CN108986455B - HOV lane dynamic control method for car pooling priority in Internet of vehicles environment - Google Patents

HOV lane dynamic control method for car pooling priority in Internet of vehicles environment Download PDF

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CN108986455B
CN108986455B CN201810693142.9A CN201810693142A CN108986455B CN 108986455 B CN108986455 B CN 108986455B CN 201810693142 A CN201810693142 A CN 201810693142A CN 108986455 B CN108986455 B CN 108986455B
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hov lane
traffic
rate
flow
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CN108986455A (en
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周桂良
刘志强
毛丽娜
陈昕
孙锋
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Jiangsu University
Huaiyin Institute of Technology
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Huaiyin Institute of Technology
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    • G08—SIGNALLING
    • G08G—TRAFFIC CONTROL SYSTEMS
    • G08G1/00—Traffic control systems for road vehicles
    • G08G1/01—Detecting movement of traffic to be counted or controlled
    • G08G1/0104—Measuring and analyzing of parameters relative to traffic conditions
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Abstract

The invention discloses a method for dynamically controlling an HOV lane of car sharing priority in an internet of vehicles environment, which comprises the steps of setting an HOV lane control boundary, wherein the HOV lane control boundary comprises high-bearing-rate car flow, high-bearing-rate passenger number and a private car flow threshold; collecting real-time traffic information of the Internet of vehicles in the current period, and calculating the value of the vehicle flow of a private car under the conditions of current vehicle flow with high bearing rate and the number of vehicle-mounted guests with high bearing rate; and comparing the current private car flow with a corresponding private car flow threshold, and if the starting condition is met, starting the HOV lane. According to the invention, the HOV lane control boundary is set, the current flow of the private car is compared with the corresponding threshold value of the flow of the private car, and if the starting condition is met, the HOV lane is started, so that the dynamic intelligent control of the HOV lane is effectively realized.

