CN111445709A - Driving route matching method and system for unmanned emergency vehicle - Google Patents
Driving route matching method and system for unmanned emergency vehicle Download PDFInfo
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- CN111445709A CN111445709A CN202010410365.7A CN202010410365A CN111445709A CN 111445709 A CN111445709 A CN 111445709A CN 202010410365 A CN202010410365 A CN 202010410365A CN 111445709 A CN111445709 A CN 111445709A
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- G—PHYSICS
- G08—SIGNALLING
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- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
- G08G1/087—Override of traffic control, e.g. by signal transmitted by an emergency vehicle
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- G—PHYSICS
- G08—SIGNALLING
- G08G—TRAFFIC CONTROL SYSTEMS
- G08G1/00—Traffic control systems for road vehicles
- G08G1/07—Controlling traffic signals
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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
- G08G1/0968—Systems involving transmission of navigation instructions to the vehicle
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Abstract
The invention relates to a running route matching method and a running route matching system for an unmanned emergency vehicle, which comprise the following steps: step S1, the cloud server receives destination address information and an emergency degree instruction sent by the unmanned emergency vehicle and acquires the current position information of the unmanned emergency vehicle; step S2, the cloud server matches a driving route of the unmanned emergency vehicle by adopting a predation search algorithm according to the current position information and the destination address information of the unmanned emergency vehicle; step S3, the cloud server acquires road condition information and traffic light information of all intersections on the driving route according to the obtained driving route, and determines the average driving speed according to the emergency degree instruction; step S4, the unmanned emergency vehicle runs according to the running route and the average running speed; and step S5, the cloud server controls traffic lights on the driving route according to the real-time driving condition of the unmanned emergency vehicle. The invention ensures that the unmanned emergency vehicle can run stably and safely, and meanwhile, takes care of the road use right of other non-emergency vehicles, so that the road use efficiency is higher.
Description
Technical Field
The invention relates to the field of unmanned emergency vehicle control, in particular to a driving route matching method and system for an unmanned emergency vehicle.
Background
At present, although the unmanned technology is not widely applied, research on the unmanned technology is gradually and deeply conducted, the current research is often focused on the control of a conventional vehicle, and the control of an unmanned special emergency vehicle is not deeply studied, and if the unmanned technology is adopted for a special emergency vehicle, such as an ambulance, more complex technical problems are bound to be faced, for example, how to ensure the driving safety of the ambulance under the unmanned condition, if the vehicle speed is randomly changed according to road conditions, the life safety of a patient on the ambulance may be threatened, and for the unmanned driving, how to ensure that the unmanned emergency vehicle including the ambulance enjoys priority right of road.
Disclosure of Invention
In view of the above, the present invention provides a method for matching a driving route of an unmanned emergency vehicle, so as to realize safe and rapid driving of the unmanned emergency vehicle to a destination.
In order to achieve the purpose, the invention adopts the following technical scheme:
a driving route matching method of an unmanned emergency vehicle comprises the following steps:
step S1, the cloud server receives destination address information and an emergency degree instruction sent by the unmanned emergency vehicle and acquires the current position information of the unmanned emergency vehicle;
step S2, the cloud server matches a driving route of the unmanned emergency vehicle by adopting a predation search algorithm according to the current position information and the destination address information of the unmanned emergency vehicle;
step S3, the cloud server acquires road condition information and traffic light information of all intersections on the driving route according to the obtained driving route, and determines the average driving speed according to the emergency degree instruction;
step S4, the unmanned emergency vehicle runs according to the running route and the average running speed;
and step S5, the cloud server controls traffic lights on the driving route according to the real-time driving condition of the unmanned emergency vehicle.
Further, the step S5 is specifically:
step S51, when the distance between the unmanned emergency vehicle and the traffic light of the first intersection on the driving route reaches a set first threshold value, the unmanned emergency vehicle obtains the first time when the unmanned emergency vehicle reaches the first intersection start line;
step S52, the unmanned emergency vehicle sends the first time to a cloud server, and the cloud server calculates a second starting time that a traffic light of the first intersection needs to be turned on in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time that the unmanned emergency vehicle is ensured to pass through the first intersection according to the road condition information of the first intersection and the average driving speed of the unmanned emergency vehicle;
step S53, the cloud server sends the second starting time and the second ending time to the traffic light of the first intersection, the traffic light of the first intersection turns on the green light for the intersection in the driving direction of the unmanned emergency vehicle according to the second starting time, and the green light is maintained to the second ending time;
and step S53, when the second ending time is reached, the cloud server calculates a third starting time when the traffic light of the next intersection needs to turn on the green light in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a third ending time when the unmanned emergency vehicle passes the next intersection according to the road condition information of the next intersection and the average driving speed of the unmanned emergency vehicle.
