A method for calculating the optimal public transportation motorization share rate in small and medium-sized cities

Abstract

The present invention discloses a method for calculating the optimal public transportation motorization share rate in small and medium-sized cities, which relates to the technical field of motorized travel structure optimization and is applied to public transportation planning in small and medium-sized cities. The method comprises: determining the composition of the motorized transportation system in the small and medium-sized cities, and determining traffic allocation parameters according to motorized transportation allocation characteristics; determining motorized travel time characteristics according to traffic supply and demand characteristics and traffic allocation parameters; determining an optimization index for the public transportation motorization share rate, and constructing an optimization objective function and constraint conditions based on traffic supply and demand characteristics, motorized travel time characteristics, and motorized mode characteristics; establishing a system optimal public transportation motorization share rate model based on the optimization objective function and constraint conditions; solving the optimal public transportation motorization share rate model based on the CRITIC-ideal point method, and determining the optimal share rate value. The method can be used to calculate the optimal public transportation motorization share rate in small and medium-sized cities, providing a basis for formulating public transportation development goals in small and medium-sized cities.

Description

Technical Field

[0001] The present invention relates to the technical field of motorized travel structure optimization, and in particular to a method for calculating an optimal public transportation motorization share rate in small and medium-sized cities. Background Art

[0002] Current research on optimizing the public transport share ratio has the following imperfections: First, in terms of optimization target selection, usually only efficiency factors or carbon emission factors are selected as indicators, failing to take into account the overall utility of the transportation system, including travelers; second, when constructing the optimization index function, parameters such as travel time and pollution emissions of each mode are regarded as fixed values, failing to consider the dynamic impact of changes in the road network supply-demand ratio caused by changes in the share ratio on multiple indicators such as travel time, resulting in a lack of accuracy in the function construction of the optimization index.

[0003] Therefore, how to consider the supply and demand relationship of the road network and the traffic volume road network distribution characteristics, construct a motorized travel time function, and construct an optimization model for the motorized share of public transportation in small and medium-sized cities from the perspective of system optimization, and determine the theoretical optimal value of the motorized share of public transportation has become a technical problem that needs to be solved urgently in this field. Summary of the Invention

[0004] In order to solve the above technical problems, the present invention provides a method for calculating the optimal public transportation motorization share rate in small and medium-sized cities, comprising the following steps:

[0005] S1. Determine the composition of the motorized transportation system in small and medium-sized cities and determine the traffic allocation parameters based on the characteristics of motorized transportation allocation;

[0006] S2. Determine the time characteristics of motorized travel based on traffic supply and demand characteristics and traffic allocation parameters;

[0007] S3. Determine the optimization index for the motorized public transport share ratio, and construct the optimization objective function and constraints based on the characteristics of traffic supply and demand, motorized travel time, and motorized mode.

[0008] S4. Establish a system optimal bus motorization share model based on the optimization objective function and constraints;

[0009] S5. Solve the optimal public transport motorization sharing rate model based on the CRITIC-ideal point method and determine the optimal sharing rate value.

[0010] The technical solution further defined in the present invention is:

[0011] Furthermore, in step S1, the motorized transportation system of small and medium-sized cities comprises conventional public transportation and automobile transportation;

[0012] Motorized traffic distribution characteristics include the length of each road segment, the capacity of each segment, the amount of car traffic carried by each segment, and the amount of bus traffic carried by each segment.

[0013] Traffic distribution parameters include the proportion of motorized traffic volume borne by roads of different grades and the traffic distribution imbalance coefficient.

[0014] The above-mentioned method for calculating the optimal bus motorization share rate in small and medium-sized cities is as follows:

[0015]

[0016] Q ij =Q car,ij +μ bus Q bus,ij

[0017] Among them, i is the road grade, j is the road section number, η i is the proportion of motorized driving volume on grade i roads, L ij is the length of the road section j in level i, unit: km; Q ij is the equivalent traffic volume of road section j in level i, unit: pcu / h; Q car,ij is the car traffic volume of road section j in level i, unit: pcu / h; Q bus,ij is the bus traffic volume on road section j in level i, unit: veh / h; μ bus is the bus equivalent coefficient, unit: pcu / veh;

[0018] The traffic distribution imbalance coefficient is the ratio of the actual traffic distribution to the congestion delay time under the condition of uniform traffic distribution. The calculation method is:

[0019]

[0020]

[0021]

[0022] Among them, ρ i is the traffic distribution imbalance coefficient of grade i road, VOC ij is the traffic supply-demand ratio of road section j in level i, is the average supply-demand ratio of grade i roads, C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of section j in level i, in km.

[0023] In the aforementioned method for calculating the optimal bus motorization share rate for small and medium-sized cities, in step S2, the traffic supply and demand characteristics include the road network capacity of each level of road, the demand for motorized travel, the average motorized travel distance, the average passenger load factor of cars, the bus operating mileage per unit time, the average walking connection distance of buses, the average bus departure interval, the average bus stop distance, the average walking speed of travelers, and the proportion of new energy cars and buses.

