CN116092308B - Vehicle collaborative lane change control method for upstream and downstream of road bottleneck section in network environment - Google Patents
Vehicle collaborative lane change control method for upstream and downstream of road bottleneck section in network environment Download PDFInfo
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- 238000011084 recovery Methods 0.000 claims description 13
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Abstract
The invention discloses a vehicle collaborative lane change control method for the upstream and downstream of a road bottleneck section in a network environment, which is to collect the number of vehicles in each lane of each section at the time t after temporary obstruction (namely bottleneck) of lanes of the section occurs, predict the number of vehicles and average speed of each lane of each section at the next time, construct an upstream section optimal lane change decision model by taking the minimum overall traffic delay and minimum lane change number generated by vehicle lane change as control targets, and solve the optimal lane change sub-combination scheme of each lane of the upstream section. The invention is beneficial to reducing the traffic efficiency reduction and frequent lane changing caused by temporary lane obstruction and ensures the road traffic capacity to the maximum extent.
Description
Technical Field
The invention belongs to the field of intelligent traffic management control, and particularly relates to a method for controlling cooperative lane changing of upstream and downstream vehicles after a bottleneck section appears on a road in a network environment.
Background
In recent years, with the development of 5G and road cooperative technology, active and extensive research has been conducted on the safe driving research and the automatic driving technology of networked automatic driving vehicles, which are expected to improve the efficiency and safety of traffic flows, because networked automatic driving vehicles can share the vehicle position, speed and other driving information with other vehicles in real time through V2V communication to realize cooperative driving between vehicles. In the current road environment, if a traffic accident or obstruction occurs on a certain lane, a traffic bottleneck is formed, and the traffic flow is smoothly changed into congestion and has negative influence on an upstream road section.
Most of current researches focus on information interaction and cooperation of bottleneck road sections and upstream road sections, only pursue the road-changing effect of the bottleneck road sections, and do not consider the downstream road-changing efficiency of vehicles after passing through the bottleneck road sections, neglect the overall traffic efficiency evaluation of the system, and meanwhile, the road-changing frequency of downstream traffic recovery road sections can be caused, the order is disordered, and the extremely high traffic safety risk is brought.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a vehicle collaborative lane change control method for the upstream and downstream of a road bottleneck section in a networked environment, which optimally determines the optimal lane change times of each upstream lane based on the overall traffic efficiency so as to improve the traffic running efficiency, reduce traffic delay and frequent lane change risks increased by traffic bottlenecks, guide the upstream and downstream vehicles to perform collaborative lane change and help the vehicles on the upstream and downstream of the bottleneck section to smoothly pass.
In order to achieve the aim of the invention, the invention adopts the following technical scheme:
the invention relates to a vehicle collaborative lane change control method for the upstream and downstream of a road bottleneck section in a network environment, which is applicable to a unidirectional three-lane road, takes the running direction of a vehicle as the positive direction, and correspondingly takes the section where the temporary barrier is located and the upstream and downstream sections as the bottleneck section, the upstream lane change decision implementation section and the downstream traffic recovery when the temporary barrier occurs at the moment tRoad section; the road section of any road section is numbered as i, the upstream road-changing decision implementing road section, the bottleneck road section and the downstream traffic recovery road section are numbered as i=1, 2 and 3 in sequence, and the length of any i-th road section is L i The method comprises the steps of carrying out a first treatment on the surface of the Numbering any lane on each road section as j, and numbering lanes from inside to outside as j=1, 2 and 3; let the lane where temporary obstruction occurs at time t be the 3 rd lane, i.e., j=3; defining the number of vehicles on the ith road section at t moment from the jth lane to the adjacent jth-1 lane as c i,j,j-1 (t) let the number of vehicles in the jth lane on the ith road section at the moment t be n i,j (t)，x i,j,m (t)、v i,j,m (T) the position and speed of the vehicle m on the jth lane on the ith road section at the moment T, respectively, each control time interval being T c The method comprises the steps of carrying out a first treatment on the surface of the The method is characterized by comprising the following steps of;
