A method for accelerating the dissipation of road congestion convoys based on drone information release

Abstract

The present invention discloses a method for accelerating the dissipation of road congestion convoys based on the release of drone information, comprising the following steps: (1) the carrier vehicle is driving and inspecting on the road, and after the vehicle initially senses congestion, the drone is launched to obtain road condition information and determine the congestion status; (2) the drone is flown alternately according to the power level to achieve full-process monitoring of the congestion status; (3) the drone informs the carrier vehicle of the signs of dissipation of the congestion convoy, the carrier vehicle evaluates the dissipation wave state, and reminds each vehicle in the congested convoy through the congestion information release system; (4) each vehicle in the congested convoy reacts in advance to accelerate the dissipation of congestion. The present invention is based on the drone obtaining road condition information, monitoring the congestion status, and discovering signs of dissipation. The carrier vehicle informs each vehicle in the congested convoy of the dissipation information in advance, breaking the information acquisition lag limitation of the driver of the following vehicle, shortening the reaction time of the starting of the following vehicle, accelerating the dissipation of the congested convoy, and saving the total travel time of the vehicles.

Description

Technical Field

[0001] The present invention relates to the fields of road operation management, traffic congestion relief and dissipation, and in particular to a method for accelerating the dissipation of road congestion fleets based on drone information release. Background Art

[0002] In recent years, with the continuous development of my country's economy and society, infrastructure construction has been increasingly strengthened, road mileage has continued to increase, and traffic flow has also continued to increase. But at the same time, road traffic accidents and emergencies such as car accidents also occur from time to time, which can easily cause congestion, and sometimes there will be congested sections of several kilometers. After the relevant incidents are resolved, the congested convoy gradually dissipates, and for the middle and end vehicles in the convoy, the driver's perspective of the rear vehicle is relatively limited, resulting in delayed information acquisition, and can only start after recognizing that the front vehicle has started. In this congestion evacuation behavior mode, the driver's reaction time is long, and the speed of dissipation of the congested convoy is relatively slow. How to minimize the negative impact of traffic congestion and accelerate the process of dissipating convoy congestion has become one of the significant issues in the field of road management and traffic congestion management that needs to be solved urgently.

[0003] At present, drones have been widely used in video surveillance, vehicle identification, data collection and other aspects, and the relevant technologies are relatively mature. However, they are rarely used in the dispersal of road congestion. It is urgent to take advantage of the characteristics of high resolution image acquisition, low application environment requirements, strong maneuverability and simple use. Through the aerial photography perspective of drones, signs of convoy dissipation can be discovered in advance, so as to promptly remind the drivers of the middle and end vehicles in the convoy, prepare to start the vehicle as soon as possible, save reaction time, and start as soon as possible to accelerate the dissipation of the congested convoy. Summary of the invention

[0004] Purpose of the invention: In view of the shortcomings of the prior art, the present invention proposes a method for accelerating the dissipation of road congestion convoys based on drone information release, and provides an effective method for accelerating the dissipation of road congestion convoys through the drone aerial photography perspective sharing function.

[0005] Technical solution: A method for accelerating the dissipation of road congestion convoys based on drone information release, comprising the following steps:

[0006] (1) The vehicle carrying the drone is patrolling on the road. After the vehicle initially senses congestion, the drone is launched to obtain road condition information and determine the congestion status;

[0007] (2) Alternate the flight of drones according to the power level to achieve full monitoring of congestion status;

[0008] (3) The drone informs the carrier vehicle of the signs of dissipation of the congestion convoy. The carrier vehicle evaluates the dissipation wave status and reminds each vehicle in the congestion convoy through the congestion information release system;

[0009] (4) Each vehicle in the congested vehicle fleet reacts in advance to accelerate the dissipation of congestion.

[0010] Furthermore, in the step 1, the carrier vehicle meets the conditions: the carrier vehicle is a road administration patrol vehicle or a social vehicle, is driving normally on the road, and has obtained a drone flight permit; multiple carrier vehicles can drive on the road at the same time, where: the total number of carrier vehicles is A, and the carrier vehicle Veh a (a = 1, 2, …, A) is loaded with i drones and j drone charging devices. To ensure the drone charging demand and alternating flight and full - process monitoring of congestion requirements, the number of charging devices needs to meet:

[0011] j = ki (k ∈ Z * )

[0012] Among them, the drone charging methods include charging and battery swapping. The proportionality coefficient k (k ∈ Z * ) is specifically determined in combination with the drone charging method, and its value range is k = 1 - 10.

