A highway bottleneck evacuation acceleration method based on vehicle networking

Abstract

The present invention discloses a method for accelerating the evacuation of highway bottlenecks based on the Internet of Vehicles, comprising: determining the corresponding congestion status of the fleet based on the fleet's status information, and feeding back the congestion status to each vehicle in the fleet; monitoring whether the bottleneck shows signs of evacuation based on the status information of the front vehicle in the fleet, predicting the time for each vehicle in the fleet to leave the bottleneck based on the fleet's status information, and reminding the drivers of each vehicle in the fleet through the Internet of Vehicles, so that the drivers of each vehicle in the fleet upstream of the highway bottleneck start their vehicles before their respective departure times from the bottleneck. The present invention solves the problem of obstructed vision for drivers in congested queues, enables the drivers of each vehicle in the fleet to grasp a more accurate start time, reduces vehicle start delays, accelerates the evacuation of bottlenecks, and effectively assists in evacuating highway traffic congestion, enhancing vehicle driving safety, improving the system's resilience to emergencies, and creating a more efficient highway network.

Description

Technical Field

[0001] The present invention belongs to the technical fields of highway bottleneck point management, intelligent transportation technology and autonomous driving, and specifically relates to a highway bottleneck point evacuation acceleration method based on vehicle networking. Background Art

[0002] In recent years, with the continuous growth of highway mileage and traffic volume, road conditions have become increasingly complex and congested. In this context, bottlenecks can easily form and cause traffic jams when a traffic accident or emergency occurs, or when lane reductions, tunnels, or toll booths occur. Once the bottleneck is resolved, the driver's view of the following vehicle is often blocked by the vehicle in front, resulting in significant start-up delays. Therefore, how to alleviate drivers' obstructed view, reduce start-up delays, and accelerate the clearing of highway bottlenecks is a pressing issue in highway operations management.

[0003] With in-depth research in the fields of intelligent transportation and autonomous driving, connected vehicle technology has achieved continuous progress and mature development. Using moving vehicles as information sensing objects, it leverages relevant information and communication technologies to connect and communicate with multiple terminals, including vehicles, pedestrians, roads, networks, and system platforms. Currently, connected vehicle technology has been widely used in areas such as collision risk warnings, green wave speed recommendations, and road speed limit reminders. However, its application in areas such as real-time road traffic guidance and bottleneck fleet management is relatively limited. There is an urgent need to leverage its interconnected advantages, share perspectives through vehicle-to-vehicle communication networks, and focus on the micro-level. This can alleviate the problem of obstructed vision for drivers of following vehicles, reduce start-up delays, accelerate bottleneck evacuation, and create a more efficient and sustainable intelligent highway network.

[0004] Patent number CN106408956B discloses a method and control system for rapidly evacuating tunnel traffic congestion. When a sudden traffic accident occurs on a tunnel road, preventing vehicles from passing normally, all vehicles upstream of the accident point begin queuing. Several roads less affected by the accident are then opened as emergency lanes. N control points are set along the length of the queue, dividing the entire road into N sections. Queuing vehicles intermittently pass through the accident point based on the control point markers. This invention can alleviate tunnel traffic congestion and save significant time for vehicle passage; however, it still requires external control for evacuation and cannot achieve bottleneck evacuation by optimizing the vehicle's own driving state. Summary of the Invention

[0005] Technical problem to be solved: This invention proposes an accelerated method for evacuating highway bottlenecks based on the Internet of Vehicles, focusing on micro-level and refined issues. From a methodological perspective, it provides an effective and feasible solution for the evacuation of highway bottlenecks through related technologies in the fields of intelligent transportation and autonomous driving, such as inter-vehicle communication and the Internet of Vehicles.

[0006] Technical solution:

[0007] The present invention discloses a highway bottleneck point evacuation acceleration method based on vehicle networking, and the highway bottleneck point evacuation acceleration method comprises the following steps:

[0008] Step A: Taking vehicle j on the highway as the center, all vehicles within its coverage area are grouped into a fleet Z, and the status information of fleet Z is continuously obtained through the Internet of Vehicles.

