CN110782651B - Non-routing public traffic control system based on quick response riding request - Google Patents
Non-routing public traffic control system based on quick response riding request Download PDFInfo
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- G08G1/00—Traffic control systems for road vehicles
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Abstract
A non-routing public transportation control system based on a quick response ride request, comprising: the system comprises a communication module, a data module, a request distribution and path planning module and a transfer planning module, wherein: the communication module receives, stores and distributes a riding request sent by a passenger terminal from any place in a service area, and receives and stores non-driving path information fed back by a vehicle-mounted control system of the bus in real time; the bus taking request to be distributed is distributed to the bus through the request distribution and path planning module and the transfer planning module, the corresponding paths of the bus are planned for the bus, and then the planned information is notified to the passengers and the bus. The invention can break the constraint of fixed lines on the transport capacity of the bus, can make quick response to the riding request sent in real time, and finally realizes urban passenger service with higher efficiency, lower cost and higher comfort. In addition, in practical application, the existing public traffic system is easy to be transformed and upgraded into the system provided by the invention.
Description
Technical Field
The invention relates to a technology in the field of intelligent control of public transport, in particular to a non-routing public transport control system based on quick response of a riding request.
Background
The public transport system can only visit each station in turn according to the scheduled route, and the transport capacity of different routes is difficult to be reasonably allocated, so the flexibility is severely restricted by the routes. The existing various improving methods are optimized aiming at specific scenes, or are only suitable for special areas, or are too cumbersome to cause poor passenger experience.
Through the search and discovery of the prior art, Chinese patent document No. CN109308574A, published 2019, 2, month and 5, a semi-flexible bus dispatching method combined with mobile communication is provided, a bus is allowed to arrive at a point designated by a passenger, but the departure point is still a bus stop. However, the technical disadvantage is that the service has great advantages only in areas with large area, small population or too far distance between sites, and is completely inapplicable in urban central population areas with heavy transportation burden.
Chinese patent document No. CN205384755U, published 2016, 7, 13, proposes an intelligent system for urban public transportation, which allows passengers to take any one bus passing through their station without paying attention to the route to which the bus belongs, and to transfer another bus at the junction near the intersection, and then reach the destination after several times. However, in the technology, the transfer times are increased along with the stroke length of the passengers, the technology is more complicated for long-distance passengers, supporting infrastructure for transfer is too complex, and the cost of upgrading and reconstruction is huge.
Disclosure of Invention
Aiming at the defects in the prior art, the invention provides a non-routing line public traffic control system based on quick response to a bus taking request, which can break the constraint of a fixed line on the transport capacity of a bus, can also make quick response to the bus taking request sent in real time, and finally realizes urban passenger transport service with higher efficiency, lower cost and higher comfort level. In addition, in practical application, the existing public traffic system is easy to be transformed and upgraded into the system provided by the invention.
The invention is realized by the following technical scheme:
the invention relates to a non-routing line public traffic control system based on quick response riding request, comprising: the system comprises a communication module, a data module, a request distribution and path planning module and a transfer planning module, wherein: the communication module collects riding request information from a passenger terminal, collects real-time non-driving path information of a bus from a vehicle-mounted control system of the bus and updates the real-time non-driving path information to the data module, acquires the updated path information from the data module and sends the updated path information to affected passengers and the affected bus; the request distribution and path planning module extracts the unallocated request information from the data module, distributes the unallocated request information to different buses, plans the updated path information for the buses and then updates the updated path information to the data module; and the transfer planning module scans the path information of the data module to obtain newly distributed passengers, arranges an optimal rear vehicle and a transfer station for the passenger with the longest riding distance, plans updated path information for the corresponding front vehicle and the rear vehicle and updates the updated path information to the data module.
Technical effects
Compared with the prior art, the bus taking system can quickly respond to the taking request of the passenger, give full play to the capacity of the bus, reduce the running distance of the bus, shorten the waiting time and the whole journey time of the passenger, realize high-efficiency transportation service without depending on a transfer mechanism in the traditional bus system, and obviously improve the comfort level of the passenger with a longer journey.
