A method and system for managing frequently congested urban road sections based on reservation-based travel

Abstract

This invention discloses a method and system for managing frequently congested urban road sections based on reservation-based travel, belonging to the field of urban traffic management and control. Based on traffic network equilibrium theory, it considers the heterogeneity of user time value, the generalized cost of merging travel time and expenses, and the impact of multiple modes of transportation transfer. A multi-user, multi-criteria, and multi-modal traffic mode classification and traffic allocation combination model is established. This model is further extended to a variational inequality model where the road segment impedance function is inseparable, and the adaptive averaging method is used to solve the model. For travelers, reservations allow them to schedule their travel time in advance, scientifically choose travel routes, and rationally select travel modes, thereby minimizing congestion losses. For managers, the reservation-based travel model can promote demand-centric urban transportation services, with traffic operation organization allocating resources on demand, regulating demand with resource constraints, alleviating congestion, and achieving maximum intensive use of resources.

Description

Technical Field

[0001] This invention relates to the field of urban traffic management and control, specifically a method and system for managing frequently congested urban road sections based on reservation-based travel. Background Technology

[0002] Effective urban traffic management is a strategic requirement for solving urban traffic problems and a concrete means to improve national and urban governance capabilities.

[0003] The rapid increase in motor vehicle ownership and travel demand, coupled with the slow expansion of urban road networks, exacerbates the supply-demand imbalance in urban road traffic systems. Highly concentrated commuting in both time and space is the primary challenge facing traffic management in large cities, leading to congestion during peak hours and resource underutilization during off-peak hours. Therefore, effective traffic management strategies should simultaneously focus on the rationality of traffic supply and the scientific control of demand to achieve a dynamic balance between supply and demand. Given that the urban road network structure is difficult to change in the short term, the focus of traffic congestion management is on vehicle right-of-way management. By adjusting the traffic supply-demand structure, balancing the temporal and spatial distribution of traffic flow in the regional road network, congestion can be prevented from forming or spreading. The essence of urban traffic congestion queuing is that travelers try to secure time and space resources by queuing to obtain passage order. In most cases, queuing (congestion) not only fails to increase system capacity but also reduces system efficiency due to mutual interference, further amplifying the supply-demand imbalance. Reservations are a tool for orderly management using information technology. In situations of resource scarcity and severe supply-demand imbalance, reservations can balance the system's supply and demand relationship, avoid unnecessary resource waste, and improve service efficiency. Therefore, drawing inspiration from scenic spot reservation mechanisms, introducing a reservation-based travel model into urban traffic management encourages travelers to plan their trips in advance, choose routes scientifically, and select modes of transportation rationally. This allows for targeted control of vehicle usage, preventing oversaturation of the main road network during peak hours and the spread of congestion. Furthermore, it regulates the balance of traffic flow across the road network, improving overall travel efficiency. While current technology cannot support reservation-based travel across the entire urban traffic network, a segment-based reservation model only serves the traffic organization of specific congested road sections and surrounding areas. It does not require precise timetables down to the second for each individual traveler; simply scheduling travel times allows for system-level adjustments to mitigate the impact of individual randomness, achieving system optimization.

[0004] In daily life, the advantages of booking in advance instead of queuing offline, avoiding inefficiency and disorder, have been validated in various scenarios such as hospital reservations, restaurant reservations, and parking reservations. The successful application of reservation-based travel projects for transportation scenarios, such as bus reservations, subway reservations, and reservations for access to scenic spots, demonstrates that existing technologies are sufficient to support a certain scale of reservation-based travel. However, compared to the aforementioned reservation practices, urban road traffic systems are more random and open, with stronger rigidity in commuting and school travel demands within cities, and are easily affected by unforeseen factors, making it difficult for individuals to control their travel time. Furthermore, existing research on reservation-based travel models suffers from homogeneity in travel choices among various user groups, failing to consider the multidimensional decision variables of individual travel and the limitations of multimodal transportation synergy in cities. Heterogeneous travelers exhibit varying sensitivities to travel time and cost; ignoring traveler heterogeneity can affect the effectiveness of strategy evaluation models. Reservation-based travel models can effectively balance traffic flow on road networks while guiding some users to choose public transportation. Given the differences in service levels among different transportation modes under various road network congestion conditions, users' travel decisions are considered as an equilibrium outcome of a game, an equilibrium that considers the demand for multimodal transportation and the interactions between different modes. Therefore, how to accurately evaluate the actual effectiveness of the reservation travel mode in a multimodal transportation system has become a key issue.

