CN114187771A - Bus driving control method and system based on cooperative adaptive cruise control - Google Patents
Bus driving control method and system based on cooperative adaptive cruise control Download PDFInfo
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Abstract
The invention provides a bus driving control method and system based on cooperative adaptive cruise control, which comprises the following steps: judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not; if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; when the time interval is smaller than a preset value, the public transport vehicle is switched to a cooperative self-adaptive cruise control mode; the invention determines the cruising mode of the bus on the basis of judging whether the bus is in the CACC fleet, combines the traditional bus control with the CACC, not only improves the service performance of a single bus line, but also coordinates and optimizes the system service performance of the buses of a plurality of lines on the same road section.
Description
Technical Field
The invention belongs to the technical field of bus operation scheduling, and particularly relates to a bus driving control method and system based on cooperative adaptive cruise control.
Background
The application of the automatic driving technology of the public transport vehicle is an important research direction for realizing a public transport priority strategy; the traditional manually driven public transport vehicles have the problems of low crossing traffic efficiency at rush hour, unbalanced arrival time, poor fuel economy and the like; aiming at the problem, the inventor researches a multi-objective optimization-based speed optimization control method of the bus running interval in the early stage, divides the bus running target into two levels of punctuality and fuel economy according to importance, and obtains the bus running interval optimization speed through a multi-objective optimization model.
The inventor finds that for a single bus line, the speed control and the station control can adjust the speed and the time interval of the bus head, so that the phenomenon of train bunching or large interval arrival is relieved; however, if a plurality of bus routes share a bus lane on the same road section, the conventional bus control may be interfered by other bus routes, and the operation efficiency and service level of the public transport system are affected.
Disclosure of Invention
The invention combines the traditional public traffic Control and Cooperative Adaptive Cruise Control (CACC), not only can improve the service performance of a single bus line, but also can coordinate and optimize the system service performance of the public traffic vehicles on a plurality of lines on the same road section.
In order to achieve the purpose, the invention is realized by the following technical scheme:
in a first aspect, the invention provides a bus driving control method based on cooperative adaptive cruise control, which comprises the following steps:
judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; and when the time interval is smaller than the preset value, the public transport vehicle is switched to a cooperative adaptive cruise control mode.
Further, the formation of the cooperative self-adaptive cruise control fleet is determined by the length of the front fleet and the standing time required by the current bus to maintain the punctuality.
Further, if the length of the motorcade exceeds the preset vehicle, the rear public transport vehicle cannot join the motorcade; when the expected speed of the bus is higher than that of the front motorcade, changing lanes to overtake the motorcade in the self-adaptive cruise control mode;
when the corresponding expected stop control time of the downstream stop exceeds the maximum allowed stop time, the current bus changes lanes and runs at the expected speed in the adaptive cruise control mode.
Further, at the intersection, the fleet is separated from the buses arriving at the red light time, and the time of each bus arriving at the intersection in the fleet is calculated as follows:
wherein, tiFor the arrival time, L, of each bus in the fleet at downstream intersection iiIs the position of intersection i, L1For public transport vehicle at t1,1Position of time, V*In order to be able to take the desired speed,is the fleet speed.
Furthermore, when the driving mode is determined according to the position of the bus in the motorcade, the front bus in the motorcade executes the self-adaptive cruise control mode, and the rear bus executes the cooperative self-adaptive cruise control following mode.
Further, in the coordinated adaptive cruise control mode, the real-time acceleration is adjusted according to the difference between the desired speed and the current speed:
a(k)=kg·[V*-v(k-1)]
wherein k is a time step; k is a radical ofgFor constant feedback gain between speed deviation and acceleration, V*V is the current speed for the desired speed.
Further, the real-time speed of the bus is determined by using the time interval error and the derivative:
wherein k ispAnd kdTo control the coefficient, ekIs the time interval error between the current bus and the front bus,is the derivative of the time interval error.
In a second aspect, the invention also provides a bus driving control system based on cooperative adaptive cruise control, which comprises a judgment module and a control module;
the determination module configured to: judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
the control module configured to: if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; and when the time interval is smaller than the preset value, the public transport vehicle is switched to a cooperative adaptive cruise control mode. But whether a CACC fleet is formed will depend on the length of the fleet ahead and the standing time required for the current vehicle to maintain punctuality.