Drawings
FIG. 1 is a schematic diagram of an architecture of a non-routing public transportation system;
FIG. 2 is a schematic view of the data flow and processing flow of the non-routing bus system;
FIG. 3 is a schematic diagram of an example operation of a matrix value selection algorithm;
fig. 4 is a diagram illustrating an example of calculation of the allocation cost.
Detailed Description
As shown in fig. 1, the non-routing public transportation control system based on quick response to a bus taking request according to the embodiment is used for receiving, storing and distributing a bus taking request sent by a passenger terminal from any point in a service area, and simultaneously receiving and storing non-driving path information fed back by a vehicle-mounted control system of a bus in real time; the bus taking requests to be distributed are distributed to the buses through the request distribution and path planning module and the transfer planning module, corresponding paths are planned for the buses respectively, and then the planned path information is notified to the passengers and the buses.
The riding request information comprises information set by the passenger, such as a departure place and a destination place of the passenger, a detour ratio upper limit which can be tolerated by the passenger, a waiting time upper limit, a walking distance upper limit and the like, and a time stamp when the request is sent.
The communication module comprises: a request information receiving unit, a path information transmitting unit and a path information updating unit, wherein: the request information receiving unit receives the riding request information sent at any time and stores the riding request information into a request information database to be distributed of the data module; the path information updating unit receives the information of the paths on which the vehicles do not run from any time and updates the information of the paths on which the vehicles do not run to a database of the path information on which the vehicles do not run of the data module; the route information transmitting unit informs the affected passengers and vehicles of the changed route information after the non-driving route information database is updated.
The data module comprises: a request information database to be allocated and a non-driving path information database, wherein: the information database of the request to be distributed is only used for temporarily storing the request which is not distributed yet and providing input data for the request distribution and path planning module; the non-driving path information database is used for storing real-time non-driving path information of all buses and providing data for communication between passengers and the buses in the two algorithms and the communication module.
The request distribution and path planning module comprises: a request distribution unit and a path planning unit, wherein: the request distribution unit periodically reads and deletes the accumulated request information from the request information database to be distributed, determines vehicles distributed for each request after calculating by combining the path information in the non-driving path information database, and then outputs the vehicles to the path planning unit; and after receiving the distribution information, the path planning unit inserts the upper and lower stop points of each riding request into the paths of the distributed vehicles by using an insertion scheme corresponding to the minimum cost, so that the path information of the vehicles is updated to the non-driving path information database.
The transfer planning module comprises: transfer request search unit, back car search unit and transfer route planning unit, wherein: the transfer request searching unit scans a batch of newly distributed passengers in the non-driving path information database, preferentially selects the passenger with the longest driving distance to try to arrange transfer, and informs the selected passenger and the vehicle in which the passenger is located, namely the path information of the front vehicle to the rear vehicle searching unit; the rear car searching unit arranges a rear car and a corresponding transfer station for the selected passenger, and then informs the path information of the front car and the rear car and the transfer station to the transfer path planning unit; the transfer path planning unit inserts the transfer station into the path of the front and rear vehicles according to the received information, and also moves the target station of the passenger in the original path of the front vehicle into the path of the rear vehicle, thereby updating the path information of the front and rear vehicles to the non-driving path information database.
Preferably, the path planning module inserts the upper station point and the lower station point of the bus taking request into the path of the vehicle according to the distribution result of the bus taking request in an insertion scheme corresponding to the minimum cost, and executes the merging operation when the two adjacent stations are the same station.
The passenger terminal can be realized by arranging a fixed terminal system for calling in a bus station, but in many cases, passengers prefer to use a private communication device (application program on) such as a mobile phone to send a riding request.
The vehicle-mounted control system is used for receiving the latest path information planned by the big data center, informing a bus driver or an automatic driving system, removing a stop from the path information which is not driven after the bus visits the stop, and informing the big data center of updating the path information database which is not driven.
The request distribution refers to: allocating the taking requests of a batch of passengers to different buses, and minimizing the newly added length sum of the corresponding bus routes, wherein the optimization targets and the limiting conditions are respectively as follows:
optimizing the target: minimizing Σ (D'i-Di) Wherein D isiAnd D'iThe total length of the non-driving path of the ith bus before and after the algorithm is executed respectively.
The limiting conditions are as follows:
1. the number of passengers C in the bus is less than or equal to CMIn which C isMThe upper limit of the number of passengers carrying the bus is consistent.