[0024] In the above-mentioned method for calculating the optimal bus motorization share rate in small and medium-sized cities, in step S2, the motorized travel time characteristics include

[0025] The normal time consumed by vehicles per unit mileage is the average time used by buses or cars to travel per unit mileage in the road network without considering the impact of congestion. The calculation method is:

[0026]

[0027] Where t0 is the normal time consumed by a vehicle per unit mileage in the road network, unit: h / km; η i is the proportion of motorized driving volume on grade i roads, V d,i is the design speed of grade i road, unit: km / h;

[0028] The average waiting time for bus travel is expressed as

[0029]

[0030] Among them, t t,w is the average waiting time for bus trips, unit: h; H is the average bus departure interval;

[0031] The average walking connection time for bus trips is expressed as

[0032] t t,a =D t,a / V w

[0033] Among them, t t,a is the average walking connection time for bus trips, unit: h; D t,a is the average walking distance to the bus station, unit: km; V w is the average walking speed of travelers, unit: km / h;

[0034] According to the extra time consumed by vehicle congestion, the function of vehicle congestion consumption time per unit mileage is constructed with the bus motorization share rate as the independent variable:

[0035]

[0036]

[0037] Among them, t cong (R T ) is the public transport motorization share rate R T The time consumed by vehicles in congestion per unit mileage, unit: h / km; its value is the extra time consumed by buses or cars per unit mileage in the road network due to congestion when considering the impact of congestion; R T is the motorization share of public transportation, μ bus is the bus equivalent coefficient, unit: pcu / veh; S transit Q is the bus operating mileage per unit time, unit: km / h; m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; δ c is the average passenger capacity of cars, unit: person / pcu; N i is the road network capacity of level i road, unit: pcu km / h;

[0038] ρ i is the traffic distribution imbalance coefficient of grade i road, η i is the proportion of motorized driving volume on grade i roads, V d,i is the design speed of grade i road, unit: km / h; C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of the road section j in level i, unit: km;

[0039] The average bus stop time function is constructed with the bus motorization share rate as the independent variable:

[0040]

[0041] Among them, t t,s (R T ) is the motorization share of public transportation R T The average bus stop time, unit: h / stop; its value is the extra time consumed by the bus at the stop; R T is the motorization share of public transportation, Q m D is the demand for motorized travel, unit: person-times / h; S is the average distance between bus stops, unit: km; S transit It is the bus operating mileage per unit time, unit: km / h.

[0042] In the aforementioned method for calculating the optimal public transportation motorization share rate for small and medium-sized cities, in step S3, the optimization indicators for the public transportation motorization share rate include total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident costs, and total carbon emissions;

[0043] The characteristics of motorization modes include the maximum passenger capacity of buses, fuel consumption of cars and buses, fuel consumption prices of cars and buses, pollution emission equivalent values ​​of cars and buses, external costs of accidents, electricity consumption of new energy cars and buses, electricity consumption prices, and carbon emission factors of the power grid.

[0044] In the above-mentioned method for calculating the optimal bus motorization share rate in small and medium-sized cities, in step S3, the construction of the optimization objective function includes the following steps:

[0045] S3.1. Sum the regular time spent in the car, congestion time, bus stop time, walking time, and waiting time of all motorized travelers to construct a total time consumption function, which is expressed as follows:

[0046]

[0047] Among them, T total (R T ) is the public transport motorization share rate R T The total time consumption of all motorized travelers at this time, unit: h; R T The motorization share of public transportation;

[0048] S3.2. Use the passenger density of travelers in the car to represent the comfort consumption value and construct the total comfort consumption function, which is expressed as follows:

[0049]

[0050] Among them, Y(R T ) is the public transport motorization share rate R T Total comfort consumption per hour, unit: km·person·person / m 2 ; R T is the motorization share of public transportation, A c The available space for passengers or drivers in a car, unit: m 2 ; A t The available space for passengers in the bus, unit: m 2 ;

[0051] S3.3. Using the sum of the total energy costs of buses and cars, construct a total energy cost function, which is expressed as follows:

[0052]

[0053] Among them, Wenergy (R T ) is the public transport motorization share rate R T Total energy consumption cost per hour, unit: yuan; R T is the motorization share of public transportation, F c is the fuel consumption of the car, unit: L / 100km; F t is the fuel consumption of the bus, unit: L / 100km; C fuel,c is the gasoline price for cars, unit: Yuan / L; C fuel,t is the price of diesel for buses, unit: Yuan / L; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses;

[0054] S3.4. Use the sum of the pollutant equivalents emitted by buses and cars to construct a total pollution emission function, as shown below:

[0055]

[0056] Among them, P(R T ) is the public transport motorization share rate R T Total pollution emissions per hour, unit: g; R T is the public transport motorization share rate, P car is the equivalent value of car pollutant emissions, unit: g / km; P transit is the pollutant emission equivalent value of buses, unit: g / km; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses;

[0057] S3.5. Use the sum of the external accident costs caused by buses and cars to construct a total accident cost function, which is expressed as follows:

[0058]

[0059] Among them, W acc (R T ) is the public transport motorization share rate R T Total accident cost per hour, unit: yuan; R T is the motorization share of public transportation, Acc car is the external cost of car accidents, unit: yuan / veh·km; Acc transit is the external cost of bus accidents, unit: yuan / veh·km;

[0060] S3.6. Use the sum of carbon emissions from buses and cars to construct a total carbon emissions function, as shown below:

[0061]

[0062] in, The motorization share of public transportation is R T Total carbon emissions per hour, unit: kg; R T is the motorization share of public transportation, E c E is the power consumption of new energy vehicles, unit: kWh / 100km; t is the power consumption of new energy buses, unit: kWh / 100km; EF is the carbon emission factor of the power grid, unit: tCO2 / MWh; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses.