step 1, predicting the number n of vehicles in the jth lane on the ith road section at the time t+1 at the current time t i,j (t+1) and average speed
Step 1.1 calculating the density k of the jth lane on the ith road section at the current t moment by using the formula (1) i,j (t)；
k i,j (t)＝n i,j (t)/L i (1)
Step 1.2 calculating the flow { q } transmitted downstream of the jth lane on the ith road segment at the t moment by using the method (2) i,j (t) |i=1, 2}; calculating the flow q transmitted downstream of the jth lane on the 3 rd road section at the t moment, namely the downstream traffic recovery road section by using the method (3) 3,j (t)；
q 3,j (t)＝v f ·k 3,j (t) (3)
In the formulas (2) and (3), v f At free flow velocity, k i+1,j (t) is the density of the jth lane on the (i+1) th road section at the current t moment,for the jam density omega of each lane on the i+1 road section at the current t moment i Is the congestion propagation speed on the i-th road section and is obtained by the formula (4);
in the formula (4), the amino acid sequence of the compound,for the critical density of each lane on the i-th road section, < > for each lane on the i-th road section>The blocking density of each lane on the ith road section;
step 1.3 predicting the density k of the jth lane on the ith road segment at time t+1 by using the method (5) i,j (t+1)；
In the formula (5), q i-1,j (t) is the flow transmitted downstream from the jth lane on the ith-1 road section at the moment t; when i=1, q i-1,j (t) is the flow of the downstream transmission of the jth lane of the upstream road section decision implementation road section, namely the 1 st road section at the moment t;
step 1.4 calculating the predicted number n of vehicles on the jth lane on the ith road segment at time t+1 by using the formula (6) and the formula (7), respectively i,j (t+1) predicted average speed of the jth lane on the ith link
n i,j (t+1)＝k i,j (t+1)·L i (6)
Step 2, constructing a vehicle optimal lane change number model of an upstream lane change decision implementation road section:
step 2.1, constructing an objective function z with the minimum sum of the whole delay of the road section and the upstream and downstream lane change times as a control target by utilizing a formula (8);
in the formula (8), lambda 1 Weight, lambda, of total delay for road segment 2 The weight of the channel changing times is controlled; c 1,2,1 (t) represents the number of vehicles on the 1 st road section from the 2 nd lane to the 1 st lane at the time t, n c ' represents the optimal number of single-lane vehicles on the 3 rd road section, namely the downstream traffic recovery road section after uniform distribution, andn 3,j (t+1) represents the predicted number of vehicles on the jth lane on the 3 rd road section at time t+1;
step 2.2 construct constraints using equation (9):
c 1,2,1 (t)≤n 1,2 (t)+n 1,3 (t) (9)
in the formula (9), n 1,2 (t) is the number of vehicles on the 2 nd lane on the 1 st road section at the moment t, n 1,3 (t) is the number of vehicles on the 3 rd lane on the 1 st road section at the time t;
step 3, solving the optimal lane change number model of the vehicle by utilizing a genetic algorithm to obtain the optimal lane change number from the 2 nd lane to the 1 st lane on the 1 st road sectionThis gives a number of vehicles on road section 1 from lane 2 to lane 1 +.>The number of vehicles changing from lane 3 to lane 2 is c 1,3，2 (t)＝n 1，3 (t)；
Step 4 of initializing i=1, controlling the time interval T between the current time T and the time t+1 c In the road, traversing all vehicles on the 2 nd and 3 rd lanes on the ith road section to change the lanes;
step 4.1 obtaining the position { x } of the vehicle m on the jth lane on the ith road segment i,j,m (t) |j=1, 2,3} and velocity { v } i,j,m (t)|j＝1,2,3}；
Step 4.2 for position x i,j,m The positions of the vehicles m, m 'and m' of the front vehicles m ', and the rear vehicles m' adjacent to each other on the j-1 th lane at the current time t are respectively denoted as x i,j-1,m′ (t) and x i,j-1,m″ (t), wherein j is greater than or equal to 2;
judging whether a safe channel change condition shown in a formula (10) is met; if so, changing the lane of the vehicle m from the jth lane to the jth-1 lane, otherwise, not allowing the lane of the vehicle m to be changed;
x i,j-1,m″ (t)+H≤x i,j,m (t)≤x i,j-1,m′ (t)-H (10)
in the formula (10), H is a specified safe lane change interval;
step 4.3, for a unidirectional three-lane road, judging whether the formula (11) is satisfied, if so, executing step 4.4, otherwise, executing step 4.5:
in the formula (11), c' 1,2,1 (t) represents the accumulated lane change times from lane 2 to lane 1; c' 1,3,2 (t) represents the accumulated lane change times from lane 3 to lane 2;
step 4.4 stopping the track switching operation and waiting for the control time interval to reach T c Then, assigning t+1 to t, and returning to the step 1 for sequential execution;
step 4.5 judging whether the control time interval reaches T c If yes, assigning t+1 to t, and returning to the step 1 for sequential execution; otherwise, returning to the step 4.1 to continue traversing.