In a third aspect, the present invention also provides a computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, implements the steps of the method for controlling the driving of a bus based on the cooperative adaptive cruise control according to the first aspect.
In a fourth aspect, the present invention further provides an electronic device, which includes a memory, a processor, and a computer program stored in the memory and executable on the processor, and when the processor executes the program, the steps of the method for controlling driving of a bus based on cooperative adaptive cruise control according to the first aspect are implemented.
Compared with the prior art, the invention has the beneficial effects that:
1. the invention determines the cruising mode of the bus on the basis of judging whether the bus is in the CACC fleet, combines the traditional bus control with the CACC, not only improves the service performance of a single bus line, but also coordinates and optimizes the system service performance of the buses of a plurality of lines on the same road section;
2. in the invention, when the CACC fleet is formed, the length of the front fleet and the standing time factor required by the current bus for keeping the punctuality are taken as determining factors, thereby effectively improving the running efficiency and the service level of a public transport system;
3. on the level of a road section, the bus control system based on the CACC dynamically optimizes the expected speed of each bus to ensure the service level of the bus, and on the level of the road section, the bus control system based on the CACC coordinates the operation speed by adjusting the time interval of the bus heads in a CACC fleet; meanwhile, between a line layer and a road section layer, a CACC-based public traffic control system carries out CACC fleet formation, team formation or team release decision; by combining the traditional bus control with the CACC, the problem that the bus control is possibly interfered by other bus lines when a plurality of bus lines share one bus lane on the same road section is solved;
4. the cooperative adaptive cruise control is combined with public transport, the advantages of the CACC technology in the aspects of improving road traffic capacity, saving fuel consumption, improving safety and the like are exerted, and the overall performance of public transport operation service is cooperatively optimized from the perspective of a system;
5. the invention can be applied to various scenes of single-line operation and multi-line cooperative operation of the urban road public traffic system, considers various operation conditions of intersection, stop, interval operation and the like of the public traffic vehicle, combines speed control and stop control, cooperatively optimizes performance indexes of the public traffic system such as integral punctuality, fuel economy and the like, and can effectively improve the operation efficiency and the service level of the public traffic system.
Drawings
The accompanying drawings, which form a part hereof, are included to provide a further understanding of the present embodiments, and are incorporated in and constitute a part of this specification, illustrate exemplary embodiments of the present embodiments and together with the description serve to explain the present embodiments without unduly limiting the present embodiments.
FIG. 1 is a bus control concept of the CACC according to embodiment 1 of the present invention;
FIG. 2 is a CACC-based bus fleet grouping condition and driving mode determination framework in embodiment 1 of the present invention;
FIG. 3 is a graph of bus transit time-distance according to embodiment 1 of the present invention;
FIG. 4 is a control flow chart of the method for determining that a vehicle is not in a CACC fleet according to embodiment 1 of the present invention;
fig. 5 is a control flowchart of the CACC fleet determination according to embodiment 1 of the present invention.
The specific implementation mode is as follows:
the invention is further described with reference to the following figures and examples.
It should be noted that the following detailed description is exemplary and is intended to provide further explanation of the disclosure. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.
Example 1:
the embodiment provides a bus driving control method based on cooperative adaptive cruise control, which comprises the following steps:
judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; when the time interval is smaller than a preset value, the public transport vehicle is switched to a cooperative self-adaptive cruise control mode;
as shown in fig. 1 and fig. 2, the overall idea in this embodiment is that, at a line level, a CACC-based bus control system dynamically optimizes the expected speed of each bus to ensure the service level thereof; on the road section level, the bus control system based on the CACC coordinates the operation speed by adjusting the time headway in the CACC fleet; meanwhile, between a line layer and a road section layer, a CACC-based bus control system carries out CACC fleet formation, team formation or team release decision.
