A traffic integration optimization method, system, program product, and storage medium

Abstract

The present application provides a method, system, program product, and storage medium for integrated traffic optimization, and relates to the field of intelligent traffic technology. The present application realizes the unified management of public transportation, online car-hailing, traffic control, and parking resources. Among them, by collecting real-time data of various public transportation tools and generating docking plans, the allocation of transportation capacity is more accurate; by planning the optimal docking route for online car-hailing, the empty mileage is reduced; by real-time monitoring of the road network status and implementing control measures, traffic congestion is promptly alleviated; by coordinating parking resources and providing navigation, vehicles are prevented from blindly searching for parking spaces. This integrated management method solves the problem that various types of traffic resources cannot be coordinated under the decentralized management model in related technologies, and improves the overall traffic operation efficiency.

Description

Technical Field

[0001] The present application relates to the field of intelligent transportation technology, and in particular to a method, system, program product, and storage medium for optimizing integrated transportation. Background Art

[0002] The urban transportation system includes public transportation, private cars, online ride-hailing and other modes of travel. These transportation tools are concentrated during peak hours in the morning and evening, which brings huge pressure to urban traffic management. Especially in crowded areas such as business districts and residential areas, there is a large demand for passenger transfers and private car parking. At the same time, the pressure on road traffic is high. Various traffic problems are intertwined and urgently need to be solved in a coordinated manner.

[0003] At present, urban traffic management adopts a decentralized management model. Buses and subways operate independently according to fixed timetables, and the operating departments preset departure intervals based on experience; taxis and online ride-hailing vehicles pick up passengers by random patrol or dispatching orders nearby; traffic management departments implement traffic control by manual observation when traffic is congested; each parking lot independently releases remaining space information through display screens, and car owners find parking spaces by themselves.

[0004] This empirical, decentralized management model leads to inefficient use of transportation resources. When passenger flow suddenly increases, bus and subway capacity allocation lags behind, resulting in a large backlog of passengers; online ride-hailing vehicles frequently run empty, increasing the burden on roads; traffic control is not timely enough, causing the scope of congestion to expand; car owners blindly look for parking spaces around their destinations, exacerbating local road pressure. These problems lead to inefficient urban transportation operations and poor travel experience for citizens.

[0005] In summary, the decentralized traffic management model of related technologies leads to low efficiency in the utilization of traffic resources. Summary of the invention

[0006] The present application provides a method, system, program product, and storage medium for optimizing integrated transportation, which are used to solve the problem that various types of transportation resources cannot be coordinated under the decentralized management mode in related technologies, thereby improving the overall transportation operation efficiency.

[0007] In a first aspect, the present application provides a method for optimizing integrated transportation, including: collecting location information and passenger data of each public transportation vehicle, generating a connection plan data packet based on the location information and passenger data, the connection plan data packet including the arrival time and the number of passengers, sending the connection plan data packet to each public transportation vehicle, so that each public transportation vehicle arrives at the corresponding station to pick up the number of passengers according to the arrival time in the connection plan data packet; receiving a reservation data packet sent by a user terminal, determining an optimal connection route based on the reservation data packet, generating a navigation data packet including the optimal connection route, sending the navigation data packet to a target vehicle, so that the target vehicle picks up the user according to the navigation data packet; acquiring traffic status data in the road network, and executing traffic control measures when the traffic status data indicates traffic congestion; receiving parking space status data and a parking reservation request of a current vehicle, planning an optimal parking lot and its navigation route based on the parking space status data and the parking reservation request, and sending the optimal parking lot and the navigation route to the current vehicle.

[0008] By adopting the above technical solutions, this application realizes the unified management of public transportation, online car-hailing, traffic control and parking resources. Among them, by collecting real-time data of various public transportation tools and generating docking plans, the allocation of transportation capacity is more accurate; by planning the optimal docking route for online car-hailing, the empty mileage is reduced; by real-time monitoring of the road network status and implementing control measures, traffic congestion is promptly alleviated; by coordinating parking resources and providing navigation, vehicles are prevented from blindly searching for parking spaces. This integrated management method solves the problem of the inability to coordinate various types of transportation resources under the decentralized management model in related technologies, and improves the overall traffic operation efficiency.

[0009] In combination with some embodiments of the first aspect, in some embodiments, the steps of receiving parking space status data and parking reservation requests, and planning the optimal parking lot and its navigation route for the user specifically include: generating parking space status data based on the parking space occupancy information sent by the parking lot; receiving a parking reservation request sent by a user terminal, the parking reservation request including the vehicle's current location information and destination information; obtaining traffic impact factors of surrounding parking lots, the traffic impact factors including parking lot capacity, surrounding road capacity and distance to the destination; calculating the suitability scores of surrounding parking lots based on the parking space status data and traffic impact factors; determining the parking lot with the highest suitability score as the optimal parking lot; generating a navigation route from the vehicle's current location to the optimal parking lot; and sending the optimal parking lot and the navigation route to the current vehicle.

[0010] By adopting the above technical solutions, the system can comprehensively evaluate the suitability of parking lots. The real-time parking resource status can be grasped through parking space occupancy information, and the scale effect can be reflected in combination with parking lot capacity; the convenience of entering and exiting the parking lot can be evaluated through the traffic capacity of surrounding roads; and the convenience of walking can be reflected through the distance to the destination. This multi-dimensional evaluation method ensures that the selection of the optimal parking lot is more reasonable, and can take into account both parking convenience and traffic diversion effects.