[0005] Based on this, the present invention aims to provide a method and system for managing frequently congested urban road sections based on reservation-based travel, so as to alleviate congestion and achieve maximum and intensive use of resources. Summary of the Invention

[0006] To address the shortcomings of existing technologies, this invention proposes a method and system for managing frequently congested urban road sections based on reservation-based travel. Based on traffic network equilibrium theory, and considering the heterogeneity of user time value, the generalized cost of merging travel time and expenses, and the impact of multiple modes of transportation transfer, a multi-user, multi-criteria, multi-modal traffic mode classification and traffic assignment combination (MDTSA) model is established to obtain the overall travel mode and route selection results of residents on the road network. For travelers, reservations allow for advance scheduling of individual travel times, scientific route selection, and rational choice of travel modes, avoiding blind travel and ineffective waiting, thereby minimizing congestion losses. For administrators, the reservation-based travel model can promote demand-centric urban transportation services, enabling traffic operation organization to allocate resources as needed, regulating demand with resource constraints, alleviating congestion, and achieving maximum intensive utilization of resources.

[0007] To achieve the above objectives, the present invention provides the following technical solution:

[0008] A method for managing frequently congested urban road sections based on reservation-based travel includes the following steps:

[0009] (1) Clarify the implementation mechanism of the reservation travel strategy in frequently congested road sections, and determine the generalized travel cost of different modes of transportation based on the random user equilibrium allocation model of multiple vehicle types, taking into account the travel time and cost of heterogeneous users.

[0010] (2) Based on the traffic network equilibrium theory, considering the heterogeneity of travelers' time value, the generalized cost of merging travel time and travel expenses, and the impact of multiple modes of transportation transfer, a multi-user, multi-criteria, and multi-mode traffic mode division and traffic allocation combination model is established. This model is further extended to a variational inequality model where the road segment impedance function is inseparable, and the adaptive averaging method is used to solve the model to determine the residents' travel mode selection and route selection results.

[0011] In this invention, the reservation travel strategy is as follows:

[0012] Determine the capacity threshold for each reservation time slot on frequently congested road sections. During the implementation of the reservation travel strategy, motor vehicles entering the reserved road sections must make a reservation in advance. Travelers who intend to make reservations will make reservations in advance on the corresponding platform before traveling. Only after a successful reservation can they drive on the reserved road. For users who participate in the reservation but do not obtain the right of way, provide them with alternative travel routes and encourage them to choose public transportation, and provide them with corresponding discounts.

[0013] In this invention, the modes of transportation include four single modes of travel: non-booked cars, booked cars, buses, and subways, as well as two combined modes of travel: car and bus transfers, and car and subway transfers.

[0014] In this invention, the method for calculating the generalized travel cost of a car on non-reserved road sections is as follows:

[0015] When a user drives a car on a road without prior reservation, the generalized cost of their trip includes travel time, fuel costs, and parking fees, calculated as follows:

[0016] (1)

[0017] (2)

[0018] in, For User Class i The generalized travel costs for private cars on non-reservation routes. ，I Number of travelers categorized; For road section a Traffic flow is The travel time of a car under certain circumstances; For road section a Traffic flow; For road section aFree time for driving in a car , A This is a collection of all road segments in the network; , Each is a road segment a Traffic flow of cars and buses; For road section a Traffic capacity for cars; Parking fees for cars when using a combination of car and bus transfers or car and subway transfers; e Fuel cost per unit mileage; For road section a Length; For User Class i The value of time; , and These are the road resistance function parameters for a car.

[0019] In this invention, the method for calculating the generalized travel cost of a car on non-reserved road sections is as follows:

[0020] Since the reservation-based travel mode itself does not require additional travel costs, the general travel cost of reserved cars is basically the same as that of non-reserved cars; considering that there is a limit to the total number of reservations for reserved road segments, the traffic flow of cars on a road segment cannot exceed the total number of reservations for that road segment.

[0021] (3)

[0022] (4)

[0023] in, It is the penalty coefficient, and ; The optimal proportion of total reservations for a given road segment; For User Class i The generalized travel cost of private cars on reserved routes; For reserved road sections a Traffic flow is The travel time of a car under certain circumstances; These are the road resistance function parameters for cars on the reserved road segment; K It is a set of paths.

