Urban bus rapid transit low-carbon dynamic scheduling method
By establishing a dynamic scheduling model of joint control of vehicle speed and station, the problem of high carbon emissions of urban rapid bus vehicles has been solved, low-carbon operation and punctual improvement have been achieved, and the quality of bus services has been improved.
Patent Information
- Application Number
- CN202510861440.4
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-06-25
- Publication Date
- 2025-09-02
AI Technical Summary
Urban rapid buses have high carbon emissions, and passengers have improved service quality requirements. The existing dynamic scheduling methods have failed to effectively reduce energy consumption and carbon emissions caused by frequent start-up and stoppage.
The top-down method is used to calculate carbon emissions, establish a dynamic scheduling model for joint control of vehicle speed and station, simplify the model through a linear method, and use branch bounding method or commercial solver to generate a BRT bus dynamic scheduling scheme for joint control of vehicle speed and station.
It reduces carbon emissions during urban rapid bus operation, improves vehicle punctuality and operational efficiency, and improves passengers' travel service quality.
Smart Images
Figure CN120580879A_ABST
Abstract
Description
Technical Field
[0001] The present invention relates to a dynamic scheduling technology, and in particular to a low-carbon dynamic scheduling method for urban rapid transit. Background Art
[0002] Bus Rapid Transit (BRT) is a highly efficient public transportation model centered around ground buses. Through dedicated closed lanes, an intelligent dispatching system, enclosed stations, and on-board ticket collection, BRT achieves rapid, high-capacity transportation similar to rail transit, with passenger flow reaching 20,000 to 30,000 passengers per hour in each direction. Its core features include independent right-of-way ensuring bus priority and a low-carbon fleet. Compared to traditional buses, BRT offers higher capacity, improved punctuality, and lower energy consumption, making it a key solution for alleviating traffic congestion and reducing carbon emissions.
[0003] Measuring carbon emissions is fundamental to optimizing the low-carbon scheduling of BRT. The IPCC 2006 Guidelines for National Greenhouse Gas Inventories provide two methods for calculating carbon dioxide emissions: the bottom-up method and the top-down method. The bottom-up method uses data on different vehicle types, energy consumption per mile, and mileage, but data collection is difficult and can result in large errors. The top-down method calculates carbon emissions based on the product of the carbon emission coefficients of various energy sources and the energy consumption of each. Its results are highly accurate and more adaptable to calculations in more refined scenarios such as acceleration and deceleration. Therefore, the top-down method is more widely used to measure carbon emissions during bus operation.
[0004] Dynamic bus scheduling is typically divided into two strategies: station control and inter-station control. Station control involves dynamically scheduling buses within specific bus stops along the route through methods such as station control and skip-station control. Inter-station control involves controlling buses between stops through methods such as speed guidance and intersection signal priority. Common dynamic scheduling methods for BRT include station control, speed guidance, and signal priority. These methods work together to ensure efficient operation and low carbon emissions of the BRT system.
[0005] Because BRT bus systems typically operate in urban core areas and serve as the backbone of the city's bus network, they experience high passenger volumes. On-time arrival and smooth operation directly impact passenger travel efficiency and public transportation satisfaction. Furthermore, routes often pass through numerous bus stops and intersections, requiring frequent acceleration and braking. Relevant research indicates that frequent starts and stops significantly increase vehicle energy consumption, leading to increased carbon emissions. Therefore, while ensuring the quality of BRT bus service, it is necessary to implement flexible dynamic scheduling measures to further reduce carbon emissions during BRT operation. Summary of the Invention
[0006] Aiming at the current problems of high carbon emissions from urban rapid transit buses and increasing passenger demand for service quality, a low-carbon dynamic scheduling method for urban rapid transit was proposed.