[0011] In conjunction with some embodiments of the first aspect, in some embodiments, the step of calculating the suitability score of surrounding parking lots according to the parking space status data and the traffic impact factor specifically includes: In the formula, C f is the parking space status data, C t is the parking lot capacity, V r is the average real-time vehicle speed of the surrounding roads in the surrounding road capacity, V m is the maximum speed limit of the surrounding roads in the surrounding road capacity, D is the distance to the destination, and D max is the preset maximum acceptable distance, and w1, w2, and w3 are the preset weights.

[0012] By adopting the above technical solution, by introducing The system uses the term "car capacity" to process parking lot capacity, so that large-capacity parking lots can obtain reasonable score improvements, but the marginal effect decreases with the increase of capacity, avoiding excessive preference for super-large parking lots; the system uses the square relationship between the real-time vehicle speed and the speed limit ratio to evaluate road capacity, so that the score will decrease rapidly when the road is congested, and increase accordingly when the road is unobstructed, so that the system is more inclined to choose parking lots in areas with smooth traffic; through the quadratic term design of distance influence, the negative impact of distance on the score accelerates with the increase of distance, avoiding the system recommending parking lots that are too far away. This scoring mechanism makes the parking lot selection more in line with actual usage needs.

[0013] In combination with some embodiments of the first aspect, in some embodiments, the step of generating a connection plan data packet based on location information and passenger data specifically includes: calculating the current travel speed and remaining mileage of each public transportation vehicle based on the location information and preset route information; calculating the arrival time of each public transportation vehicle at each station along the route based on the current travel speed, remaining mileage and historical travel time data; obtaining the remaining number of seats for each public transportation vehicle by subtracting the passenger data from the total number of seats; predicting the number of waiting passengers at each station based on the historical passenger flow data of each station, and allocating the number of waiting passengers based on the remaining number of seats: when the number of waiting passengers is less than or equal to the remaining number of seats, the number of waiting passengers is used as the number of passengers; when the number of waiting passengers is greater than the remaining number of seats, the remaining number of seats is used as the number of passengers, and the excess number of waiting passengers is allocated to the public transportation vehicles that arrive at the subsequent stations; generating a connection plan data packet containing the arrival time and the number of passengers.

[0014] By adopting the above technical solution, the arrival time is calculated based on real-time location information and driving speed, and the capacity is allocated based on the remaining number of seats and the predicted number of waiting passengers. When there is insufficient capacity, the system will automatically allocate the excess to subsequent vehicles, forming a dynamic scheduling mechanism. This precise scheduling method based on real-time data avoids the capacity mismatch problem caused by traditional fixed timetables.

[0015] In combination with some embodiments of the first aspect, in some embodiments, the steps of receiving a reservation data packet sent by a user terminal, determining an optimal connecting route based on the reservation data packet, and generating a navigation data packet containing the optimal connecting route specifically include: receiving a reservation data packet sent by the user terminal containing a user location, a destination location, and an expected travel time; obtaining the vehicle's location information, passenger data, and service area data; filtering vehicles with zero passenger data based on the matching relationship between the user location and the service area data to obtain candidate target vehicles; calculating the total connecting time of the candidate target vehicles based on the location information, wherein the total connecting time is the sum of the estimated driving time for the candidate target vehicle to reach the user location and the estimated driving time from the user location to the destination location; sorting the candidate target vehicles according to the total connecting time, and selecting the vehicle with the shortest total connecting time as the target vehicle; planning an optimal connecting route for the target vehicle based on real-time road condition information, the optimal connecting route including a pick-up route from the current location of the target vehicle to the user location, and a drop-off route from the user location to the destination location; generating a navigation data packet containing the optimal connecting route, and sending the navigation data packet to the target vehicle.

[0016] By adopting the above technical solutions, the dispatching and route planning of online ride-hailing vehicles are optimized. The system screens empty vehicles through service area data to avoid invalid dispatching; then sorts and selects by calculating the total connection time to ensure the optimal connection efficiency; finally, the route is planned based on real-time traffic conditions, taking the pick-up and drop-off routes into consideration as a whole. This full-process optimization from vehicle screening to route planning not only improves the operational efficiency of online ride-hailing vehicles, but also reduces the waiting time for passengers.

[0017] In combination with some embodiments of the first aspect, in some embodiments, traffic status data in a road network is obtained, and when the traffic status data indicates that traffic congestion has occurred, the steps of executing traffic control measures specifically include: obtaining traffic status data in the road network, the traffic status data including standard travel time and actual travel time; calculating the ratio of the actual travel time of vehicles on the road to the standard travel time; according to a preset circle road grade, a weighted average of the comparison values ​​is calculated to obtain a traffic congestion index; a road having a traffic congestion index greater than a preset congestion threshold is determined as a congested road; increasing the green light duration of congested roads, reducing the green light duration of associated roads, and generating a new signal light timing plan; and sending the new signal light timing plan to the signal controller of the corresponding intersection to adjust the traffic capacity of the congested road and the associated roads.