[0024] In this invention, the generalized travel cost calculation method for bus travel is as follows:

[0025] When a bus travels on a route, its generalized cost includes travel time, bus waiting time, the congestion effect caused by passengers inside the bus, and the fare. The calculation formula is as follows:

[0026] (5)

[0027] (6)

[0028] in, For User Class i The generalized cost of public transportation; For road section a Free time to ride the bus; For road section a The capacity for buses to pass through; , and These are the road resistance function parameters for the bus; For bus departure intervals; This refers to the waiting time for buses, including waiting time for transfers. For bus fares; This is the cost coefficient for vehicle congestion. A congestion coefficient related to the number of passengers; This is the sum of the number of passengers waiting to board at the station and the number of passengers already on the train. This indicates that the ticket price is converted into time, regardless of the travel route; This refers to the passenger capacity of a single bus.

[0029] In this invention, the generalized travel cost calculation method for subway travel is as follows:

[0030] The generalized cost of subway travel includes travel time, waiting time, and fare. Since subways operate on dedicated tracks, their efficiency is not affected by traffic flow from other modes of transportation; therefore, the BPR function is used to calculate travel time. The formula for calculating the generalized travel cost is shown below:

[0031] (7)

[0032] (8)

[0033] in, For User Class i The generalized cost of subway travel; For road section a Free time to travel on the subway; For rail transit fares; The subway congestion coefficient, A congestion coefficient related to the number of passengers; For passenger flow; For subway train intervals; Limit the number of passengers per subway train; This indicates that fares are converted to time, regardless of the travel route; subway waiting time. .

[0034] In this invention, during the calculation of the generalized travel cost of combined transfers, the transfer nodes are determined, the generalized travel costs before and after the transfers are calculated separately, and then summed.

[0035] In this invention, a multi-user, multi-criteria, and multi-mode traffic mode classification and traffic assignment combination model is used:

[0036] Assume OD pairs ( r,s )between i The number of people traveling in this category is And choose the mode of transportation m The number of travelers was , where path selection k The number of people is The traveler's route selection behavior and mode of transportation selection behavior are calculated using the following formula:

[0037] ① Path selection behavior; i Type of traveler at OD ( r,s The mode of transportation between them is m path k The probability of selection is:

[0038] (9)

[0039] in, for i Type of traveler at OD ( r,s The mode of transportation between them is m path k Choose the probability; For OD pairs ( r,s The mode of transportation between them is m path k Generalized costs; Choose the discrete coefficients for the path;

[0040] ② Transportation mode selection behavior: i Type of traveler at OD ( r,s The probability of choosing a mode of transportation between () is:

[0041] (10)

[0042] (11)

[0043] in, for i Type of traveler at OD ( r,s The probability of choosing a mode of transportation between ( ) For OD pairs ( r,s )between i Travelers using transportation m The path with the expected minimum cost, Choose the coefficient of variation for each mode of transportation;

[0044] Therefore, the traffic mode classification and traffic assignment models in the four-stage model are represented by the following formulas:

[0045] (12)

[0046] (13)

[0047] The objective function and constraints for constructing the MDTSA model loaded from Nested Logit are shown below:

[0048] (14)

[0049] (15a)

[0050] (15b)

[0051]

[0052] Equation (14) is the objective function of the multi-user, multi-criteria, and multi-mode combination model. For transportation m On the road section a The unit travel cost, For User Class i The value of time This refers to the sum of the discounted travel times for all passengers. The mode of transportation is m User class i On the road section a Traffic volume; For road section a above transportation m The required time; Equation (15a) is the traffic mode classification constraint; Equation (15b) is the traffic assignment constraint; Equation (15c) is the travel demand constraint for the booked users. For decision variables, representing when user class i And car travelers who obtain access rights through reservations are subject to OD (Operational Development) restrictions. r,s Path between k The value is 1 if the road segment includes a reservation-based travel management system, and 0 otherwise; Equation (15d) constrains the travel demand of non-reservation users. For decision variables, representing when user class iAnd private car riders who have not obtained the right of way for the reserved road section at OD r,s Path between k The value is 0 when the road segment includes a segment implementing reservation-based travel management, and 1 otherwise; Equation (15e) represents the traffic flow constraint for the road segment. For decision variables, representing when user class i Use of transportation m travel route k Passing section a The value is 1 if it is true, and 0 otherwise. The optimal total reservation ratio for the road segment; Equation (15f) is a descriptive constraint; Equation (15g) is the total reservation constraint for the road segment. The set of road segments for implementing the reservation-based travel mode; Equation (15h) represents a non-negative constraint;

[0053] In actual traffic systems, the road segment impedance function is inseparable; therefore, using variational inequalities, formula (14) can be rewritten as follows:

[0054] (16).

[0055] A travel reservation system, comprising a computing system, a reservation system, and a management system;

[0056] The calculation system analyzes the road network congestion segments and time periods based on historical traffic patterns, considers the spatiotemporal supply and demand balance of each road segment at different times, determines the capacity threshold for each reservation time period, and outputs travel plans for users.