2. Bypass ratio (d) of each passengerj-sdj)/sdj≤δjWherein d isjAnd sdjRespectively the actual riding distance of the jth passenger and the shortest distance between the getting-on and getting-off stations, deltajAnd setting a bypass ratio upper limit for the passenger in the riding request.
3. Waiting time tj≤σjWhere σ isjFor passengersThe upper limit of the waiting time set in the riding request.
4. Distance of walking wdj≤ωjWherein ω isjAnd setting the upper limit of the walking distance for the passenger in the riding request. wdjComprises two parts, namely a walking distance a before getting on the vehiclejAnd a distance z of walking after getting off the vehiclejI.e. wdj＝aj+zj。
5. Number of transfer times kjK is less than or equal to K, wherein K is the upper limit of transfer times.
6. The order of the receiving and sending points of the original path is ensured to be unchanged.
As shown in fig. 2, the request allocation and path planning module calculates the minimum value of the path newly-increased length of each bus, which is the allocation cost of the request to the bus, when the request is allocated to each bus by using a matrix value selection method designed according to a greedy strategy, for all the bus requests to be allocated. When all the path planning schemes for the bus to pick up and deliver the passenger can cause the failure of any limiting condition, the distribution cost is set to be infinite. And constructing an allocation cost matrix by using the allocation costs, wherein the row of the allocation cost matrix corresponds to each bus taking request, and the column of the allocation cost matrix corresponds to each bus. And selecting the minimum distribution cost in the matrix each time, then distributing the bus taking request corresponding to the cost to the corresponding bus, and constructing the optimal path of the bus. After that, the row corresponding to the bus taking request is deleted from the matrix, and then the distribution cost of all the remaining requests to the bus is updated. The above selection, assignment and construction of paths, deletion and update operations are performed until all rows are deleted and all passengers achieve the assignment at a local minimum cost.
As shown in fig. 3, the calculation method of the distribution cost specifically includes: the path in the figure has 4 pick-up points, so there are 5 positions for insertion; the passenger getting-on station and getting-off station can be inserted into the positions, but because the access to the getting-off station cannot be earlier than that of the getting-on station, the total number of insertion schemes is equal to the sum of arithmetic progression elements with the step length of 1 to 5 and the step length of 1; when the passenger gets on or off the station, firstly, the limiting conditions of all passengers including the passenger are not destroyed, otherwise, the insertion scheme is judged to be invalid; when all the insertion schemes are judged to be invalid, setting the distribution cost of the passenger to the bus to be infinite; and if not, subtracting the length before the insertion from the new path length obtained after the insertion to obtain the insertion cost of the insertion scheme for all effective insertion schemes. And selecting the minimum value from all the insertion costs as the distribution cost of the passenger to the bus.
The insertion refers to adding a station needing to be visited between two adjacent stations of the existing route of the bus or at the tail of the route, so that the station visiting sequence of the bus is changed. The insertion location cannot be before the first stop in the path because the bus is likely moving toward the first stop.
Preferably, the shortest distance of all stations from each other can be calculated and stored for standby at system start-up.
The matrix value selection method can be used as an initial solution generator of other heuristic algorithms, and can also be directly rewritten into the heuristic algorithms. Based on the characteristic that the matrix value selection method is high in operation speed, the rewritten heuristic algorithm obtains a better optimization target by randomly searching for many times in a solution space near the initial solution.
As shown in fig. 2, the present embodiment is based on computer simulations of a conventional transit system and a non-routing transit system:
1. the experimental area is selected as an area surrounded by inner ring elevated roads in Shanghai city of China, the area exceeds 100 square kilometers, the number of residents exceeds 300 million, the mobility of personnel is very large, and the experimental area is also an area with dense coverage of a public transport system.
2. The simulation period is centered at two hours of the peak period of the day, such as 7 to 9 am. The simulation of the peak time can more obviously show the performance comparison of the two systems.
3. The simulator will generate data for 2 ten thousand ride requests during this period, the origin, destination and time of request issuance will be extracted from taxi data in Shanghai city. The data recorded by the public transportation system is not used because the public transportation data does not contain the exact departure place and destination of the passenger, so the walking process and time consumption of the passenger cannot be simulated.