[0018] By adopting the above technical solution, the ratio of actual travel time to standard travel time is calculated and weighted by considering the road grade to obtain an accurate congestion index. When congestion occurs, the traffic capacity is reasonably allocated by adjusting the signal light timing plan, which not only ensures the relief of congested sections, but also avoids the chain reaction of related roads.

[0019] In combination with some embodiments of the first aspect, in some embodiments, after the step of sending a new traffic light timing plan to the signal controller of the corresponding intersection and adjusting the traffic capacity of the congested road and the associated roads, the method also includes: obtaining the adjusted traffic status data of the congested road; calculating a new traffic congestion index based on the adjusted traffic status data; when the new traffic congestion index is not greater than the preset congestion threshold, restoring the original traffic light timing plan.

[0020] By adopting the above technical solution, the system continuously monitors the traffic status and calculates a new congestion index after implementing control measures. When the congestion is alleviated, the original solution is restored in time, avoiding unnecessary impact of excessive control on overall traffic.

[0021] In a second aspect, the present application provides a traffic integration optimization system, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the traffic integration optimization system to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0022] In a third aspect, the present application provides a computer program product comprising instructions, which, when executed on a traffic integration optimization system, enables the traffic integration optimization system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0023] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions, which, when executed on a traffic integration optimization system, enables the traffic integration optimization system to execute the method described in the first aspect and any possible implementation of the first aspect.

[0024] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. This application realizes the unified management of public transportation, online car-hailing, traffic control and parking resources. Among them, by collecting real-time data of various public transportation tools and generating docking plans, the allocation of transportation capacity is more accurate; by planning the best docking routes for online car-hailing, the empty mileage is reduced; by real-time monitoring of road network status and implementing control measures, traffic congestion is promptly alleviated; by coordinating parking resources and providing navigation, vehicles are prevented from blindly searching for parking spaces. This integrated management method solves the problem of the inability to coordinate various types of transportation resources under the decentralized management model in related technologies, and improves the overall traffic operation efficiency.

[0025] 2. The system can comprehensively evaluate the suitability of parking lots. It can grasp the real-time parking resource status through parking space occupancy information, and reflect the scale effect in combination with parking lot capacity; evaluate the convenience of entering and exiting the parking lot through the traffic capacity of surrounding roads; and reflect the convenience of walking through the distance to the destination. This multi-dimensional evaluation method ensures that the selection of the optimal parking lot is more reasonable, and can take into account both parking convenience and traffic diversion effects.

[0026] 3. By introducing The system uses the term "car capacity" to process parking lot capacity, so that large-capacity parking lots can obtain reasonable score improvements, but the marginal effect decreases with the increase of capacity, avoiding excessive preference for super-large parking lots; the system uses the square relationship between the real-time vehicle speed and the speed limit ratio to evaluate road capacity, so that the score will decrease rapidly when the road is congested, and increase accordingly when the road is unobstructed, so that the system is more inclined to choose parking lots in areas with smooth traffic; through the quadratic term design of distance influence, the negative impact of distance on the score accelerates with the increase of distance, avoiding the system recommending parking lots that are too far away. This scoring mechanism makes the parking lot selection more in line with actual usage needs. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] Figure 1 This is a flow chart of traffic integration optimization in the embodiment of the present application; Figure 2 This is a specific flow chart of step S101 in the embodiment of the present application; Figure 3 This is a specific flow chart of step S102 in the embodiment of the present application; Figure 4 This is a specific flow chart of step S103 in the embodiment of the present application; Figure 5 This is a specific flow chart of step S104 in the embodiment of the present application; Figure 6 It is an exemplary hardware structure diagram of the traffic integration optimization system in the embodiment of the present application. DETAILED DESCRIPTION

[0028] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all possible combinations of one or more listed items.

[0029] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0030] See also Figure 1 , Figure 1 This is a flow chart of traffic integration optimization in the embodiment of the present application; S101, collecting the location information and passenger data of each public transportation tool, generating a docking plan data packet according to the location information and passenger data, the docking plan data packet including the arrival time and the number of passengers, sending the docking plan data packet to each public transportation tool, so that each public transportation tool arrives at the corresponding station to pick up the number of passengers according to the arrival time in the docking plan data packet; wherein, public transportation tool refers to buses, subways and other transportation tools that provide fixed-line transportation services; the location information represents the real-time geographic coordinate data of the public transportation tool; the passenger data is used to represent the number of passengers in the current car; the docking plan data packet refers to the scheduling information including the arrival time and the number of passengers; the arrival time represents the specific time expected to arrive at each station; the number of passengers refers to the number of passengers expected to be picked up at each station.

[0031] This step is continuously performed during the operation of urban public transportation to achieve intelligent scheduling of public transportation. In some embodiments, the system first collects the location and passenger information of each public transportation vehicle in real time through the on-board terminal, and transmits this data to the central scheduling system. The scheduling system combines historical passenger flow data and real-time road conditions to calculate the estimated time for each vehicle to arrive at the subsequent station, and reasonably allocates the passenger tasks of each vehicle according to the waiting situation at each station, and generates a scheduling plan including specific arrival time and number of passengers. Finally, the scheduling plan is issued to each public transportation vehicle to guide it to arrive at the corresponding station according to the planned time to pick up a specified number of passengers.