[0057] The reservation system displays a travel timetable to travelers, showing the remaining capacity of the road segment requiring reservation within a specific time period. Travelers make reservations through the system, and once a reservation is successful, the system reserves the traveler's time slot for using the reserved road. For users who participate in the reservation but do not obtain the right of way, the system provides them with alternative travel routes and encourages them to choose public transportation, offering them corresponding discounts. Ultimately, this group will have three travel options: public transportation, taking a detour via the alternative routes, and illegally passing through the reserved road segment.

[0058] The management system transmits road traffic control information by setting up corresponding traffic signs and markings in the upstream area of ​​the reserved road segment; it uses vehicle license plate recognition technology to verify the fulfillment of the reserved vehicle's reservation and implements corresponding reward and punishment systems.

[0059] Compared with the prior art, the beneficial effects of the present invention are:

[0060] 1. This invention proposes a method for managing frequently congested urban road sections based on reservation-based travel. Compared with traditional traffic demand management methods, the reservation-based travel model replaces mandatory measures with more flexible management, refined adjustment, and full-chain travel guidance. It uses intelligent means to meet increasingly diverse travel needs without having a substantial impact on travel.

[0061] 2. This invention proposes a travel decision-making model that considers heterogeneous users within an urban multimodal transportation framework and multidimensional decision variables. It establishes a multi-user, multi-criteria, multi-modal traffic mode classification and traffic assignment combination (MDTSA) model, and further extends it to a variational inequality model where the road segment impedance function is inseparable. For travelers, reservations allow for advance scheduling of individual travel times, enabling scientific route selection and rational choice of travel modes, avoiding blind travel and ineffective waiting, thereby minimizing congestion losses. For administrators, the reservation-based travel model promotes demand-centric urban transportation services, allowing traffic operations to be configured on demand, adjusting demand with resource constraints, alleviating congestion, and achieving maximum intensive resource utilization. Attached Figure Description

[0062] Figure 1 This is a flowchart of the method of the present invention.

[0063] Figure 2 This is a schematic diagram of the reservation travel implementation mechanism of the present invention.

[0064] Figure 3 This is a schematic diagram illustrating the generalized cost calculation for each travel route in this invention.

[0065] Figure 4 This is a road network structure diagram of the research area of ​​this invention.

[0066] Figure 5 This is a public transportation network diagram for this invention.

[0067] Figure 6 This is a schematic diagram illustrating the changes in user travel patterns before and after the implementation of the reservation-based travel system of this invention. Detailed Implementation

[0068] The technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments.

[0069] like Figure 1-6 As shown, (a) establish a reservation-based travel system for traffic congestion management (such as...). Figure 2 As shown in the figure, it includes a computing system, a reservation system, and a management system.

[0070] The computing system is responsible for developing reasonable travel plans. Based on historical traffic patterns, the system analyzes congested road segments and times, considers the spatiotemporal supply and demand balance of each road segment at different times, determines the capacity threshold for each reservation time period, and outputs scientific and reasonable travel plans for users.

[0071] The reservation system manages reservation requests. It displays a travel timetable to travelers, showing the remaining capacity of the reserved road segment within a specific time period, allowing travelers to plan their travel time and route accordingly. Travelers make reservations before their trip using smartphones and the internet. Once a reservation is successful, the system reserves the traveler's time slot for using the reserved road. For users who participate in the reservation but do not receive passage rights, the system provides alternative travel routes and encourages them to choose public transportation, offering corresponding discounts. Ultimately, this group will have three travel options: public transportation, taking alternative routes, and illegally passing through the reserved road segment.

[0072] The management system is responsible for maintaining order in the reservation process and coordinating traffic services. It transmits road traffic control information by setting up appropriate traffic signs and markings in the upstream area of ​​the reserved route. Vehicle license plate recognition technology is used to verify the fulfillment of reservations and to implement corresponding reward and penalty systems.