[0009] Step B: determining the congestion status of the fleet Z according to the status information of the fleet Z, and feeding back the congestion status to each vehicle in the fleet Z;

[0010] Step C: The head of the blocked convoy is regarded as the bottleneck point of the convoy. Based on the status information of the leading vehicle in convoy Z, the bottleneck point is monitored for signs of evacuation. The time for each vehicle in convoy Z to leave the bottleneck point is predicted based on the status information of convoy Z. The drivers of each vehicle in convoy Z are reminded through the Internet of Vehicles, so that the drivers of each vehicle in the convoy upstream of the bottleneck point on the highway start their vehicles before their respective departure time from the bottleneck point.

[0011] Furthermore, in step A, the interval coverage of vehicle j is a rectangle with the lane width a as the width and the distance b before and after vehicle j as the length, where a and b are both positive numbers.

[0012] Furthermore, in step A, the status information of the fleet Z includes: the total number of vehicles n in the fleet, the speed s of vehicle j at time t, j (t), the position P of vehicle j at time t j (t); Speed ​​difference Δs between vehicle j+1 and preceding vehicle j j+1 (t), the headway between vehicle j+1 and vehicle j and headway Vehicle j is the preceding vehicle of vehicle j+1, where:

[0013] Δs j+1 (t) = s j+1 (t)-s j (t);

[0014]

[0015]

[0016] Where s j+1 (t) is the speed of vehicle j+1 at time t; P j+1 (t) is the position of vehicle j+1 at time t.

[0017] Further, in step A, Using Euclidean distance, the headway between vehicle j+1 and vehicle j is and headway Respectively expressed as:

[0018]

[0019]

[0020] Where, is the latitude and longitude coordinates of vehicle j at time t, are the latitude and longitude coordinates of vehicle j+1 at time t.

[0021] Furthermore, in step B, the process of determining the congestion state corresponding to the fleet Z according to the state information of the fleet Z includes the following steps:

[0022] Step B1: Calculate the average speed of team Z at time t based on the status information of team Z. and average headway

[0023]

[0024]

[0025] Where n is the total number of vehicles in the fleet Z, s j (t) is the speed of vehicle j at time t; is the headway between vehicle j and vehicle j-1 at time t, where vehicle j-1 is the preceding vehicle of vehicle j;

[0026] Step B2: Assume that the average speed congestion threshold of the fleet is s min , the average headway congestion threshold is Judgment condition of bottleneck point congestion state γ congestion for:

[0027]

[0028] Among them, event C represents Event D indicates When γ congestion = 0, the fleet Z is running smoothly and is in a non-blocked state. congestion =1, convoy Z is moving slowly or blocked and is in a congested state.

[0029] Furthermore, in step C, based on the status information of the front vehicle of the convoy Z, the judgment standard γ of the evacuation sign is calculated. mitigation :

[0030]

[0031] Among them, event E represents Event F indicates is the speed of the front vehicle j1 at time t, is the headway between the front vehicle j2 and the front vehicle j1 at time t; s mitigation is the vehicle speed evacuation threshold, h gmitigation is the headway evacuation threshold; when γ mitigation = 0, the team Z in the bottleneck point shows no signs of evacuation and is still in a blocked state. mitigation =1, there are signs of evacuation at the head of convoy Z in the bottleneck point, and the congestion begins to be evacuated.

[0032] Furthermore, in step C, the following formula is used to predict the time for each vehicle in the fleet Z to leave the bottleneck point:

[0033]

[0034] Among them, T j (t) is the total time it takes for vehicle j in the fleet Z at the highway bottleneck point to leave the bottleneck point after the evacuation sign appears ahead; The time delay caused by the drivers of the first vehicle in the convoy Z to vehicle j at time t due to their reaction and starting the vehicle; is the travel time taken by vehicle j from time t to leaving the bottleneck point.

[0035] Furthermore, in step C, the following formula is used to calculate Know

[0036]

[0037]

[0038] Among them, τ i (t) is the starting delay time of the i-th vehicle in the fleet Z at the bottleneck point of the highway at time t; is the headway between vehicle i and the preceding vehicle at time t; |ω| is the bottleneck congestion dissipation speed, in km / h. According to the traffic flow and traffic wave theory, its calculation formula is:

[0039]

[0040] Where ω is the speed of the bottleneck dissipation wave, in km / h; Q upstream and K upstream are the traffic volume and density upstream of the bottleneck point, in veh / h and veh / km respectively; Q downstream and K downstream are the traffic volume and density downstream of the bottleneck point respectively.