The electronic device of the present invention includes a memory and a processor, wherein the memory is configured to store a program for supporting the processor to execute the vehicle cooperative lane change control method, and the processor is configured to execute the program stored in the memory.
The invention relates to a computer readable storage medium, wherein a computer program is stored on the computer readable storage medium, and the computer program is executed by a processor to execute the steps of the vehicle collaborative lane change control method.
Compared with the prior art, the invention has the beneficial technical effects that:
1. according to the vehicle collaborative lane change control method for the upstream and downstream of the road bottleneck section in the network environment, which is disclosed by the invention, the overall vehicle running delay of the road section after the bottleneck appears and the minimum total lane change number of the upstream and downstream of the bottleneck section are taken as control targets, and an optimal calculation model of the optimal lane change times of the vehicles in each upstream lane is constructed, so that the optimal lane change number of the vehicles in each lane based on the current bottleneck is solved, the collaborative lane change of the vehicles in the upstream and downstream of the bottleneck is helped, the vehicles in the bottleneck smoothly pass, and the traffic running efficiency and safety are improved.
2. According to the method, the transmission flow of each lane is calculated by utilizing a cellular transmission idea, the number and average speed of vehicles in each lane in the next control time interval are predicted, the accuracy of the predicted speed is improved, and the calculation efficiency of the control method is optimized.
3. The invention utilizes the superiority of real-time sharing of the network-linked automatic driving vehicle information to obtain the real-time state information of the road, such as the number of vehicles in the road section, the speed and the like, and improves the accuracy of the optimal change number optimization calculation model.
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FIG. 1 is a schematic view of a scenario of the present invention;
fig. 2 is a general flow chart of the present invention.
Detailed Description
In this embodiment, a method for controlling collaborative lane changing of vehicles at the upstream and downstream of a bottleneck section of a road in a networked environment is suitable for multi-lane collaborative lane changing control after temporary obstruction (i.e. bottleneck) occurs on the road in the networked environment, as shown in fig. 1, all vehicles driving on the road in the networked environment are networked autopilot vehicles, the basic section of the bottleneck is unidirectional three lanes, and the driving direction of the vehicles is the sameIn the forward direction, when the temporary lane blocking occurs at the moment t, the road section where the temporary lane blocking exists and the road sections above and below the road section are correspondingly used as a bottleneck road section, an upstream lane changing decision implementation road section and a downstream traffic recovery road section; the road section of any road section is numbered as i, the upstream road-changing decision implementing road section, the bottleneck road section and the downstream traffic recovery road section are numbered as i=1, 2 and 3 in sequence, and the length of any i-th road section is L i The method comprises the steps of carrying out a first treatment on the surface of the Numbering any lane on each road section as j, and numbering lanes from inside to outside as j=1, 2 and 3; let the lane where temporary obstruction occurs at time t be the 3 rd lane, i.e., j=3; defining the number of vehicles on the ith road section at t moment from the jth lane to the adjacent jth-1 lane as c i,j,j-1 (t) obtaining the number n of the jth lane on the ith road section at the moment t by using the road side unit and the positioning module installed on the networked automatic driving vehicle i,j (t), position x of vehicle m on jth lane in ith road section i,j,m (t) and velocity v i,j,m (T) each control time interval is T c 。
As shown in fig. 2, the collaborative lane change control method is performed according to the following steps:
step 1, predicting the number n of vehicles in the jth lane on the ith road section at the time t+1 at the current time t i,j (t+1) and average speed
Step 1.1 calculating the density k of the jth lane on the ith road section at the current t moment by using the formula (1) i,j (t)；
k i,j (t)＝n i,j (t)/L i (1)
Step 1.2, calculating the traffic flow of each lane based on the thought of a cell transmission model:
