A scheduling method and system for multi-line bunching of intelligent buses

Abstract

The present invention relates to a scheduling method and system for multi-line tandem buses in intelligent public transportation. The method includes the following steps: M1: Calculate the headway h of the vehicle according to the expected vehicle driving conditions and expected vehicle driving speed. n , preset the tandem control threshold h of the vehicle d and the large interval control threshold h of the vehicle k ; M2: For buses on the same line, judge the relationship between the headway h n and the large interval control threshold h k , and use the intersection priority algorithm to schedule the vehicle to skip stations and enter the next station; M3: Optimally adjust the speed of the vehicle so that the vehicle satisfies h d < h n , and when the vehicle does not meet the speed adjustment condition, park and wait; M4: When tandem buses occur at the first station in the overlapping area for buses on different lines, re-arrange the timetable for the vehicles to enter the overlapping area. The present invention not only solves the problems of tandem buses and large intervals, but also improves the efficiency of public transportation and facilitates passengers to take the bus.

Description

Technical Field

[0001] The present invention relates to the field of public transportation technology, and in particular to a dispatching method and system for multi-line stringing of intelligent public transportation. Background Art

[0002] With the rapid development of intelligent driving technology, the application scenarios of unmanned driving technology are becoming more and more extensive, extending from closed or semi-closed factory areas, mining areas, industrial parks, etc. to complex public roads. At present, unmanned buses and robotaxi unmanned vehicles have begun to be put into trial operation in major cities, greatly facilitating passengers' short-distance travel in the city. With the increasing perfection of unmanned driving technology and the enhancement of passengers' psychological acceptance, more and more vehicles and types are put into operation by different intelligent driving technology companies, and urban traffic management will become complicated. How to efficiently dispatch different vehicles put into operation is a difficult problem to be considered at present. At present, due to uncertain factors such as road traffic, passenger flow changes, and weather conditions, the city's intelligent bus dispatching system is prone to phenomena such as stringing and large intervals, resulting in low bus efficiency and affecting the convenience of passengers' travel. Summary of the invention

[0003] In view of the above problems, the present invention provides a dispatching method and system for multi-line string buses of intelligent buses, which not only solves the problems of string buses and large intervals, but also improves bus efficiency and facilitates passengers to take buses.

[0004] In order to achieve the above-mentioned purpose and other related purposes, the technical solution provided by the present invention is as follows:

[0005] A dispatching method for multi-line buses of intelligent public transportation comprises the following steps:

[0006] M1: Calculate the headway h of the vehicle according to the expected vehicle driving conditions and expected vehicle driving speed n , preset the vehicle string control threshold h d and the large interval control threshold h of the vehicle k ;

[0007] M2: For buses on the same route, determine the headway h n and the large interval control threshold h k The relationship between n ≥h k , the vehicle is dispatched by using an intersection priority algorithm, and the vehicle skips a station and enters the next station;

[0008] M3: When h n ≤h d <h k When the speed of the vehicle is optimized, the vehicle satisfies hd <h n When the vehicle does not meet the speed adjustment condition, park and wait;

[0009] M4: When buses on different routes enter the first stop in the overlapping area and bunching occurs, re - arrange the timetable for the vehicles to enter the overlapping area.

[0010] Further optimized, in step M4, the specific steps for re - arranging the timetable for the vehicles to enter the overlapping area are as follows:

[0011] M41: Calculate the uniform single - stop interval and record the expected arrival time of the vehicles reaching the overlapping area;

[0012] M42: Arrange the arrival time of the first vehicle on each route;

[0013] M43: For each route, calculate the theoretical number of additional vehicles at each moment;

[0014] M44: Arrange the arrival trips;

[0015] M45: Judge whether trips are arranged for all arrival times. If not, repeat steps M43 and M44 until trips are arranged for all arrival times.

[0016] Further optimized, in step M2, the intersection priority algorithm specifically includes the following steps:

[0017] 1) Calculate the interval of the turning radius and the interval of the turning speed of the intelligent bus vehicles in each direction of the intersection according to the expected road driving conditions and the expected vehicle speed;

[0018] 2) Calculate the conflict areas of the intelligent bus in each direction of the intersection, and then calculate the total length of the conflict areas between each direction and other directions and the conflict area passing time;

[0019] 3) According to the big - data sample statistical method, calculate the traffic flow information of the conflict area, and then calculate the time for the intelligent bus to pass through the conflict area;

[0020] 4) Judge the length of the time for the intelligent bus to pass through the conflict area, and then control the intelligent bus to pass through the conflict area.