[0073] (II) A method for managing frequently congested urban road sections based on reservation-based travel, the flowchart of which is as follows: Figure 1 As shown, the specific steps include:

[0074] Step 1: Based on the implementation steps and mechanisms of the reservation travel strategy (e.g., Figure 2 As shown in the diagram, during the implementation of the reservation-based travel strategy, motor vehicles entering reserved road segments must make reservations in advance. Travelers with reservation preferences will make reservations in advance on the corresponding platform before their trip, and can only travel on the reserved road after a successful reservation. If the reserved road segment has reached its total reservation limit, travelers must choose an alternative route or take public transportation. In other words, reserved vehicles can travel on reserved road segments, while ordinary vehicles cannot. This invention first considers the travel time and cost of heterogeneous users, determining the generalized travel cost of different modes of transportation (including non-reserved cars, reserved cars, buses, and subways). During peak hours, traffic flow in the urban road network mainly consists of cars (regardless of whether they are reserved) and buses. When these vehicles travel on specific road segments, their travel time is affected by the interaction of mixed traffic flow. To describe this effect, this invention calculates the road segment impedance function corresponding to each mode of transportation based on a multi-vehicle type random user equilibrium allocation model and further determines the generalized travel cost of each mode of transportation:

[0075] (1) Generalized travel costs of cars on non-reserved road sections

[0076] When a user drives a car on a road without prior reservation, the generalized cost of their trip includes travel time, fuel costs, and parking fees, calculated as follows:

[0077] (1)

[0078] (2)

[0079] in, For User Class i The generalized travel costs for private cars on non-reservation routes. ，I Number of travelers categorized; For road section a Traffic flow is The travel time of a car under certain circumstances; For road section a Traffic flow; For road section a Free time for driving in a car (h). , A This is a collection of all road segments in the network; , Each is a road segment a Traffic volume of cars and buses (vehicles). For road section a Traffic capacity for cars (vehicles / hour); Parking fee (in yuan) for cars in P+R mode; e Fuel cost per unit distance (yuan / km); For road section a Length (km); For User Class i Time value (yuan / h); , and These are the road resistance function parameters for a car.

[0080] (2) Generalized travel costs of cars on reserved road segments

[0081] Since the reservation-based travel mode itself does not require additional travel costs, the general travel cost of reserved cars is basically the same as that of non-reserved cars. It is worth noting that, considering the total number of reservations for a given route segment, the traffic flow on that segment cannot exceed the total number of reservations.

[0082] (3)

[0083] (4)

[0084] in, It is the penalty coefficient, and ; The optimal proportion of total reservations for a given road segment; For User Class i The generalized travel cost of private cars on reserved routes; For reserved road sections a Traffic flow is The travel time of a car under certain circumstances; These are the road resistance function parameters for cars on the reserved road segment; K It is a set of paths.

[0085] (3) Generalized travel costs of public transportation

[0086] When a bus travels on a route, its generalized cost includes travel time, bus waiting time, the congestion effect caused by passengers inside the bus, and the fare. The calculation formula is as follows:

[0087] (5)

[0088] (6)

[0089] in, For User Class i The generalized cost of public transportation; For road section a Free time to travel on public transportation (h); For road section a Bus capacity (vehicles / hour); , and These are the road resistance function parameters for the bus; Let be the bus departure interval (min), assuming the bus departure intervals are consistent. That is, the frequency of buses per hour; The bus waiting time (h) includes the waiting time for transfers, and is assumed to be half the departure interval, i.e. ; The fare is in yuan. This is the cost coefficient for vehicle congestion. The congestion coefficients related to passenger numbers are set to 5 and 3 respectively; This is the sum of the number of passengers waiting to board at the station and the number of passengers already on the train. This indicates that the ticket price is converted into time, regardless of the travel route; The passenger capacity of a single bus is taken as 60 people per bus.

[0090] (4) The generalized travel cost of the subway

[0091] The generalized cost of subway travel includes travel time, waiting time, and fare. Since subways operate on dedicated tracks, their efficiency is not affected by traffic flow from other modes of transportation; therefore, the BPR function is used to calculate travel time. The formula for calculating the generalized travel cost is shown below:

[0092] (7)

[0093] (8)

[0094] in, For User Class i The generalized cost of subway travel; For road section a Free time to travel on the subway (h); The fare for rail transit is (in yuan). The subway congestion coefficient, The congestion coefficients, which are related to the number of passengers, are set to 0.019 and 4.520, respectively. For passenger flow; The train interval (min) is the interval between subway trains. The passenger limit for each subway train is set at 600 people per train. This indicates that fares are converted to time, regardless of the travel route; subway waiting time. Similar to bus waiting time, take half of the departure interval, that is... .

[0095] (5) Generalized travel costs of combined transfers

[0096] This invention only considers transfers between cars and buses (C&B) and cars and subways (C&M), and does not consider transfers between two or more different modes of transportation. A path set generation algorithm based on the road segment penalty method is used to determine the shortest path for each mode of transportation. Figure 3 The network shown is used as an example to briefly outline the generalized cost calculation method for each travel path. Figure 3 The road network in the diagram contains 3 nodes and 5 travel modes. Node 1 is the origin-destination (OD) point, node 2 is a park-and-ride (P+R) transfer node, and node 3 is the destination-destination (OD) point. The travel modes are car, bus, subway, car-to-bus transfer, and car-to-subway transfer. Calculate the generalized cost of each arc using the following method:

[0097] (1) The generalized cost of the arc from the OD starting point to the road node is 0, and the generalized cost of the arc from the bus or subway node is the waiting time plus the ticket price.