[0041] Beneficial effects:

[0042] The present invention's highway bottleneck evacuation acceleration method based on the Internet of Vehicles focuses on micro-level and refined issues. From a methodological perspective, it uses Internet of Vehicles technology to continuously obtain fleet status information, monitor the congestion status of highway bottlenecks, and detect signs of bottleneck evacuation. It promptly informs the evacuation status, predicts and reminds the time to leave the bottleneck, and solves the problem of obstructed vision of drivers in congested queues. After receiving the evacuation prompt information, the drivers of each vehicle in the fleet can grasp a more accurate starting time, reduce vehicle start-up delays, and accelerate bottleneck evacuation, providing effective assistance for evacuating highway traffic congestion, enhancing vehicle driving safety, improving the system's resilience to emergencies, and creating a more efficient highway network. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flow chart of a highway bottleneck point evacuation acceleration method based on the Internet of Vehicles according to an embodiment of the present invention. DETAILED DESCRIPTION

[0044] The following examples may enable those skilled in the art to more fully understand the present invention, but are not intended to limit the present invention in any way.

[0045] See also Figure 1 The present invention discloses a highway bottleneck point evacuation acceleration method based on the Internet of Vehicles, and the highway bottleneck point evacuation acceleration method comprises the following steps:

[0046] In step A, with vehicle j on the highway as the center, all vehicles within its coverage area are grouped into fleet Z, and the status information of fleet Z is continuously obtained through the Internet of Vehicles.

[0047] Step B: Determine the congestion status corresponding to the fleet Z based on the status information of the fleet Z, and feed back the congestion status to each vehicle in the fleet Z.

[0048] Step C: Based on the status information of the front vehicle of convoy Z, monitor whether the bottleneck point (blocking the head of the convoy) shows any signs of evacuation, predict the time for each vehicle in convoy Z to leave the bottleneck point based on the status information of convoy Z, and remind the drivers of each vehicle in convoy Z through the Internet of Vehicles, so that the drivers of each vehicle in the convoy upstream of the highway bottleneck point start their vehicles before their respective departure time from the bottleneck point.

[0049] In step A, the process of constructing fleet Z is as follows: with vehicle j as the center, all vehicles within its coverage range form fleet Z; the range of vehicle j is specifically represented by a rectangle with the lane width a as the width and the distance b in front and behind vehicle j as the length (i.e., the length is 2b).

[0050] In step A, the fleet status information obtained is the status information of all vehicles in fleet Z, including: the total number of vehicles n in the fleet, the speed sj(t) of a certain vehicle j at time t, and the position (latitude and longitude) of vehicle j at time t The speed difference Δs between vehicle j+1 and the preceding vehicle j can be calculated. j+1 (t), the headway between vehicle j+1 and the preceding vehicle j Time distance to the vehicle in:

[0051] Δs j+1 (t) = s j+1 (t)-s j (t);

[0052]

[0053]

[0054] in, Using Euclidean distance, it is expressed as:

[0055]

[0056]

[0057] In step B, the process of determining the congestion state corresponding to convoy Z (interval length is 2b) based on the state information of convoy Z includes the following steps:

[0058] Step B1: Calculate the average speed of team Z at time t based on the status information of team Z. and average headway

[0059]

[0060]

[0061] Where n is the total number of vehicles in the fleet Z, s j (t) is the speed of vehicle j at time t; is the headway between vehicle j and vehicle j-1 at time t, where vehicle j-1 is the preceding vehicle of vehicle j;

[0062] Step B2: Assume that the average speed congestion threshold of the fleet is s min , the average headway congestion threshold is Judgment condition of bottleneck point congestion state γ congestion for:

[0063]

[0064] Among them, event C represents Event D indicates When γ congestion = 0, the fleet Z is running smoothly and is in a non-blocked state. congestion = 1, the fleet Z is moving slowly or blocked and is in a jammed state. In other words, when and Right now When the length of the interval 2b is reached, it is considered that the fleet Z is running smoothly and is in a non-blocked state. congestion The value is 0; when and / or That is, when C∧D and CVD, it is considered that the fleet Z is slow or blocked within the interval length 2b and is in a congested state. congestion The value is 1.

