CN115880919A - Intelligent traffic light command system and method - Google Patents
Intelligent traffic light command system and method Download PDFInfo
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Abstract
The invention relates to an intelligent traffic light command system and method, comprising the following steps: the motorcade length related parameter acquisition module comprises an integrated navigation device and a navigation module integrated in the internet of vehicles mobile terminal and is used for acquiring motorcade length related parameters; the vehicle networking mobile terminal is used for transmitting the relevant parameters of the motorcade length to the intersection calculation center; the intersection calculation center is used for receiving the fleet length related parameters and the vehicle length information sent by each vehicle, determining the comprehensive road condition information of the intersection according to the fleet length related parameters and the vehicle length information, determining a signal lamp control scheme according to the comprehensive road condition information of the intersection, and transmitting the signal lamp control scheme to the signal lamp control module; the vehicle networking mobile terminal is also used for generating a vehicle guiding scheme according to the intersection feedback information, the position of the vehicle at the intersection and the queuing sequence, and guiding the vehicle to pass through the intersection. The scheme can meet the real-time demand of the current intelligent traffic light.
Description
Technical Field
The invention relates to the field of intelligent traffic control of Internet of vehicles, in particular to an intelligent traffic light command system and method.
Background
The traffic light command system has been developed through the following stages: a fixed timing stage, a variable fixed timing stage and a traffic flow self-adapting stage.
Currently, the more researched traffic adaptive command means that a sensor is used for acquiring road traffic information in real time, and then duration of each phase of a command system is set according to the actual traffic quantity in each direction. Most of the road condition sensors in the method are induction coils, and some manufacturers try to acquire actual road conditions by using visual recognition equipment. The induction coils are used for acquiring road conditions, and if the induction coils are buried far away from a command system, the quantity of traffic flow in each direction can be acquired, but the steering demand at the intersection cannot be acquired; if the induction coil is buried at the entrance of each direction guide way, although the number of traffic flow entering the induction coil can be collected, the queuing length cannot be collected. The visual recognition equipment can theoretically realize the detection of traffic flow in all directions, but the image processing and analyzing time is long, and the visual recognition effect can be influenced at night and in severe weather. Therefore, the above method is not enough to meet the demand of current intelligent traffic light command.
Disclosure of Invention
The invention aims to provide an intelligent traffic light real-time command system and method considering steering requirements and queuing lengths.
In order to achieve the purpose, the invention provides the following scheme:
the invention provides an intelligent traffic light command system, comprising:
the system comprises a motorcade length related parameter acquisition module, a vehicle speed acquisition module and a vehicle speed acquisition module, wherein the motorcade length related parameter acquisition module is arranged in each vehicle, comprises a combined navigation device and a navigation module integrated in a vehicle networking mobile terminal and is used for acquiring motorcade length related parameters, and the motorcade length related parameters comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at an intersection;
the mobile terminal of the internet of vehicles is arranged in each vehicle and is used for transmitting the relevant parameters of the motorcade length to a cross port calculation center;
the intersection calculation center is in communication connection with the Internet of vehicles mobile terminal and the signal lamp control module and is used for receiving the motorcade length related parameters and the vehicle length information sent by each vehicle and determining comprehensive road condition information of the road intersection according to the motorcade length related parameters and the vehicle length information sent by each vehicle; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction;
and the intersection calculation center is also used for determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection and outputting the signal lamp control scheme to the signal lamp control module.
Optionally, the intersection calculation center is configured to use the constraint conditions that the length of green light in each direction of the intersection is in direct proportion to the number of queued vehicles in each direction, and the length of green light in each direction is equal to the longest length of green light, and use the maximum passing rate as a target to solve the signal lamp control scheme.
Optionally, the signal lamp control scheme includes a green light starting time, and the intersection calculation center is further configured to transmit the green light starting time and the number of vehicles in front of the target vehicle in the fleet to the internet-of-vehicles mobile terminal of the target vehicle; the mobile terminal of the target vehicle is also used for: determining the starting time of a target vehicle according to the starting time of the green light and the starting delay of the front vehicle, calculating the theoretical speed of the target vehicle at any time according to the starting time of the green light, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection, and guiding the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
Optionally, the intersection calculation center is connected with the internet of vehicles mobile terminal through 5G signal communication.
The invention also provides an intelligent traffic light command method, which comprises the following steps:
receiving relevant parameters of the motorcade length and length information of each vehicle, which are acquired by a motorcade length relevant parameter acquisition module; the relevant parameters of the fleet length comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at the intersection; the motorcade length related parameter acquisition module is arranged in each vehicle;
determining comprehensive road condition information of the road intersection according to the relevant parameters of the motorcade length and the vehicle length information; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction;
and determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection, and transmitting the signal lamp control scheme to the signal lamp control module.
Optionally, determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection specifically includes:
determining the traffic state of the intersection according to the comprehensive road condition information of the road intersection; the traffic states include high and low traffic peaks; the traffic peak refers to the number of vehicles which can pass in the longest green light time period and are queued in a single phase or a plurality of phases; the traffic low peak means that the queuing number of vehicles in all phases is less than the number of vehicles which can pass in the longest green light time; the phases comprise a first phase, a second phase, a third phase and a fourth phase, and the first phase is uplink and downlink; the second phase is uplink and downlink left turn; the third phase is a left-right straight line; the fourth phase is left-right turning;
when the traffic state is a traffic low peak, calculating the signal lamp control scheme by using a first model; the first model is a model established by taking the maximum crossing vehicle passing rate as an optimization target, the direct proportion of the green light duration of each direction of the crossing to the number of queued vehicles in each direction and the constraint condition that the green light duration of each phase is less than or equal to the longest green light duration;
when the traffic state is a traffic peak, calculating the signal lamp control scheme by using a second model; the second model is a model established under the constraint conditions that the maximum crossing vehicle passing rate is an optimization target, the green light duration of each direction of the crossing is in direct proportion to the number of queued vehicles in each direction, and the maximum queuing length phase green light duration is equal to the longest green light duration.