[0021] Further optimized, when h d <h n <h k the vehicle travels normally and enters and exits the bus stop.

[0022] Further optimized, the bunching control valve value h of the vehicle d is the minimum headway of the vehicle, and its functional formula is as follows:

[0023] Where I is the vehicle headway, J i is the total number of vehicles, Z is the headway, s is the distance traveled by the vehicle in the i-th second, and v α(i,j+1) represents the speed of the (j + 1)-th vehicle, is the headway of the (j + 1)-th vehicle, is the headway of the j-th vehicle, and H i is the error parameter.

[0024] To achieve the above and other related purposes, the present invention also provides a scheduling system applied to intelligent bus multi-line bunching, including a computer device, which is programmed or configured to execute the steps of any one of the scheduling methods applied to intelligent bus multi-line bunching.

[0025] To achieve the above and other related purposes, the present invention also provides a computer-readable storage medium, on which a computer program is stored that is programmed or configured to execute the scheduling method applied to intelligent bus multi-line bunching according to any one of the above.

[0026] The present invention has the following positive effects:

[0027] 1) The present invention improves the operation efficiency of driverless buses;

[0028] 2) The present invention solves the unified management and scheduling of driverless buses or robotaxis put into operation by various enterprises in the city. BRIEF DESCRIPTION OF THE DRAWINGS

[0029] Figure 1 is a schematic flowchart of the method of the present invention;

[0030] Figure 2 is a schematic flowchart of re-scheduling the timetable for vehicles to enter the overlapping area of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0031] The following further describes the preferred embodiments of the present invention in detail with reference to the accompanying drawings of the specification. The following description is exemplary and not a limitation of the present invention. Any other similar situation will also fall within the protection scope of the present invention.

[0032] Embodiment: As Figure 1 shown, a scheduling method applied to intelligent bus multi-line bunching includes the following steps:

[0033] M1: Calculate the headway h of the vehicle according to the expected vehicle driving conditions and the expected vehicle driving speed, and preset the bunching control valve value h of the vehicle n , dand the large interval control threshold h of the vehicle k ;

[0034] M2: For buses on the same route, judge the headway h n and the large interval control threshold h k between them. When h n ≥h k , use the intersection priority algorithm to schedule the vehicle, and the vehicle jumps stations and enters the next station;

[0035] M3: When h n ≤h d <h k , perform speed optimization adjustment on the vehicle so that the vehicle satisfies h d <h n . When the vehicle does not meet the speed adjustment condition, park and wait;

[0036] M4: When buses on different routes have bunching at the first station in the overlapping area, re - arrange the timetable for the vehicles to enter the overlapping area.

[0037] Further optimized, in step M4, the specific steps for re - arranging the timetable for the vehicles to enter the overlapping area are as follows:

[0038] M41: Calculate the uniform single - station interval and record the expected arrival time of the vehicles at the overlapping area;

[0039] M42: Arrange the arrival times of the first vehicles on each route;

[0040] M43: For each route, calculate the theoretical number of additional vehicles at each moment;

[0041] M44: Arrange the arrival trips;

[0042] M45: Judge whether there are trips arranged for all arrival times. If not, repeat steps M43 and M44 until all arrival times have trips arranged.

[0043] Further optimized, in step M2, the intersection priority algorithm specifically includes the following steps:

[0044] 1) Calculate the interval of the turning radius and the interval of the turning speed of the intelligent bus vehicles in each direction of the intersection according to the expected road driving conditions and the expected vehicle speed;

[0045] 2) Calculate the conflict areas of the intelligent bus in each direction of the intersection, and then calculate the total length of the conflict areas between each direction and other directions and the conflict area passing time;

[0046] 3) Calculate the traffic flow information of the conflict area according to the big data sample statistical method, and then calculate the time for the intelligent bus to pass through the conflict area;

[0047] 4) Judge the length of the time for the intelligent bus to pass through the conflict area, and then control the intelligent bus to pass through the conflict area.

[0048] Further optimized, when h d < h n < h k the vehicle travels normally and enters and exits the bus stop.

[0049] Further optimized, the platoon control threshold h of the vehicle d is the minimum headway of the vehicle, and its functional formula is as follows:

[0050] where I is the vehicle interval time, J i is the total number of vehicles, Z is the headway, s is the distance traveled by the vehicle in the i-th second, v α(i,j+1) represents the speed of the (j + 1)-th vehicle, is the headway of the (j + 1)-th vehicle, is the headway of the j-th vehicle, H i is the error parameter.