[0063] In the aforementioned method for calculating the optimal bus motorization share rate for small and medium-sized cities, in step S3, the constraint condition is set to restrict the value of the bus motorization share rate based on the overall bus supply, and the expression is as follows:

[0064] R T ∈R,R={R T |Q m R T (D m -D t,a )≤S transit C transit ,0≤R T ≤1}

[0065] Among them, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate;

[0066] Q m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; D t,a is the average walking distance to the bus station, unit: km; S transit C is the bus operating mileage per unit time, unit: km / h; transit The maximum passenger capacity of a public bus, unit: persons / veh.

[0067] In the aforementioned method for calculating the optimal bus motorization share rate for small and medium-sized cities, in step S4, the optimal bus motorization share rate model is constructed with the bus motorization share rate as the decision variable, the minimization of total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident costs and total carbon emissions as the optimization objectives, and the overall bus supply limit as the constraint condition for multi-objective optimization modeling. The model is expressed as follows

[0068]

[0069] sqFt T ∈R

[0070] Among them, f j (R T ) is the objective function of index j, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate;

[0071] T total is the total time consumption, Y is the total comfort consumption, W energy Total energy cost, P(R T ) is the total pollution emission, W acc is the total accident cost, is the total carbon emissions.

[0072] The above-mentioned method for calculating the optimal bus motorization share rate in small and medium-sized cities, in step S5, solves the optimal bus motorization share rate model based on the CRITIC-ideal point method, including the following steps:

[0073] S5.1. Calculate the function values ​​of each optimization indicator under different travel demand and sharing rate scenarios to form a set of objective function value matrices.

[0074] B=[b ij ] n×6

[0075] Among them, B is the objective function value matrix, b ij is the function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6;

[0076] S5.2. Dimensionless process the objective function value matrix B to obtain the matrix,

[0077] A=[a ij ] n×6 ,

[0078]

[0079] Among them, A is the dimensionless objective function value matrix, a ij is the dimensionless function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6;

[0080] S5.3. Based on the dimensionless objective function value matrix, calculate the standard deviation of each indicator. The calculation method is as follows:

[0081]

[0082] Among them, σ jis the standard deviation of index j, j = 1, 2, ..., 6;

[0083] S5.4. Based on the dimensionless objective function value matrix, calculate the correlation coefficient matrix between each indicator.

[0084] R=[r ij ] 6×6

[0085] Among them, R is the correlation coefficient matrix between each indicator, r ij is the correlation coefficient between the optimization indicators i and j, i, j = 1, 2, ..., 6;

[0086] S5.5. Calculate the information content of each optimization indicator. The calculation method is as follows:

[0087]

[0088] Among them, C j is the information content of index j. The larger the value, the greater the role of the index in the entire evaluation index system, where j = 1, 2, ..., 6;

[0089] S5.6. The weight value of each indicator is obtained by weighted calculation of the information amount of the optimization indicator. The calculation method is as follows:

[0090]

[0091] Among them, ω j is the weight value of indicator j;

[0092] S5.7. Based on the weight values ​​of each objective function, construct the Euclidean distance function between the standardized index function values ​​and the optimal index value.

[0093]

[0094]

[0095] Among them, D(R T ) is the public transport motorization share rate R T The Euclidean distance between the objective function value and the optimal value, f j (R T ) is the objective function of index j, f z,j (R T ) is the dimensionless objective function of index j, R is the feasible domain of the public transport motorization share rate;

[0096] S5.8. Using the Euclidean distance function as the single objective function to be optimized, calculate the optimal public transport motorization share rate. The calculation method is as follows:

[0097]

[0098] Among them, R T * is the optimal public transport motorization share rate.

[0099] The beneficial effects of the present invention are:

[0100] (1) In the present invention, based on the demand, supply and traffic distribution characteristics of motorized traffic in small and medium-sized cities, motorized travel time parameters are constructed; based on the motorized travel time parameters, with the public transportation motorization share rate as the decision variable, objective functions of optimization indicators such as time consumption, comfort consumption, energy consumption, pollution emissions, accident costs, and carbon emissions are constructed, as well as objective functions of constraints such as motorized travel demand constraints and public transportation supply constraints; an optimal public transportation motorization share rate model is established, and the optimal share rate value is determined. The invention results can be applied to the public transportation development planning of small and medium-sized cities, improving the scientificity and rationality of the public transportation share rate target setting;

[0101] (2) The method for calculating motorized travel time constructed in the present invention is based on the characteristics of traffic supply and demand and traffic distribution, and takes into account the impact of the overall demand-supply ratio of the road network on travel time; the impact of the uneven distribution of traffic volume in the road network on travel time, and can provide a more accurate estimate of the motorized traffic travel time of the entire road network under a certain total traffic volume;

[0102] (3) In this invention, based on the characteristics of motorized travel time and traffic supply and demand, a method for constructing various optimization indicators in a motorized traffic system is proposed, while also considering the impact of traffic volume on the indicators. The consumption or emission values ​​of the optimization indicators per unit traffic volume change with different supply and demand relationships, making the calculation of the indicator values ​​more in line with the actual situation.