[0065] In step C, based on the status information of the front vehicle of convoy Z, the judgment standard γ of the evacuation sign is calculated. mitigation :

[0066]

[0067] Among them, event E represents Event F indicates is the speed of the front vehicle j1 at time t, is the headway between the front vehicle j2 and the front vehicle j1 at time t; s mitigation is the vehicle speed evacuation threshold, is the headway evacuation threshold; when γ mitigation = 0, the team Z in the bottleneck point shows no signs of evacuation and is still in a blocked state. mitigation = 1, the head of the convoy Z in the bottleneck point shows signs of evacuation, and the congestion begins to be relieved. In other words, when and Right now When , it is considered that the team Z in the bottleneck point has no signs of evacuation and is still in a non-blocked state, and Y mitigation Set the value to 0 to continue monitoring the status of the blocked convoy: and / or That is, when E∧F and EVF, it is considered that the Z head of the team in the bottleneck point shows signs of evacuation, and the congestion state begins to evacuate, and Y mitigation The value is 1, and the next stage is to predict the time for each vehicle in fleet Z to leave the bottleneck point based on the status information of fleet Z.

[0068] In step C, the following formula is used to predict the time it takes for each vehicle in the fleet Z to leave the bottleneck point:

[0069]

[0070] Among them, T j (t) is the total time it takes for vehicle j in the fleet Z at the highway bottleneck point to leave the bottleneck point after the evacuation sign appears ahead; The time delay caused by the drivers of the first vehicle in the convoy Z to vehicle j at time t due to their reaction and starting the vehicle; is the travel time taken by vehicle j from time t to leaving the bottleneck point.

[0071] In this embodiment, Know The calculation formula is:

[0072]

[0073]

[0074] Among them, τ i (t) is the starting delay time of the i-th vehicle in the fleet Z at the bottleneck point of the highway at time t; is the headway between vehicle i and the preceding vehicle at time t; |ω| is the bottleneck congestion dissipation speed, in km / h. According to the traffic flow and traffic wave theory, its calculation formula is:

[0075]

[0076] Where ω is the speed of the bottleneck dissipation wave, in km / h; Q upstream and K upstream are the traffic volume and density upstream of the bottleneck point, in veh / h and veh / km respectively; Q downstream and K downstream are the traffic volume and density downstream of the bottleneck point respectively.

[0077] After predicting the time for each vehicle in fleet Z to leave the bottleneck point, the Internet of Vehicles technology is used to remind the drivers of each vehicle in the fleet that the fleet at the bottleneck point ahead has begun to evacuate, and the estimated time to leave the bottleneck point is displayed. After receiving the evacuation prompt information, the drivers of each vehicle in the fleet can grasp a more accurate starting time, reduce vehicle starting delays, and accelerate the evacuation of the bottleneck point.

[0078] Examples

[0079] The technical solution of the present invention is further described below by taking an expressway with a speed limit of 120 km / h as an example.

[0080] The highway bottleneck point evacuation acceleration method based on the vehicle network of the present invention mainly includes the following steps:

[0081] Step (1): Continuously obtain fleet status information through Internet of Vehicles technology.

[0082] For a convoy within a rectangular interval with a standard lane width of 3.5m and a length of 1km in front and behind the vehicle (a total of 2km), the number of vehicles detected in the interval is 150. For vehicle number j=55, its status information is obtained at time t0: driving speed s 55 (t0) is 20km / h, and the vehicle is at position P 55 The latitude and longitude coordinates of (t0) is (118.921224, 31.921391); for vehicle number j = 56, at t o The status information obtained at all times is: driving speed s 56 (t o ) is 22km / h, the vehicle is at position P 56 The latitude and longitude coordinates of (t0) =(118.921174, 31.921486); the speed difference Δs between vehicle No. 56 and vehicle No. 55 56 (t0) is 22-20=2km / h, the distance between the front wheels for Headway It is 1.89s.

[0083] Step (2) determines the congestion status and promptly informs each vehicle in the convoy. For this 2km interval, the average speed of the convoy at time t0 is detected. 25km / h, average headway is 15m. According to the relevant regulations and documents such as the "Road Traffic Congestion Evaluation Method (GA / T 115-2020)" and the "Road Traffic Safety Law", Less than 30km / h, Less than 50m, in a serious congestion state, γcongestion is 1.