[0007] The technical solution of the present invention is:
[0008] A low-carbon dynamic scheduling method for urban rapid transit includes the following steps:
[0009] Step 1: The objective function is to minimize carbon emissions, bus arrival punctuality deviation, intersection delay, and interval speed deviation during bus operation. Carbon emissions are calculated using a top-down approach based on electricity consumption and electricity carbon emission coefficient.
[0010] Step 2: Comprehensively consider the dwell time, intersection signal timing, and speed fluctuation constraints to establish a bus dynamic scheduling model that combines speed and dwell time control.
[0011] Step 3: In the process of solving the model, simplify the model through linearization method and solve it using branch and bound method or commercial solver; finally, generate a BRT bus dynamic scheduling scheme with joint control of vehicle speed and station stay.
[0012] Furthermore, in step 1, the objective function is established as follows:
[0013] The number of stations in a single direction of a BRT line is set to J, the number of intersections it passes through is set to K, and the number of sections the line is divided into is set to I. Punctuality, intersection efficiency, passenger comfort, and carbon emissions are used as BRT dynamic scheduling optimization objectives. By setting priority factors for each objective function, multiple objectives are converted into a single objective function.
[0014] The first is punctuality, which is expressed as the deviation between the actual arrival time and the expected arrival time; the second is intersection operation efficiency, which is expressed as intersection delay; the third is ride comfort, which is expressed as the deviation between the actual speed and the expected speed in the section; the fourth is carbon emissions, including those generated during normal vehicle driving and acceleration and deceleration at intersections and bus stops; according to the priority order of carbon emissions, punctuality, intersection delay, and comfort, different priority factors P1, P2, P3, P4 and deviation weights w are set. 11 、w 12 、w 31 、w 32 , establish the objective function:
[0015]
[0016] Where: i represents the section of the BRT line, that is, the section between two stations; j represents the station of the BRT line; k represents the intersection along the BRT line; w11 、w 12 Respectively represent the weights of BRT vehicles arriving early and late at the station; represent the deviation variables of BRT vehicles arriving early and late at the station respectively; The deviation variable indicates that the delay value of BRT vehicles at the intersection is greater than 0; w 31 、w 32 denote the weights of the BRT vehicle speed being lower or higher than the expected speed in section i; The deviation variables representing the actual speed of the BRT vehicle being lower or higher than the expected speed; E Q Indicates the carbon emissions during the operation of BRT vehicles, and uses the electricity carbon emission factor EF to calculate the carbon emissions of public buses;
[0017] The total carbon emissions of a bus are equal to the sum of the carbon emissions generated by the vehicle traveling at a constant speed in interval i and accelerating and decelerating at intersections and stations:
[0018]
[0019] Where: EF is the carbon emission factor of electricity, FC0 is the power consumption of the interval constant speed driving (kwh / h), a1 is the starting acceleration of the BRT vehicle (m / s 2 ); a2 is the braking acceleration of the BRT vehicle (m / s 2 ) ; FC1 is the unit energy consumption of the BRT vehicle in the accelerating state (kwh / s); FC2 is the unit energy consumption of the BRT vehicle in the decelerating state (kwh / s); L i Indicates the length of interval i in km; v i Indicates the running speed of interval i, in km / h.
[0020] Furthermore, in step 2, the constraints are established as follows:
[0021] According to the objective function composition, punctuality constraints, intersection delay constraints and interval operation speed constraints are established respectively;
[0022] Punctuality constraints
[0023] The BRT starting station only contains the departure time. The departure time of the first station should be as close as possible to the expected departure time:
[0024]
[0025] Where: t d1 Indicates the actual departure time of the BRT at the first stop, in seconds; Indicates the expected departure time of the BRT at the first stop; They represent the deviation of the actual departure time of the BRT at the first stop being earlier or later than the expected departure time;
[0026] The actual arrival time of the BRT at other stations should be as close as possible to the expected arrival time given in the timetable;
[0027]
[0028] Where: t aj Indicates the actual BRT arrival time; represents the expected arrival time; the actual arrival time of station j is t aj It is composed of the departure time of the upstream station, the total travel time between stations and the total delay of each intersection;
[0029]
[0030] Where: t dj represents the departure time of the bus at station j; D k is the delay at intersection k;
[0031] The departure time of BRT at other stations is calculated by the arrival time and the station time, and should not be earlier than the expected arrival time. The station time at station j is T j Should not be less than the time for picking up and dropping off passengers:
[0032]
[0033] Where: T j represents the bus's stay time at station j, in seconds; represents the boarding and alighting time at station j, in seconds. The station time consists of the boarding and alighting time and the additional station time.