calculating the flow { q } transmitted downstream of the jth lane on the ith road section at the t moment by using the method (2) i,j (t)|i＝1,2}；
Calculating the flow q transmitted downstream of the jth lane on the 3 rd road section at the t moment, namely the downstream traffic recovery road section by using the method (3) 3,j (t)；
q 3,j (t)＝v f ·k 3,j (t) (3)
In the formulas (2) and (3), v f At free flow velocity, k i+1,j (t) is the density of the jth lane on the (i+1) th road section at the current t moment,for the jam density omega of each lane on the i+1 road section at the current t moment i Is the congestion propagation speed on the i-th road section and is obtained by the formula (4);
in the formula (4), the amino acid sequence of the compound,for the critical density of each lane on the i-th road section, < > for each lane on the i-th road section>The blocking density of each lane on the ith road section;
step 1.3 predicting the density k of the jth lane on the ith road segment at time t+1 by using the method (5) i,j (t+1)；
In the formula (5), q i-1,j (t) is the flow transmitted downstream from the jth lane on the ith-1 road section at the moment t; when i=1, q i-1,j (t) is the flow of the downstream transmission of the jth lane of the upstream road section decision implementation road section, namely the 1 st road section at the moment t;
step 1.4 calculating the predicted number n of vehicles on the jth lane on the ith road segment at time t+1 by using the formula (6) and the formula (7), respectively i,j (t+1) predicted average speed of the jth lane on the ith link
n i,j (t+1)＝k i,j (t+1)·L i (6)
Step 2, constructing a vehicle optimal lane change number model of an upstream lane change decision implementation road section:
step 2.1, constructing an objective function z with the minimum sum of the whole delay of the road section and the upstream and downstream lane change times as a control target by utilizing a formula (8);
in the formula (8), lambda 1 Weight, lambda, of total delay for road segment 2 The weight of the channel changing times is controlled; c 1,2,1 (t) represents the number of vehicles on the 1 st road section from the 2 nd lane to the 1 st lane at the time t, n c ' represents the optimal number of single-lane vehicles on the 3 rd road section, namely the downstream traffic recovery road section after uniform distribution, andn 3,j (t+1) represents the predicted number of vehicles on the jth lane on the 3 rd road section at time t+1;
step 2.2 construct constraints using equation (9):
c 1,2,1 (t)≤n 1,2 (t)+n 1,3 (t) (9)
in the formula (9), n 1,2 (t) is the number of vehicles on the 2 nd lane on the 1 st road section at the moment t, n 1,3 (t) is the number of vehicles on the 3 rd lane on the 1 st road section at the time t;
step 3, solving the optimal lane change number model of the vehicle by utilizing a genetic algorithm to obtain the optimal lane change number from the 2 nd lane to the 1 st lane on the 1 st road sectionThis gives a number of vehicles on road section 1 from lane 2 to lane 1 +.>The number of vehicles changing from lane 3 to lane 2 is c 1,3，2 (t)＝n 1，3 (t)；
Step 4 of initializing i=1, controlling the time interval T between the current time T and the time t+1 c In the road, traversing all vehicles on the 2 nd and 3 rd lanes on the ith road section to change the lanes;
step 4.1 obtaining the position { x } of the vehicle m on the jth lane on the ith road segment i,j,m (t) |j=1, 2,3} and velocity { v } i,j,m (t)|j＝1,2,3}；
Step 4.2 Using the positioning Module and roadside Intelligent Equipment mounted on the networked autonomous vehicle for position x i,j,m The positions of the vehicles m, m 'and m' of the front vehicles m ', and the rear vehicles m' adjacent to each other on the j-1 th lane at the current time t are respectively denoted as x i,j-1,m′ (t) and x i,j-1,m″ (t), wherein j is greater than or equal to 2;
judging whether a safe channel change condition shown in a formula (10) is met; if so, changing the lane of the vehicle m from the jth lane to the jth-1 lane, otherwise, not allowing the lane of the vehicle m to be changed;
x i,j-1,m″ (t)+H≤x i,j,m (t)≤x i,j-1,m′ (t)-H (10)
in the formula (10), H is a specified safe lane change interval;
step 4.3, for a unidirectional three-lane road, judging whether the formula (11) is satisfied, if so, executing step 4.4, otherwise, executing step 4.5:
in the formula (11), c' 1,2,1 (t) represents the accumulated lane change times from lane 2 to lane 1; c' 1,3,2 (t) represents the accumulated lane change times from lane 3 to lane 2;
step 4.4 stopping the track switching operation and waiting for the control time interval to reach T c Then, assigning t+1 to t, and returning to the step 1 for sequential execution;
step 4.5 judging whether the control time interval reaches T c If yes, assigning t+1 to t, and returning to the step 1 for sequential execution; otherwise, returning to the step 4.1 to continue traversing.