[0103] (4) In the present invention, each indicator in the optimization model comprehensively considers the travel utility of travelers, transportation systems and the external environment, and is solved based on the "CRITIC-ideal point method". It can objectively assign weights according to the correlation and changes of each optimization indicator. The obtained optimization calculation results provide a reference for the formulation of the target value of the public transportation share rate in small and medium-sized cities, which is conducive to the coordinated and sustainable development of urban transportation economy, society and environment, and improves the scientificity and rationality of the formulation of the public transportation share rate target. BRIEF DESCRIPTION OF THE DRAWINGS

[0104] Figure 1 Flowchart for calculating the optimal public transport motorization share rate according to an embodiment of the present invention;

[0105] Figure 2 This is a schematic diagram of the structure of a multi-objective optimization model for public transport motorization share rate according to an embodiment of the present invention;

[0106] Figure 3 This is a table showing the road network capacity and design speed of each level of roads in the case city in the embodiment of the present invention;

[0107] Figure 4 Schematic diagram of the statistical results of the demand-supply ratio of each road section of each grade in the case city in an embodiment of the present invention;

[0108] Figure 5 Schematic diagram of calculation results of supply-demand ratio, travel volume ratio and traffic distribution imbalance coefficient of each grade of roads in the case city in an embodiment of the present invention;

[0109] Figure 6 This is a statistical diagram of motorized travel demand and public transportation supply characteristics during morning and evening peak hours in the main urban area of ​​a case city in an embodiment of the present invention;

[0110] Figure 7 This is a schematic diagram of the calculation results of the travel time consumption parameters of the case city in the embodiment of the present invention, which include the normal vehicle driving consumption, congestion consumption time, average bus stop time, average bus waiting time, and walking connection time;

[0111] Figure 8 Schematic diagram of model parameter values ​​of the optimal public transportation motorization share model of the case city in an embodiment of the present invention;

[0112] Figure 9 This is a schematic diagram of the calculation results of the optimization index weights of the case cities in an embodiment of the present invention;

[0113] Figure 10 Schematic diagram of calculation results of various index function values ​​after normalization under different sharing ratio values ​​in an embodiment of the present invention;

[0114] Figure 11 Schematic diagram of the calculation results of the optimal public transport motorization share rate in an embodiment of the present invention. DETAILED DESCRIPTION

[0115] This embodiment provides a method for calculating the optimal public transportation motorization share rate in small and medium-sized cities, such as Figure 1 As shown, the following steps are included

[0116] S1. Determine the composition of the motorized transportation system in small and medium-sized cities and determine the traffic allocation parameters based on the characteristics of motorized transportation allocation;

[0117] Among them, the motorized transportation system of small and medium-sized cities includes conventional public transportation and automobile transportation; the motorized traffic distribution characteristics include the length of road sections of various levels in the road network, the traffic capacity of road sections, the automobile traffic volume borne by the road sections, and the bus traffic volume borne by the road sections; the traffic distribution parameters include the proportion of motorized driving volume borne by roads of different levels and the traffic distribution imbalance coefficient.

[0118] The calculation method for the proportion of motorized traffic carried by different levels of roads is as follows:

[0119]

[0120] Q ij =Q car,ij +μ bus Q bus,ij

[0121] Among them, i is the road grade, j is the road section number, η i is the proportion of motorized driving volume on grade i roads, L ij is the length of the road section j in level i, unit: km; Q ij is the equivalent traffic volume of road section j in level i, unit: pcu / h; Q car,ij is the car traffic volume of road section j in level i, unit: pcu / h; Q bus,ij is the bus traffic volume on road section j in level i, unit: veh / h; μ bus It is the bus equivalent coefficient, unit: pcu / veh.

[0122] The traffic distribution imbalance coefficient is the ratio of the actual traffic distribution to the congestion delay time under the condition of uniform traffic distribution. The calculation method is:

[0123]

[0124]

[0125]

[0126] Among them, ρ i is the traffic distribution imbalance coefficient of grade i road, VOC ij is the traffic supply-demand ratio of road section j in level i, is the average supply-demand ratio of grade i roads, C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of section j in level i, in km.

[0127] S2. Determine the time characteristics of motorized travel based on traffic supply and demand characteristics and traffic allocation parameters;

[0128] Among them, the traffic supply and demand characteristics include the road network capacity of various levels, the demand for motorized travel, the average distance of motorized travel, the average passenger occupancy rate of cars, the operating mileage of buses per unit time, the average walking connection distance of buses, the average bus departure interval, the average bus stop spacing, the average walking speed of travelers, and the proportion of new energy cars and buses.

[0129] Motorized travel time characteristics include

[0130] The normal time consumed by vehicles per unit mileage is the average time used by buses or cars to travel per unit mileage in the road network without considering the impact of congestion. The calculation method is:

[0131]

[0132] Where t0 is the normal time consumed by a vehicle per unit mileage in the road network, unit: h / km; η i is the proportion of motorized driving volume on grade i roads, V d,i is the design speed of grade i road, unit: km / h;

[0133] The average waiting time for bus travel is expressed as

[0134]

[0135] Among them, t t,w is the average waiting time for bus trips, unit: h; H is the average bus departure interval;

[0136] The average walking connection time for bus trips is expressed as

[0137] t t,a =D t,a / V w

[0138] Among them, t t,a is the average walking connection time for bus trips, unit: h; D t,a is the average walking distance to the bus station, unit: km; V w is the average walking speed of travelers, unit: km / h;

[0139] According to the extra time consumed by vehicle congestion, the function of vehicle congestion consumption time per unit mileage is constructed with the bus motorization share rate as the independent variable:

[0140]

[0141]

[0142] Among them, t cong (RT ) is the public transport motorization share rate R T The time consumed by vehicles in congestion per unit mileage, unit: h / km; its value is the extra time consumed by buses or cars per unit mileage in the road network due to congestion when considering the impact of congestion; R T is the motorization share of public transportation, μ bus is the bus equivalent coefficient, unit: pcu / veh; S transit Q is the bus operating mileage per unit time, unit: km / h; m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; δ c is the average passenger capacity of cars, unit: person / pcu; N i is the road network capacity of level i road, unit: pcu km / h;

[0143] ρ i is the traffic distribution imbalance coefficient of grade i road, η i is the proportion of motorized driving volume on grade i roads, V d,i is the design speed of grade i road, unit: km / h; C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of the road section j in level i, unit: km;

[0144] The average bus stop time function is constructed with the bus motorization share rate as the independent variable:

[0145]

[0146] Among them, t t,s (R T ) is the motorization share of public transportation R T The average bus stop time, unit: h / stop; its value is the extra time consumed by the bus at the stop; R T is the motorization share of public transportation, Q m D is the demand for motorized travel, unit: person-times / h; S is the average distance between bus stops, unit: km; S transit It is the bus operating mileage per unit time, unit: km / h.