[0034] Intersection delay constraints
[0035] In order to minimize the intersection delay, the corresponding objective constraint is obtained:
[0036]
[0037] BRT arrives at the intersection at time t ak If the intersection is red, the delay is the difference between the time when the green light turns on in the current cycle and the time when the BRT arrives. If the intersection is green, the delay is 0:
[0038]
[0039] Where: δ k is the signal cycle number of the current intersection k; The green light turns on for the current cycle; The red light start time of the current cycle; The time when the red light turns on in the next cycle; tak The time when the BRT arrives at the intersection is calculated using the departure time and running time of the previous station:
[0040]
[0041] The time when the red light starts in the signal cycle when the BRT arrives at the intersection The initial red light on time r of the intersection k and cycle length C k calculate:
[0042]
[0043] Among them, δ represents the total number of cycles experienced by the current intersection from the initial to the current moment;
[0044] The green light start time of the current signal cycle can be and red light duration R k Calculation, the default cycle starts from the red light:
[0045]
[0046] Section running speed constraint
[0047] To ensure smooth operation and reduce carbon emissions, the BRT section design speed should be as close to the expected speed as possible:
[0048]
[0049] In addition, considering the comfort of passengers and the convenience of drivers, the speed deviation between intervals and the speed difference between adjacent intervals should not be too large:
[0050]
[0051] Where: represents the expected speed of the bus in section i, in km / h; Δ 1i , Δ 2i , Δ 3i They represent the low-speed deviation constraint, high-speed deviation constraint, and speed difference constraint between two adjacent intervals in interval i, respectively, and the unit is km / h.
[0052] Furthermore, in step 3, the model solution is as follows:
[0053] By introducing the decision variable α, D k Linearization:
[0054]
[0055] Where: M is a sufficiently large positive number;
[0056] L i / v i It is also a nonlinear term and can be represented by fitting three piecewise functions, dividing the speed into three intervals: [1, 5], [5, 20], and [20, 60];
[0057]
[0058]
[0059] Where: f σ Indicates the use of 1 / v i Linearized auxiliary continuous decision variables, σ = 1, 2, 3, corresponding to the three speed intervals mentioned above; z σ Indicates the use of 1 / v i Linearized auxiliary 0-1 decision variables, σ=1,2,3, corresponding to the three speed intervals mentioned above; then 1 / v i The expression is as follows:
[0060]
[0061] Adopting the above linearization method makes the model solvable by branch and bound method or commercial solvers;
[0062] The final solution is the recommended operating speed v for BRT vehicles in each section of the line. i , and the optimal residence time T at each station j , that is, to generate a BRT bus dynamic scheduling plan that jointly controls vehicle speed and station stops.
[0063] The beneficial effects of the present invention are:
[0064] This method reduces carbon emissions generated during the operation of urban rapid transit through flexible and low-carbon bus dynamic scheduling, improves vehicle punctuality, and reduces single-vehicle delays, thereby improving the operational efficiency of bus companies and the quality of travel services for passengers. BRIEF DESCRIPTION OF THE DRAWINGS
[0065] Figure 1 This is a schematic diagram of the operation of the BRT section of the present invention. DETAILED DESCRIPTION
[0066] The present invention is described in detail below with reference to the accompanying drawings and specific embodiments. This embodiment is implemented based on the technical solution of the present invention, and provides a detailed implementation method and specific operation process, but the protection scope of the present invention is not limited to the following embodiments.