In this embodiment, the optimization of the bicycle speed specifically includes:
the method for optimizing the speed of the single bus comprises the steps of adopting the real-time control of the running speed of the bus proposed by a hierarchical sequence method based on multi-target planning, classifying and solving multiple targets according to the importance of the multiple targets; specifically, the bus operation target is divided into a punctuality target and a fuel economy target, the punctuality target is set as a most important target, the fuel economy target is a secondary important target, an optimal solution set is obtained aiming at the most important target (namely the punctuality target), and an optimal solution is obtained for the secondary important target (namely the fuel economy) on the basis of the optimal solution set; the specific implementation procedure is as follows: firstly, according to real-time position data and current time acquired by a vehicle-mounted unit equipped on a bus, determining whether the current bus can arrive at a station on time or not by combining a bus arrival punctuality area judgment model: if the bus speed is located in the punctuality area, optimizing the bus running speed according to the fuel economy on the basis of preferentially meeting the punctuality requirement to obtain an optimal bus running suggested speed value; if the bus stop is located in the early or late area, the bus stop is optimized through fuel economy on the basis of preferentially ensuring the minimum arrival deviation time, and the bus running suggested speed is obtained.
In the embodiment, assuming that the number of stations along the bus is m, a signalized intersection exists on a road section between a current station s-1(1, …, m-1) and a downstream adjacent station s (s is 2, …, m); if n (n is more than or equal to 0) intersections exist between the two stations, n +1 road sections and n +2 nodes exist; v is the set of desired velocities, ViRepresenting a desired speed on road segment i (i ═ 1, …, n +1) in meters per second; when the bus is positioned in the punctual arrival interval, the bus can arrive at a downstream bus station on time no matter how the speed of the bus changes; the interval desired speed over the entire road section is now optimized by minimizing the Total Fuel Consumption (TFC):
wherein, FC (V)i) Fuel consumption on road section i is given in ml/sec.
On the contrary, when the bus is in an early or late area, the speed regulation is difficult to meet the requirement of quasi-point arrival, and only the arrival time deviation can be minimized; for such buses, the punctuality should be guaranteed, i.e. the arrival time deviation should be minimized, regardless of the fuel economy; first, the expected speeds of the early and late vehicles are set to V, respectivelyminAnd VmaxMaking the arrival time as close to the schedule as possible; sequentially estimating the time of the bus reaching a downstream intersection; if the vehicle reaches the intersection i (i ═ 1, …, n) within the red time, the desired speed should be adjusted by minimizing fuel consumption for the road segment; as a secondary important objective, fuel economy can be optimized:
minFC(Vi) (2)
for calculating an optimum desired speed V*Adopting the upper and lower limits (V) of the bus running speedmin≤Vi≤Vmax) Solving the objective functions (1) and (2) as constraint conditions; further, the ideal speed V*Is the target speed which can be reached by the bus needing to accelerate or decelerate. A group V can determine a specific bus speed track V; in consideration of signal timing, the present embodiment proposes a method for adjusting the desired speed V*Calculating the vehicle speed trajectory v*The algorithm of (1) is specifically as follows: first, three trajectories are defined: 1) between two successive nodes, the bus accelerates or decelerates, maintaining the desired speed through the downstream intersection; 2) the bus reaches and keeps the expected speed, and decelerates to a downstream intersection to stop; 3) the bus reaches and maintains the expected speed, then decelerates to the downstream intersection, and passes through the intersection at a non-zero speed; then, estimating the arrival time of the intersection by using the first track, and if the bus arrives at the intersection in the green light phase, determining the speed track as the first track; otherwise, entering the next step; next, estimating the arrival time by using a second track, and if the second track is in the red light phase, determining the second track as a speed track; otherwise, selecting a third track; for the third trace, the arrival time is the start time of the green light.