[0147] S3. Determine the optimization index for the motorized public transport share ratio, and construct the optimization objective function and constraints based on the characteristics of traffic supply and demand, motorized travel time, and motorized mode.

[0148] Among them, the optimization indicators of public transportation motorization share rate include total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident costs and total carbon emissions;

[0149] The characteristics of motorization modes include the maximum passenger capacity of buses, fuel consumption of cars and buses, fuel consumption prices of cars and buses, pollution emission equivalent values ​​of cars and buses, external costs of accidents, electricity consumption of new energy cars and buses, electricity consumption prices, and carbon emission factors of the power grid.

[0150] The construction of the optimization objective function includes the following steps

[0151] S3.1. Sum the regular time spent in the car, congestion time, bus stop time, walking time, and waiting time of all motorized travelers to construct a total time consumption function, which is expressed as follows:

[0152]

[0153] Among them, T total (R T ) is the public transport motorization share rate R T The total time consumption of all motorized travelers at this time, unit: h; R T The motorization share of public transportation;

[0154] S3.2. Use the passenger density of travelers in the car to represent the comfort consumption value and construct the total comfort consumption function, which is expressed as follows:

[0155]

[0156] Among them, Y(R T ) is the public transport motorization share rate R T Total comfort consumption per hour, unit: km·person·person / m 2 ; R T is the motorization share of public transportation, A c The available space for passengers or drivers in a car, unit: m 2 ; A t The available space for passengers in the bus, unit: m 2 ;

[0157] S3.3. Using the sum of the total energy costs of buses and cars, construct a total energy cost function, which is expressed as follows:

[0158]

[0159] Among them, W energy (R T ) is the public transport motorization share rate R TTotal energy consumption cost per hour, unit: yuan; R T is the motorization share of public transportation, F c is the fuel consumption of the car, unit: L / 100km; F t is the fuel consumption of the bus, unit: L / 100km; C fuel,c is the gasoline price for cars, unit: Yuan / L; C fuel,t is the price of diesel for buses, unit: Yuan / L; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses;

[0160] S3.4. Use the sum of the pollutant equivalents emitted by buses and cars to construct a total pollution emission function, as shown below:

[0161]

[0162] Among them, P(R T ) is the public transport motorization share rate R T Total pollution emissions per hour, unit: g; R T is the public transport motorization share rate, P car is the equivalent value of car pollutant emissions, unit: g / km; P transit is the pollutant emission equivalent value of buses, unit: g / km; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses;

[0163] S3.5. Use the sum of the external accident costs caused by buses and cars to construct a total accident cost function, which is expressed as follows:

[0164]

[0165] Among them, W acc (R T ) is the public transport motorization share rate R T Total accident cost per hour, unit: yuan; R T is the motorization share of public transportation, Acc car is the external cost of car accidents, unit: yuan / veh·km; Acc transit is the external cost of bus accidents, unit: yuan / veh·km;

[0166] S3.6. Use the sum of carbon emissions from buses and cars to construct a total carbon emissions function, as shown below:

[0167]

[0168] Among them, E CO2(R T ) is the public transport motorization share rate R T Total carbon emissions per hour, unit: kg; R T is the motorization share of public transportation, E c E is the power consumption of new energy vehicles, unit: kWh / 100km; t is the power consumption of new energy buses, unit: kWh / 100km; EF is the carbon emission factor of the power grid, unit: tCO2 / MWh; r new,c is the proportion of new energy vehicles, r new,t The proportion of new energy buses.

[0169] The constraint condition is set to limit the value of the bus motorization share rate based on the overall bus supply. The expression is as follows:

[0170] R T ∈R,R={R T |Q m R T (D m -D t,a )≤S transit C transit ,0≤R T ≤1}

[0171] Among them, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate;

[0172] Q m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; D t,a is the average walking distance to the bus station, unit: km; S transit C is the bus operating mileage per unit time, unit: km / h; transit The maximum passenger capacity of a public bus, unit: persons / veh.

[0173] S4. Establish a system optimal bus motorization share model based on the optimization objective function and constraints;

[0174] The optimal bus motorization share model is constructed with the bus motorization share as the decision variable, the minimization of total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident cost and total carbon emissions as the optimization goal, and the overall bus supply limit as the constraint condition for multi-objective optimization modeling. Figure 2 As shown, the model is represented as follows

[0175]

[0176] Among them, fj (R T ) is the objective function of index j, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate;

[0177] T total is the total time consumption, Y is the total comfort consumption, W energy Total energy cost, P(R T ) is the total pollution emission, W acc is the total accident cost, is the total carbon emissions.

[0178] S5. Solve the optimal public transport motorization sharing rate model based on the CRITIC-ideal point method and determine the optimal sharing rate value;

[0179] Solving the optimal bus motorization share model based on the "CRITIC-ideal point method" includes the following steps:

[0180] S5.1. Calculate the function values ​​of each optimization indicator under different travel demand and sharing rate scenarios to form a set of objective function value matrices.