[0013] Furthermore, the criteria for the drone in the step 1 to obtain road condition information and judge the congestion status are:

[0014]

[0015]

[0016] Among them, is the average travel speed (km / h) of the road section S (km), N is the total number of measured vehicles (veh) within the road section S, t m is the time (s) for vehicle n to pass through the road section S, and ρ is the traffic flow density (veh / km) within the road section S.

[0017] Let the congestion threshold of the average travel speed of the road section be V (km / h), and the congestion threshold of the traffic flow density be P (veh / km). The congestion status x c Judgment conditions:

[0018]

[0019] Among them, if and ρ < P, it is considered that the road section is unobstructed and in a non - congested state, and x c is 0; if and / or ρ > P, it is considered that the road section is in a congested state, and x c is 1.

[0020] Furthermore, the step 2 includes the following steps:

[0021] (21), determine the battery level b of drone i: the drone battery warning level is B (B = 20% to 70%), and the drone battery warning state x b Judgment conditions:

[0022]

[0023] If b>B, it means the drone has sufficient power and can continue monitoring. b If b≤B, it means that the drone battery has reached or is below the warning level and needs to be returned for charging. b is 1, go to step (22);

[0024] (22), UAV i+1 from the carrier vehicle Veh a Take off (the drone is fully charged at takeoff, b = 100%) and fly to the location of drone i;

[0025] (23), UAV i returns to the carrier vehicle for charging;

[0026] Repeat steps (21) to (23) to continuously monitor the traffic information and congestion status of the road section.

[0027] Furthermore, the step 3 comprises the following steps:

[0028] (31) The drone discovered that the head of the congested convoy showed signs of dissipation, and reminded the carrier vehicle to pay attention to the congestion dissipation wave;

[0029] (32), the carrier vehicle evaluates the position and speed of the congestion dissipation wave and predicts the time when vehicle n in the congested convoy leaves the congested section:

[0030] t n =t nd +t ne

[0031]

[0032]

[0033]

[0034]

[0035]

[0036] Among them, the total time t for vehicle n in the congested vehicle group to leave the congested section is n is the total start-up loss time t from the first car to the nth car in the convoy nd and the total dissipated travel time t neSum(s);μ r S is the single vehicle start loss time of the rth vehicle in the congested vehicle fleet (s); n is the length of the convoy ahead of vehicle n at time t (km); is the average length of a single vehicle in the congested fleet (m), N is the total number of vehicles (veh), L r0 is the length of vehicle r (m), L rfront is the distance between vehicle r and the rear of vehicle r-1 in front (m), L rback is the distance between vehicle r and the front of the following vehicle r+1 (m); u e is the speed of the congestion dissipation wave (km / h); Q and Q′ respectively represent the flow rates before and after the congestion dissipation (veh / h); ρ and ρ′ respectively represent the density before and after the congestion dissipation (veh / km);

[0037] (33) The carrier vehicle informs the vehicles in the congested convoy through the congestion information release system that the congestion ahead has begun to dissipate, and informs the vehicle n in the congested convoy of the predicted time t required to leave the congested section. n .

[0038] Beneficial effects: The present invention utilizes the aerial cruising function of the drone to obtain road condition information in advance, continuously monitor the congestion status, and promptly discover signs of dissipation, and utilizes the congestion information release system to promptly inform the dissipation information of each vehicle in the congested fleet, reminding the driver to prepare to start the vehicle as soon as possible, breaking the information acquisition lag limitation of the following driver, shortening the vehicle starting reaction time, and accelerating the dissipation of the congested fleet, providing effective help for improving the overall road traffic level, improving the road traffic quality, and improving the road traffic efficiency, and providing an effective basis for path planning in the traffic network, command and operation of the traffic management department, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1 This is a flow chart of a method for accelerating the dissipation of road congestion fleets based on drone information release according to the present invention. DETAILED DESCRIPTION

[0040] In conjunction with the accompanying drawings, the technical solution of the present invention in a specific implementation is further described below by taking a road with a design speed of 120 km / h as an example.

[0041] Figure 1 The flowchart of the method for accelerating the dissipation of a road congestion convoy based on drone information release of the present invention is shown. The method for accelerating the dissipation of a road congestion convoy based on drone information release of the present invention mainly includes the following steps:

[0042] Step (1), the carrier vehicle is driving on the road for inspection. After the vehicle initially senses congestion, it launches a drone to obtain road condition information and determine the congestion status. The carrier vehicle is a road inspection vehicle or a social vehicle, driving normally on the road, and has obtained a drone flight permit; the total number of carrier vehicles is A, and the number of carrier vehicles Veh a (a=1,2,…,A) is loaded with i drones and j drone charging equipment; the driver of the carrier vehicle meets the following conditions: the driver has received preliminary training, is in good driving condition, and can initially identify congestion based on the road conditions, fleet and vehicle conditions ahead. In this embodiment, the carrier vehicle is driving on the road for inspection. The driver of the carrier vehicle initially senses that there may be congestion ahead and launches drone No. 1 to obtain road condition information. For the 1km section ahead, the drone detects the average travel speed of the section. It is 30km / h. According to the road traffic congestion evaluation method, the road section is in a congested state.