[0084] Step (3) monitors whether there are signs of evacuation at the bottleneck point, predicts the time it will take for vehicles to leave the bottleneck point based on the fleet status information, and alerts the drivers of each vehicle in the fleet through vehicle networking technology. The specific steps include:

[0085] Step (31), monitor whether there are signs of evacuation at the bottleneck point:

[0086] At time t1, the speed of the vehicle number j=1 at the front of the convoy is detected. The distance between the rear vehicle number j=2 and the front vehicle number j=1 is 45km / h. The bottleneck point is 50m, and the convoy shows signs of evacuation. The congestion begins to be evacuated. Y mitigation is 1.

[0087] Step (32), predicting the time for vehicles to leave the bottleneck point based on the fleet status information:

[0088] Traffic flow Q upstream of the bottleneck upstream 1000veh / h, density K upstream The traffic volume downstream of the bottleneck is Q, which is 100 veh / km. downstream 1600veh / h, density K downstream =60veh / km. According to the traffic flow and traffic wave theory, the speed of the bottleneck congestion dissipation wave ω is calculated as Taking vehicle j=150 at the end of the convoy as an example, at time t2 when the front of the convoy shows signs of evacuation, the sum of the headway distances between vehicles in front of vehicle j=150 is 1.2 km. The estimated travel time for vehicle 150 from time t2 to leave the bottleneck is: for

[0089] In the absence of evacuation prompt information, the average start delay time of each vehicle in the convoy is 2.45s, and the total delay time is The total time T for leaving the bottleneck point is 367.5s. * 150 (t2) is 367.5+288=655.5s; when the evacuation start prompt information is displayed through the vehicle networking technology, the average start delay time of each vehicle in the fleet is 1.15s, and the total delay time is 1.15s. The total time T for leaving the bottleneck point is 172.5s. 150 (t2) is 172.5+288=460.5s, and the evacuation acceleration time is ΔT 150 (t2) = T * 150 (t2)-T 150(t2) = 655.5-460.5 = 195s = 3.25min. The evacuation acceleration time of other vehicles in the bottleneck point is calculated in the same way. The overall evacuation acceleration time of the fleet is In summary, this method shows a relatively significant acceleration effect in evacuating highway bottlenecks for both individual vehicles and the entire fleet.

[0090] Step (33) uses the Internet of Vehicles technology to remind the drivers of each vehicle in the fleet that the bottleneck point ahead has begun to be evacuated, and displays the estimated time to leave the bottleneck point.

[0091] In step (4), the drivers of the vehicles in the fleet upstream of the highway bottleneck respond in advance to reduce the start-up delay and accelerate the evacuation of the bottleneck.

[0092] From the above description of the specific implementation methods in combination with the accompanying drawings, it can be seen that the embodiments of the present invention utilize vehicle networking technology to achieve real-time monitoring of signs of evacuation at bottleneck points on highways, promptly remind each vehicle driver of relevant evacuation start prompt information, eliminate the situation where the vision of drivers of vehicles upstream of the highway bottleneck point is blocked, and accelerate the evacuation of bottleneck points by shortening the vehicle start delay time. It also provides effective assistance for evacuating highway traffic congestion, enhancing highway network resilience, and improving vehicle driving safety.

[0093] The above are merely preferred embodiments of the present invention. The scope of protection of the present invention is not limited to the above embodiments. All technical solutions based on the principles of the present invention are within the scope of protection of the present invention. It should be noted that for those skilled in the art, various improvements and modifications that do not depart from the principles of the present invention should be considered within the scope of protection of the present invention.