Optionally, the calculating the signal lamp control scheme by using the first model specifically includes:
calculating the green light time of the first phase by using a uniform acceleration motion equation according to the average value of the number of the uplink vehicles and the number of the downlink vehicles in the first phase, the vehicle length information, the distance between two adjacent vehicles, the vehicle acceleration and the starting time delay of the next vehicle relative to the previous vehicle;
according to the green light time length of the first phase, a formula T is utilized 1 :T 2 :T 3 :T 4 ＝K 1 :K 2 :K 3 :K 4 Calculating the green light time length of the second phase, the green light time length of the third phase and the green light time length of the fourth phase;
wherein, T 1 、T 2 、T 3 、T 4 Respectively setting the green light time of a first phase, the green light time of a second phase, the green light time of a third phase and the green light time of a fourth phase; k 1 、K 2 、K 3 、K 4 The average value of the first phase ascending vehicle number and the first phase descending vehicle number, the average value of the second phase ascending vehicle number and the second phase descending vehicle number, the average value of the third phase ascending vehicle number and the third phase descending vehicle number, and the average value of the fourth phase ascending vehicle number and the fourth phase descending vehicle number are respectively;
calculating the green light starting time of each phase according to the green light duration of each phase and the non-execution time of the current cycle of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
Optionally, the calculating the signal lamp control scheme by using the second model specifically includes:
calculating a selected phase according to the comprehensive road condition information of the road intersection; the selected phase is the phase with the most queued vehicles in the intersection;
determining the longest green light duration as the green light duration of the selected phase;
according to the green light duration of the selected phase, calculating the green light durations of the other phases except the selected phase according to the principle that the green light duration of each phase is in direct proportion to the number of vehicles queued in each phase;
calculating the green light starting time of each phase according to the green light duration of each phase and the current cycle non-execution time of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
Optionally, the method further includes:
transmitting the green light starting time of the phase to which the target vehicle belongs and the number of vehicles in front of the target vehicle in the fleet to an Internet of vehicles mobile terminal of the target vehicle;
the Internet of vehicles mobile terminal of the target vehicle determines the starting time of the target vehicle according to the green light starting time and the starting delay of the front vehicle;
and the Internet of vehicles mobile terminal of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle.
Optionally, the method further includes:
the vehicle networking mobile terminal of the target vehicle calculates the theoretical speed of the target vehicle at any moment according to the green light starting moment of the phase to which the target vehicle belongs, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection;
and the Internet of vehicles mobile terminal of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
According to the specific embodiment provided by the invention, the invention discloses the following technical effects:
the invention provides an intelligent traffic light command system and method, comprising the following steps: the system comprises a motorcade length related parameter acquisition module, a vehicle speed acquisition module and a vehicle speed acquisition module, wherein the motorcade length related parameter acquisition module is arranged in each vehicle, comprises a combined navigation device and a navigation module integrated in a vehicle networking mobile terminal and is used for acquiring motorcade length related parameters, and the motorcade length related parameters comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at an intersection; the mobile terminal of the internet of vehicles is arranged in each vehicle and is used for transmitting the relevant parameters of the motorcade length to a cross port calculation center; the intersection calculation center is in communication connection with the Internet of vehicles mobile terminal and the signal lamp control module and is used for receiving the motorcade length related parameters and the vehicle length information sent by each vehicle and determining comprehensive road condition information of the road intersection according to the motorcade length related parameters and the vehicle length information sent by each vehicle; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction; and the intersection calculation center is also used for determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection and transmitting the signal lamp control scheme to the signal lamp control module. According to the scheme, the steering requirement and the queuing length are considered, the relevant parameters of the motorcade length can be extracted in real time, the signal lamp control scheme is calculated, and the current intelligent traffic light command requirement can be met.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
Fig. 1 is a structural diagram of an intelligent traffic light command system according to embodiment 1 of the present invention;
fig. 2 is a flowchart of an intelligent traffic light command method according to embodiment 2 of the present invention;
fig. 3 is a first phase plan view provided in embodiment 2 of the present invention;
fig. 4 is a second phase plan view provided in embodiment 2 of the present invention;
fig. 5 is a plan view of a third phase provided in embodiment 2 of the present invention;
fig. 6 is a fourth phase plan view provided in embodiment 2 of the present invention.
