CN-116644974-B - Optimization method and system for attraction charging strategy under traffic demand management

Abstract

The invention provides an optimization method and system for attractive charging strategies under traffic demand management. The method comprises the steps of establishing a double-layer planning model, wherein an upper layer model aims at pursuing profit maximization attractively, decision variables of the upper layer model are charged attractively, generalized travel cost of a traveler in a lower layer model is changed through charging attractively, so that route selection of the traveler is influenced, and the lower layer model is a traveler route selection model considering attractively and travel cost under random requirements. The system comprises an information acquisition module, a model establishment module and a model solving module. The invention transfers the function of congestion charge to the attraction, the attraction in the congestion area charges the traveler arriving at the attraction positively, the attraction in the road supply surplus area charges the traveler arriving at the attraction negatively, and the traveler selects the travel path based on the attraction, the attraction charge and the road section impedance, thereby relieving the road section congestion and leading the road network flow distribution to be more balanced.

Inventors

• SUN ZHANBO
• LAI MIN
• Li Qinxu
• TANG HUIMIN
• WANG XUTING

Assignees

• 西南交通大学

Dates

Publication Date

20260505

Application Date

20230609

Claims (5)

1. 1. A method for optimizing attractive charging strategies under traffic demand management, the method comprising: Establishing a double-layer planning model, wherein the double-layer planning model comprises an upper layer model and a lower layer model, the upper layer model aims at pursuing profit maximization attractively, decision variables of the upper layer model are toll attractively, and the generalized travel cost of a traveler in the lower layer model is changed through toll attractively so as to influence the path selection of the traveler; Solving the double-layer planning model to obtain an optimal strategy for attractive charging under traffic demand management; The attraction refers to facilities with attraction to urban residents and tourists; The attractive charging means charging measures adopted by attractive to the traveler reaching the attractive place, wherein the charging measures comprise positive charging and negative charging, the attractive place in the road congestion area charges the traveler reaching the attractive place positively, and the attractive place in the road supply surplus area charges the traveler reaching the attractive place negatively; the step of establishing the lower model comprises the following steps: s1, constructing a traffic network , For a set of nodes, The road segments are numbered and the number of the road segments, For a set of road segment numbers, For the purpose of numbering the places of travel, For a collection of travel location numbers, In order to number the objects in an attractive manner, In order to attractively number the collection, The number of the path is given by the number, A set of path numbers; Is a road section Traffic flow on the road; Is that For a pair of Inter-path Traffic flow on the road; Is that For a pair of Traffic flow between; is 0-1 variable, when For a pair of Road section On the path In the process of being put on the machine, Has a value of 1, otherwise The value of (2) is 0; Road section Traffic flow on road The method meets the following conditions: ; (1) For a pair of Traffic flow between The method meets the following conditions: ; (2) s2, establishing a generalized travel cost function of the traveler, and recording as Generalized travel costs including road section impedance and attractively charging, then The expression of (2) is: , (3) Wherein, the Is a road section Travel time on road section A function of traffic flow on; 、 Unified parameters for units; representing attractively charged fees, decision variables for the upper model; s3, establishing a traveler path selection utility function based on a random user balance model, and recording the traveler path selection utility function as The traveler path selection utility consists of a fixed utility and a random utility, then The expression of (2) is: , (4) , (5) Wherein, the Selecting a route for a traveler The fixed utility of the impedance is represented in the form of negative number on the utility value, the larger the impedance value is, the smaller the utility is, the attractive force of the attracted ground Generalized travel cost Is a function of (1); Selecting a route for a traveler Is also indicative of the traveler's path Deviation between the understanding value and the actual value of the travel cost; the traveler is influenced by attraction of attraction and generalized travel cost, a path with the largest attraction to the traveler and the smallest generalized travel cost is selected, and the traveler is obtained according to the utility maximization theory: , ; (6) random utility Obeys Gumbel distribution, so travelers choose paths Probability of (2) Expressed in a logic model as: ; (7) Thus (2) For a pair of Inter-path The traffic flow is as follows: ; (8) S4, considering that attractive charging influences generalized travel cost and further influences For a pair of Traffic flow between, thus, will said For a pair of Traffic flow between Represented as For a pair of Continuous single reduction function of minimum generalized trip cost between: , (9) Wherein, the Is that For a pair of Correlation coefficients of the traffic flow functions between the two; Is that For a pair of Maximum potential traffic flow between; For OD pair The minimum generalized travel cost between is expressed as: , (10) Wherein, the Is that For a pair of An inverse of the traffic flow function between.
2. 2. The method for optimizing an attractive charging strategy under traffic demand management according to claim 1, wherein the lower model is an optimization model L1; The objective function of the optimization model L1 is: (11) The constraint conditions of the optimization model L1 are as follows: , (11a) , (11b) , (11c) ; (11d) In the above, the first step of, The road segments are numbered and the number of the road segments, For a set of road segment numbers, For the purpose of numbering the places of travel, For a collection of travel location numbers, In order to number the objects in an attractive manner, In order to attractively number the collection, The number of the path is given by the number, A set of path numbers; Is a road section Traffic flow on the road; Is a road section Travel time on road section The function of traffic flow, herein denoted as ; Is that For a pair of Traffic flow between; An attractive force that is attractive; Is that For a pair of Inter-path Traffic flow on the road; 、 Unified parameters for units; representing attractively charged fees, decision variables for the upper model; Is that For a pair of An inverse of the traffic flow function between; is 0-1 variable, when For a pair of Road section On the path In the process of being put on the machine, Has a value of 1, otherwise The value of (2) is 0.