[0032] See also Figure 2 , Figure 2 This is a specific flow chart of step S101 in the embodiment of the present application; In some embodiments, step S101 specifically includes: S1011. Calculate the current speed and remaining mileage of each public transportation vehicle based on the location information and preset route information; wherein the preset route information refers to the geographic coordinate sequence of the fixed operating lines of the public transportation; the current speed is used to represent the instantaneous speed of the public transportation vehicle; and the remaining mileage represents the remaining distance to reach the terminal.

[0033] In some embodiments, the system continuously collects location data based on the on-board positioning device, matches the real-time location with the preset route, obtains the current driving speed by calculating the position change per unit time, and calculates the remaining distance to be traveled based on the traveled trajectory and the preset route, providing basic data support for subsequent arrival time predictions.

[0034] S1012, calculating the arrival time of each public transportation vehicle at each station along the route based on the current travel speed, remaining mileage and historical travel time data; Among them, the historical travel time data is used to represent the historical operating time statistics of the line in the same period.

[0035] In some embodiments, the system first calculates the remaining distance to each station based on the current position of the vehicle, and combines the current driving speed to obtain the theoretical running time. The system then analyzes the historical travel time data, including the actual running time records under different time periods, weather conditions, and road conditions, and obtains a more accurate running time prediction value through weighted calculation. Finally, the predicted running time is superimposed with the current time to obtain the specific time expected to arrive at each station.

[0036] S1013, obtaining the remaining number of seats of each public transportation vehicle according to the total number of seats minus the passenger data; Among them, the total number of seats represents the rated passenger capacity of public transportation.

[0037] S1014. Predict the number of waiting passengers at each station based on the historical passenger flow data of each station, and allocate the number of waiting passengers based on the number of remaining seats: Among them, the historical passenger flow data represents the passenger volume statistics of each station at different time periods; the number of waiting passengers refers to the number of passengers currently waiting to board the bus at each station.

[0038] S1015. When the number of waiting passengers is less than or equal to the number of remaining seats, the number of waiting passengers is used as the number of passengers to be carried; S1016. When the number of waiting passengers is greater than the number of remaining seats, the remaining number of seats is used as the number of passengers, and the excess number of waiting passengers is allocated to the public transportation vehicles that arrive at the station later; These two steps are used to handle passenger arrangements under different passenger flow conditions. In some embodiments, the system first compares the number of waiting passengers at the station with the number of remaining seats on the vehicle. When the number of waiting passengers does not exceed the number of remaining seats, all waiting passengers are arranged to board the vehicle; when the number of waiting passengers exceeds the number of remaining seats, the system gives priority to arranging passengers with the remaining seats to board the vehicle, and records the information of the excess passengers in the system, and allocates them to subsequent vehicles through the scheduling algorithm to ensure that all passengers can be reasonably arranged.

[0039] S1017: Generate a connection plan data packet including the arrival time and the number of passengers.

[0040] It can be seen that the arrival time is calculated through real-time location information and driving speed, and the capacity is allocated based on the remaining number of seats and the predicted number of waiting passengers. When there is insufficient capacity, the system will automatically allocate the excess to subsequent vehicles, forming a dynamic scheduling mechanism. This precise scheduling method based on real-time data avoids the capacity mismatch problem caused by traditional fixed timetables.

[0041] S102, receiving a reservation data packet sent by a user terminal, determining an optimal connecting route according to the reservation data packet, generating a navigation data packet containing the optimal connecting route, and sending the navigation data packet to a target vehicle, so that the target vehicle picks up the user according to the navigation data packet; Among them, the user terminal refers to mobile devices such as mobile phones used by passengers; the reservation data packet refers to the ride request information containing the user location, destination location and expected travel time; the optimal connection route represents the best driving route from the current location of the vehicle to the user location and then to the destination; the navigation data packet is used to represent navigation information containing detailed route guidance; the target vehicle refers to the online-ordered vehicle selected to perform the connection task.

[0042] This step is triggered and executed when the user initiates an online car-hailing reservation request, and is used to implement intelligent dispatching and route planning for online car-hailing. In some embodiments, when a user initiates a car request through a mobile phone APP, the system first receives reservation information including the user's current location, destination location, and expected car use time. The system then analyzes the distribution of currently available vehicles, comprehensively considers factors such as vehicle location, road conditions, and service scope, and selects the most suitable vehicle as the target vehicle. The system plans a pick-up route from the current location to the user's location, as well as a drop-off route from the user's location to the destination for the target vehicle, and packages this route information into a navigation data packet and sends it to the vehicle to guide the vehicle to complete the pick-up service.

[0043] See also Figure 3 , Figure 3 This is a specific flow chart of step S102 in the embodiment of the present application; In some embodiments, step S102 specifically includes: S1021, receiving a reservation data packet including a user location, a destination location, and an expected travel time sent by a user terminal; Among them, the user location refers to the passenger's current geographic coordinates; the destination location refers to the location coordinates where the passenger expects to arrive; and the expected travel time is used to indicate the specific time when the passenger plans to use the car.