Description

HOV lane dynamic control method for car pooling priority in Internet of vehicles environment
Technical Field
The invention relates to a dynamic control method for an HOV lane with car sharing priority in an Internet of vehicles environment, and belongs to the technical field of urban traffic service.
Background
An hov (high Occupancy vehicle) lane is a lane which is set up for providing priority right of way for vehicles with high bearing rate, the types of vehicles are more cars, and the number of people on the vehicles is more than 2. At present, the HOV lane has a plurality of forms such as a special lane or sharing with a bus special lane, and the HOV lane can improve the running efficiency and the service level of a bus or a car sharing trip vehicle and attract more people to share the car for trip, thereby reducing the running amount of private cars with low bearing rate and being an effective measure for relieving urban traffic jam.
At present, all-weather fixed scheme setting is mostly adopted for the use of the HOV lanes, and with the rich and real-time car sharing information processing of an information acquisition means under the environment of the Internet of vehicles, the dynamic intelligent management and control of the road HOV lanes become possible, and the optimal management of road resources can be realized.
Disclosure of Invention
The invention provides a dynamic control method of an HOV lane with car sharing priority in an Internet of vehicles environment, which realizes dynamic intelligent control of the HOV lane of a road.
In order to solve the technical problems, the technical scheme adopted by the invention is as follows:
a method for dynamically controlling the HOV lane with car sharing priority in the Internet of vehicles environment comprises the following steps,
setting an HOV lane control boundary, wherein the HOV lane control boundary comprises high-bearing-rate vehicle traffic, high-bearing-rate passenger number and a private vehicle traffic threshold;
collecting real-time traffic information of the Internet of vehicles in the current period, and calculating the value of the vehicle flow of a private car under the conditions of current vehicle flow with high bearing rate and the number of vehicle-mounted guests with high bearing rate;
and comparing the current private car flow with a corresponding private car flow threshold, and if the starting condition is met, starting the HOV lane.
When the flow threshold value of the private car is set, the delay of everyone is used as an evaluation index, and the specific setting criterion is that,
assuming that the vehicle flow rate and the vehicle-mounted guests with high bearing rate are constant, the private vehicle flow rate Q is greater than the private vehicle flow rate threshold value, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is greater than d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and high carrying rate is constant, the vehicle flow Q of the private vehicle is equal to the vehicle flow threshold value of the private vehicle, the per-capita delay corresponding to the Q under the mixed driving condition is d1, the per-capita delay corresponding to the Q under the HOV lane condition is d2, and d1 is d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and vehicle-mounted traffic with high carrying rate is constant, the traffic Q of the private vehicle is smaller than the traffic threshold of the private vehicle, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is less than d 2.
The formula for the per-person delay is,
d′＝(qb×nb×db+qc×nc×dc)/(qb×nb+qc×nc)
wherein d' is the human mean error, qbFor high carrying capacity vehicle traffic, nbThe number of passengers in the vehicle with high carrying rate dbFor high load-bearing rate vehicle-to-vehicle delay, qcFor low load capacity vehicle traffic, qcTraffic Q-Q of private carb，ncThe number of passengers in the vehicle is low, dcThe vehicles are delayed for low bearing rate.
The formula for the delay of the vehicle is that,
d＝L/Vq-L/V0
wherein d is the delay of the vehicle, L is the length of the standard road section, and VqThe speed V of the road section is the traffic flow q0Under the condition of hybrid driving of vehicles with different bearing rates, intersection signals and free travel speed of vehicles stopped at stations are considered.
VqAnd V0The formula of (a) is as follows,
V0＝L/(L/Vf+d)
Vq＝31/(1+1.03(q/c)3.01)
wherein, VfIs the free flow speed of the vehicle without any influence, and c is the road section traffic capacity.
And if the current private car flow is larger than the corresponding private car flow threshold value, judging that the starting condition is met, starting the HOV lane, and otherwise, not starting the HOV lane.
The invention achieves the following beneficial effects: according to the invention, the HOV lane control boundary is set, the current flow of the private car is compared with the corresponding threshold value of the flow of the private car, and if the starting condition is met, the HOV lane is started, so that the dynamic intelligent control of the HOV lane is effectively realized.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a carpooling intent bar chart;
FIG. 3 is a bar graph of the number of people sharing a car;
FIG. 4 is qbDelaying people under different driving conditions of 160 veh/h;
FIG. 5 is qbThe delay is delayed under different driving conditions of 180 veh/h.
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
As shown in fig. 1, a car pooling preferred HOV lane dynamic management and control method in an internet of vehicles environment includes the following steps:
step 1, setting an HOV lane control boundary, wherein the HOV lane control boundary comprises high-bearing-rate vehicle traffic, high-bearing-rate passenger number and a private vehicle traffic threshold; wherein the high bearing rate means that the number of carpools is more than or equal to 2.
In the traffic flow operation law model, what is more classical is a bpr (highway of Public roads) function of the U.S. highway bureau, namely a speed-flow model, which reflects a functional relationship between the driving time of vehicles on a road section and the traffic load, and the form of the model is expressed as follows:
Tq＝T0[1+α(q/c)β] (1)
wherein, TqThe travel time of the road section with the traffic flow of q is T0The road section travel time when the traffic flow is 0, c the road section traffic capacity, alpha and beta are parameters, and data are needed to be calibrated.
For the same traveler, the distance traveled is the same, so equation 1 can be translated into,
Vq＝V0[1+α(q/c)β] (2)
wherein, VqWhen the traffic flow is qSpeed of travel on road section, V0Under the condition of hybrid driving of vehicles with different bearing rates, intersection signals and free travel speeds of vehicles stopped at stations are considered;
V0may be determined according to road grade, and the specific reference values are shown in table 1.
TABLE 1 recommended value of free-run speed
Figure GDA0002698371440000041
On urban roads, V0The method is mainly related to intersection distance, station stop time, signal period duration and green-to-green ratio, and can be calculated by the following formula:
V0＝L/(L/Vf+d) (3)
wherein d is the delay of the vehicle, VfFor the free flow velocity of the vehicle without any influence, L is the standard road section length.