Further, when the distance between the first intersection and the next intersection is less than the second threshold and the road condition of the two intersections reaches the preset good state,
the cloud server calculates a second starting time when the traffic lights of the first intersection and the next intersection need to turn on green lights in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time when the unmanned emergency vehicle passes through the next intersection according to the road condition information of the first intersection and the next intersection, the distance between the two intersections and the average driving speed of the unmanned emergency vehicle;
the cloud server sends the second starting time and the second ending time to traffic lights of the first intersection and the next intersection;
and the traffic lights of the first intersection and the next intersection turn on green lights for the intersections in the driving direction of the unmanned emergency vehicle according to the second starting time, and the traffic lights of the next intersection maintain the green lights to the second ending time.
The running route matching system of the unmanned emergency vehicle comprises a cloud server and the unmanned emergency vehicle, wherein computer programs are stored in the cloud server and the unmanned emergency vehicle, and the method steps can be realized when the computer programs are operated.
Compared with the prior art, the invention has the following beneficial effects:
the invention can ensure that the unmanned emergency vehicle has stable speed and priority right during emergency driving, and can safely and stably drive the emergency vehicle to a destination.
Drawings
FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is further explained below with reference to the drawings and the embodiments.
Referring to fig. 1, the present invention provides a driving route matching method for an unmanned emergency vehicle, including the steps of:
step S1, the cloud server receives destination address information and an emergency degree instruction sent by the unmanned emergency vehicle and acquires the current position information of the unmanned emergency vehicle;
step S2, the cloud server matches a driving route of the unmanned emergency vehicle by adopting a predation search algorithm according to the current position information and the destination address information of the unmanned emergency vehicle;
step S3, the cloud server acquires road condition information and traffic light information of all intersections on the driving route according to the obtained driving route, and determines the average driving speed according to the emergency degree instruction;
step S4, the unmanned emergency vehicle runs according to the running route and the average running speed;
and step S5, the cloud server controls traffic lights on the driving route according to the real-time driving condition of the unmanned emergency vehicle.
Preferably, in this embodiment, the emergency instruction is determined according to the disease type or severity of the disease of the patient, and may be divided into general, severe and urgent, where the higher the emergency degree is, the higher the average traveling speed of the vehicle calculated in the cloud server is, for example, according to three different emergency degrees, the calculated average traveling speed may be: 40 km/h, 60 km/h and 80 km/h.
Of course, the speed is not only dependent on the degree of urgency, but also dependent on the road condition of the intersection of the driving route and the distance of the driving route, and a weight can be added to each factor according to a formula, so as to calculate the optimal average driving speed. For example, if the weight of speed a corresponding to the degree of urgency is x, the weight of speed b corresponding to the road condition at the intersection is y, and the weight of speed c corresponding to the distance of the travel route is z, then the average travel speed = (ax + by + cz)/(x + y + z), specifically, when a =80 km/h, x =5, b =20 km/h, y =3, c =10 km/h, z =2, and the average travel speed = (80 + 5+20 x 3+10 + 2)/(5 +3+2) = (400+60+20)/10=480/10=48 km/h.
Preferably, in this embodiment, the step S5 specifically includes:
step S51, when the distance between the unmanned emergency vehicle and the traffic light of the first intersection on the driving route reaches a set first threshold value, the unmanned emergency vehicle obtains the first time when the unmanned emergency vehicle reaches the first intersection start line;
step S52, the unmanned emergency vehicle sends the first time to a cloud server, and the cloud server calculates a second starting time that a traffic light of the first intersection needs to be turned on in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time that the unmanned emergency vehicle is ensured to pass through the first intersection according to the road condition information of the first intersection and the average driving speed of the unmanned emergency vehicle;
step S53, the cloud server sends the second starting time and the second ending time to the traffic light of the first intersection, the traffic light of the first intersection turns on the green light for the intersection in the driving direction of the unmanned emergency vehicle according to the second starting time, and the green light is maintained to the second ending time;
and step S53, when the second ending time is reached, the cloud server calculates a third starting time when the traffic light of the next intersection needs to turn on the green light in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a third ending time when the unmanned emergency vehicle passes the next intersection according to the road condition information of the next intersection and the average driving speed of the unmanned emergency vehicle.
Preferably, in this embodiment, when the distance between the current intersection and the next intersection is less than the second threshold, and the road condition of the two intersections reaches the predetermined good state,
the cloud server calculates a second starting time when the traffic lights of the current intersection and the next intersection need to turn on the green light in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time when the unmanned emergency vehicle passes through the next intersection according to the road condition information of the current intersection and the next intersection, the distance between the two intersections and the average driving speed of the unmanned emergency vehicle;
the cloud server sends the second starting time and the second ending time to traffic lights of the current intersection and the next intersection;
and the traffic lights of the current intersection and the next intersection turn on green lights for the intersection in the driving direction of the unmanned emergency vehicle according to the second starting time, and the traffic light of the next intersection maintains the green lights to the second ending time.
Wherein, the current intersection can be the first intersection.
Preferably, in the present embodiment, the road condition at the two intersections reaches a good state, and the good state is a preset standard, for example, the good state is obtained when the traffic flow at the intersection reaches 5 vehicles/second.