3. 3. A method of optimizing an attractive charging strategy under traffic demand management according to any one of claims 1-2, wherein the step of building the upper model comprises: Suppose that in a traffic network Is present in (a) There is no fee-charging game between different attractions, all attractions belong to one group, and all attractions seek to maximize common profit, in which case the upper model aims at seeking profit maximization of attractions, that is, seeking profit maximization of groups to which the attractions belong, expressed as: , (12) , (13) , (14) Namely: ; (15) In the above, the first step of, For a set of nodes, The road segments are numbered and the number of the road segments, For a set of road segment numbers, For the purpose of numbering the places of travel, For a collection of travel location numbers, In order to number the objects in an attractive manner, A set numbered attractively; In order to be attractive for profit, Is a group profit, W% ) Is attractive operating benefit; Is attractive operating cost; Is that For a pair of The traffic flow between the two is obtained by solving the lower model; the income brought to the attraction for each traveler to reach the attraction; representing attractively charged fees, decision variables for the upper model; Is attractive service level and attractive service providing cost is , Is a cost factor that attractively serves each arrival; is an attractive fixed cost.
4. 4. A method of optimizing an attractive charging strategy under traffic demand management according to any one of claims 1-2, wherein the step of building the upper model comprises: Suppose that in a traffic network Is present in (a) Charging games exist among different attractions, all attractions belong to a group, but each attraction pursues maximization of self profit, in which case the upper model aims at pursuing maximization of profit of the attraction, namely maximization of self profit of each attraction; the decision content of each attraction is that the optimal attraction charge is selected to maximize the profit of the attraction, the attraction performs non-cooperative competition, and the attraction competition is the result of game to reach Nash equilibrium; Suction ground The profit function of (2) is: , (16) In the above, the first step of, For a set of nodes, The road segments are numbered and the number of the road segments, For a set of road segment numbers, For the purpose of numbering the places of travel, For a collection of travel location numbers, In order to number the objects in an attractive manner, Set numbered for attraction, W% ) Is an attractive way to operate the revenues, ; Is an attractive operating cost for the system, ; Is that For a pair of The traffic flow between the two is obtained by solving the lower model; the income brought to the attraction for each traveler to reach the attraction; representing attractively charged fees, decision variables for the upper model; Is attractive service level and attractive service providing cost is , Is a cost factor that attractively serves each arrival; Is a fixed cost of attractions; Recording device A set of attraction numbers representing vectors for all attraction charges ; When attractively competing with each other to achieve Nash equilibrium, attractively charging satisfies a non-negative constraint, namely: ; (17) Recording device Represents the attraction Is a set of charging policies of (a), ; Recording device When the attractive charge reaches the Nash equilibrium, all vectors of the attractive charge are the Nash equilibrium points of the attractive charge, and the filling condition is that the formula (18) is satisfied: ; (18) Equation (18) indicates that when attraction charging reaches Nash equilibrium, each attraction charging policy is the best reflection of the other attraction charging policies, each attraction cannot increase revenue by unilaterally changing its own attraction charging, wherein, Representing attraction under attraction charging's Nash equilibrium point Is a fee for (1); indicating that the attraction is removed at the Nash equilibrium point of the attraction charge All attractive charging vectors outside, i.e. ; Indicating that at the Nash equilibrium point of attractively charged, For a pair of The traffic flow between the two is obtained by solving the lower model; representing road segments under the Nash equilibrium point of attractively charging The traffic flow on the road is obtained by solving the lower model; as can be seen from the formula (16), Is about Is herein denoted as a function of Hypothesis is that Is that On a continuous microcompact because of The Nash equilibrium point for attractive charge, so equation (18) is equivalent to the following variational inequality: , (19) Wherein, the 。
5. 5. An attractive charging strategy optimization system under traffic demand management is characterized by adopting the attractive charging strategy optimization method under traffic demand management as claimed in any one of claims 1-4, and comprises an information acquisition module, a model building module and a model solving module; the information collected by the information collection module comprises urban road network information, historical trip distribution information and attraction information; The model building module is used for building a double-layer planning model, wherein the double-layer planning model comprises an upper layer model and a lower layer model, the upper layer model aims at pursuing profit maximization attractively, decision variables of the upper layer model are toll attractively, and the generalized travel cost of a traveler in the lower layer model is changed through toll attractively so as to influence the path selection of the traveler; And the model solving module solves the double-layer planning model to obtain an optimal strategy for attractive charging under traffic demand management.