[0043] Step (2), the drone continuously monitors the road conditions throughout the entire process. The drones are flown alternately according to the power level to achieve full-time monitoring of the congestion status, and the drone power warning level B is set to 30%. At time t, the power b of drone No. 1 is 29%, which is lower than the power warning level. At this time, the carrier vehicle takes off drone No. 2 (the drone is fully charged at takeoff). Drone No. 2 arrives at the position of drone No. 1 and takes over the congestion status monitoring task. Drone No. 1 returns to the carrier vehicle for charging; at time t+m, the power b of drone No. 2 is 30%, reaching the power warning level. At this time, drone No. 3 takes over the congestion status monitoring task of the carrier vehicle, and drone No. 2 returns to the carrier vehicle for charging.

[0044] Step (3), the drone finds signs of dissipation, and the vehicle carrying the drone predicts the information and alerts the congested convoy. The dissipation sign condition is: the speed of the first vehicle at the head of the convoy (n=1) ,in, Set as the speed threshold for dissipating congested convoys;

[0045] The specific steps include:

[0046] (31), UAV No. 3 detected the signs of dispersal at the head of the congested convoy and informed the carrier vehicle of the dispersal information.

[0047] (32), the carrier vehicle estimates the position and speed of the evanescent wave and predicts the time when vehicle n in the congested convoy will leave the congested section.

[0048] In this embodiment, small vehicles account for 80% of the road, and the average length of small vehicles is L r0 4.5m, small vehicle L rfronr , L rback All are 2m; other vehicles account for 20%, and the average length of other vehicles is Lr0 10m, other vehicles L rfront , L rback are 3m, then the average length of a single vehicle in a congested fleet is The traffic volume before and after congestion dissipation is 1000veh / h and 1500veh / h respectively, and the density before and after congestion dissipation is 100veh / km and 50veh / km respectively. According to traffic flow theory, the congestion dissipation wave velocity u is calculated. e = Taking the 100th vehicle at the end of the convoy (n=100) as an example, at the moment t0=0 when the first vehicle at the head of the congested convoy begins to dissipate, the length of the convoy in front of vehicle n is That is, the distance that the 100th vehicle needs to travel to the congestion dissipation point is 752.4m, and the dissipation travel time is Assume that in the original state (no countdown, the following vehicle is unaware of the dissipation state), the average start-up reaction time is 2.56s, and in the case of drone information release (informing the dissipation state and the countdown of the predicted time), the average reaction time is 1.45s. Then, in the original state, the total time t for the 100th vehicle in the congested convoy to leave the congested section is n =t nd +t ne =256+270.864=526.864s, the total time t′ for the 100th vehicle in the congested vehicle fleet to leave the congested section when the drone information is released n =t′ nd +t ne =145+270.864=415.864d. Compared with the original situation, this vehicle saves 111s, about 2 minutes, in the process of congestion dissipation, and the time saved by all vehicles is more significant when added together. Therefore, this method shows a good acceleration effect of dissipating road congestion fleets.

[0049] (33) The carrier vehicle uses the congestion information release system to inform the vehicles in the congested convoy that the congestion ahead has begun to dissipate, and informs the vehicle n in the congested convoy of the predicted time t′ required to leave the congested section. n .

[0050] Step (4), the vehicles in the congested convoy react in advance, the drivers concentrate their attention, start the engine in advance, start the vehicle to speed up, speed up the exit from the congested section, and accelerate the dissipation of congestion.

[0051] From the above description of the specific implementation method in combination with the accompanying drawings, it can be seen that the present invention utilizes drone aerial cruising technology to realize road condition monitoring and congestion status tracking of congested road sections, promptly discover signs of dissipation of congested convoys, and inform the carrier vehicle. The carrier vehicle reminds the queued vehicles through the congestion information release system. After receiving the reminder, the vehicle driver makes preparations for starting in advance, thereby accelerating the process of dissipation of road congested convoys and providing effective assistance for road traffic management and traffic quality.

[0052] The above content is only a further detailed description of the present invention through a specific embodiment, and the present invention cannot be considered to be limited to these descriptions. For ordinary technicians in the technical field to which the present invention belongs, several simple deductions or substitutions can be made without departing from the concept of the present invention, which should be regarded as falling within the protection scope of the present invention.