Description of the symbols: 1: a motorcade length related parameter acquisition module; 2: an intersection calculation center; 3: a signal lamp control module; 11: an integrated navigation device; 12: vehicle networking mobile terminal.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide an intelligent traffic light command system and method considering steering requirements and queuing length.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
Example 1
The embodiment provides an intelligent traffic light command system, please refer to fig. 1, which includes:
the motorcade length related parameter acquisition module 1 is arranged in each vehicle, comprises an integrated navigation device 11 and a navigation module integrated in an internet of vehicles mobile terminal 12 and is used for acquiring motorcade length related parameters, wherein the motorcade length related parameters comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at an intersection;
the mobile terminal 12 of the internet of vehicles is arranged in each vehicle and is used for transmitting the relevant parameters of the motorcade length to the intersection calculation center 2;
the intersection calculation center 2 is in communication connection with the internet of vehicles mobile terminal 12 and the signal lamp control module 3, and is used for receiving the fleet length related parameters and the vehicle length information sent by each vehicle and determining the comprehensive road condition information of the road intersection according to the fleet length related parameters and the vehicle length information sent by each vehicle; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction;
the intersection calculation center 2 is further configured to determine a signal lamp control scheme according to the comprehensive road condition information of the road intersection, and output the signal lamp control scheme to the signal lamp control module 3.
The accurate motorcade length related parameter information is obtained on the premise of calculating a timing scheme according to needs, and the motorcade length related parameter information is obtained by utilizing a motorcade length related parameter acquisition module 1, wherein the length related parameter acquisition module comprises two parts, namely an integrated navigation device 11 and a navigation module integrated in a vehicle networking mobile terminal 12. The integrated navigation device 11 includes a satellite positioning device and an inertial navigation device, and the satellite positioning device includes: satellite, base station and GNSS (Global Navigation Satellite System) positioning devices; the inertial navigation device includes: gyroscopes and accelerometers.
The satellite is an orbiting flight satellite, and a space observed target has known coordinates at any time, and is a space reference for the inverse calculation of GNSS coordinates. The satellite sends broadcast signals to the ground, the ground GNSS receiver can calculate the distance rho from the receiver to each satellite after receiving the broadcast signals, and after at least 4 satellites are locked, the three-dimensional coordinate of the GNSS phase center can be obtained through back intersection space back calculation, and the precision is about 10 meters.
The base station is composed of a GNSS receiver installed at a known point, a communication line, an unattended computer, and the like. The base station GNSS receiver can calculate satellite difference and signal propagation error of each satellite by observing signals of a visible satellite constellation, and then sends the errors to the vehicle-mounted GNSS terminal through a 5G network according to a request of the vehicle-mounted GNSS, so that the positioning accuracy of the vehicle-mounted GNSS is improved to a centimeter level.
The combined navigation GNSS receiver has the functions of receiving signals from satellites in an open environment and simultaneously receiving correction data from a base station, calculating the distance from the GNSS receiver to each satellite, and reversely calculating the three-dimensional coordinates, the driving direction and the speed of a vehicle.
The connection relation among the satellite, the base station and the vehicle-mounted GNSS receiver is as follows: satellite signals are sent outwards in a broadcasting mode and can be received by a base station and a vehicle-mounted GNSS receiver; the vehicle-mounted GNSS receiver can upload the coordinates and the instrument ID to the base station through a 5G network, and obtain the correction number from the base station, so that the positioning accuracy of the vehicle-mounted GNSS receiver is improved.
The inertial navigation device mainly comprises a gyroscope and an accelerometer, is used as an effective supplement for GNSS positioning, can measure the driving direction of the vehicle in a hidden environment, the speed and the acceleration of the vehicle, and reversely calculates the three-dimensional coordinates of the vehicle in a hidden space at any moment.
A navigation module of the internet-of-vehicles mobile terminal 12 is provided with an electronic map for recording traffic elements such as roads, intersections and signal lamps and geographical position information of districts, factories and mining enterprises; the mobile terminal 12 in the internet of vehicles can display the current position of the vehicle according to the coordinates of the combination and the transmission, calculate the queuing length of the vehicle from the intersection, perform route optimization according to the destination, and also can issue information according to the intersection calculation center 2 to calculate a guidance scheme and guide the vehicle to navigate.
The intersection calculation center 2 is composed of a high-performance computer and a wireless network, is a neural center of the system, and realizes the collection of the queuing vehicle information of the intersection, the calculation of the optimal timing scheme of each direction of the intersection, the command control of traffic lights, the acquisition of the current state of the traffic lights, the command of the mobile terminals 12 of the internet of vehicles and the like.
Considering that the vehicle may be in an open position area or a hidden position area, different devices are respectively adopted to acquire the position of the vehicle, the driving direction and the driving speed for the two cases.
When the vehicle is in an open area, the vehicle-mounted GNSS is adopted to receive signals from 4 or more satellites, and the distance from the satellite to the vehicle can be calculated; the vehicle-mounted GNSS is used for receiving correction signals from the base station, so that the common error of the satellite can be calculated, and the observed distance can be corrected; the three-dimensional coordinates (Pos) of the vehicle in the open environment can be solved by using a space rear intersection algorithm. Since the differential positioning accuracy can reach the centimeter level, the driving speed (V) and the driving direction (Dir) of the vehicle can be directly obtained from the three-dimensional coordinates of the vehicle at the time 2. Let t 1 The three-dimensional coordinate of the vehicle at the moment is Pos (x) 1 ，y 1 ，z 1 Composition) t) 2 The three-dimensional coordinate of the vehicle at the moment is Pos (x) 2 ，y 2 ，z 2 Composition). The instantaneous speed of the vehicle is calculated as follows.
Since the map used for vehicle navigation is a plane map, the vehicle traveling direction is only a plane direction, and the traveling direction is expressed by a coordinate azimuth sandwiched with a north direction (the north direction in the survey is the X direction).