In the present embodiment, fig. 3 shows how the time-distance map is used to determine the time-of-arrival range; suppose a bus is at t1,1Time at L1Where, predicted at ts,n+2To the downstream station Ln+2At least one of (1) and (b); here, ts,n+2The arrival time can be extracted from a timetable, or can be calculated from the ideal headway of the previous bus on the same route; in the present embodiment, ts,n+2The time is defined as the time, and the time period of the punctual arrival can be defined in the application; at site L1And Ln+2Between them there is an intersection LiThe time range of the vehicle reaching the intersection can be limited by the lower limit t of the punctualitylbAnd the punctual region upper limit tubThree ranges of arrival time are divided: quasi-point region [ tlb,tub]Early region (-infinity, t)lb) And late region (t)ub, + ∞); judging the current time tcQuasi-point time range:
wherein, the lower limit of the intersection punctuation interval is in a period p (p is 1, 2, …), and the upper limit of the punctuation interval is in a period q (q is 1, 2, …); t is tgIs the start time of the green phase, trThe start time of the red light phase.
In the present embodiment, a fuel consumption model based on Vehicle Specific Power (VSP) is adopted, as follows:
therein, FCphFor the fuel consumption of the vehicle at phase PH (PH 1, …, PH), units of mL/s, ERbIs the instantaneous fuel consumption, ER, of VSP interval bb=ER0×NERbUnit mL/s; ER0Is the average fuel consumption rate of VSP interval, ER for public traffic vehicles0=1.69mL/s;NERbNormalized fuel consumption b (b 1, …, b) in VSP interval, unit mL/s:
in this embodiment, the VSP model of the bus is:
VSP=1.1av+0.09199v+0.000168v3 (7)
in the formula, VSP is the instantaneous power of the engine required by each vehicle for pulling unit mass, and the unit is kilowatt/ton (kW/t); a is acceleration in meters per second squared (m/s)2) (ii) a v is vehicle speed in m/s.
In this embodiment, in CACC control, speed control and vehicle time interval control are:
in the bus control system based on the CACC, in the embodiment, a cruise model in a formula (8) is adopted to adjust the speed track of the bus in a speed control mode; the cruise model adjusts the real-time acceleration according to the difference between the desired speed and the current speed so that the actual speed may be as close as possible to the desired speed.
a(k)=kg·[V*-v(k-1)] (8)
Wherein k is the time step; k is a radical ofgIs a constant feedback gain between the speed deviation and the acceleration, k in this embodimentgCan be set to 0.3 to 0.4s-1。
In the vehicle time interval control mode, in the present embodiment, the following model control as formula (9) is adopted, and the vehicle is operated at a constant time interval; the first order model in the following equation determines the bus real time speed using the time interval error and the derivative.
Wherein k ispAnd kdTo control the coefficient (k)p0.45 and kd=0.25);ekIs the time interval error with the front bus,xr-1is the real-time position, x, of the preceding vehiclerAnd vrRespectively the real-time position (m) and the speed (m/s) of the current vehicle;is the desired time interval.
In this embodiment, the CACC fleet formation, formation and dequeue mechanism specifically includes: in this embodiment, a CACC fleet may be formed by an Ad-hoc cluster, and when a bus is running, it continuously obtains vehicle and traffic information from various intelligent networked vehicle (CAV) devices, and updates the driving mode suitable for the vehicle according to a certain period of time; if the vehicle is in a CACC fleet, its position in the fleet is needed to determine the driving pattern; the method comprises the following steps that a head vehicle in a fleet executes an Adaptive Cruise Control (ACC) mode, and a rear vehicle executes a CACC following mode; conversely, as shown in fig. 4, if a bus is not in the CACC fleet, the time interval between the vehicle and the preceding adjacent vehicle is needed to determine its subsequent behavior; if the time interval is greater than the preset value, the bus continues cruising in the ACC mode, and when the time interval is less than the preset value, the bus can be switched to the CACC mode, wherein in the embodiment, the preset value can be set to be 2 seconds; it should be noted that whether or not the CACC fleet is formed will depend on the length of the fleet ahead and the standing time required for the current vehicle to maintain punctuality.
In this embodiment, as shown in fig. 4, as the CACC fleet grows longer, its operation becomes more complex and the interference to other traffic becomes more severe; the maximum fleet length is limited by the wireless-to-vehicle communication (V2V) communication range between motor vehicles, the length of the vehicles, the headway in the fleet, and the actual traffic environment; in this embodiment, the maximum fleet length is set to four buses, if the current CACC fleet length exceeds four, the rear vehicle cannot join the CACC fleet, and the driver is required to switch lanes to overtake the fleet in ACC mode when the vehicle's desired speed is higher than the front fleet.