And (3) calibrating alpha and beta in the speed-flow model by using a least square method to respectively obtain the speed-flow model under the hybrid driving condition and the HOV lane condition as follows:
Vq＝31/(1+1.03(q/c)3.01) (4)
the model equations are the same under the hybrid driving conditions and the HOV lane conditions, and the difference is only that the c value is different under different conditions.
As obtained from equations 3 and 4, d ═ L/Vq-L/V0。
For the travelers, an important index for evaluating the trip quality is the time of trip, which changes with the change of the traffic state, and if the traffic state is divided according to the ideal state and the actual state, the time of trip is generally divided into the ideal time of trip and the actual time of trip, and the actual time of trip generally includes the ideal time of trip and the delay. The ideal travel time is only related to travel distance and travel mode, namely when the travel distance and the travel mode are fixed, the ideal travel time is a fixed value, however, the delay is determined by the traffic state, the delay is continuously increased along with the deterioration of the state, the delay is reduced along with the improvement of the state, and the running efficiency of the road network can be effectively reflected. Therefore, the average delay of people is used as an evaluation index of the road network operation benefit, and the setting basis of the HOV lane is determined by taking the minimum average delay of people as a target.
The formula for the per-person delay is:
d′＝(qb×nb×db+qc×nc×dc)/(qb×nb+qc×nc) (5)
wherein d' is the human mean error, qbFor high carrying capacity vehicle traffic, nbThe number of passengers in the vehicle with high carrying rate dbFor high load-bearing rate vehicle-to-vehicle delay, qcFor low load capacity vehicle traffic, qcTraffic Q-Q of private carb，ncThe number of passengers in the vehicle is low, compared with the high load ncIs 1, dcThe vehicles are delayed for low bearing rate.
Based on the formula, some historical traffic information of the internet of vehicles is collected, and HOV lane control boundaries can be configured, specifically as follows:
according to the actual research and questionnaire analysis, the occupation of a private car and the car sharing is 2/3, and the occupation of a car sharing is 1/3 when the car sharing is not willing to be carried out, namely, the car with low carrying rate. Meanwhile, the number of the vehicles with high carrying rate is 24.56% of 2 persons, 50.30% of 3 persons, 24.26% of 4 persons and 0.89% of more than 4 persons, and the specific share is shown in the following figures 2 and 3.
The historical internet of vehicles traffic information is as follows: bidirectional 4-lane road, qbWhen the number of passengers in the high-carrying-rate vehicle is 3 at 160veh/h, the per-person error under the hybrid driving condition and the HOV lane condition is calculated, and a graph of the traffic Q of the private car and the per-person error is constructed, which is specifically shown in fig. 4.
Bidirectional 4-lane road, qbAnd (3) calculating the average pedestrian error under the hybrid driving condition and the HOV lane condition, and constructing a curve graph of the traffic Q and the average pedestrian error of the private car, wherein the number of the passengers in the high-carrying-rate car is 180veh/h, and the average pedestrian error is shown in fig. 5.
As can be seen from fig. 4, when the number of the high-carrying-rate vehicle-mounted guests is 3, and when the private car traffic Q is lower than 600veh/h, the man-average error under hybrid driving is smaller than that of the HOV lane, and therefore, the HOV lane does not need to be set; when the flow Q of the private car exceeds 600veh/h, the average human error under hybrid driving is larger than that of the HOV lane, so the HOV lane needs to be set; at the moment, the flow threshold value of the private car is set to 600 veh/h. Similarly, the private car traffic threshold value is 640veh/h as can be seen from FIG. 5.
Different private car traffic thresholds can be obtained under different conditions, as shown in table 2.
TABLE 2 threshold value of private car traffic under different conditions
Figure GDA0002698371440000061
Figure GDA0002698371440000071
As can be seen from table 2, when the car traffic of the high-carrying rate car is constant, the number of different high-carrying rate car-mounted guests corresponds to a corresponding threshold value of the car traffic of the private car.
As can be seen from fig. 4 and 5, when the traffic threshold of the private car is set, the average delay of people is used as an evaluation index, and the specific setting criteria are as follows:
assuming that the vehicle flow rate and the vehicle-mounted guests with high bearing rate are constant, the private vehicle flow rate Q is greater than the private vehicle flow rate threshold value, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is greater than d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and high carrying rate is constant, the vehicle flow Q of the private vehicle is equal to the vehicle flow threshold value of the private vehicle, the per-capita delay corresponding to the Q under the mixed driving condition is d1, the per-capita delay corresponding to the Q under the HOV lane condition is d2, and d1 is d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and vehicle-mounted traffic with high carrying rate is constant, the traffic Q of the private vehicle is smaller than the traffic threshold of the private vehicle, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is less than d 2.
And 2, acquiring real-time vehicle networking traffic information in the current period, and calculating the value of the vehicle flow of the private car under the conditions of the current high-bearing-rate vehicle-mounted guest number and the high-bearing-rate vehicle-mounted guest number.
In the environment of the internet of vehicles, the real-time traffic information of the internet of vehicles, such as vehicle positions, driving speeds, carrying numbers, routes and the like, is acquired through equipment such as a GPS (global positioning system), an RFID (radio frequency identification device) and the like. Due to the existence of storage space, data abnormality, data redundancy and other conditions, particularly the influences of weak GPS signals, overlarge distance between an RFID radio frequency card and a receiver, wireless transmission errors and the like, the acquired information needs to be further processed, such as preprocessing, data cleaning and the like, so as to complete the identification and repair of the information, and after the identification and repair are completed, calculation is carried out.
Step 3, comparing the current private car traffic with a corresponding private car traffic threshold, and if the current private car traffic meets the starting condition, starting the HOV lane; namely, if the current private car traffic is larger than the corresponding private car traffic threshold, judging that the starting condition is met, and starting the HOV lane, otherwise, not starting the HOV lane.
According to the method, the HOV lane control boundary is set firstly, the current flow of the private car is compared with the corresponding private car flow threshold value, if the starting condition is met, the HOV lane is started, and dynamic intelligent control over the HOV lane is effectively achieved.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.