When the vehicle is in the hidden area, the perception of the vehicle information in the hidden area can be realized by using the inertial navigation device 12; the inertial navigation device 12 is composed of a gyroscope and an accelerometer, wherein the gyroscope rotating at a high speed can keep the original direction for a long time, and the running direction of the vehicle at any time can be measured by the gyroscope; the accelerometer can measure the acceleration of the vehicle at any time in real time, and the acceleration can be used for measuring the speed of the vehicle at any time by combining the elapsed time. The combination of the two devices can measure the position (Pos), the driving direction (Dir) and the speed (V) of the vehicle at any time.
Therefore, the vehicle position, the driving direction and the driving speed can be accurately obtained no matter a satellite positioning device or an inertial navigation device is adopted in the scheme. The turning demand (Tur) of the vehicle at the intersection in the parameter related to the fleet length needs to be determined after the route is optimized through the current vehicle position (Pos), the destination position (Pos) and a navigation module of the internet-of-vehicles mobile terminal 12.
It should be noted that the above-mentioned solution only shows one solution for obtaining the parameter related to the length of the fleet, and other methods may be adopted in the present invention to obtain the parameter related to the length of the fleet.
In addition, the device provided by the invention can also acquire information such as the distance between the vehicle and the intersection, the type and the length of the vehicle and the like. For example, according to the position (Pos) of the vehicle, the distance between the vehicle and the intersection is calculated through a spatial distance formula by using the coordinates of the traffic lights in the map stored by the navigation module of the mobile terminal 12 in the internet of vehicles. The type (Typ), length (Len) and other parameters of the vehicle can be manually entered when the vehicle-mounted map is used.
The traditional coil sensing means can only sense traffic information of roads, and the number of vehicles in each lane of an intersection needs to be judged according to experience; although the video identification means can sense the number and the queuing length of partial vehicles entering the guide lane, the traffic flow requirement which does not enter the guide lane cannot be sensed, and the video algorithm is greatly influenced by external light rays and cannot meet the requirement of all-weather command. The invention adopts a combined navigation and electronic map mode, can sense the comprehensive road condition information such as vehicle positions, driving directions, steering requirements, queuing lengths and the like in all directions of a road in a detection range in real time, thereby really realizing the comprehensive detection of the road condition information.
As an alternative embodiment, the intersection computing center 2 and the internet-of-vehicles mobile terminal 12 are connected through 5G signal communication.
The vehicles at the intersection are more, the data volume transmitted by information uploading is huge, the traditional communication technology cannot process the connection at the same time, and the data at the intersection can not be transmitted in real time. The fifth generation communication technology (5G) has the characteristics of high speed, low time delay, wide connection and the like, and the 5G network can be used for real-time high-speed bidirectional communication between a base station and a vehicle-mounted GNSS receiver, between a vehicle-mounted mobile terminal and an intersection calculation center 2.
After the vehicle length related information acquisition module acquires the road condition information, the vehicle length related information is uploaded to the intersection calculation center 2 through the Internet of vehicles mobile terminal by adopting a 5G network.
As an optional implementation manner, the intersection calculation center 2 is configured to use the constraint conditions that the green light duration of each direction of the intersection is in direct proportion to the number of queued vehicles in each direction, and the green light duration of each direction is less than or equal to the longest green light duration, and use the maximum passing rate as the target to solve the signal light control scheme.
The system optimizes the optimal timing of each phase of the traffic lights by taking the maximum traffic capacity of the intersection as an optimization target and taking the direct proportion of the green light duration and the queuing length in each direction as a constraint condition. The timing scheme of the invention really distributes the time length of the traffic lights according to the actual road condition requirements, so that the intersection command is more targeted, the average waiting time of the vehicles is shortened, and the traffic capacity of the intersection is improved.
As another alternative, the signal light control scheme includes a green light start time, and the intersection calculation center 2 is further configured to transmit the green light start time and the number of vehicles in front of the target vehicle in the fleet to the internet-of-vehicles mobile terminal 12 of the target vehicle. The target vehicle's internet of vehicle mobile terminal 12 is also configured to: determining the starting time of a target vehicle according to the starting time of the green light and the starting delay of the front vehicle, calculating the theoretical speed of the target vehicle at any time according to the starting time of the green light, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection, and guiding the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
The intersection calculation center 2 and the internet of vehicles mobile terminal 12 calculate a vehicle-to-vehicle scheme according to the road condition information reported in real time, the calculated optimal timing scheme, the current traffic light state and other information, and perform the whole process guidance service, including: the system has the advantages that starting countdown reminding, vehicle whole-course acceleration and deceleration prompting and the like are achieved, the situations of delay, insufficient speed, over-violent acceleration and the like caused by unconcentrated starting are avoided, the traffic capacity of the intersection is improved, and the safety of the vehicle is ensured.
The main reason for achieving the above effects of the present invention is that with the help of a 5G network, a traffic light command system knows precise road condition information (traffic flow change, vehicle position, driving speed, etc.) in real time, each vehicle knows the command scheme of an intersection, and the guidance scheme of each vehicle is different and is adjusted in real time.
Example 2
The embodiment provides an intelligent traffic light directing method, please refer to fig. 2, which includes:
s1, receiving relevant parameters of the motorcade length and length information of each vehicle, which are acquired by a motorcade length relevant parameter acquisition module 1; the relevant parameters of the fleet length comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at the intersection. The motorcade length related parameter acquisition module is arranged in each vehicle;
the motorcade length related parameters acquired by the motorcade length related parameter acquisition module 1 specifically include:
obtaining the position of the vehicle and the driving direction by adopting a satellite positioning device or an inertial navigation device;
and determining the steering demand at the intersection according to the position of the vehicle, the position of the destination and a route navigation scheme.