As shown in fig. 4, for different buses, different expected speeds are determined according to their on-time conditions even if they run in succession, if a bus at a later point joins a low-speed fleet that is lower than its own expected speed, it will delay more than the arrival time determined by the schedule, in contrast, when the bus joins the high-speed fleet and arrives at a bus stop ahead in advance, it can stop at the station until a predetermined departure time; but the residence time cannot be too long in consideration of the riding experience of passengers; therefore, it is expected that the standing control time is also a key factor in CACC fleet formation when new vehicles are usedWhen a vehicle joins the CACC fleet, V is taken as the expected speed of the fleet*And fleet operating speedThe larger value between the two, due to the shorter travel time of the vehicle in the acceleration and deceleration phases; thus, when the corresponding desired stop control time for a downstream stop exceeds the maximum allowed stop time, the driver will be required to manually switch lanes and drive at the desired speed in ACC mode to meet the punctuality requirements, otherwise the bus will join the CACC fleet and switch to CACC follow-up mode.
Wherein, tholdingIs the potential residence time of the bus at the downstream stop n + 2.
In the existing bus signal priority control research, a vehicle detector is generally arranged at the position 100 meters ahead of a stop line at an intersection; in the embodiment, a vehicle detector is arranged at the position 100m upstream of the intersection in consideration of the bus running speed, the dequeue time and the lane change time before the intersection; calculating the time of each bus in the CACC fleet reaching the intersection by using a formula (11), wherein the CACC fleet needs to be decomposed with the buses reaching at the red light time to ensure that the buses in front of the CACC fleet pass through the intersection at the green light time; in addition, the driver is required to take over the steering control of the bus according to the bus route requirements.
Wherein, tiIs the arrival time of each bus at the downstream intersection i in the fleet.
Example 2:
the embodiment provides a bus driving control system based on cooperative adaptive cruise control, which comprises a judgment module and a control module;
the determination module configured to: judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
the control module configured to: if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; and when the time interval is smaller than the preset value, the public transport vehicle is switched to a cooperative adaptive cruise control mode.
Example 3:
the present embodiment provides a computer-readable storage medium on which a computer program is stored, which when executed by a processor, implements the steps of the method for controlling bus driving based on cooperative adaptive cruise control described in embodiment 1.
Example 4:
the embodiment provides an electronic device, which includes a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the program to implement the steps of the method for controlling driving of a bus based on cooperative adaptive cruise control according to embodiment 1.
The above description is only a preferred embodiment of the present invention, and is not intended to limit the present invention, and those skilled in the art can make various modifications and variations. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present embodiment should be included in the protection scope of the present embodiment.
Claims (10)
1. A bus driving control method based on cooperative adaptive cruise control is characterized by comprising the following steps:
judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; and when the time interval is smaller than the preset value, the public transport vehicle is switched to a cooperative adaptive cruise control mode.
2. The method as claimed in claim 1, wherein the formation of the fleet of cooperative adaptive cruise control is determined by the length of the fleet in front and the stopping time required for the current bus to maintain the punctuality.
3. The cooperative adaptive cruise control based bus driving control method according to claim 2, wherein if the length of the fleet exceeds a preset vehicle, the rear bus cannot join the fleet; when the expected speed of the bus is higher than that of the front motorcade, changing lanes to overtake the motorcade in the self-adaptive cruise control mode;
when the corresponding expected stop control time of the downstream stop exceeds the maximum allowed stop time, the current bus changes lanes and runs at the expected speed in the adaptive cruise control mode.
4. The method as claimed in claim 1, wherein at the intersection, the fleet of buses is separated from the buses arriving at red time, and the time of arrival of each bus in the fleet of buses at the intersection is calculated as:
wherein, tiFor the arrival time, L, of each bus in the fleet at downstream intersection iiIs the position of intersection i, L1For public transport vehicle at t1,1Position of time, V*To a desired speed, Vs *For vehicle fleet operating speed。
5. The method as claimed in claim 1, wherein when the driving mode is determined according to the position of the bus in the platoon, the front bus in the platoon executes the adaptive cruise control mode, and the rear bus executes the cooperative adaptive cruise control following mode.