In this embodiment, an electronic device includes a memory for storing a program for supporting the processor to execute the above-described vehicle co-channel change control method, and a processor configured to execute the program stored in the memory.
In this embodiment, a computer readable storage medium stores a computer program, which when executed by a processor, performs the steps of the vehicle co-channel change control method described above.
In this embodiment, the method of the present invention is not limited to the road bottleneck section of three lanes passing in one direction, and other embodiments obtained by those skilled in the art without creative changes are all within the scope of the present invention.
Claims (3)
1. A kind of vehicle that links up and down in the bottleneck section of road under the network and links the environment cooperatees and trades the road control method, its applicable scene is one-way three lanes, regard vehicle driving direction as the positive direction, when the temporary obstacle of the lane occurs at time t, regard section and upper and lower road section where temporary obstacle is located as bottleneck section, upstream trade the decision to implement section and downstream traffic recovery section correspondingly; the road section of any road section is numbered as i, the upstream road-changing decision implementing road section, the bottleneck road section and the downstream traffic recovery road section are numbered as i=1, 2 and 3 in sequence, and the length of any i-th road section is L i The method comprises the steps of carrying out a first treatment on the surface of the Numbering any lane on each road section as j, and numbering lanes from inside to outside as j=1, 2 and 3; let the lane where temporary obstruction occurs at time t be the 3 rd lane, i.e., j=3; defining the number of vehicles on the ith road section at t moment from the jth lane to the adjacent jth-1 lane as c i,j,j-1 (t) let t be the ith road section at timeThe number of vehicles on lane j is n i,j (t)，x i,j,m (t)、v i,j,m (T) the position and speed of the vehicle m on the jth lane on the ith road section at the moment T, respectively, each control time interval being T c The method comprises the steps of carrying out a first treatment on the surface of the The method is characterized by comprising the following steps of;
step 1, predicting the number n of vehicles in the jth lane on the ith road section at the time t+1 at the current time t i,j (t+1) and average speed
Step 1.1 calculating the density k of the jth lane on the ith road section at the current t moment by using the formula (1) i,j (t)；
k i,j (t)＝n i,j (t)/L i (1)
Step 1.2 calculating the flow { q } transmitted downstream of the jth lane on the ith road segment at the t moment by using the method (2) i,j (t) |i=1, 2}; calculating the flow q transmitted downstream of the jth lane on the 3 rd road section at the t moment, namely the downstream traffic recovery road section by using the method (3) 3,j (t)；
q 3,j (t)＝v f ·k 3,j (t) (3)
In the formulas (2) and (3), v f At free flow velocity, k i+1,j (t) is the density of the jth lane on the (i+1) th road section at the current t moment,for the jam density omega of each lane on the i+1 road section at the current t moment i Is the congestion propagation speed on the i-th road section and is obtained by the formula (4);
in the formula (4), the amino acid sequence of the compound,for the critical density of each lane on the i-th road section, < > for each lane on the i-th road section>The blocking density of each lane on the ith road section;
step 1.3 predicting the density k of the jth lane on the ith road segment at time t+1 by using the method (5) i,j (t+1)；
In the formula (5), q i-1,j (t) is the flow transmitted downstream from the jth lane on the ith-1 road section at the moment t; when i=1, q i-1,j (t) is the flow of the downstream transmission of the jth lane of the upstream road section decision implementation road section, namely the 1 st road section at the moment t;
step 1.4 calculating the predicted number n of vehicles on the jth lane on the ith road segment at time t+1 by using the formula (6) and the formula (7), respectively i,j (t+1) predicted average speed of the jth lane on the ith link
n i,j (t+1)＝k i,j (t+1)·L i (6)
Step 2, constructing a vehicle optimal lane change number model of an upstream lane change decision implementation road section:
step 2.1, constructing an objective function z with the minimum sum of the whole delay of the road section and the upstream and downstream lane change times as a control target by utilizing a formula (8);