Claims

1. A highway bottleneck evacuation acceleration method based on vehicle networking, characterized in that: The highway bottleneck point evacuation acceleration method comprises the following steps: Step A: Taking vehicle j on the highway as the center, all vehicles within its coverage area are grouped into a fleet Z, and the status information of fleet Z is continuously obtained through the Internet of Vehicles. Step B: determining the congestion status of the fleet Z according to the status information of the fleet Z, and feeding back the congestion status to each vehicle in the fleet Z; Step C: The head of the blocked convoy is considered the bottleneck. Based on the status information of the leading vehicle in convoy Z, the bottleneck is monitored for signs of evacuation. The time for each vehicle in convoy Z to leave the bottleneck is predicted based on the status information of convoy Z. The driver of each vehicle in convoy Z is reminded through the Internet of Vehicles, so that the drivers of vehicles in the convoy upstream of the bottleneck on the highway start their vehicles before their respective departure times. In step C, the following formula is used to predict the time it takes for each vehicle in the fleet Z to leave the bottleneck point: Among them, T j (t) is the total time it takes for vehicle j in the fleet Z at the highway bottleneck point to leave the bottleneck point after the evacuation sign appears ahead; The time delay caused by the drivers of the first vehicle in the convoy Z to vehicle j at time t due to their reaction and starting the vehicle; is the travel time taken by vehicle j from time t to leaving the bottleneck point; In step C, the following formula is used to calculate and Among them, τ i (t) is the starting delay time of the i-th vehicle in the fleet Z at the bottleneck point of the highway at time t; h gi (t) is the headway between vehicle i and the preceding vehicle at time t; |ω| is the bottleneck congestion dissipation speed, in km / h. According to the traffic flow and traffic wave theory, its calculation formula is: Where ω is the speed of the bottleneck dissipation wave, in km / h; Q upstream and K upstream are the traffic volume and density upstream of the bottleneck point, in veh / h and veh / km respectively; Q downstream and K downstream are the traffic volume and density downstream of the bottleneck point respectively.

2. The highway bottleneck point evacuation acceleration method based on the vehicle network according to claim 1 is characterized in that: In step A, the interval coverage of vehicle j is a rectangle with the lane width a as the width and the distance b in front of and behind vehicle j as the length, where a and b are both positive numbers.

3. The highway bottleneck point evacuation acceleration method based on the Internet of Vehicles according to claim 1 is characterized in that: In step A, the status information of the fleet Z includes: the total number of vehicles n in the fleet, the speed s of vehicle j at time t j (t), the position P of vehicle j at time t j (t); Speed ​​difference Δs between vehicle j+1 and preceding vehicle j j+1 (t), the headway between vehicle j+1 and vehicle j and headway Vehicle j is the preceding vehicle of vehicle j+1, where: Δs j+1 (t)=s j+1 (t)-s j (t); Where s j+1 (t) is the speed of vehicle j+1 at time t; P j+1 (t) is the position of vehicle j+1 at time t.

4. The highway bottleneck evacuation acceleration method based on the Internet of Vehicles according to claim 3 is characterized in that: In step A, Using Euclidean distance, the headway between vehicle j+1 and vehicle j is and headway Respectively expressed as: Where, are the latitude and longitude coordinates of vehicle j at time t, are the latitude and longitude coordinates of vehicle j+1 at time t.

5. The highway bottleneck evacuation acceleration method based on the Internet of Vehicles according to claim 1 is characterized in that: In step B, the process of determining the congestion state corresponding to fleet Z based on the state information of fleet Z includes the following steps: Step B1: Calculate the average speed of team Z at time t based on the status information of team Z. and average headway Where n is the total number of vehicles in the fleet Z, s j (t) is the speed of vehicle j at time t; is the headway between vehicle j and vehicle j-1 at time t, where vehicle j-1 is the preceding vehicle of vehicle j; Step B2: Assume that the average speed congestion threshold of the fleet is s min , the average headway congestion threshold is h gmin , the judgment condition of bottleneck point congestion state γ congestion for: Among them, event C represents Event D indicates When γ congestion = 0, the fleet Z is running smoothly and is in a non-blocked state. congestion =1, convoy Z is moving slowly or blocked and is in a congested state.

6. The highway bottleneck point evacuation acceleration method based on the Internet of Vehicles according to claim 1 is characterized in that: In step C, the evacuation sign judgment criterion γ is calculated based on the status information of the front vehicle of convoy Z. mitigation : Among them, event E represents Event F indicates is the speed of the front vehicle j1 at time t, is the headway between the front vehicle j2 and the front vehicle j1 at time t; s mitigation is the vehicle speed evacuation threshold, h gmitigation is the headway evacuation threshold; when γ mitigation = 0, the team Z in the bottleneck point shows no signs of evacuation and is still in a blocked state. mitigation =1, there are signs of evacuation at the head of convoy Z in the bottleneck point, and the congestion begins to be evacuated.

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