4. For convenience, the upper limit δ of the bypass ratio of all passengersjAre all set to 0.4, the upper limit of the waiting time σjThe total upper limit omega of the walking distance before getting on or off the bus is set to be 15 minutesjSet to 1 km. The walking speed of the passenger was set to 1.4 m/s.
5. The time of the bus stopping at each station is simulated according to the following method: when passengers get on the train, the basic parking time is 25 seconds, otherwise, the basic parking time is 15 seconds; every more passenger gets on the bus, the parking time is increased by 5 seconds; every more passenger gets off the train, the parking time is increased by 3 seconds.
6. Upper limit of number of passengers in vehicle CM20 persons were set. The vehicle speed was uniformly set to 15 m/s.
In the non-routing bus system, a simulator calls a request distribution and path planning module once every 100 seconds, and all bus taking requests received within 100 seconds are distributed to buses.
After the system is started, passengers send bus taking requests to the big data center by using information sending terminals (such as mobile phones), the system should provide enough buses to meet the bus taking requirements of all the passengers, but only a part of the buses selected by the algorithm are mobilized at the same time. After the algorithm is completed, the system sends the planned route information to the passenger, who needs to go to the station within a specified time (which is not shorter than the minimum time required for normal walking speed). Buses do not move without servicing any passengers, with their initial stopping locations dispersed throughout the service area. After receiving the route planned by the system for the bus, the bus starts to run according to the route information, and visits the departure station and the arrival station of the served passengers in sequence according to the sequence in the route. As shown in fig. 4, the system may insert a new pickup station between any two stations in the bus non-travel path if the restriction condition is satisfied, so as to allocate more passengers to the traveling bus in the future.
For a reasonable comparison with conventional public transportation systems,in the embodiment, the existing bus stop in the inner ring area of Shanghai city is adopted, but for the passengers far away from the bus stop, the system sets the getting-on or getting-off point of the passenger as a virtual 'newly-added bus stop' so as to strictly follow the limit condition of the walking distance of the passenger, and simultaneously, other passengers in the blind area which cannot be covered by the current bus stop are brought into the service range. In addition, since the waiting time of the passenger can be used for traveling from the departure point to the boarding station, the walking time before the passenger gets on the vehicle has little influence on the travel time of the passenger all over the vehicle. The walking time after the passenger gets off the bus is a component of the whole journey time of the passenger. In view of this, the get-off station of the passenger in this embodiment is selected as the station closest to the passenger, thereby determining the walking distance z after getting-offj(ii) a The upper limit of the distance between the passenger boarding station and the passenger departure point is omegaj-zjAll available pick-up stations within the range are determined by the request distribution module to be the optimal choice when calculating the distribution cost.
In the transfer and multiplication strategy of the system, the embodiment increases the requirement on the transfer and multiplication effect:
otherwise, no transfer is performed.
The limiting ratio is determined by repeated experiments. The transfer with unobvious improvement on the system efficiency is frequently caused by too low proportion, and the system efficiency is easily reduced due to the fact that the transfer is stopped every time; too high a ratio may result in more efficient transfer. The embodiment also makes a limit of 15 minutes on the sum of waiting time of passengers at all transfer stations so as to ensure the quality of transfer service.
The basic implementation method of the heuristic algorithm is to give a certain degree of disturbance to the process of selecting the matrix values. In this embodiment, the heuristic algorithm reduces the probability of selecting the minimum value in the matrix (the probability in the original algorithm is 100%), so that the second smallest value in the column where the minimum value is located also has a probability of being selected. Therefore, the method not only applies disturbance with small cost to the selection process, but also enables the unselected minimum value to be updated immediately, and ensures that the selection scheme made by the algorithm each time is different enough with a large probability.