[0051] To achieve the above and other related purposes, the present invention also provides a scheduling system for platooning of intelligent buses on multiple lines, including a computer device, which is programmed or configured to execute the steps of any one of the scheduling methods for platooning of intelligent buses on multiple lines.

[0052] To achieve the above and other related purposes, the present invention also provides a computer-readable storage medium, on which a computer program is stored that is programmed or configured to execute the scheduling method for platooning of intelligent buses on multiple lines according to any one of the above.

[0053] In summary, the present invention not only solves the problems of platooning and large intervals, but also improves the bus efficiency and facilitates passengers to take the bus.

[0054] Although the specific embodiments of the present invention have been described above, those skilled in the art should understand that these are only examples, and the protection scope of the present invention is defined by the appended claims. Without departing from the principles and essence of the present invention, those skilled in the art can make various changes or modifications to these embodiments, and these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A scheduling method applied to multi-line tandem buses of intelligent public transportation, characterized in that, It includes the following steps: M1: Calculate the time headway h of the vehicle according to the expected vehicle driving conditions and the expected vehicle driving speed n , preset the platoon control valve value h of the vehicle d and the large interval control valve value h of the vehicle k , the platoon control valve value h of the vehicle d is the minimum time headway of the vehicle; M2: For buses on the same route, determine the headway h of the vehicle n and the large interval control threshold h k to determine the relationship between them. When h n ≥h k , use the intersection priority algorithm to schedule the vehicle, and the vehicle skips the station and enters the next station; M3: When h n ≤h d <h k , perform speed optimization adjustment on the vehicle so that the vehicle satisfies h d <h n , when the vehicle does not meet the speed adjustment condition, park and wait; M4: When buses on different routes have bunching at the first station in the overlapping area, re - arrange the timetable for the vehicles entering the overlapping area; In step M2, the intersection priority algorithm specifically includes the following steps: 1) Calculate the intervals of the turning radii and turning speeds of the intelligent bus vehicles in each direction of the intersection according to the expected road driving conditions and expected vehicle speeds; 2) Calculate the conflict areas of the intelligent bus in each direction at the intersection according to the intervals of the turning radii and turning speeds, and then calculate the total length of the conflict areas between each direction and other directions and the passing time of the conflict areas; 3) Calculate the traffic flow information of the conflict areas by using the big - data sample statistical method according to the total length of the conflict areas between each direction and other directions and the passing time of the conflict areas, and then calculate the time for the intelligent bus to pass through the conflict areas; Judge the length of the time for the intelligent bus to pass through the conflict areas according to the time for the intelligent bus to pass through the conflict areas, and then control the intelligent bus to pass through the conflict areas.

2. The scheduling method for multi-line bunching of intelligent buses according to claim 1, characterized in that: In step M4, the specific steps for re - arranging the timetable for the vehicles entering the overlapping area are as follows: M41: Calculate the uniform single - station interval and record the expected arrival time of the vehicles arriving at the overlapping area; M42: Arrange the arrival times of the first vehicles on each route; M43: For each route, calculate the theoretical number of additional vehicles at each moment; M44: Arrange the arrival trips; M45: Judge whether there are trips arranged for all arrival times. If not, repeat steps M43 and M44 until all arrival times have trips arranged.

3. The scheduling method applied to the multi-line tandem buses of intelligent buses according to claim 1, wherein: When h d <h n <h k the vehicle travels normally and enters and exits the bus stop.

4. The scheduling method for multi-line bunching of intelligent buses according to claim 1, characterized in that: The platoon control valve value h of the vehicle d is the minimum headway of the vehicle, and its functional formula is as follows: , where I is the vehicle headway time, J i is the total number of vehicles, Z is the headway time, s is the distance traveled by the vehicle in the i-th second, v α(i ,j+1) represents the speed of the (j + 1)-th vehicle, is the headway time of the (j + 1)-th vehicle, is the headway time of the j-th vehicle, H i is the error parameter.

5. A scheduling system applied to multi-line bunching of intelligent buses, including a computer device, characterized in that, The computer device is programmed or configured to execute the steps of the scheduling method for multi - route bunching of intelligent buses described in any one of claims 1 to 4.

6. A computer-readable storage medium, characterized in that, The computer - readable storage medium stores a computer program that is programmed or configured to execute the scheduling method for multi - route bunching of intelligent buses described in any one of claims 1 to 4.

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