[0044] This step is performed when the user initiates an online car-hailing reservation, and is used to receive and analyze the user's car-hailing needs. In some embodiments, when the user initiates a car-hailing request through a mobile phone APP, the system receives reservation information including the user's current GPS location, destination location, and expected car-hailing time.

[0045] S1022, obtaining the vehicle's location information, passenger data, and service area data; Among them, the location information represents the real-time geographic coordinates of the vehicle; the passenger data refers to the status information of whether the vehicle is currently carrying passengers; and the service area data is used to indicate the geographical range of services that the vehicle can provide.

[0046] In some embodiments, the system collects the location information of all operating vehicles in real time through the vehicle terminal, and obtains the passenger status of each vehicle and the preset service area range. These data will be used for subsequent vehicle screening and scheduling decisions to ensure that appropriate vehicle resources are allocated to users.

[0047] S1023, filtering vehicles with zero passenger data according to the matching relationship between the user location and the service area data to obtain candidate target vehicles; In some embodiments, the system first determines whether the user's location is within the service area of ​​each vehicle, and removes vehicles that are not within the service area. Then, the vehicle's passenger status is checked, and only empty vehicles with no passengers are retained. Through these two screenings, a set of candidate vehicles with suitable locations and immediate service is obtained.

[0048] S1024, calculating the total connection time of the candidate target vehicle according to the location information, wherein the total connection time is the sum of the estimated travel time of the candidate target vehicle to reach the user's location and the estimated travel time from the user's location to the destination location; Among them, the total connection time refers to the estimated time to complete the entire service; the estimated driving time is used to indicate the time required to travel the section; and the candidate target vehicles refer to the set of available vehicles that have passed the initial screening.

[0049] In some embodiments, the system calculates the time it takes for a candidate vehicle to pick up a passenger at the passenger's location and the time it takes to drop off the passenger from the passenger's location to the destination. The calculation process takes into account factors such as real-time road conditions and traffic control, and uses an intelligent path planning algorithm to obtain a more accurate time estimate. Finally, the two time periods are added together to obtain the total pick-up time for each candidate vehicle.

[0050] S1025, sorting the candidate target vehicles according to the total connection time, and selecting the vehicle with the shortest total connection time as the target vehicle; S1026, planning an optimal connecting route for the target vehicle based on the real-time traffic information, the optimal connecting route including a pick-up route from the current location of the target vehicle to the user's location, and a drop-off route from the user's location to the destination location; Among them, real-time traffic information indicates the current road traffic conditions; the optimal connecting route refers to the best driving route planned after comprehensive consideration of various factors; the pick-up route is used to indicate the driving route to the passenger's location; and the drop-off route indicates the driving route to carry passengers to the destination.

[0051] In some embodiments, the system plans the optimal driving routes for the pick-up and drop-off stages based on real-time traffic data, including road congestion, construction diversion information, traffic control measures, etc. The planning process comprehensively considers multiple goals such as shortest distance, optimal time, and best road conditions to ensure that the driving route is safe, reliable, efficient, and convenient.

[0052] S1027: Generate a navigation data packet containing an optimal connecting route, and send the navigation data packet to the target vehicle.

[0053] The navigation data packet refers to a data set containing complete route information.

[0054] In some embodiments, the system converts the planned optimal connecting route into a navigation data packet in a standard format, including detailed path point information, turn instructions, mileage data, etc. After the data packet is encrypted, it is sent to the on-board terminal of the target vehicle in real time through the wireless communication network to guide the driver to drive according to the planned route.

[0055] It can be seen that the optimization of online car-hailing dispatch and route planning has been achieved. The system screens empty vehicles through service area data to avoid invalid dispatch; then sorts and selects by calculating the total connection time to ensure the optimal connection efficiency; finally, the route is planned based on real-time traffic conditions, taking into account the pick-up and drop-off routes as a whole. This full-process optimization from vehicle screening to route planning not only improves the operational efficiency of online car-hailing, but also reduces the waiting time for passengers.

[0056] S103, acquiring traffic status data in the road network, and executing traffic control measures when the traffic status data indicates that traffic congestion occurs; Among them, road network refers to the urban road traffic network; traffic status data is used to represent real-time information on road conditions; traffic congestion refers to a state in which road traffic efficiency is significantly reduced; traffic control measures refer to traffic regulation measures taken to improve road conditions.

[0057] This step is performed during the continuous operation of the traffic monitoring system to achieve intelligent control of traffic congestion. In some embodiments, the system continuously collects traffic status data such as vehicle flow and speed through sensors and monitoring equipment distributed throughout the road network. When the system detects that the traffic efficiency of certain sections is lower than the threshold, it determines that traffic congestion has occurred, and then takes corresponding control measures according to the degree and scope of congestion, such as adjusting the timing of traffic lights, restricting vehicle traffic, optimizing traffic flow guidance, etc., to alleviate traffic congestion.

[0058] See also Figure 4 , Figure 4 This is a specific flow chart of step S103 in the embodiment of the present application; In some embodiments, step S103 specifically includes: S1031, obtaining traffic status data in the road network, the traffic status data including standard travel time and actual travel time; Among them, the road network refers to the network structure of urban roads; traffic status data refers to various indicators reflecting road traffic conditions; standard travel time is used to indicate the time required to pass a certain section of road under normal traffic conditions; actual travel time indicates the actual time it takes for a vehicle to pass through the section of road under current road conditions.