[0181] B=[b ij ] n×6

[0182] Among them, B is the objective function value matrix, b ij is the function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6;

[0183] S5.2. Dimensionless process the objective function value matrix B to obtain the matrix,

[0184] A=[a ij ] n×6 ,

[0185]

[0186] Among them, A is the dimensionless objective function value matrix, a ij is the dimensionless function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6;

[0187] S5.3. Based on the dimensionless objective function value matrix, calculate the standard deviation of each indicator. The calculation method is as follows:

[0188]

[0189] Among them, σ j is the standard deviation of index j, j = 1, 2, ..., 6;

[0190] S5.4. Based on the dimensionless objective function value matrix, calculate the correlation coefficient matrix between each indicator.

[0191] R=[r ij ] 6×6

[0192] Where R is the correlation coefficient matrix between each indicator, rij is the correlation coefficient between the optimization indicators i and j, i, j = 1, 2, ..., 6;

[0193] S5.5. Calculate the information content of each optimization indicator. The calculation method is as follows:

[0194]

[0195] Among them, C j is the information content of index j. The larger the value, the greater the role of the index in the entire evaluation index system, where j = 1, 2, ..., 6;

[0196] S5.6. The weight value of each indicator is obtained by weighted calculation of the information amount of the optimization indicator. The calculation method is as follows:

[0197]

[0198] Among them, ω j is the weight value of indicator j;

[0199] S5.7. Based on the weight values ​​of each objective function, construct the Euclidean distance function between the standardized index function values ​​and the optimal index value.

[0200]

[0201]

[0202] Among them, D(R T ) is the public transport motorization share rate R T The Euclidean distance between the objective function value and the optimal value, f j (R T ) is the objective function of index j, f z,j (R T ) is the dimensionless objective function of index j, R is the feasible domain of the public transport motorization share rate;

[0203] S5.8. Using the Euclidean distance function as the single objective function to be optimized, calculate the optimal public transport motorization share rate. The calculation method is as follows:

[0204]

[0205] Among them, R T * is the optimal public transport motorization share rate.

[0206] In order to demonstrate the applicability of the method of the present invention, the following examples are used for illustration:

[0207] Taking Binhai County, Yancheng City as an example, the population of the main urban area of ​​the city is about 300,000 in 2020, which is a Class I small city. The roads in the main urban area of ​​the city are mainly divided into three levels: main roads, secondary roads and branch roads. The road network capacity and design speed of each level are as follows: Figure 3 shown.

[0208] The current bus motorization share rate in the main urban area is about 8.2%. During the morning and evening rush hours, a small number of road sections are congested or slow-moving. The proposed optimal bus motorization share rate calculation method is applied to solve the optimal bus motorization share rate during the morning and evening rush hours in the main urban area of ​​the case city.

[0209] Collect traffic volume information for each road section in the road network and calculate the demand-supply ratio of each road section at each level. The statistical results are as follows: Figure 4 As shown; calculate the supply-demand ratio of each level of road, the proportion of travel volume and the traffic distribution imbalance coefficient value, the calculation results are as follows Figure 5 shown.

[0210] Collect the characteristics of motorized travel demand and public transportation supply during the morning and evening peak hours in the main urban area of ​​the case city, and make statistics such as Figure 6 As shown; according to the supply and demand characteristics and the characteristic parameters of traffic volume distribution in the road network, the travel time consumption parameters are calculated. The travel time consumption parameters include regular vehicle driving consumption, congestion consumption time, average bus stop time, average bus waiting time and walking connection time. The calculation results are shown as follows Figure 7 As shown, where R T It is the motorization share of public transportation.

[0211] According to the motorized travel demand and travel time consumption parameters during the morning and evening peaks in the main urban area of ​​the case city, a multi-objective optimization objective function and constraint function are constructed, and an optimal bus motorization share model is established, where the model parameter values ​​are as follows: Figure 8 shown.

[0212] The “CRITIC-ideal point method” is used to calculate the weights of each optimization indicator and determine the optimal sharing rate. The calculation results of the optimization indicator weights are as follows: Figure 9 As shown in the figure; the changes of the index function values ​​after standardization with the bus motorization share rate are shown in the figure Figure 10 As shown in the figure, the Euclidean distance between the optimization target and the ideal point changes with the sharing rate as shown in the figure. Figure 11As shown in the figure, the optimal bus motorization share rate in the main urban area of ​​the case city during morning and evening peak hours is determined to be 19.3%.

[0213] The present invention constructs motorized travel time parameters based on the motorized traffic demand, supply and traffic distribution characteristics of small and medium-sized cities; based on the motorized travel time parameters, with the public transportation motorization share rate as the decision variable, constructs objective functions of optimization indicators such as time consumption, comfort consumption, energy consumption, pollution emissions, accident costs, carbon emissions, and objective functions of constraints such as motorized travel demand constraints and public transportation supply constraints; establishes an optimal public transportation motorization share rate model, and determines the optimal share rate value. The invention results can be applied to public transportation development planning in small and medium-sized cities, improving the scientificity and rationality of public transportation share rate target setting.

[0214] In addition to the above embodiments, the present invention may also have other implementations. Any technical solution formed by equivalent replacement or equivalent transformation falls within the scope of protection required by the present invention.