in the formula (8), lambda 1 Weight, lambda, of total delay for road segment 2 The weight of the channel changing times is controlled; c 1,2,1 (t) represents the number of vehicles on the 1 st road section from the 2 nd lane to the 1 st lane at the time t, n c ' represents the optimal number of single-lane vehicles on the 3 rd road section, namely the downstream traffic recovery road section after uniform distribution, andn 3,j (t+1) represents the predicted number of vehicles on the jth lane on the 3 rd road section at time t+1;
step 2.2 construct constraints using equation (9):
c 1,2,1 (t)≤n 1,2 (t)+n 1,3 (t) (9)
in the formula (9), n 1,2 (t) is the number of vehicles on the 2 nd lane on the 1 st road section at the moment t, n 1,3 (t) is the number of vehicles on the 3 rd lane on the 1 st road section at the time t;
step 3, solving the optimal lane change number model of the vehicle by utilizing a genetic algorithm to obtain the optimal lane change number from the 2 nd lane to the 1 st lane on the 1 st road sectionThis gives a number of vehicles on road section 1 from lane 2 to lane 1 +.>The number of vehicles changing from lane 3 to lane 2 is c 1,3，2 (t)＝n 1，3 (t)；
Step 4 of initializing i=1, controlling the time interval T between the current time T and the time t+1 c In the road, traversing all vehicles on the 2 nd and 3 rd lanes on the ith road section to change the lanes;
step 4.1 obtaining the position { x } of the vehicle m on the jth lane on the ith road segment i,j,m (t) |j=1, 2,3} and velocity { v } i,j,m (t)|j＝1,2,3}；
Step 4.2 for position x i,j,m Vehicle m of (t) with current time t at the firstThe positions of the adjacent front vehicles m 'and rear vehicles m' on the j-1 lane are respectively marked as x i,j-1,m′ (t) and x i,j-1,m″ (t), wherein j is greater than or equal to 2;
judging whether a safe channel change condition shown in a formula (10) is met; if so, changing the lane of the vehicle m from the jth lane to the jth-1 lane, otherwise, not allowing the lane of the vehicle m to be changed;
x i,j-1,m″ (t)+H≤x i,j,m (t)≤x i,j-1,m′ (t)-H (10)
in the formula (10), H is a specified safe lane change interval;
step 4.3, for a unidirectional three-lane road, judging whether the formula (11) is satisfied, if so, executing step 4.4, otherwise, executing step 4.5:
in the formula (11), c' 1,2,1 (t) represents the accumulated lane change times from lane 2 to lane 1; c' 1,3,2 (t) represents the accumulated lane change times from lane 3 to lane 2;
step 4.4 stopping the track switching operation and waiting for the control time interval to reach T c Then, assigning t+1 to t, and returning to the step 1 for sequential execution;
step 4.5 judging whether the control time interval reaches T c If yes, assigning t+1 to t, and returning to the step 1 for sequential execution; otherwise, returning to the step 4.1 to continue traversing.
2. An electronic device comprising a memory and a processor, wherein the memory is configured to store a program that supports the processor to execute the vehicle co-channel change control method of claim 1, the processor being configured to execute the program stored in the memory.
3. A computer-readable storage medium, on which a computer program is stored, characterized in that the computer program, when being executed by a processor, performs the steps of the vehicle co-channel change control method according to claim 1.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN113744539A (en) * | 2021-09-17 | 2021-12-03 | 合肥工业大学 | Dynamic regulation and control method for network connection vehicle special lane based on permeability |
| CN114387781A (en) * | 2021-12-30 | 2022-04-22 | 北京建筑大学 | Vehicle guidance control method |
| CN115240442A (en) * | 2022-07-26 | 2022-10-25 | 合肥工业大学 | Optimal lane changing control method for following vehicles of front accident vehicles in internet environment and application |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113744539A (en) * | 2021-09-17 | 2021-12-03 | 合肥工业大学 | Dynamic regulation and control method for network connection vehicle special lane based on permeability |
| CN114387781A (en) * | 2021-12-30 | 2022-04-22 | 北京建筑大学 | Vehicle guidance control method |
| CN115240442A (en) * | 2022-07-26 | 2022-10-25 | 合肥工业大学 | Optimal lane changing control method for following vehicles of front accident vehicles in internet environment and application |
Non-Patent Citations (2)
| Title |
|---|
| Locations and Length of Entrances and Exits of an Automated Truck Lane on a U.S. Freeway;Ximena Jauregui 等;《2021 Smart City Symposium Prague (SCSP)》;全文 * |
| 混入智能车的下匝道瓶颈路段交通流建模与仿真分析;董长印;王昊;王炜;李烨;华雪东;;物理学报(第14期);全文 * |
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