[0067] A low-carbon dynamic scheduling method for urban rapid transit buses (BRT) is proposed. Its objective function is to minimize carbon emissions, bus arrival punctuality deviation, intersection delays, and speed deviation during bus operation. Carbon emissions are calculated using a top-down approach using electricity consumption and the electricity carbon emission coefficient. Constraints such as dwell time, intersection signal timing, and speed fluctuation are also considered, leading to a dynamic bus scheduling model that combines speed and dwell time control. The model is simplified through linearization and solved using a branch-and-bound approach or a commercial solver.
[0068] 1. Description of BRT dynamic scheduling strategy
[0069] The number of stations in the one-way direction of the BRT line is set to J, the number of intersections it passes through is K, and the number of sections it is divided into is I. The operation process of BRT in three adjacent sections is used as an example to illustrate the combined control strategy of vehicle speed and station station. Figure 1 shown.
[0070] After the vehicle completes the boarding and unloading at station j, it will travel at the desired speed in section i to intersection k, where it will encounter a red light and cause a delay. Consider implementing a station control strategy at station j, taking into account the boarding and unloading time. The station time T is generated by factors such as the downstream station schedule and intersection signal timing. j , and then the bus at t dj After the BRT leaves at the desired speed in section i, it can reach intersection k when the green light turns on. Run, and arrive at intersection k+1 during the green light period, so the actual speed v i+1 and expected speed Equal. In interval i+2, at the desired speed Arriving at station j+1 later than the planned timetable Considering the speed of the vehicle in the adjustment interval i+2, by controlling the actual vehicle speed v i+2 Expected speed Deviations are made to ensure that the BRT arrives at downstream stations as punctually as possible while maintaining a reasonable speed.
[0071] 2. Model building
[0072] (1) Objective function
[0073] Punctuality, intersection operation efficiency, passenger comfort, and carbon emissions are used as BRT dynamic scheduling optimization targets. By setting the priority factors of each objective function, multiple objectives are converted into a single objective function.
[0074] The first is punctuality, which is expressed as the deviation between the actual arrival time and the expected arrival time; the second is intersection operation efficiency, which is expressed as intersection delay; the third is ride comfort, which is expressed as the deviation between the actual speed and the expected speed in the section; the fourth is carbon emissions, including those generated during normal vehicle driving and acceleration and deceleration at intersections and bus stops. According to the priority order of carbon emissions, punctuality, intersection delay, and comfort, different priority factors P1, P2, P3, P4 and deviation weights w are set. 11 、w 12 、w 31 、w 32 , establish the objective function:
[0075]
[0076] Where: i represents the section of the BRT line, that is, the section between two stations; j represents the station of the BRT line; k represents the intersection along the BRT line; w 11 、w 12 Respectively represent the weights of BRT vehicles arriving early and late at the station; represent the deviation variables of BRT vehicles arriving early and late at the station respectively; The deviation variable indicates that the delay value of BRT vehicles at the intersection is greater than 0; w 31 、w 32 denote the weights of the BRT vehicle speed being lower or higher than the expected speed in section i; The deviation variables representing the actual speed of the BRT vehicle being lower or higher than the expected speed; E Q It represents the carbon emissions during the operation of BRT vehicles. Although electric buses do not directly emit carbon dioxide during operation, part of the electricity generation process requires the combustion of fossil energy to release carbon dioxide. Therefore, the electricity carbon emission factor EF is used to calculate the carbon emissions of buses.