Claims

1. A method for calculating the optimal public transport motorization share rate in small and medium-sized cities, characterized by: The following steps are included S1. Determine the composition of the motorized transportation system in small and medium-sized cities and determine the traffic allocation parameters based on the characteristics of motorized transportation allocation; S2. Determine the time characteristics of motorized travel based on traffic supply and demand characteristics and traffic allocation parameters; S3. Determine the optimization index for the motorized public transport share ratio, and construct the optimization objective function and constraints based on the characteristics of traffic supply and demand, motorized travel time, and motorized mode. S4. Establish a system optimal bus motorization share model based on the optimization objective function and constraints; S5. Solve the optimal public transport motorization sharing rate model based on the CRITIC-ideal point method and determine the optimal sharing rate value; In step S1, the motorized transportation system of small and medium-sized cities includes conventional public transportation and automobile transportation; Motorized traffic distribution characteristics include the length of each road segment, the capacity of each segment, the amount of car traffic carried by each segment, and the amount of bus traffic carried by each segment. Traffic distribution parameters include the proportion of motorized traffic carried by roads of different grades and the traffic distribution imbalance coefficient; In step S2, traffic supply and demand characteristics include road network capacity of various levels, demand for motorized travel, average motorized travel distance, average car passenger load factor, bus operating mileage per unit time, average bus walking distance, average bus departure interval, average bus stop spacing, average walking speed of travelers, and the proportion of new energy cars and buses; In step S3, the optimization indicators of the public transport motorization share rate include total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident costs, and total carbon emissions; The characteristics of motorization modes include the maximum passenger capacity of buses, fuel consumption of cars and buses, fuel consumption prices of cars and buses, pollution emission equivalent values ​​of cars and buses, external costs of accidents, electricity consumption of new energy cars and buses, electricity consumption prices, and carbon emission factors of the power grid.

2. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: The calculation method for the proportion of motorized traffic volume borne by roads of different grades is as follows: Q ij =Q car，ij +μ bus Q bus，ij Among them, i is the road grade, j is the road section number, η i is the proportion of motorized driving volume on grade i roads, L ij is the length of the road section j in level i, unit: km; Q ij is the equivalent traffic volume of road section j in level i, unit: pcu / h; Q car，ij is the car traffic volume of road section j in level i, unit: pcu / h; Q bus,ij is the bus traffic volume on road section j in level i, unit: veh / h; μ bus is the bus equivalent coefficient, unit: pcu / veh; The traffic distribution imbalance coefficient is the ratio of the actual traffic distribution to the congestion delay time under the condition of uniform traffic distribution. The calculation method is: Among them, ρ i is the traffic distribution imbalance coefficient of grade i road, VOC ij is the traffic supply-demand ratio of road section j in level i, is the average supply-demand ratio of grade i roads, C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of section j in level i, in km.

3. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: In step S2, the motorized travel time characteristics include The normal time consumed by vehicles per unit mileage is the average time used by buses or cars to travel per unit mileage in the road network without considering the impact of congestion. The calculation method is: Where t0 is the normal time consumed by a vehicle per unit mileage in the road network, unit: h / km; η i is the proportion of motorized driving volume on grade i roads, V d，i is the design speed of grade i road, unit: km / h; The average waiting time for bus travel is expressed as Among them, t t，w is the average waiting time for bus trips, unit: h; H is the average bus departure interval; The average walking connection time for bus trips is expressed as t t,a =D t，a / V w Among them, t t，a is the average walking connection time for bus trips, unit: h; D t，a is the average walking distance to the bus station, unit: km; V w is the average walking speed of travelers, unit: km / h; According to the extra time consumed by vehicle congestion, the function of vehicle congestion consumption time per unit mileage is constructed with the bus motorization share rate as the independent variable: Among them, t cong (R T ) is the public transport motorization share rate R T The time consumed by vehicles in congestion per unit mileage, unit: h / km; its value is the extra time consumed by buses or cars per unit mileage in the road network due to congestion when considering the impact of congestion; R T is the motorization share of public transportation, μ bus is the bus equivalent coefficient, unit: pcu / veh; S transit Q is the bus operating mileage per unit time, unit: km / h; m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; δ c is the average passenger capacity of cars, unit: person / pcu; N i is the road network capacity of level i road, unit: pcu km / h; ρ i is the traffic distribution imbalance coefficient of grade i road, η i is the proportion of motorized driving volume on grade i roads, V d，i is the design speed of grade i road, unit: km / h; C i is the traffic capacity of grade i road, unit: pcu / h; L ij is the length of the road section j in level i, unit: km; The average bus stop time function is constructed with the bus motorization share rate as the independent variable: Among them, t t，s (R T ) is the motorization share of public transportation R T The average bus stop time, unit: h / stop; its value is the extra time consumed by the bus at the stop; R T is the motorization share of public transportation, Q m D is the demand for motorized travel, unit: person-times / h; S is the average distance between bus stops, unit: km; S transit It is the bus operating mileage per unit time, unit: km / h.

4. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: In step S3, the construction of the optimization objective function includes the following steps: S3.

1. Sum the regular time spent in the car, congestion time, bus stop time, walking time, and waiting time of all motorized travelers to construct a total time consumption function, which is expressed as follows: Among them, T total (R T ) is the public transport motorization share rate R T The total time consumption of all motorized travelers at this time, unit: h; R T The motorization share of public transportation; S3.

2. Use the passenger density of travelers in the car to represent the comfort consumption value and construct the total comfort consumption function, which is expressed as follows: Among them, Y(R T ) is the public transport motorization share rate R T Total comfort consumption per hour, unit: km·person·person / m 2 ; R T is the motorization share of public transportation, A c The available space for passengers or drivers in a car, unit: m 2 ; A t The available space for passengers in the bus, unit: m 2 ; S3.