[0059] S1032, calculating the ratio of the actual travel time of vehicles on the road to the standard travel time; In some embodiments, the system divides the actual travel time of each road section by its corresponding standard travel time to obtain a time ratio reflecting the degree of congestion. The closer the ratio is to 1, the smoother the road section is, and the larger the ratio is, the more serious the congestion is.

[0060] S1033, according to the preset circle road grade, the comparison value is calculated as a weighted average to obtain a traffic congestion index; Among them, the circle road grade represents the importance of the road in the road network.

[0061] In some embodiments, the system divides roads into different levels and assigns corresponding weights based on factors such as road functional positioning, traffic capacity, and service scope. Trunk roads have higher weights, while secondary roads and branch roads have relatively lower weights. The time ratio of each road section is multiplied by the corresponding weight and then averaged to obtain a congestion index that reflects the overall road network status.

[0062] S1034, determining a road whose traffic congestion index is greater than a preset congestion threshold as a congested road; S1035. Increase the green light duration of the congested road, reduce the green light duration of the associated roads, and generate a new signal light timing plan; wherein the associated roads are used to represent other roads connected to the congested road.

[0063] In some embodiments, the system dynamically adjusts the signal light timing plan according to the congestion situation. By appropriately extending the green light time of congested roads, the traffic capacity is improved; at the same time, the green light time of related roads is shortened accordingly to avoid too much traffic flowing into the congested area. The adjustment of the timing plan needs to comprehensively consider multiple parameters such as cycle length, phase difference, green-to-signal ratio, etc.

[0064] S1036. Send a new traffic light timing plan to the signal controller of the corresponding intersection to adjust the traffic capacity of the congested road and related roads.

[0065] In some embodiments, the system sends the optimized timing plan to the signal controllers at each intersection through the communication network. After receiving the instruction, the controller immediately executes the new timing plan and adjusts the green light duration of the signal light, thereby changing the traffic capacity in each direction and achieving a reasonable distribution of traffic flow.

[0066] It can be seen that by calculating the ratio of actual travel time to standard travel time and weighting it by considering the road grade, an accurate congestion index can be obtained. When congestion occurs, by adjusting the signal light timing plan and reasonably allocating the traffic capacity, it can not only ensure the relief of congested sections, but also avoid the chain reaction of related roads.

[0067] S1037, obtaining traffic status data after adjustment of the congested road; S1038. Calculate a new traffic congestion index according to the adjusted traffic status data; S1039: When the new traffic congestion index is not greater than the preset congestion threshold, the original traffic light timing plan is restored.

[0068] It can be seen that after implementing control measures, the system continuously monitors the traffic status and calculates a new congestion index. When the congestion is alleviated, the original plan is restored in time, avoiding unnecessary impact of excessive control on the overall traffic.

[0069] S104, receiving parking space status data and a parking reservation request of the current vehicle, planning an optimal parking lot and a navigation route thereof according to the parking space status data and the parking reservation request, and sending the optimal parking lot and the navigation route to the current vehicle.

[0070] Among them, the parking space status data indicates the occupancy status of each parking space in the parking lot; the parking reservation request is used to indicate the parking demand information of the vehicle, including the vehicle location and the expected parking period; the optimal parking lot refers to the parking lot with the highest comprehensive score; the navigation route indicates the best driving path from the current location to the target parking lot; the current vehicle refers to the target vehicle that issued the parking reservation request.

[0071] This step is triggered when the vehicle initiates a parking request, and is used to implement intelligent parking lot recommendation and guidance. In some embodiments, when the system receives a parking reservation request from a vehicle, it first obtains real-time parking space status data of surrounding parking lots, including information such as the number of remaining parking spaces, parking space types, and charging standards. The system then calculates the comprehensive score of each candidate parking lot based on factors such as parking lot capacity, current road conditions, and distance. The parking lot with the highest score is selected as the optimal parking lot, and the system then plans an optimal navigation route that takes into account real-time road conditions, and sends the parking lot information and navigation route to the current vehicle to guide it to park.

[0072] See also Figure 5 , Figure 5 This is a specific flow chart of step S104 in the embodiment of the present application; In some embodiments, step S104 specifically includes: S1041. Generate parking space status data according to parking space occupancy information sent by the parking lot; Among them, parking space occupancy information refers to data reflecting the use status of parking spaces; parking space status data is used to indicate the real-time available parking spaces in the parking lot. In some embodiments, the system receives parking space use data uploaded by each parking lot in real time, including total number of parking spaces, number of occupied parking spaces, number of remaining parking spaces, etc. The system processes and integrates these raw data to generate standardized parking space status data for subsequent parking guidance decisions.

[0073] S1042, receiving a parking reservation request sent by a user terminal, where the parking reservation request includes current location information and destination information of the vehicle; In some embodiments, the system receives parking reservation information sent by the user through a mobile application. The request includes the real-time location coordinates of the vehicle obtained through GPS positioning, as well as the destination location information manually entered by the user or determined by selecting a point on the map, which provides basic data for subsequent parking lot recommendations.