The vehicle length information is manually entered at the time of use of the in-vehicle map and is therefore retrieved directly from the in-vehicle network mobile terminal 12.
S2, determining comprehensive road condition information of the road intersection according to the relevant parameters of the motorcade length and the vehicle length information; the comprehensive road condition information of the road intersection comprises the following steps: the length of the fleet going straight in each direction and the length of the fleet turning left in each direction at the intersection.
After receiving the relevant parameters of the lengths of the fleets of vehicles, the intersection calculation center 2 collects the data collected in all directions, counts the number of the straight and left-turn queuing waiting traffic flows, the queuing length and the like in all directions, and provides a data basis for model calculation.
When the intersection calculation center 2 summarizes relevant parameters of the motorcade length, a detection distance can be set, and motorcade information in the detection distance is summarized.
The detection distance can be set to be Lt, uploaded vehicle information is analyzed one by one, the distance L between the vehicle and the intersection is calculated according to the current position (Pos) of the vehicle, and only when the distance L is less than Lt, the vehicle quantity in each direction can be obtained by classifying and summarizing according to the driving direction (Dir) and the intersection turning requirement (Tur).
The number of vehicles in each direction is represented by the following characters: n is a radical of hydrogen 1 (number of vehicles on the upper side in the vertical straight direction), N 2 (number of vehicles on lower side in vertical straight direction), N 3 (number of vehicles on the upper side in the vertical and left-turn directions), N 4 (number of vehicles on the lower side in the vertical and left-turn directions), N 5 (number of left-hand vehicles in left-right straight-ahead direction), N 6 (number of right-hand vehicles in left-right straight-ahead direction), N 7 (number of left-hand vehicles in left-hand and right-hand turning directions), N 8 (number of vehicles on right in left-right turn direction).
And S3, determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection, and transmitting the signal lamp control scheme to the signal lamp control module 3.
As an optional implementation manner, the S3 specifically includes:
and determining the traffic state of the intersection according to the comprehensive road condition information of the road intersection.
Wherein the traffic state comprises a traffic peak and a traffic low peak. The traffic peak refers to the number of vehicles which can pass in the longest green light time period and are queued in a single phase or a plurality of phases; the traffic low peak means that the number of the vehicles in the queue in all phases is less than the number of the vehicles which can pass in the longest green light duration. The phases comprise a first phase, a second phase, a third phase and a fourth phase, and the first phase is uplink and downlink; the second phase is uplink and downlink left turn; the third phase is a left-right straight line; the fourth phase is left-right left-turn.
In the first case: when the traffic state is a traffic low peak, calculating the signal lamp control scheme by using a first model; the first model is a model established by taking the maximum crossing vehicle passing rate as an optimization target, the direct proportion of the green light duration of each direction of the crossing to the number of queued vehicles in each direction and the constraint condition that the green light duration of each phase is less than or equal to the longest green light duration.
The signal lamp control scheme is an optimal timing scheme of each phase of the intersection, the intersection is taken as an example to illustrate the optimal timing process, 4 phases are adopted for conducting, and for convenience of understanding, fig. 3-6 show a plane diagram of each phase.
In the second case: when the traffic state is a traffic peak, calculating the signal lamp control scheme by using a second model; the second model is a model established by using the maximum optimization target of the crossing vehicle passing rate, the direct proportion of the green light duration of each direction of the crossing to the number of queued vehicles in each direction and the constraint condition of the maximum green light duration of the longest queuing phase.
Since 3 parameters of the average acceleration (a) of the vehicle, the average starting delay (delta t) of the following vehicle compared with the previous vehicle and the average stopping interval data (delta l) of the following vehicle and the previous vehicle are used in the process of calculating the optimal timing of the intersection, the parameters are determined in advance for the convenience of subsequent calculation. For the average acceleration (a), an accelerometer is placed on a vehicle, multiple observations are carried out in the starting process of an intersection, and then the average acceleration is obtained by an averaging method; after multiple observations on different small vehicles, the average acceleration of the small vehicles at the intersection is 0.8 m/s 2. The average starting delay (delta t) of the rear vehicle to the front vehicle is obtained by adopting a long-term observation averaging method, and the average starting delay of the rear vehicle to the front vehicle of the small-sized vehicle is 1 second according to multiple timing observations. Average parking interval data (delta l) of the next vehicle and the previous vehicle are obtained in an averaging mode through multiple observations, and the average parking interval (delta l) between the vehicles is 0.9 m through the multiple observations.
It should be noted that the above method for acquiring data of acceleration, start-up time delay, parking interval, etc. is only an exemplary scheme and data provided for a person skilled in the art to have a clearer understanding of the scheme of the present invention, and does not limit the protection scope of the present invention. For example, the length of each vehicle is needed in subsequent calculation, but in the scheme, a certain value is adopted as the average length of the vehicles in the fleet for convenient calculation, and in practical application, because each vehicle uploads the length data of the vehicle to the intersection calculation center 2, the intersection calculation center 2 can calculate by adopting the actually uploaded length data of each vehicle, so that the calculation accuracy is improved.