6. The cooperative adaptive cruise control based bus driving control method according to claim 1, wherein in the cooperative adaptive cruise control mode, the real-time acceleration is adjusted according to the difference between the desired speed and the current speed:
a(k)=kg·[V*-v(k-1)]
wherein k is a time step; k is a radical ofgFor constant feedback gain between speed deviation and acceleration, V*V is the current speed for the desired speed.
7. The method as claimed in claim 6, wherein the time interval error and derivative are used to determine the real-time speed of the bus:
8. The bus driving control system based on the cooperative adaptive cruise control is characterized by comprising a judgment module and a control module;
the determination module configured to: judging whether the public transport vehicle is in a cooperative self-adaptive cruise control fleet or not;
the control module configured to: if the bus is in the fleet, determining a driving mode according to the position of the bus in the fleet; if the bus is not in the fleet, judging the time interval between the bus and the adjacent bus in front of the bus, and if the time interval is greater than a preset value, the bus cruises in a self-adaptive cruise control mode; and when the time interval is smaller than the preset value, the public transport vehicle is switched to a cooperative adaptive cruise control mode.
9. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out the steps of the method for controlling the driving of a bus based on a cooperative adaptive cruise control according to any one of claims 1 to 7.
10. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, characterized in that the processor implements the steps of the method for controlling the driving of a bus based on a cooperative adaptive cruise control according to any of claims 1 to 7 when executing said program.
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Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN105835882A (en) * | 2016-03-01 | 2016-08-10 | 乐视云计算有限公司 | Automatic vehicle traveling method and device |
US20180093668A1 (en) * | 2015-06-29 | 2018-04-05 | Hyundai Motor Company | Cooperative adaptive cruise control system based on driving pattern of target vehicle |
CN108877231A (en) * | 2018-07-07 | 2018-11-23 | 程子涵 | A kind of vehicle vehicle interconnected method and system based on vehicle start-stop prompting |
CN110070707A (en) * | 2019-05-16 | 2019-07-30 | 吴鼎新 | A method of realizing that cooperating type adaptive learning algorithms fleet forms a team and separates |
CN110816529A (en) * | 2019-10-28 | 2020-02-21 | 西北工业大学 | Vehicle cooperative type self-adaptive cruise control method based on variable time-distance strategy |
CN111191904A (en) * | 2019-12-24 | 2020-05-22 | 中车工业研究院有限公司 | Intelligent vehicle formation method and device, electronic equipment and storage medium |
CN112116822A (en) * | 2020-09-21 | 2020-12-22 | 长沙理工大学 | Expressway traffic capacity cooperative regulation and control method based on CAVs mixed traffic flow lane dynamic allocation |
-
2021
- 2021-12-09 CN CN202111500936.7A patent/CN114187771B/en active Active
Patent Citations (7)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US20180093668A1 (en) * | 2015-06-29 | 2018-04-05 | Hyundai Motor Company | Cooperative adaptive cruise control system based on driving pattern of target vehicle |
CN105835882A (en) * | 2016-03-01 | 2016-08-10 | 乐视云计算有限公司 | Automatic vehicle traveling method and device |
CN108877231A (en) * | 2018-07-07 | 2018-11-23 | 程子涵 | A kind of vehicle vehicle interconnected method and system based on vehicle start-stop prompting |
CN110070707A (en) * | 2019-05-16 | 2019-07-30 | 吴鼎新 | A method of realizing that cooperating type adaptive learning algorithms fleet forms a team and separates |
CN110816529A (en) * | 2019-10-28 | 2020-02-21 | 西北工业大学 | Vehicle cooperative type self-adaptive cruise control method based on variable time-distance strategy |
CN111191904A (en) * | 2019-12-24 | 2020-05-22 | 中车工业研究院有限公司 | Intelligent vehicle formation method and device, electronic equipment and storage medium |
CN112116822A (en) * | 2020-09-21 | 2020-12-22 | 长沙理工大学 | Expressway traffic capacity cooperative regulation and control method based on CAVs mixed traffic flow lane dynamic allocation |
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