[0098] (2) The generalized cost of the arc between road nodes is the travel time plus fuel cost.

[0099] (3) The generalized cost of the arc between buses and subways on the same route is travel time and the congestion effect inside the vehicle.

[0100] (4) The generalized cost of the arc from the road node to the bus or subway node at node 2 is the waiting time plus the parking transfer fee and the corresponding transportation fare.

[0101] (5) The generalized cost of the arc from node 3 to the endpoint of OD is 0.

[0102] Step 2: Based on the traffic network equilibrium theory, considering the heterogeneity of travelers' time value, the generalized cost of integrating travel time and travel expenses, and the impact of multiple modes of transportation transfer, establish a multi-user, multi-criteria, multi-mode traffic division and traffic assignment combination (MDTSA) model, and further extend it to a variational inequality model where the road segment impedance function is inseparable.

[0103] Assume OD pairs ( r,s )between i The number of people traveling in this category is And choose the mode of transportation m The number of travelers was , where path selection k The number of people is The traveler's route selection behavior and mode of transportation selection behavior can be calculated using the following formula:

[0104] ① Path selection behavior. i Type of traveler at OD ( r,s The mode of transportation between them is m path k The probability of selection is:

[0105] (9)

[0106] in, for i Type of traveler at OD ( r,s The mode of transportation between them is m path k Choose the probability; For OD pairs ( r,s The mode of transportation between them is m path k Generalized costs; Choose the discrete coefficients for the path.

[0107] ② Transportation mode selection behavior: i Type of traveler at OD ( r,s The probability of choosing a mode of transportation between () is:

[0108] (10)

[0109] (11)

[0110] in, for i Type of traveler at OD ( r,s The probability of choosing a mode of transportation between ( ) For OD pairs ( r,s )between i Travelers using transportation m The path with the expected minimum cost, Choose the coefficient of variation for each mode of transportation.

[0111] Therefore, the traffic mode division and traffic assignment models in the four-stage model can be expressed by the following formulas:

[0112] (12)

[0113] (13)

[0114] The objective function and constraints for constructing the MDTSA model loaded from Nested Logit are shown below:

[0115] (14)

[0116]

[0117] Equation (14) is the objective function of the multi-user, multi-criteria, and multi-mode combination model. For transportation m On the road section a The unit travel cost, For User Class i The value of time (yuan / h). This refers to the sum of the discounted travel times for all passengers. The mode of transportation is m User class i On the road section a Traffic volume; For road section a above transportation m The required time; Equation (15a) is the traffic mode classification constraint. Equation (15b) is the traffic assignment constraint. Equation (15c) is the travel demand constraint for the booked users. For decision variables, representing when user class i And car travelers who obtain access rights through reservations are subject to OD (Operational Development) restrictions. r,s Path between kThe value is 1 if the road segment includes a reservation-based travel management system, and 0 otherwise. Equation (15d) defines the travel demand constraints for non-reservation users. For decision variables, representing when user class i And private car riders who have not obtained the right of way for the reserved road section at OD r,s Path between k The value is 0 if the road segment includes a segment implementing reservation-based travel management, and 1 otherwise. Equation (15e) represents the traffic flow constraint for the road segment. For decision variables, representing when user class i Use of transportation m travel route k Passing section a It is 1 if it is true, otherwise it is 0. This represents the optimal total reservation ratio for the road segment. Equation (15f) is a descriptive constraint; Equation (15g) is the total reservation constraint for the road segment. This is the set of road segments for which a reservation-based travel mode is implemented. Equation (15h) represents a non-negative constraint.

[0118] In actual traffic systems, the road segment impedance function is inseparable; therefore, using variational inequalities, formula (14) can be rewritten as follows:

[0119] (16).

[0120] Step 3: Solve the MDTSA model using the Method of Successive Weighted Averages (MSWA). The algorithm's calculation process is shown below.

[0121] (1) Main flow of the solution algorithm:

[0122]

[0123] (2) Algorithm flow for solving the allocation subproblem:

[0124]

[0125] Step 4: Using the Sioux Falls network as the study area, and utilizing resident travel data based on the Sioux Falls network provided by the MATSim community as the basic data, the road network structure is as follows: Figure 4 As shown in Table 1, the effectiveness of the proposed MDTSA model was tested using travel data from the morning peak hours (07:00-08:00), and the improvement effect of the reservation travel mode on the road network traffic conditions was further quantified. Figure 6 As shown.