Preferably, the implementation further provides a running route matching system for the unmanned emergency vehicle, which includes a cloud server and the unmanned emergency vehicle, wherein the cloud server and the unmanned emergency vehicle store computer programs, and when the computer programs are operated, the method steps described in this embodiment can be implemented.
The above description is only a preferred embodiment of the present invention, and all equivalent changes and modifications made in accordance with the claims of the present invention should be covered by the present invention.
Claims (5)
1. A driving route matching method of an unmanned emergency vehicle is characterized by comprising the following steps:
step S1, the cloud server receives destination address information and an emergency degree instruction sent by the unmanned emergency vehicle and acquires the current position information of the unmanned emergency vehicle;
step S2, the cloud server matches the driving route of the unmanned emergency vehicle according to the current position information and the destination address information of the unmanned emergency vehicle;
step S3, the cloud server acquires road condition information and traffic light information of all intersections on the driving route according to the obtained driving route, and determines the average driving speed according to the emergency degree instruction;
step S4, the unmanned emergency vehicle runs according to the running route and the average running speed;
and step S5, the cloud server controls traffic lights on the driving route according to the real-time driving condition of the unmanned emergency vehicle.
2. The driving route matching method for unmanned emergency vehicles according to claim 1, wherein the driving route matching in step S2 employs a predation search algorithm.
3. The method for matching a driving route of an unmanned emergency vehicle according to claim 1, wherein the step S5 specifically comprises:
step S51, when the distance between the unmanned emergency vehicle and the traffic light of the first intersection on the driving route reaches a set first threshold value, the unmanned emergency vehicle obtains the first time when the unmanned emergency vehicle reaches the first intersection start line;
step S52, the unmanned emergency vehicle sends the first time to a cloud server, and the cloud server calculates a second starting time that a traffic light of the first intersection needs to be turned on in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time that the unmanned emergency vehicle is ensured to pass through the first intersection according to the road condition information of the first intersection and the average driving speed of the unmanned emergency vehicle;
step S53, the cloud server sends the second starting time and the second ending time to the traffic light of the first intersection, the traffic light of the first intersection turns on the green light for the intersection in the driving direction of the unmanned emergency vehicle according to the second starting time, and the green light is maintained to the second ending time;
and step S53, when the second ending time is reached, the cloud server calculates a third starting time when the traffic light of the next intersection needs to turn on the green light in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a third ending time when the unmanned emergency vehicle passes the next intersection according to the road condition information of the next intersection and the average driving speed of the unmanned emergency vehicle.
4. The method as claimed in claim 2, wherein when the distance between the first intersection and the next intersection is less than the second threshold and the road condition at the two intersections reaches the predetermined good condition,
the cloud server calculates a second starting time when the traffic lights of the first intersection and the next intersection need to turn on green lights in advance for the intersection in the driving direction of the unmanned emergency vehicle from the current moment and a second ending time when the unmanned emergency vehicle passes through the next intersection according to the road condition information of the first intersection and the next intersection, the distance between the two intersections and the average driving speed of the unmanned emergency vehicle;
the cloud server sends the second starting time and the second ending time to a traffic light of the first intersection and a traffic light of the next intersection;
and the traffic lights of the first intersection and the next intersection turn on green lights for the intersections in the driving direction of the unmanned emergency vehicle according to the second starting time, and the traffic lights of the next intersection maintain the green lights to the second ending time.
5. A driving route matching system of an unmanned emergency vehicle, which is characterized by comprising a cloud server and the unmanned emergency vehicle, wherein the cloud server and the unmanned emergency vehicle are stored with computer programs, and when the computer programs are operated, the method steps of any one of claims 1-4 can be realized.
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Cited By (7)
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| CN112185133A (en) * | 2020-10-19 | 2021-01-05 | 苏州冀联通信工程有限公司 | Emergency vehicle intersection intervention communication system and method |
| CN112382109A (en) * | 2020-10-22 | 2021-02-19 | 华南理工大学 | Emergency rescue vehicle cooperative control method, system and medium in intelligent networking state |
| CN113205697A (en) * | 2021-05-08 | 2021-08-03 | 联陆智能交通科技(上海)有限公司 | Vehicle emergency avoidance method, system and medium |
| CN113240919A (en) * | 2021-04-20 | 2021-08-10 | 中国汽车技术研究中心有限公司 | Emergency vehicle priority passing method based on Internet of vehicles |
| CN113635893A (en) * | 2021-07-16 | 2021-11-12 | 安徽工程大学 | Urban intelligent traffic-based unmanned vehicle steering control method |
| CN113706908A (en) * | 2021-08-26 | 2021-11-26 | 中汽创智科技有限公司 | Emergency channel dredging method, device and equipment |
| CN114743397A (en) * | 2020-12-23 | 2022-07-12 | 大陆泰密克汽车系统（上海）有限公司 | Special emergency lane configuration method and system |
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| CN113706908A (en) * | 2021-08-26 | 2021-11-26 | 中汽创智科技有限公司 | Emergency channel dredging method, device and equipment |
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Application publication date: 20200724 |