[0077] The total carbon emissions of a bus are equal to the sum of the carbon emissions generated by the vehicle traveling at a constant speed in interval i and accelerating and decelerating at intersections and stations:
[0078]
[0079] Where: EF is the carbon emission factor of electricity, FC0 is the power consumption of the interval constant speed driving (kwh / h), a1 is the starting acceleration of the BRT vehicle (m / s 2 ); a2 is the braking acceleration of the BRT vehicle (m / s 2 );FC1 is the unit energy consumption of BRT vehicle in accelerating state (kwh / s); FC2 is the unit energy consumption of BRT vehicle in decelerating state (kwh / s). i Indicates the length of interval i in km; v iIndicates the running speed of interval i, in km / h.
[0080] (2) Constraints
[0081] According to the composition of the objective function, punctuality constraints, intersection delay constraints and interval operating speed constraints are established respectively.
[0082] 1) Punctuality constraints
[0083] The BRT starting station only contains the departure time. The departure time of the first station should be as close as possible to the expected departure time:
[0084]
[0085] Where: t d1 Indicates the actual departure time of the BRT at the first stop, in seconds; Indicates the expected departure time of the BRT at the first stop; They represent the deviation of the actual departure time of the BRT at the first stop being earlier or later than the expected departure time.
[0086] The actual arrival time of BRT at other stations should be as close as possible to the expected arrival time given in the timetable.
[0087]
[0088] Where: t aj Indicates the actual BRT arrival time; represents the expected arrival time; the actual arrival time of station j is t aj It consists of the departure time of the upstream station, the total running time between stations and the total delay of each intersection.
[0089]
[0090] Where: t dj represents the departure time of the bus at station j; D k is the delay at intersection k.
[0091] The departure time of BRT at other stations is calculated by the arrival time and the station time, and should not be earlier than the expected arrival time. The station time at station j is T j Should not be less than the time for picking up and dropping off passengers:
[0092]
[0093] Where: T j represents the bus's stay time at station j, in seconds; It represents the boarding and alighting time at station j, in seconds. The station time consists of the boarding and alighting time and the additional station time.
[0094] 2) Intersection delay constraints
[0095] In order to minimize the intersection delay, the corresponding objective constraint is obtained:
[0096]
[0097] BRT arrives at the intersection at time t ak If the intersection is red, the delay is the difference between the time the green light turns on in the current cycle and the time the BRT arrives. If the intersection is green, the delay is 0:
[0098]
[0099] Where: δ k is the signal cycle number of the current intersection k; The green light turns on for the current cycle; The red light start time of the current cycle; The time when the red light turns on in the next cycle; t ak The time when the BRT arrives at the intersection is calculated using the departure time and running time of the previous station:
[0100]
[0101] The red light start time of the signal cycle when the BRT arrives at the intersection The initial red light on time r of the intersection k and cycle length C k calculate:
[0102]
[0103] Among them, δ represents the total number of cycles experienced by the current intersection from the initial time to the current time.
[0104] The green light start time of the current signal cycle can be and red light duration R k Calculation, the default cycle starts from the red light:
[0105]
[0106] 3) Interval operating speed constraints
[0107] To ensure smooth operation and reduce carbon emissions, the BRT section design speed should be as close to the expected speed as possible:
[0108]
[0109] In addition, considering the comfort of passengers and the convenience of drivers, the speed deviation between intervals and the speed difference between adjacent intervals should not be too large:
[0110]
[0111] Where: represents the expected speed of the bus in section i, in km / h; Δ 1i , Δ 2i , Δ 3i They represent the low-speed deviation constraint, high-speed deviation constraint, and speed difference constraint between two adjacent intervals in interval i, respectively, and the unit is km / h.
[0112] 3. Model solution
[0113] Since the established model D k The expression is a piecewise function and cannot be solved directly by linear programming. Therefore, by introducing the decision variable α, D k Linearization:
[0114]
[0115] Where: M is a sufficiently large positive number.
[0116] L i / v i It is also a nonlinear term and can be represented by fitting three piecewise functions, dividing the speed into three intervals: [1, 5], [5, 20], and [20, 60].