In order to judge the traffic high and low peaks, the maximum time T of the green light needs to be calculated max Maximum number N of vehicles capable of passing through intersection in time queue max The calculation method adopts a uniform acceleration motion equation for calculation. Let a certain direction have N max The vehicles wait for passing the intersection in a queue, the green light is not lighted, and all the vehicles are in a static state; after the green light is turned on, T max Exactly N in time max If all vehicles pass through the intersection, the last vehicle N max The distance traveled is N max X (Len +. DELTA.l); the first vehicle is started when the green light is on, and the latter vehicles are started after 1 second delay compared with the former vehicles, so the Nth vehicle max The actual travel time of the vehicle passing through the intersection is T max -(N max -1), substituting each data into the following formula to solve for N max 。
Different timing methods are respectively adopted under two conditions of traffic peak and traffic low peak, and the green light time length of the longest queuing phase is set as T during the traffic peak max The duration of the rest phases is proportional to the vehicle in each phase, and the optimal timing of each phase is calculated according to the requirement; when the traffic is low, firstly, the passing intersection of all vehicles in a certain direction is calculated according to the average number of queued vehicles in the direction and the acceleration of the vehiclesThe time required by the fork opening and the duration of the green lights in other directions are calculated and configured according to the proportion of the green lights to the traffic flow.
When the traffic light command system enters the next period, vehicles in all phases detected in the previous period are subjected to summary statistics, and the average value of the vehicles going up and down in all the phases is used as the traffic flow in the direction. Since the execution process of the traffic lights is repeated continuously, a complete period is the time interval from the turning of the green light to the red light in a certain direction to the turning of the green light to the red light again in the next direction. A cycle may also be understood as the time when the intersection passes once in each direction.
The number of the vehicles which are counted by each phase and are queued averagely in the uplink and the downlink and N max Comparing, if the average queued vehicles in each phase are less than N max If the traffic peak is not the traffic peak, otherwise, the traffic peak is the traffic peak.
Specifically, for the first case:
as an optional implementation, the calculating an optimal solution of the first model to obtain the signal lamp control scheme under the low peak of traffic specifically includes:
(1) Calculating the green light time of the first phase by using a uniform acceleration motion equation according to the average value of the number of the uplink vehicles and the number of the downlink vehicles in the first phase, the vehicle length information, the distance between two adjacent vehicles, the vehicle acceleration and the starting time delay of the next vehicle relative to the previous vehicle;
wherein the number N of vehicles descending in the first phase 1 Uplink vehicle N 2 The ascending vehicles and the descending vehicles are unequal, the ascending vehicles and the descending vehicles share one green light phase, so that the average value K of the ascending vehicles and the descending vehicles is adopted to avoid waste and reduce waiting at the same time 1 The required green light duration is calculated as the base. The calculation method still adopts a uniform acceleration motion equation of the object started from rest, and the constraint condition is to ensure that the motion equation is K 1 The vehicle smoothly passes through the intersection. Then K is 1 The distance traveled by the vehicle is K 1 X (Len +. DELTA.l), K 1 The time taken for the vehicle to pass through the intersection is T 1 -(K 1 -1); wherein, K 1 (average value of up-down going vehicles), len (vehicle is)Vehicle length), Δ l (as vehicle interval), a 1 (as vehicle acceleration) are all known values, T 1 For evaluation, only one unknown number is used to determine the longest green duration T in that direction 1 。
(2) According to the green light time length of the first phase, a formula T is utilized 1 :T 2 :T 3 :T 4 ＝K 1 :K 2 :K 3 :K 4 Calculating the green light duration of the second phase, the green light duration of the third phase and the green light duration of the fourth phase;
wherein, T 1 、T 2 、T 3 、T 4 Respectively setting the green light time of a first phase, the green light time of a second phase, the green light time of a third phase and the green light time of a fourth phase; k 1 、K 2 、K 3 、K 4 The average value of the first phase ascending vehicle number and the first phase descending vehicle number, the average value of the second phase ascending vehicle number and the second phase descending vehicle number, the average value of the third phase ascending vehicle number and the third phase descending vehicle number, and the average value of the fourth phase ascending vehicle number and the fourth phase descending vehicle number are respectively;
(3) Calculating the green light starting time of each phase according to the green light duration of each phase and the current cycle non-execution time of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
The intersection computing center 2 calculates the current time (Now) and the non-execution time (T) according to the system w ) Optimum timing of each phase (T) 1 、T 2 、T 3 、T 4 ) Yellow light interval (T) j ) Four can be calculatedPhase green light turn-on time (T) k ) Respectively is as follows: now + T w 、Now+T w +T 1 +T j 、Now+T w +T 1 +T 2 +2*T j 、 Now+T w +T 1 +T 2 +T 3 +3*T j 。
For the second case described above:
as an optional implementation, the calculating an optimal solution of the second model to obtain the signal lamp control scheme under the traffic peak specifically includes:
(1) Calculating a selected phase according to the comprehensive road condition information of the road intersection; the selected phase is the phase with the most queued vehicles at the intersection;
(2) Determining the longest green light duration as the green light duration of the selected phase;
(3) According to the green light duration of the selected phase, calculating the green light durations of the other phases except the selected phase according to the principle that the green light duration of each phase is in direct proportion to the number of vehicles queued in each phase;
if it is at the traffic peak, the phase with the maximum average queuing length is selected, and the green light time length in the direction is set as the maximum allowable time length T max The green light time of other directions is calculated in proportion to the number of vehicles in each phase.