[0126] Table 1. Road network performance results before and after the implementation of the reservation-based travel mode.

[0127]

[0128] The above description is merely a preferred embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any equivalent substitutions or modifications made by those skilled in the art within the scope of the technology disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the scope of protection of the present invention.

Claims

1. A method for managing urban recurrent congestion road sections based on pre-booking travel, characterized in that, The method comprises the following steps: (1) The implementation mechanism of the pre-trip strategy on the frequently congested road section is clarified, the generalized travel cost of different traffic modes is determined based on the multi-vehicle random user equilibrium distribution model and the travel time and cost of heterogeneous users are considered; (2) Based on the traffic network equilibrium theory, the heterogeneous time value of the traveler, the generalized cost of the travel time and the travel cost, and the influence of the multi-traffic mode transfer are considered to establish a multi-user, multi-criterion and multi-mode traffic mode division and traffic distribution combination model, the model is extended to a variational inequality model with a non-separable road section impedance function, and the adaptive average method is used to solve the model to determine the travel mode selection and path selection results of the residents; Assume OD pairs ( r,s )between i The number of people traveling in this category is And choose the mode of transportation m The number of travelers was , where path selection k The number of people is ; The traffic mode division and traffic distribution model in the model are represented by the following formulas: （12） （13） is i the probability of a traveler of the class r,s ) to choose a mode of transportation; is i the probability of a traveler of the class r,s ) to choose a mode of transportation m from the set of paths k ; The objective function and the constraint condition of the MDTSA model based on the Nested Logit loading are as follows: （14） （15a） （15b） （15c） （15d） （15e） （15f） （15g） （15h） Equation (14) is the objective function of the multi-user, multi-criteria, and multi-mode combined model. For transportation m On the road section a The unit travel cost, For User Class i The value of time This refers to the sum of the discounted travel times for all passengers. The mode of transportation is m User class i On the road section a Traffic volume; For road section a above transportation m The time required; Choose the discrete coefficients for the path; The dispersion coefficients are selected for each mode of transportation; Equation (15a) represents the mode of transportation classification constraint; Equation (15b) represents the traffic assignment constraint; and Equation (15c) represents the travel demand constraint for users making reservations. For decision variables, representing when user class i And car travelers who obtain access rights through reservations are subject to OD (Operational Development) restrictions. r,s Path between k The value is 1 if the road segment includes a reservation-based travel management system, and 0 otherwise; Equation (15d) represents the travel demand constraint for non-reservation users. For decision variables, representing when user class i And private car riders who have not obtained the right of way for the reserved road section at OD r,s Path between k The value is 0 when the road segment includes a segment implementing reservation-based travel management, and 1 otherwise; Equation (15e) represents the traffic flow constraint for the road segment. For decision variables, representing when user class i Use of transportation m travel route k Passing section a The value is 1 if it is true, and 0 otherwise. The optimal total reservation ratio for the road segment; Equation (15f) is a descriptive constraint; Equation (15g) is a constraint on the total reservation volume for the road segment. For road section a Traffic flow The set of road segments for implementing the reservation-based travel mode; Equation (15h) represents a non-negative constraint; In the actual traffic system, the road section impedance function is non-separable, and the variational inequality is used to represent the formula (14) in the following form: （16）。 2. The method of claim 1, wherein the method further comprises: The pre-trip strategy: The capacity threshold of each pre-trip period of the frequently congested road section is determined, and the motor vehicle entering the pre-trip road section must be pre-tripped in advance during the implementation of the pre-trip strategy; The pre-trip strategy:

3. The method of claim 1, wherein the method further comprises: The pre-trip strategy:

4. The method of claim 3, wherein the method further comprises: The pre-trip strategy: The traffic mode includes four single travel modes of non-pre-trip car, pre-trip car, bus and subway, and two combined travel modes of car and bus transfer and car and subway transfer. （1） （2） wherein, is the generalized travel cost of a car of user class i on a non-reserved link, ，I is the number of traveler classes; is the travel time of a car on a link a with traffic volume ; is the free travel time of a car on a link a , , A is the set of all links in the network; , are the traffic volumes of cars and buses on a link a , respectively; is the capacity of a link a for cars; is the parking fee for a car in the two combined travel modes of car-bus transfer and car-metro transfer; e is the fuel cost per unit distance; is the length of a link a ; is the time value of a car of user class i ; , and are the road impedance function parameters of a car.