[0117]
[0118]
[0119] Where: f σ Indicates the use of 1 / v i Linearized auxiliary continuous decision variables, σ = 1, 2, 3, corresponding to the three speed intervals mentioned above; z σ Indicates the use of 1 / v i The linearized auxiliary 0-1 decision variables, σ=1, 2, 3, correspond to the three speed intervals mentioned above. Then 1 / v i The expression is as follows:
[0120]
[0121] The linearization method described above makes the model solvable by branch and bound method or commercial solvers.
[0122] The final solution is the recommended operating speed v for BRT vehicles in each section of the line. i , and the optimal residence time T at each stationj , that is, to generate a BRT bus dynamic scheduling plan that jointly controls vehicle speed and station stops. Under the premise of meeting punctuality constraints, intersection delay constraints and interval operation speed constraints, it improves the punctuality rate, intersection operation efficiency, passenger comfort and reduces carbon emissions during BRT bus operation.
[0123] The above-described embodiment merely represents one embodiment of the present invention. While the description is relatively specific and detailed, it should not be construed as limiting the scope of the patent. It should be noted that a person skilled in the art would be able to make various modifications and improvements without departing from the spirit of the present invention, and these modifications and improvements fall within the scope of protection of the present invention. Therefore, the scope of protection of the patent for this invention shall be determined by the appended claims.
Claims
1. A low-carbon dynamic scheduling method for urban rapid transit, characterized in that: The following steps are involved: Step 1: The objective function is to minimize carbon emissions, bus arrival punctuality deviation, intersection delay, and interval speed deviation during bus operation. Carbon emissions are calculated using a top-down approach based on electricity consumption and electricity carbon emission coefficient. Step 2: Comprehensively consider the dwell time, intersection signal timing, and speed fluctuation constraints to establish a bus dynamic scheduling model that combines speed and dwell time control. Step 3: In the process of solving the model, simplify the model through linearization method and solve it using branch and bound method or commercial solver; finally, generate a BRT bus dynamic scheduling scheme with joint control of vehicle speed and station stay.
2. The low-carbon dynamic scheduling method for urban rapid transit according to claim 1 is characterized in that: In step 1, the objective function is established as follows: The number of stations in a single direction of a BRT line is set to J, the number of intersections it passes through is set to K, and the number of sections the line is divided into is set to I. Punctuality, intersection efficiency, passenger comfort, and carbon emissions are used as BRT dynamic scheduling optimization objectives. By setting priority factors for each objective function, multiple objectives are converted into a single objective function. The first is punctuality, which is expressed as the deviation between the actual arrival time and the expected arrival time; the second is intersection operation efficiency, which is expressed as intersection delay; the third is ride comfort, which is expressed as the deviation between the actual speed and the expected speed in the section; the fourth is carbon emissions, including those generated during normal vehicle driving and acceleration and deceleration at intersections and bus stops; according to the priority order of carbon emissions, punctuality, intersection delay, and comfort, different priority factors P1, P2, P3, P4 and deviation weights w are set. 11 、w 12 、w 31 、w 32 , establish the objective function: Where: i represents the section of the BRT line, that is, the section between two stations; j represents the station of the BRT line; k represents the intersection along the BRT line; w 11 、w 12 Respectively represent the weights of BRT vehicles arriving early and late at the station; represent the deviation variables of BRT vehicles arriving early and late at the station respectively; The deviation variable indicates that the delay value of BRT vehicles at the intersection is greater than 0; w 31 、w 32 denote the weights of the BRT vehicle speed being lower or higher than the expected speed in section i; The deviation variables representing the actual speed of the BRT vehicle being lower or higher than the expected speed; E Q Indicates the carbon emissions during the operation of BRT vehicles, and uses the electricity carbon emission factor EF to calculate the carbon emissions of public buses; The total carbon emissions of a bus are equal to the sum of the carbon emissions generated by the vehicle traveling at a constant speed in interval i and accelerating and decelerating at intersections and stations: Where: EF is the carbon emission factor of electricity, FC0 is the power consumption of the interval constant speed driving (kwh / h), a1 is the starting acceleration of the BRT vehicle (m / s 2 ); a2 is the braking acceleration of the BRT vehicle (m / s 2 ) ; FC1 is the unit energy consumption of the BRT vehicle in the accelerating state (kwh / s); FC2 is the unit energy consumption of the BRT vehicle in the decelerating state (kwh / s); L i Indicates the length of interval i in km; v i Indicates the running speed of interval i, in km / h.