For example, if the first phase vehicle queue length is longest, the first phase green light duration is determined as T max According to T max :T 2 :T 3 :T 4 ＝K 1 :K 2 :K 3 :K 4 Calculating the green light time lengths of other phases; if other phases are queued the longest, only the green light duration of the phase is replaced by T max And (4) finishing.
After the optimal timing scheme (signal lamp control scheme) of each phase of the intersection is obtained, the intersection calculation center 2 calculates the optimal green timing T of the phases 1, 2, 3 and 4 according to the requirement 1 、T 2 、T 3 、T 4 The result is converted into a control instruction and transmitted to the signal lamp control module 3 through the network, and the control module controls the lamps to display according to the instruction requirement.
(4) Calculating the green light starting time of each phase according to the green light duration of each phase and the current cycle non-execution time of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
As an optional implementation, the method further comprises:
and S4, transmitting the green light starting time of the phase of the target vehicle and the number of vehicles in front of the target vehicle in the fleet to the Internet of vehicles mobile terminal of the target vehicle.
And S5, the Internet of vehicles mobile terminal 12 of the target vehicle determines the starting time of the target vehicle according to the green light starting time and the starting delay of the front vehicle.
Before calculating the starting time of the target vehicle, the delay time T of the target vehicle relative to the green light starting time of the phase position of the target vehicle needs to be calculated y ：
T y ＝△t×(Ln-1)
Wherein Ln is the position of the target vehicle on the guide way, and Deltat is the average delay of starting of the rear vehicle compared with the front vehicle during starting.
The green light turning-on time T according to the phase position of the target vehicle k And a start delay time T of the target vehicle y And the starting time of the target vehicle can be obtained.
And S6, the Internet of vehicles mobile terminal 12 of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle.
In practical application, the internet of vehicles mobile terminal 12 can perform countdown reminding on the vehicle owner n seconds before the starting time of the target vehicle, so as to avoid starting delay.
As another optional embodiment, the method further comprises:
the internet of vehicle mobile terminal 12 of the target vehicle calculates the theoretical speed of the target vehicle at any time according to the green light starting time of the phase to which the target vehicle belongs, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection.
Wherein the theoretical speed V of the vehicle at any time T Theory of things ：
V Theory of things ＝a Flat plate ×(T-T k -T y )
And the Internet of vehicles mobile terminal 12 of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
And according to the theoretical speed of the vehicle at any time calculated by the mobile terminal, the acceleration and deceleration of the vehicle is guided at any position at any time, and the vehicle is guided to pass through the intersection as early as possible under the condition of ensuring safety.
The behavior of a vehicle driver greatly influences the traffic capacity of the intersection, for example, when attention is not concentrated during a red light period, starting can be delayed; in addition, if the vehicle is driven by a new hand, due to insufficient experience, the vehicle may drive too slowly at the intersection, so that starting delay is caused; too fast driving may also cause safety risks, and collision accidents, etc. The invention adopts a one-vehicle scheme to guide the vehicle to pass through the intersection in the whole process, thereby ensuring the driving safety and the passing efficiency.
At present, most traffic light command systems in the whole country are in blind command stages based on experience rather than real-time road conditions, and although part of road condition sensing equipment begins to be applied to the field of intelligent command, the following problems still exist: the traffic flow can be sensed, but the queuing length cannot be sensed; or the vehicle queuing number can be sensed, but the efficiency cannot meet the demand of real-time command; or only a timing function, no interactive guiding function and the like.
The scheme of the invention not only can sense the queuing length and calculate the optimal timing scheme of the traffic lights at the intersection, but also can provide a scheme of one vehicle for each vehicle at the intersection so as to guide the vehicles to pass.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other. For the system disclosed by the embodiment, the description is relatively simple because the system corresponds to the method disclosed by the embodiment, and the relevant points can be referred to the method part for description.
The principle and the embodiment of the present invention are explained by applying specific examples, and the above description of the embodiments is only used to help understanding the method and the core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.
Claims (10)
1. An intelligent traffic light command system, comprising:
the system comprises a motorcade length related parameter acquisition module, a vehicle speed acquisition module and a vehicle speed acquisition module, wherein the motorcade length related parameter acquisition module is arranged in each vehicle, comprises a combined navigation device and a navigation module integrated in a vehicle networking mobile terminal and is used for acquiring motorcade length related parameters, and the motorcade length related parameters comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at an intersection;
the mobile terminal of the internet of vehicles is arranged in each vehicle and is used for transmitting the relevant parameters of the motorcade length to a cross port calculation center;
the intersection calculation center is in communication connection with the Internet of vehicles mobile terminal and the signal lamp control module and is used for receiving the motorcade length related parameters and the vehicle length information sent by each vehicle and determining comprehensive road condition information of the road intersection according to the motorcade length related parameters and the vehicle length information sent by each vehicle; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction;
and the intersection calculation center is also used for determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection and transmitting the signal lamp control scheme to the signal lamp control module.
2. The system according to claim 1, wherein the intersection calculation center is configured to use the constraint conditions that the intersection has a green time in each direction proportional to the number of queued vehicles in each direction, and the green time in each direction is less than or equal to the longest green time, and the intersection calculation center is configured to calculate the traffic light control scheme with the maximum passing rate as a target.