Claims

1. A method for accelerating the dissipation of road congestion fleets based on drone information release, characterized in that: The method comprises the following steps: (1) The carrier vehicle is driving on the road for inspection. After the vehicle initially senses congestion, it launches a drone to obtain road condition information and determine the congestion status. The carrier vehicle is a road inspection vehicle or a social vehicle, driving normally on the road, and has obtained a drone flight permit; the total number of carrier vehicles is A, and the number of carrier vehicles Veh a (a=1, 2, ..., A) loads i drones and j drone charging devices; (2) Each vehicle carrying the drone will fly the drone it carries alternately according to the power level to achieve full monitoring of the congestion status; (3) The UAV informs the carrier vehicle of the signs of dissipation of the congestion convoy, and the carrier vehicle evaluates the dissipation wave status and reminds each vehicle in the congestion convoy through the congestion information release system; the following steps are included: (31) The UAV finds that the head of the congested convoy shows signs of dissipation, and reminds the carrier vehicle to pay attention to the congestion dissipation wave. The dissipation sign condition is: the speed of the first vehicle at the head of the convoy (n=1) in, Set as the speed threshold for dissipating congested convoys; (32), the carrier vehicle evaluates the position and speed of the congestion dissipation wave and predicts the time when vehicle n in the congested convoy leaves the congested section: t n =t nd +t ne Among them, the total time t for vehicle n in the congested vehicle group to leave the congested section is n is the total start-up loss time t from the first car to the nth car in the convoy nd and the total dissipated travel time t ne Sum(s);μ r S is the single vehicle start loss time of the rth vehicle in the congested vehicle fleet (s); n is the length of the convoy ahead of vehicle n at time t (km); is the average length of a single vehicle in the congested fleet (m), N is the total number of vehicles (veh), L r0 is the length of vehicle r, L rfront is the distance between vehicle r and the rear of vehicle r-1, L rback is the distance between vehicle r and the front of the following vehicle r+1; u e is the congestion dissipation wave velocity (km / h); Q, Q′ respectively represent the flow rate before and after congestion dissipation (veh / h); ρ, p′ respectively represent the density before and after congestion dissipation (veh / km); (33) The carrier vehicle informs the vehicles in the congested convoy through the congestion information release system that the congestion ahead has begun to dissipate, and informs the vehicle n in the congested convoy of the predicted time t required to leave the congested section. n ; (4) Vehicles in the congested convoy respond in advance to speed up the dissipation of congestion.

2. The method for accelerating the dissipation of road congestion fleets based on drone information release according to claim 1 is characterized in that: In step 1, multiple vehicles carrying drones can be driven on the road at the same time, where: to ensure the charging needs of drones and the requirements of alternating flights and full-time monitoring of congestion, the vehicle carrying drone Veh a (a=1,2,...,A) The number of charging devices j loaded must satisfy: j=ki Among them, the UAV charging methods include charging and battery replacement, and the proportional coefficient k(k∈Z * ) is determined in combination with the UAV charging method, and its value range is k=1~10.

3. The method for accelerating the dissipation of road congestion fleets based on drone information release according to claim 1, characterized in that: The conditions for the vehicle to initially sense congestion in step 1 are: in, is the average travel speed (km / h) of all vehicles in section S (km), N is the total number of vehicles in section S (veh), t m is the time for vehicle n to pass through section S (s), ρ is the traffic density in section S (veh / km); Assume that the average travel speed congestion threshold of the road section is V (km / h), the traffic density congestion threshold is P (veh / km), and the congestion state x c Judgment conditions: Among them, event G is Event H is ρ > P; if and ρ < P, that is then it is considered that the road section is unobstructed and in a non-congested state, and x c is 0; if and / or ρ > P, that is, G ∧ H, GVH, then it is considered that the road section is in a congested state, and x c is 1.

4. The method for accelerating the dissipation of road congestion fleets based on drone information release according to claim 1, characterized in that: The step 2 comprises the following steps: (21), determine the battery level b of drone i: the drone battery warning level is B, the warning level B is determined according to the length S of the drone detection range, and the drone battery warning state x b Judgment conditions: If b>B, it means the drone has sufficient power and can continue monitoring. b If b≤B, it means that the drone battery has reached or is below the warning level and needs to be returned for charging. b is 1, go to step (22); (22), UAV i+1 from the carrier vehicle Veh a Take off and fly to the location of drone i; (23), UAV i returns to the carrier vehicle for charging; Repeat steps (21) to (23) to continuously monitor the traffic information and congestion status of the road section.

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