[0074] S1043. Obtain traffic impact factors of surrounding parking lots, where the traffic impact factors include parking lot capacity, surrounding road capacity, and distance to the destination; Among them, surrounding parking lots refer to parking facilities near the current location of the vehicle; traffic impact factors refer to key parameters that affect parking choices; parking lot capacity is used to indicate the total number of parking spaces that can be accommodated; traffic capacity refers to the traffic flow on the road; and distance to destination refers to the spatial distance from the parking lot to the destination.

[0075] In some embodiments, the system obtains data on various influencing factors of parking lots within a preset range. The parking lot capacity reflects the scale and service capacity of the parking facilities, the surrounding road traffic capacity reflects the convenience of entering and exiting the parking lot, and the distance to the destination is related to the user's walking comfort. These factors together determine the practicality of the parking lot.

[0076] S1044. Calculate the suitability scores of surrounding parking lots based on parking space status data and traffic impact factors; Among them, the suitability score is used to represent the comprehensive evaluation score of the parking lot.

[0077] In some embodiments, the system uses parking space status data and traffic impact factors as evaluation indicators and applies a multi-factor evaluation model to calculate the suitability score of each parking lot.

[0078] In some embodiments, step S1044 specifically includes: In the formula, C f is the parking space status data, C t is the parking lot capacity, V r is the average real-time vehicle speed of the surrounding roads in the surrounding road capacity, Vm is the maximum speed limit of the surrounding roads in the surrounding road capacity, D is the distance to the destination, and D max is the preset maximum acceptable distance, and w1, w2, and w3 are the preset weights.

[0079] It can be seen that by introducing The system uses the term "car capacity" to process parking lot capacity, so that large-capacity parking lots can obtain reasonable score improvements, but the marginal effect decreases with the increase of capacity, avoiding excessive preference for super-large parking lots; the system uses the square relationship between the real-time vehicle speed and the speed limit ratio to evaluate road capacity, so that the score will decrease rapidly when the road is congested, and increase accordingly when the road is unobstructed, so that the system is more inclined to choose parking lots in areas with smooth traffic; through the quadratic term design of distance influence, the negative impact of distance on the score accelerates with the increase of distance, avoiding the system recommending parking lots that are too far away. This scoring mechanism makes the parking lot selection more in line with actual usage needs.

[0080] S1045, determining the parking lot with the highest suitability score as the optimal parking lot; In some embodiments, the system sorts and compares the suitability scores of all candidate parking lots, and selects the parking lot with the highest score as the optimal recommendation. This selection method based on quantitative scores ensures the objectivity and scientificity of the recommendation results, and can meet the user's parking needs to the greatest extent.

[0081] S1046, generating a navigation route from the current position of the vehicle to the optimal parking lot; In some embodiments, the system uses a path planning algorithm based on real-time road network data to calculate the best driving route from the vehicle's current location to the optimal parking lot. The planning process takes into account multiple factors such as road distance, estimated time, road conditions, etc. to provide users with the best driving suggestions.

[0082] S1047. Send the optimal parking lot and navigation route to the current vehicle.

[0083] It can be seen that the system can comprehensively evaluate the suitability of parking lots. The real-time parking resource status can be grasped through parking space occupancy information, and the scale effect can be reflected in combination with parking lot capacity; the convenience of entering and exiting the parking lot can be evaluated through the traffic capacity of surrounding roads; and the convenience of walking can be reflected through the distance to the destination. This multi-dimensional evaluation method ensures that the selection of the optimal parking lot is more reasonable, and can take into account both parking convenience and traffic diversion effects.

[0084] It can be seen that this application realizes the unified management of public transportation, online car-hailing, traffic control and parking resources. Among them, by collecting real-time data of various public transportation tools and generating docking plans, the allocation of transportation capacity is more accurate; by planning the best docking routes for online car-hailing, the empty mileage is reduced; by real-time monitoring of the road network status and implementing control measures, traffic congestion is promptly alleviated; by coordinating parking resources and providing navigation, vehicles are prevented from blindly searching for parking spaces. This integrated management method solves the problem of the inability to coordinate various types of transportation resources under the decentralized management model in related technologies, and improves the overall traffic operation efficiency.

[0085] The following introduces an exemplary traffic integration optimization system 600 provided in an embodiment of the present application. Figure 6 It is a schematic diagram of an exemplary hardware structure of the traffic integration optimization system 600 provided in an embodiment of the present application.

[0086] In some embodiments, the traffic integration optimization system 600 is a computer device or the traffic integration optimization system 600 includes a computer device. The computer device includes a processor, a memory and a network interface connected by a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0087] Those skilled in the art will understand that Figure 6 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0088] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0089] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0090] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from a website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) mode to another website site, computer, server or data center. The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media integration. The available medium can be a magnetic medium, (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0091] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A traffic integration optimization method, characterized in that: include: Collecting the location information and passenger data of each public transportation vehicle, generating a docking plan data packet according to the location information and the passenger data, wherein the docking plan data packet includes the arrival time and the number of passengers, and sending the docking plan data packet to each public transportation vehicle, so that each public transportation vehicle arrives at the corresponding station according to the arrival time in the docking plan data packet to pick up the passengers with the number of passengers; receiving a reservation data packet sent by a user terminal, determining an optimal connecting route according to the reservation data packet, generating a navigation data packet containing the optimal connecting route, and sending the navigation data packet to a target vehicle so that the target vehicle picks up the user according to the navigation data packet; Acquire traffic status data in the road network, and when the traffic status data indicates traffic congestion, implement traffic control measures; receive parking space status data and a parking reservation request of the current vehicle, plan an optimal parking lot and a navigation route thereof according to the parking space status data and the parking reservation request, and send the optimal parking lot and the navigation route to the current vehicle.