3. Using the sum of the total energy costs of buses and cars, construct a total energy cost function, which is expressed as follows: Among them, W energy (R T ) is the public transport motorization share rate R T Total energy consumption cost per hour, unit: yuan; R T is the motorization share of public transportation, F c is the fuel consumption of the car, unit: L / 100km; F t is the fuel consumption of the bus, unit: L / 100km; C fuel，c is the gasoline price for cars, unit: Yuan / L; C fuel，t is the price of diesel for buses, unit: Yuan / L; r new，c is the proportion of new energy vehicles, r new，t The proportion of new energy buses; S3.

4. Use the sum of the pollutant equivalents emitted by buses and cars to construct a total pollution emission function, as shown below: Among them, P(R T ) is the public transport motorization share rate R T Total pollution emissions per hour, unit: g; R T is the motorization share of public transportation, P car is the equivalent value of car pollutant emissions, unit: g / km; P transit is the pollutant emission equivalent value of buses, unit: g / km; r new，c is the proportion of new energy vehicles, r new，t The proportion of new energy buses; S3.

5. Use the sum of the external accident costs caused by buses and cars to construct a total accident cost function, which is expressed as follows: Among them, W acc (R T ) is the public transport motorization share rate R T Total accident cost per hour, unit: yuan; R T is the motorization share of public transportation, Acc car is the external cost of car accidents, unit: yuan / veh·km; Acc transit is the external cost of bus accidents, unit: yuan / veh·km; S3.

6. Use the sum of carbon emissions from buses and cars to construct a total carbon emissions function, as shown below: in, The motorization share of public transportation is R T Total carbon emissions per hour, unit: kg; R T is the motorization share of public transportation, E c E is the power consumption of new energy vehicles, unit: kWh / 100km; t is the power consumption of new energy buses, unit: kWh / 100km; EF is the carbon emission factor of the power grid, unit: tCO2 / MWh; r new，c is the proportion of new energy vehicles, r new,t The proportion of new energy buses.

5. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: In step S3, the constraint condition is set to limit the value of the bus motorization share rate based on the overall bus supply, and the expression is as follows: R T ∈R,R={R T |Q m R T (D m -D t，a )≤S transit C transit ,0≤R T ≤1} Among them, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate; Q m D is the demand for motorized travel, unit: person-times / h; m is the average distance of motorized travel, unit: km; D t，a is the average walking distance to the bus station, unit: km; S transit C is the bus operating mileage per unit time, unit: km / h; transit The maximum passenger capacity of a public bus, unit: persons / veh.

6. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: In step S4, the optimal bus motorization share model is constructed with the bus motorization share as the decision variable, the minimization of total time consumption, total comfort consumption, total energy consumption cost, total pollution emissions, total accident cost and total carbon emissions as the optimization goal, and the overall bus supply limit as the constraint condition for multi-objective optimization modeling. The model is expressed as follows Among them, f j (R T ) is the objective function of index j, R T is the public transport motorization share rate, R is the feasible region of the public transport motorization share rate; T total is the total time consumption, Y is the total comfort consumption, W energy Total energy cost, P(R T ) is the total pollution emission, W acc is the total accident cost, is the total carbon emissions.

7. The method for calculating the optimal public transportation motorization share rate for small and medium-sized cities according to claim 1 is characterized by: In step S5, solving the optimal public transport motorization sharing rate model based on the CRITIC-ideal point method includes the following steps: S5.

1. Calculate the function values ​​of each optimization indicator under different travel demand and sharing rate scenarios to form a set of objective function value matrices. B=[b ij ] n×6 Among them, B is the objective function value matrix, b ij is the function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6; S5.

2. Dimensionless process the objective function value matrix B to obtain the matrix, A=[a ij ] n×6 , Among them, A is the dimensionless objective function value matrix, a ij is the dimensionless function value of the optimization index j in the i-th record, i = 1, 2, ..., n; j = 1, 2, ..., 6; S5.

3. Based on the dimensionless objective function value matrix, calculate the standard deviation of each indicator. The calculation method is as follows: Among them, σ j is the standard deviation of index j, j = 1, 2, ..., 6; S5.

4. Based on the dimensionless objective function value matrix, calculate the correlation coefficient matrix between each indicator. R＝[r ij ] 6×6 Among them, R is the correlation coefficient matrix between each indicator, r ij is the correlation coefficient between the optimization indicators i and j, i, j = 1, 2, ..., 6; S5.

5. Calculate the information content of each optimization indicator. The calculation method is as follows: Among them, C j is the information content of index j. The larger the value, the greater the role of the index in the entire evaluation index system, where j = 1, 2, ..., 6; S5.

6. The weight value of each indicator is obtained by weighted calculation of the information amount of the optimization indicator. The calculation method is as follows: Among them, ω j is the weight value of indicator j; S5.

7. Based on the weight values ​​of each objective function, construct the Euclidean distance function between the standardized index function values ​​and the optimal index value. Among them, D(R T ) is the public transport motorization share rate R T The Euclidean distance between the objective function value and the optimal value, f j (R T ) is the objective function of index j, f z,j (R T ) is the dimensionless objective function of index j, R is the feasible domain of the public transport motorization share rate; S5.

8. Using the Euclidean distance function as the single objective function to be optimized, calculate the optimal public transport motorization share rate. The calculation method is as follows: Among them, R T * is the optimal public transport motorization share rate.

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