Claims (5)

1. A method for dynamically controlling a car pooling preferential HOV lane under the environment of the Internet of vehicles is characterized in that: comprises the following steps of (a) carrying out,
setting an HOV lane control boundary, wherein the HOV lane control boundary comprises high-bearing-rate vehicle traffic, high-bearing-rate passenger number and a private vehicle traffic threshold;
collecting real-time traffic information of the Internet of vehicles in the current period, and calculating the value of the vehicle flow of a private car under the conditions of current vehicle flow with high bearing rate and the number of vehicle-mounted guests with high bearing rate;
comparing the current private car traffic with a corresponding private car traffic threshold, and if the current private car traffic meets the starting condition, starting the HOV lane; wherein when the flow threshold value of the private car is set, the delay of everyone is used as an evaluation index, the specific setting criterion is,
assuming that the vehicle flow rate and the vehicle-mounted guests with high bearing rate are constant, the private vehicle flow rate Q is greater than the private vehicle flow rate threshold value, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is greater than d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and high carrying rate is constant, the vehicle flow Q of the private vehicle is equal to the vehicle flow threshold value of the private vehicle, the per-capita delay corresponding to the Q under the mixed driving condition is d1, the per-capita delay corresponding to the Q under the HOV lane condition is d2, and d1 is d 2;
assuming that the number of vehicle-mounted guests with high carrying rate and vehicle-mounted traffic with high carrying rate is constant, the traffic Q of the private vehicle is smaller than the traffic threshold of the private vehicle, the per-capita delay corresponding to Q under the mixed driving condition is d1, the per-capita delay corresponding to Q under the HOV lane condition is d2, and d1 is less than d 2.
2. The method according to claim 1, wherein the HOV lane dynamic management and control method is characterized in that: the formula for the per-person delay is,
d′＝(qb×nb×db+qc×nc×dc)/(qb×nb+qc×nc)
wherein d' is the human mean error, qbFor high carrying capacity vehicle traffic, nbThe number of passengers in the vehicle with high carrying rate dbFor high load-bearing rate vehicle-to-vehicle delay, qcFor low load capacity vehicle traffic, qcTraffic Q-Q of private carb，ncThe number of passengers in the vehicle is low, dcThe vehicles are delayed for low bearing rate.
3. The method according to claim 2, wherein the HOV lane dynamic management and control method is characterized in that: the formula for the delay of the vehicle is that,
d＝L/Vq-L/V0
wherein d is the delay of the vehicle, L is the length of the standard road section, and VqThe speed V of the road section is the traffic flow q0Under the condition of hybrid driving of vehicles with different bearing rates, intersection signals and free travel speed of vehicles stopped at stations are considered.
4. The method according to claim 3, wherein the method comprises the following steps: vqAnd V0The formula of (a) is as follows,
V0＝L/(L/Vf+d)
Vq＝31/(1+1.03(q/c)3.01)
wherein, VfIs the free flow speed of the vehicle without any influence, and c is the road section traffic capacity.
5. The method according to claim 1, wherein the HOV lane dynamic management and control method is characterized in that: and if the current private car flow is larger than the corresponding private car flow threshold value, judging that the starting condition is met, starting the HOV lane, and otherwise, not starting the HOV lane.
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