0.2 seconds and α be 4 seconds and ε be 3 seconds.
The running distance of the special vehicle is 50 meters within 2 seconds, the speed of the special vehicle is 25m/S, the time of arriving at S1 is 12 seconds, t =17 seconds, the traffic signal lamp S1 is just 2 seconds after the red light, and the judgment shows that when the special vehicle passes through the traffic signal lamp, the S1 is the red light. Namely A 2 ≤t≤A 3 . Therefore, let A2=0+17+3+4 + 24 seconds, when the special vehicle passes S1, its traffic signal light is green. The camera of S1 shoots the license plate of the special vehicle and the position of the GPS passing S1, and the terminal module judges that the special vehicle passes S1. At this time, the time for the special vehicle to travel to S2 is 32 seconds, t =49 seconds, and at this time, the traffic signal lamp S2 is a green lamp, and the special vehicle normally passes through. When the special vehicle reaches the purposeAnd when the current is L, the terminal module stops calculating, and the work is finished.
As shown in fig. 3, the traffic signal timing diagram is as follows:
the starting time of the time when the traffic signal lamp is located at the moment for calculation is set to be A1, and then the time is set to be A2, A3 and A4 in sequence for 82308230. The green light duration is 15 seconds and the red light duration is 30 seconds.
Claims (1)
1. A dynamically adjusted special vehicle path optimization method is characterized by comprising the following steps: the path optimization method is realized through a vehicle machine module and a terminal module, and comprises the following steps:
(1) Acquiring position information and a path of the special vehicle; the specific process is as follows:
(1.1) the special vehicle receives a special task execution command;
(1.2) the vehicle machine module sends license plate information E1;
(1.3) the terminal module receives license plate information E1 and inputs the license plate information into a database;
(1.4) the vehicle-mounted machine module sends the information E2 of the starting place and the destination;
(1.5) the terminal module receives the information E2 of the origin and the destination;
(1.6) planning a path by the terminal module, and sending a special vehicle running path;
(1.7) the vehicle-mounted machine module conducts path navigation and guides a special vehicle to run;
(1.8) the special vehicle sends the GPS information E3 every n seconds;
(1.9) the terminal module identifies license plate information and assists in judging the position of a special vehicle;
(1.10) the car machine module sends destination arrival information E4;
(2) Judging the timing state of the passing traffic signal lamp; the method comprises the following steps:
(2.1) the terminal module receives the GPS information E3 in the step (1.8);
(2.2) the terminal module calculates the speed v of the special vehicle;
wherein v represents vehicle speed, x m Geographical position, x, of the current time of the particular vehicle n D is the time interval of the vehicle sending the GPS information;
(2.3) the terminal module detects road traffic information and calculates a traffic influence factor alpha;
α＝η·∑num (2)
in the formula (2), num is the number of vehicles on the road, and eta is a conversion parameter; when one vehicle is added to the road, the alpha is increased by eta seconds;
(2.4) judging whether the next traffic light is a green light when the special vehicle passes by; the judgment process of the green light is as follows:
A n ≤t≤A n+1 (4)
A n+1 -A n ＝T (5)
in the formula (3), x is the distance from the special vehicle to the next signal lamp, t is the time for the special vehicle to reach the traffic light, and v is the speed of the special vehicle;
in the formulae (4) and (5), A n The predicted time point of changing the traffic signal lamp is A 1 I.e. A 1 To initiate a change of lamp time point, A n+1 The next lamp changing time point;
when A is 1 When the green light starting time is reached and n is an odd number, judging that the special vehicle passes through the traffic signal light; when n is an even number, judging that the traffic signal lamp cannot pass through; when A is 1 When the time is the red light starting time and n is an even number, judging that the special vehicle passes through the traffic signal lamp; when n is an odd number, judging that the special vehicle does not pass through the traffic signal lamp;
when A is 1 When the time is the starting time of the green light, when n is an odd number, T is the duration of the green light; when n is an even number, T is the red light duration;when A is 1 When the time is the red light starting time, when n is an even number, T is the green light duration; when n is an odd number, T is the red light duration;
(2.5) if the judgment result is yes, not carrying out the next operation;
(2.6) if the judgment result is no, adjusting the timing of the signal lamp to meet the requirement that the special vehicle is green when passing;
the adjusting process of the step (2.6) comprises the following steps:
TE n ＝TE 1 +t+α-ε，TE 1 start time of green light
TE n+1 ＝TE 1 +t+α-ε,TE 1 Starting time for red light (6)
In formula (6), TE 1 The time TE when the special vehicle starts to emit red light or green light when the special vehicle arrives at the traffic signal light n+1 The time when the next special vehicle starts to turn red or green when reaching the traffic signal lamp; t is the time when the special vehicle reaches the traffic signal lamp, alpha is the traffic flow influence factor, and epsilon is the allowable error;
(2.7) the terminal module receives the GPS information to know that the special vehicle passes through the regulated traffic light, and the regulated traffic light is recovered;
and (2.8) the terminal module receives the destination arrival information E4 and ends the work.
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Application publication date: 20220405 Assignee: Suzhou Hangli Transportation Technology Co.,Ltd. Assignor: HUAIYIN INSTITUTE OF TECHNOLOGY Contract record no.: X2023980039116 Denomination of invention: A Dynamic Adjustment Method for Path Optimization of Special Vehicles Granted publication date: 20230321 License type: Common License Record date: 20230807 |
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