3. The system of claim 1, wherein the signal light control scheme comprises a green light start time, and wherein the intersection computing center is further configured to transmit the green light start time and a number of vehicles in front of a target vehicle in the fleet to the networked mobile terminal of the target vehicle; the mobile terminal of the target vehicle is also used for: determining the starting time of a target vehicle according to the starting time of the green light and the starting delay of the front vehicle, calculating the theoretical speed of the target vehicle at any time according to the starting time of the green light, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection, and guiding the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
4. The system according to any one of claims 1 to 3, wherein the intersection calculation center is connected with the Internet of vehicles mobile terminal through 5G signal communication.
5. An intelligent traffic light command method, comprising:
receiving relevant parameters of the motorcade length and length information of each vehicle, which are acquired by a motorcade length relevant parameter acquisition module; the relevant parameters of the fleet length comprise the position of the vehicle, the driving direction of the vehicle and the steering requirement of the vehicle at the intersection; the motorcade length related parameter acquisition module is arranged in each vehicle;
determining comprehensive road condition information of the road intersection according to the relevant parameters of the length of each motorcade and the length information of the vehicles; the comprehensive road condition information of the road intersection comprises the following steps: the length of a straight motorcade in each direction of the intersection and the length of a left-turning motorcade in each direction;
and determining a signal lamp control scheme according to the comprehensive road condition information of the road intersection, and transmitting the signal lamp control scheme to the signal lamp control module.
6. The method according to claim 5, wherein the determining of the signal lamp control scheme according to the comprehensive road condition information of the intersection specifically comprises:
determining the traffic state of the intersection according to the comprehensive road condition information of the road intersection; the traffic state comprises a traffic peak and a traffic low peak; the traffic peak refers to the number of vehicles which can pass in the longest green light time period and are queued in a single phase or a plurality of phases; the traffic low peak means that the queuing number of vehicles in all phases is less than the number of vehicles which can pass in the longest green light time; the phases comprise a first phase, a second phase, a third phase and a fourth phase, and the first phase is uplink and downlink; the second phase is uplink and downlink left turn; the third phase is a left-right straight line; the fourth phase is left-right left-turn;
when the traffic state is a traffic low peak, calculating the signal lamp control scheme by using a first model; the first model is a model established by taking the maximum intersection vehicle passing rate as an optimization target, the direct proportion of the green light duration of each direction of the intersection to the number of queued vehicles in each direction and the constraint condition that the green light duration of each phase is less than or equal to the longest green light duration;
when the traffic state is a traffic peak, calculating the signal lamp control scheme by using a second model; the second model is an optimization target with the maximum crossing vehicle passing rate, the length of green light in each direction of the crossing is in direct proportion to the number of vehicles in line in each direction, and the length of green light in the longest phase of line is T max Models built for the constraints.
7. The method according to claim 6, wherein the calculating the signal lamp control scheme using the first model specifically comprises:
calculating the green light time of the first phase by using a uniform acceleration motion equation according to the average value of the number of the uplink vehicles and the number of the downlink vehicles in the first phase, the vehicle length information, the distance between two adjacent vehicles, the vehicle acceleration and the starting time delay of the next vehicle relative to the previous vehicle;
according to the green light time length of the first phase, a formula T is utilized 1 :T 2 :T 3 :T 4 ＝K 1 :K 2 :K 3 :K 4 Calculating the green light time length of the second phase, the green light time length of the third phase and the green light time length of the fourth phase;
wherein, T 1 、T 2 、T 3 、T 4 Respectively setting the green light time of a first phase, the green light time of a second phase, the green light time of a third phase and the green light time of a fourth phase; k 1 、K 2 、K 3 、K 4 The average value of the first phase ascending vehicle number and the first phase descending vehicle number, the average value of the second phase ascending vehicle number and the second phase descending vehicle number, the average value of the third phase ascending vehicle number and the third phase descending vehicle number, and the average value of the fourth phase ascending vehicle number and the fourth phase descending vehicle number are respectively;
calculating the green light starting time of each phase according to the green light duration of each phase and the current cycle non-execution time of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
8. The method according to claim 6, wherein the calculating the signal lamp control scheme using the second model specifically comprises:
calculating a selected phase according to the comprehensive road condition information of the road intersection; the selected phase is the phase with the most queued vehicles at the intersection;
determining the longest green light duration as the green light duration of the selected phase;
according to the green light duration of the selected phase, calculating the green light durations of the other phases except the selected phase according to the principle that the green light duration of each phase is in direct proportion to the number of vehicles queued in each phase;
calculating the green light starting time of each phase according to the green light duration of each phase and the current cycle non-execution time of each phase; the current cycle non-execution time refers to the time of one cycle minus the executed time; the time of one period refers to the time difference between two times of lighting of the signal lamps with the same color at the same position.
9. The method of claim 6, further comprising:
transmitting the green light starting time of the phase to which the target vehicle belongs and the number of vehicles in front of the target vehicle in the fleet to an Internet of vehicles mobile terminal of the target vehicle;
the Internet of vehicles mobile terminal of the target vehicle determines the starting time of the target vehicle according to the green light starting time and the starting delay of the front vehicle;
and the Internet of vehicles mobile terminal of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle.
10. The method of claim 9, further comprising:
the vehicle networking mobile terminal of the target vehicle calculates the theoretical speed of the target vehicle at any moment according to the green light starting moment of the phase to which the target vehicle belongs, the starting delay of the front vehicle and the average acceleration of the target vehicle at the intersection;
and the Internet of vehicles mobile terminal of the target vehicle guides the target vehicle to pass through the intersection according to the starting time of the target vehicle and the theoretical speed of the target vehicle at any time.
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