Description

Optimization method and system for attraction charging strategy under traffic demand management Technical Field The invention relates to the traffic field, in particular to a method and a system for optimizing attractive charging strategies under traffic demand management. Background In recent years, social development accelerates urban construction and the increase of the number of motor vehicles, and traffic jam phenomenon is increasingly serious. In the past, students have sequentially proposed means for increasing road supply such as road expansion, but when the theorem indicates that the increasing speed of traffic demand is often greater than that of traffic supply, the increased traffic facilities can lead to more traffic demands. Traffic demand management, including traffic restrictions, congestion charging, parking charging, and the like, is therefore increasingly being a strategy for alleviating congestion. For limited traffic, studies have shown that the short term effect of limited traffic is more pronounced because high-income residents can open and not limit traffic by purchasing two or more vehicles when one vehicle is limited traffic, and the effect of relieving congestion is not obvious in the long term. For congestion charging based on road sections, the implementation method is to set charging points on the congested road sections for manual charging or install an electronic charging system. Even though existing billing systems have been relatively mature, the technical hurdles of implementation have been greatly reduced, as most methods require the installation of a device in each vehicle that can exchange information with the metering system. The incorporation of these devices into a vehicle is both a technical problem and an economic problem. In addition, there is a coordination problem between different toll authorities, and it is not possible for drivers to equip each of the different toll road systems they may use with different devices. For parking charging, compared with two traffic demand management modes of traffic restriction and road congestion charging, the acceptance of parking charging is higher, and the implementation cost is lower than that of road congestion charging. But only by way of parking charging, the charging form is single, and many destinations offer free parking for attractive traffic, which even exacerbates congestion around the destination. In the past, research on parking charging has mostly utilized statement preference checks to study specific venues, such as workplace charging, hospital parking charging, scenic spot parking charging, roadside parking charging. Many cities are priced for parking fees, usually based on the scarcity level of land, and there is less literature to charge fees based on regional appeal and surrounding traffic congestion conditions. Legorreta and Newmark surveys found that only norbuhan, peltier, sydney, melbourne and singapore actually imposed regional tax on each parking space. In some studies, even if the charging area is distinguished, it is mostly divided into suburban areas and urban centers. In practice, areas with low urban central attraction and no congestion do not need to charge high charges, and areas with high suburban attraction and easy congestion should charge certain charges to relieve traffic congestion. Arnott shows that the effect of spatially differentiated parking fees can be compared to time-differentiated congestion fees. In fact, many places still provide free parking for travelers, only about 10 tens of thousands of public parking spaces in the state of China are provided for all free parking, and more than 80% of companies in the United states are provided for staff by Bruckner and Franco survey reports, and the free parking can bring more traffic and thus obtain greater benefits. The free parking seems to bring more benefits, but in practice, the extra benefits of operators are commonly borne by the whole society to bear the cost of excess traffic demands, because the traffic demands stimulated by free parking bring great negative externality to the society, and the generated influence is far beyond the range of a single operator. Firstly, a large number of people drive out, road congestion is increased, negative externality caused by the congestion is brought, and secondly, excessive parking also causes land area loss, especially because most automobile commuters drive independently. If parking is not charged, fairness issues may be involved because, in general, parkers are more abundant than passengers using a public transportation system, they share the cost of traffic negative externality to all public transportation users, even those walking, riding buses or riding bicycles to stop, are unfair (traffic jams, air pollution, etc.). Calthrop indicates that cancelling free stops at a workplace generally reduces the number of independent driving trips. Proost it is believed that employer pay-to-employ