5. The method of claim 3, wherein the method further comprises: The generalized travel cost calculation method of the car on the non-pre-trip road section is as follows: When the non-pre-trip user drives the car on the road section, the generalized cost of the travel includes the travel time, fuel cost and parking cost, and the calculation formula is as follows: （3） （4） wherein, is a penalty coefficient, and ; is the total optimal reservation volume ratio of the link; is the generalized travel cost of the car in the reservation link for the user class i ; is the travel time of the car in the reservation link a under the traffic volume ; is the link impedance function parameter of the car in the reservation link.

6. The method of claim 3, wherein the method further comprises: The generalized travel cost calculation method of the car on the pre-trip road section is as follows: Since the pre-trip mode itself does not require additional travel cost, the generalized travel cost of the pre-trip car is basically the same as that of the non-pre-trip car; considering that the pre-trip road section has a total pre-trip limit, therefore, the car flow on the road section cannot exceed the total pre-trip amount of the road section; （5） （6） wherein, is the generalized travel cost of a bus for a user class i ; , is the flow of cars and buses on link a ; is the free-flow travel time of a bus on link a ; is the capacity of a bus on link a ; , and are the bus link impedance function parameters; is the headway of a bus; is the waiting time of a bus, including the waiting time of transfer mode; is the bus fare; is the in-vehicle crowding cost coefficient, is the passenger number related crowding coefficient; is the sum of the number of passengers waiting to board at a stop and the number of passengers on the bus; denotes the conversion of fare to time, independent of the travel path; is the passenger-carrying capacity of a single bus.

7. The method of claim 3, wherein the method further comprises: The generalized travel cost calculation method of the bus is as follows: When the bus travels on the road section, the generalized cost of the travel includes the travel time, bus waiting time, congestion effect caused by passengers in the bus and ticket price, and the calculation formula is as follows: （7） （8） wherein, is the generalized travel cost of the subway for the user class i ; is the free travel time on the subway for the link a ; is the fare of the subway; is the congestion coefficient of the subway, is the congestion coefficient related to the number of passengers; is the passenger flow; is the headway of the subway; is the passenger limit of each subway; denotes the conversion of the fare into time, independent of the travel path; t metro is the subway waiting time.

8. The method of claim 3, wherein the method further comprises: The generalized travel cost calculation method of the subway is as follows:

9. The method of claim 1, wherein, When the subway is traveled, the generalized cost includes the travel time, waiting time and ticket price; since the subway has a special running track, the travel efficiency will not be affected by the flow of other modes, therefore, the BPR function is used to calculate the travel time; the calculation formula of the generalized travel cost is as follows: ① route choice behavior; i The path selection probability of a class of travelers between OD pair r,s with traffic mode m is: k ​ （9） wherein, is the generalized cost of a path between OD pairs (i, j) for a mode of transportation r,s ) between OD pairs (i, j) for a mode of transportation m is the generalized cost of a path between OD pairs (i, j) for a mode of transportation k is the generalized cost ②Traffic mode choice behavior: i The traffic mode choice probability of a trip maker between OD pairs (i, j) is: r,s Pij=exp(βTij)∑k∈Sexp(βTik) （10） （11） wherein, OD pairs (ODi, ODj) between r,s i The path expectation of the class of travelers using the transportation mode m has the minimum cost.​ 10. A trip reservation system implementing the method of any one of claims 1-9, characterized by In the generalized travel cost calculation process of the combined transfer, the transfer node is determined, the generalized travel costs before and after the transfer are calculated respectively, and the sum is calculated. The path selection behavior and the traffic mode selection behavior of the traveler are calculated by the following formulas: The method comprises a calculation system, a pre-trip system and a management system. The computing system determines the congested road sections and time periods according to historical traffic conditions, considers the space-time supply-demand balance of each road section at different time periods, determines the capacity threshold of each reservation time period, and outputs a travel plan for the user; The reservation system displays a reservation travel schedule to the traveler, which shows the remaining capacity of the road section that needs to be reserved within a specific time period. The traveler makes a reservation through the reservation system, and the reservation system reserves the time slot for the traveler to use the reserved road after the reservation is successful. For users who participate in the reservation but do not obtain the right of way, the reservation system provides alternative travel paths for them and encourages them to choose public transportation, providing corresponding discounts. Ultimately, the user will have three travel options: taking public transportation, taking a detour according to the alternative path, or violating the reservation road; The management system transmits road traffic control information by setting corresponding traffic signs and markings in the upstream area of the reserved road section. Vehicle license plate recognition technology is used to verify the compliance of reserved vehicles and implement corresponding reward and punishment systems.

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