2. The method according to claim 1, characterized in that The step of receiving parking space status data and parking reservation request and planning the optimal parking lot and navigation route for the user specifically includes: Generate the parking space status data according to the parking space occupancy information sent by the parking lot; Receiving the parking reservation request sent by the user terminal, wherein the parking reservation request includes the vehicle's current location information and destination information; Obtaining traffic impact factors of surrounding parking lots, wherein the traffic impact factors include parking lot capacity, surrounding road capacity, and distance to the destination; Calculate the suitability scores of surrounding parking lots according to the parking space status data and the traffic impact factor; Determine the parking lot with the highest suitability score as the optimal parking lot; generating the navigation route from the current position of the vehicle to the optimal parking lot; The optimal parking lot and the navigation route are sent to the current vehicle.

3. The method according to claim 2, characterized in that The step of calculating the suitability score of surrounding parking lots according to the parking space status data and the traffic impact factor specifically includes: In the formula, C f is the parking space status data, C t is the parking lot capacity, V r is the average real-time vehicle speed of the surrounding roads in the surrounding road capacity, V m is the maximum speed limit of the surrounding roads in the surrounding road capacity, D is the distance to the destination, and D max is the preset maximum acceptable distance, and w1, w2, and w3 are the preset weights.

4. The method according to claim 1, characterized in that: The step of generating a connection plan data packet according to the location information and the passenger data specifically includes: Calculate the current speed and remaining mileage of each public transportation vehicle according to the location information and the preset route information; Calculate the arrival time of each public transportation vehicle at each station along the route based on the current travel speed, the remaining mileage and the historical travel time data; Deducting the passenger data from the total number of seats to obtain the remaining number of seats for each public transportation vehicle; The number of waiting passengers at each station is predicted based on the historical passenger flow data of each station, and the number of waiting passengers is allocated based on the remaining number of seats: When the number of waiting passengers is less than or equal to the number of remaining seats, the number of waiting passengers is used as the number of passengers to be carried; When the number of waiting passengers is greater than the number of remaining seats, the remaining number of seats is used as the number of passengers, and the excess number of waiting passengers is allocated to the public transportation vehicles that arrive at the station later; Generate the connection plan data packet including the arrival time and the number of passengers.

5. The method according to claim 1, characterized in that The step of receiving a reservation data packet sent by a user terminal, determining an optimal connecting route according to the reservation data packet, and generating a navigation data packet including the optimal connecting route specifically includes: receiving a reservation data packet including a user location, a destination location and an expected travel time sent by the user terminal; Obtain vehicle location information, passenger data, and service area data; According to the matching relationship between the user location and the service area data, the vehicle with zero passenger data is selected to obtain a candidate target vehicle; Calculating the total docking time of the candidate target vehicle according to the location information, wherein the total docking time is the sum of the estimated travel time of the candidate target vehicle to the user location and the estimated travel time from the user location to the destination location; The candidate target vehicles are sorted according to the total connection time, and the vehicle with the shortest total connection time is selected as the target vehicle; Based on real-time traffic information, an optimal connecting route is planned for the target vehicle, wherein the optimal connecting route includes a pick-up route from the current position of the target vehicle to the user's position, and a drop-off route from the user's position to the destination position; the navigation data packet including the optimal connecting route is generated, and the navigation data packet is sent to the target vehicle.

6. The method according to claim 1, characterized in that The step of acquiring traffic status data in the road network and executing traffic control measures when the traffic status data indicates that traffic congestion occurs specifically includes: Acquire the traffic status data in the road network, wherein the traffic status data includes standard travel time and actual travel time; Calculating the ratio of the actual travel time of vehicles on the road to the standard travel time; According to the preset circle road grade, a weighted average value of the ratio is calculated to obtain a traffic congestion index; a road whose traffic congestion index is greater than a preset congestion threshold is determined as a congested road; Increase the green light duration of the congested road, reduce the green light duration of the associated roads, and generate a new signal light timing plan; The new traffic light timing plan is sent to the signal controller of the corresponding intersection to adjust the traffic capacity of the congested road and the associated roads.

7. The method according to claim 6, characterized in that After the step of sending the new signal light timing scheme to the signal controller of the corresponding intersection to adjust the traffic capacity of the congested road and the associated road, the method further includes: obtaining the traffic status data of the congested road after adjustment; Calculating a new traffic congestion index based on the adjusted traffic status data; When the new traffic congestion index is not greater than the preset congestion threshold, the original traffic light timing plan is restored.

8. A traffic integration optimization system, characterized in that: The traffic integration optimization system includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the traffic integration optimization system to execute the method described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a traffic integration optimization system, the traffic integration optimization system is enabled to execute the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the traffic integration optimization system, the traffic integration optimization system is caused to execute the method as described in any one of claims 1-7.

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