In a conventional public transportation system, map data used by a simulator includes about 280 bus routes and corresponding stops in the shanghai inner circle area. The system distributes all buses to each line according to the length of each bus line, and the buses move back and forth on each line and stop at each station. The optimal routing of the passengers can be determined in advance by a simulator before the system runs, and the specific implementation method is as follows: finding all feasible combinations of the boarding station and the alighting station of the passenger under the limit condition of the walking distance with the total length of 1 kilometer (if the combination is not found, the limit of the walking distance is relaxed until the combination is found); for each combination of the upper station and the lower station, whether transfer can be avoided or not is preferentially searched, namely, the upper station and the lower station are connected through only one bus line; when the passenger is available, finding the route with the shortest sitting distance from all the routes which are not transferred as the route planned by the simulator for the passenger; otherwise, the optimal route is selected from the feasible routes which are transferred by 1 time and 2 times according to the method.
The data results of simulation experiments for various algorithms are included in the table below. The partial indicators used to evaluate the experimental results and the performance of each system or algorithm are described below:
1. the total distance traveled by the vehicle and the total distance traveled by the passenger refer to the distance traveled by the vehicle and the passenger during travel of the vehicle, wherein the former does not include the distance traveled when the vehicle is empty. The index is an accumulation result of an optimization target of the request allocation and path planning algorithm after the algorithm is operated for multiple times, directly reflects the cost of transporting all passengers by the system, and is a key index for measuring the operation cost of the system.
In practical applications, the operating costs of a transit system include the fuel consumption of the vehicle, the maintenance costs of the system, and the labor costs of the driver. In the embodiment, only the fuel consumption of the vehicle is considered for the convenience of showing the technical effect.
2. The global detour ratio is:
it reflects the overall level of passenger detour in the system and is an important index for measuring passenger comfort.
3. The global sharing factor is:
it reflects the overall level of vehicle sharing in the system, better weighing the ability of the algorithm to concentrate on utilizing the capacity resources of the activated vehicle in the process of passenger allocation.
4. Similar to the total distance traveled by a vehicle, the number of vehicle stops also has a significant effect on the energy consumption of the vehicle, and is another key indicator for measuring transportation cost. Furthermore, the reduction of the number of stops is also important for the improvement of passenger comfort. In a conventional transit system, vehicles stop at each station, whereas in a non-routing transit system vehicles only stop as needed.
5. The average time taken by a passenger before boarding includes three parts: the time for the passenger to wait for the system to respond after sending the request, the time it takes for the passenger to walk to the station and the time it takes for the passenger to wait for the vehicle to arrive. The time index can reflect the acceptance speed of the bus system to the passenger request, and is helpful for improving the comfort of the passenger.
6. The average time consumption of the passenger transfer period is a unique index of an algorithm adopting a transfer mechanism, and consists of two parts of the time consumption of the passenger walking between transfer stations and the time consumption of the passenger waiting for the vehicle to arrive at the transfer point. The former takes 0 if walking is not required.
7. The average time consumed by the passengers in the whole journey is the sum of the average time consumed by the passengers before getting on the bus, the average time consumed by the passengers during transfer, the average time consumed by the passengers after getting off the bus and the average time consumed by the passengers after walking. For the same batch of passengers, the average time consumption of the passengers in the whole process is the most direct embodiment of the transportation efficiency of the whole bus system.
8. The maximum value of the number of vehicle maneuvers refers to the peak value of the number of vehicles in a running state during the whole operation process of the system. The index is the most direct embodiment of the system transport capacity and represents the congestion pressure of the public transport system to the whole urban traffic system. Obviously, the vehicles equipped in the conventional public transportation system are in a running state at any time, the pressure on urban traffic can be maintained at a high level under the condition of not defining a special traffic lane, and the defined special traffic lane actually extrudes the running space of other vehicles on the same road.
MS-X represents that at most X times of transfer are allowed in the algorithm mainly based on the Matrix value Selection method, wherein MS represents an abbreviation of english Matrix Selection of the Matrix value Selection method. Compared to the performance of conventional transit systems, the non-routing transit system using MS-0 achieves a comprehensive override on all comparable data, with the most prominent being the total distance traveled by the vehicle, the global sharing factor, and the average time spent by the passengers at each stage. Compared with MS-0, MS-1 and MS-2 have small advantages in terms of total driving distance of the vehicle and global sharing factors, but pay certain cost in other indexes, particularly mainly the number of times of vehicle parking and average time consumption of passengers during transfer. Considering the damage of transfer to the comfort level of passengers, the transfer mechanism in the non-routing bus system is proved by a simulation experiment to be a mechanism which cannot bring obvious improvement. This makes the mechanism design of the non-routing public traffic system can be effectively simplified.
Compared with MS-0, the heuristic algorithm has no outstanding effect, and the experimental result only indicates that the greedy strategy is not the optimal method for solving the problem. However, the heuristic algorithm still cannot obtain a much better solution after a large-scale search, which helps to show that the matrix value selection method approaches the optimal solution of the problem to some extent.
Although the present embodiment only considers vehicle fuel consumption, it is anticipated that shorter vehicle travel distances, fewer vehicle stops and starts, and a substantially reduced number of mobilized vehicles will result in further reductions in system maintenance costs; along with the rapid development and popularization of the unmanned bus, the labor reward of a driver does not need to be considered any more, and the pricing strategy of the future bus industry is shifted to a binary game of an operator and a passenger. If more reasonable and personalized service cost can be determined for each passenger in real time according to the actual service cost, the bus industry has stronger competitiveness.
The foregoing embodiments may be modified in many different ways by those skilled in the art without departing from the spirit and scope of the invention, which is defined by the appended claims and all changes that come within the meaning and range of equivalency of the claims are therefore intended to be embraced therein.
Claims (7)
1. A non-routing public transportation control system based on a quick response ride request, comprising: the system comprises a communication module, a data module, a request distribution and path planning module and a transfer planning module, wherein: the communication module collects riding request information from a passenger terminal, collects real-time non-driving path information of a bus from a vehicle-mounted control system of the bus and updates the real-time non-driving path information to the data module, acquires the updated path information from the data module and sends the updated path information to affected passengers and the affected bus; the request distribution and path planning module extracts the unallocated request information from the data module, distributes the unallocated request information to different buses, plans the updated path information for the buses and then updates the updated path information to the data module; the transfer planning module scans the path information of the data module to obtain newly distributed passengers, arranges an optimal rear vehicle and a transfer station for the passengers with the longest riding distance, plans updated path information for the corresponding front vehicle and the rear vehicle and updates the updated path information to the data module;
the riding request information comprises information set by the passenger, such as a departure place and a target place of the passenger, a detour ratio upper limit which can be tolerated by the passenger, a waiting time upper limit, a walking distance upper limit and the like, and a time stamp when the request is sent;
the request distribution refers to: allocating the taking requests of a batch of passengers to different buses, and minimizing the newly added length sum of the corresponding bus routes, wherein the optimization targets and the limiting conditions are respectively as follows:
optimizing the target: minimum sizeSigma (D'i-Di) Wherein D isiAnd D'iRespectively calculating the total length of the non-driving path of the ith bus before and after the algorithm is executed;
the limiting conditions include:
1) the number of passengers C in the bus is less than or equal to CMIn which C isMThe upper limit of the number of passengers carrying the bus is consistent;
2) bypass ratio (d) of each passengerj-sdj)/sdj≤δjWherein d isjAnd sdjRespectively the actual riding distance of the jth passenger and the shortest distance between the getting-on and getting-off stations, deltajA detour ratio upper limit set for the passenger in the riding request;
3) waiting time tj≤σjWhere σ isjSetting a waiting time upper limit for the passenger in the riding request;
4) distance of walking wdj≤ωjWherein ω isjUpper limit of distance travelled, wd, set by the passenger in the request for a ridej＝aj+zjDistance a of walking before getting onjAnd a distance z of walking after getting off the vehiclej；
5) Number of transfer times kjK is less than or equal to K, wherein K is the upper limit of transfer times;
6) ensuring the order of the receiving and sending points of the original path to be unchanged;
the request distribution and path planning module respectively calculates the minimum value of the newly increased path length caused by the request distributed to each bus for all the bus taking requests to be distributed by adopting a matrix value selection method designed based on a greedy strategy, namely the distribution cost of the request to the bus; when all path planning schemes for the bus to pick up and deliver the passengers lead to the failure of any limiting condition, the distribution cost is infinite, a distribution cost matrix is constructed according to the distribution cost, the row of the distribution cost matrix corresponds to each bus taking request, the column of the distribution cost matrix corresponds to each bus, the minimum distribution cost is selected in the matrix each time, then the bus taking request corresponding to the cost is distributed to the corresponding bus, and the optimal path of the bus is constructed; after that, deleting the row corresponding to the bus taking request from the matrix and updating the distribution cost of all the remaining requests to the bus; the above selection, assignment and construction of paths, deletion and update operations are performed until all rows are deleted and all passengers achieve the assignment at a local minimum cost.
2. The system of claim 1, wherein the allocation cost is specifically: determining the positions for insertion, namely a passenger boarding station and a passenger disembarking station, according to the pick-up points, determining the number of insertion schemes, and determining that the insertion schemes meet the following requirements when the passenger boarding station and the passenger disembarking station are inserted:
the restriction conditions of all passengers including the passenger are not destroyed, otherwise, the insertion scheme is judged to be invalid;
when all the insertion schemes are judged to be invalid, setting the distribution cost of the passenger to the bus to be infinite; otherwise:
for all effective insertion schemes, subtracting the length before insertion from the new path length obtained after insertion to obtain the insertion cost of the insertion scheme, and selecting the minimum value from all the insertion costs as the distribution cost of the passenger to the bus;
the insertion refers to adding a station needing to be visited between two adjacent stations of the existing route of the bus or at the tail of the route, so that the station visiting sequence of the bus is changed.
3. The system of claim 1 or 2, wherein said request distribution and path planning module comprises: a request distribution unit and a path planning unit, wherein: the request distribution unit periodically reads and deletes the accumulated request information from the request information database to be distributed, determines vehicles distributed for each request after calculating by combining the path information in the non-driving path information database, and then outputs the vehicles to the path planning unit; and after receiving the distribution information, the path planning unit inserts the upper and lower stop points of each riding request into the paths of the distributed vehicles by using an insertion scheme corresponding to the minimum cost, so that the path information of the vehicles is updated to the non-driving path information database.
4. The system of claim 1, wherein the matrix value selection method is used as an initial solution generator or is adapted to a heuristic algorithm, and the adapted heuristic algorithm obtains a better optimization objective by performing multiple random searches in a solution space around the initial solution.
5. The system of claim 1, wherein said communication module comprises: a request information receiving unit, a path information transmitting unit and a path information updating unit, wherein: the request information receiving unit receives the riding request information sent at any time and stores the riding request information into a request information database to be distributed of the data module; the path information updating unit receives the information of the paths on which the vehicles do not run from any time and updates the information of the paths on which the vehicles do not run to a database of the path information on which the vehicles do not run of the data module; the route information transmitting unit informs the affected passengers and vehicles of the changed route information after the non-driving route information database is updated.
6. The system of claim 1, wherein said data module comprises: a request information database to be allocated and a non-driving path information database, wherein: the information database of the request to be distributed is only used for temporarily storing the request which is not distributed before the next algorithm operation and providing input data for the algorithm of the request distribution; the non-driving path information database is used for storing real-time non-driving path information of all buses.
7. The system of claim 1, wherein the transfer planning module comprises: transfer request search unit, back car search unit and transfer route planning unit, wherein: the transfer request searching unit scans a batch of newly distributed passengers in the non-driving path information database, preferentially selects the passenger with the longest driving distance to try to arrange transfer, and informs the selected passenger and the vehicle in which the passenger is located, namely the path information of the front vehicle to the rear vehicle searching unit; the rear car searching unit arranges a rear car and a corresponding transfer station for the selected passenger, and then informs the path information of the front car and the rear car and the transfer station to the transfer path planning unit; the transfer path planning unit inserts the transfer station into the path of the front and rear vehicles according to the received information, and also moves the target station of the passenger in the original path of the front vehicle into the path of the rear vehicle, thereby updating the path information of the front and rear vehicles to the non-driving path information database.
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| CN112215418B (en) * | 2020-10-12 | 2024-04-16 | 苏州大学 | Method, device and storage medium for automatically generating washing inspection arrangement scheme of multi-rail vehicle |
| CN112590816B (en) * | 2020-12-21 | 2022-05-20 | 东风汽车集团有限公司 | Automatic driving back-and-forth switching method and device based on four-wheel steering automobile |
| CN116681196B (en) * | 2023-06-07 | 2023-10-31 | 北京安录国际技术有限公司 | Intelligent traffic route planning method and system |
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