3. The low-carbon dynamic scheduling method for urban rapid transit according to claim 1 is characterized in that: In step 2, the constraints are established as follows: According to the objective function composition, punctuality constraints, intersection delay constraints and interval operation speed constraints are established respectively; Punctuality constraints The BRT starting station only contains the departure time. The departure time of the first station should be as close as possible to the expected departure time: Where: t d1 Indicates the actual departure time of the BRT at the first stop, in seconds; Indicates the expected departure time of the BRT at the first stop; They represent the deviation of the actual departure time of the BRT at the first stop being earlier or later than the expected departure time; The actual arrival time of the BRT at other stations should be as close as possible to the expected arrival time given in the timetable; Where: t aj Indicates the actual BRT arrival time; represents the expected arrival time; the actual arrival time of station j is t aj It is composed of the departure time of the upstream station, the total travel time between stations and the total delay of each intersection; Where: t dj represents the departure time of the bus at station j; D k is the delay at intersection k; The departure time of BRT at other stations is calculated by the arrival time and the station time, and should not be earlier than the expected arrival time. The station time at station j is T j Should not be less than the time for picking up and dropping off passengers: Where: T j represents the bus's stay time at station j, in seconds; T j (0) represents the boarding and alighting time at station j, in seconds. The station time consists of the boarding and alighting time and the additional station time. Intersection delay constraints In order to minimize the intersection delay, the corresponding objective constraint is obtained: BRT arrives at the intersection at time t ak If the intersection is red, the delay is the difference between the time when the green light turns on in the current cycle and the time when the BRT arrives. If the intersection is green, the delay is 0: Where: δ k is the signal cycle number of the current intersection k; The green light turns on for the current cycle; The red light start time of the current cycle; The time when the red light turns on in the next cycle; t ak The time when the BRT arrives at the intersection is calculated using the departure time and running time of the previous station: The time when the red light starts in the signal cycle when the BRT arrives at the intersection The initial red light on time r of the intersection k and cycle length C k calculate: Among them, δ represents the total number of cycles experienced by the current intersection from the initial to the current moment; The green light start time of the current signal cycle can be and red light duration R k Calculation, the default cycle starts from the red light: Interval operating speed constraints To ensure smooth operation and reduce carbon emissions, the BRT section design speed should be as close to the expected speed as possible: In addition, considering the comfort of passengers and the convenience of drivers, the speed deviation between intervals and the speed difference between adjacent intervals should not be too large: Where: represents the expected speed of the bus in section i, in km / h; Δ 1i , Δ 2i , Δ 3i They represent the low-speed deviation constraint, high-speed deviation constraint, and speed difference constraint between two adjacent intervals in interval i, respectively, and the unit is km / h.
4. The low-carbon dynamic scheduling method for urban rapid transit according to claim 1 is characterized in that: In step 3, the model solution is as follows: By introducing the decision variable α, D k Linearization: Where: M is a sufficiently large positive number; L i / v i It is also a nonlinear term and can be represented by fitting three piecewise functions, dividing the speed into three intervals: [1, 5], [5, 20], and [20, 60]; Where: f σ Indicates the use of 1 / v i Linearized auxiliary continuous decision variables, σ = 1, 2, 3, corresponding to the three speed intervals mentioned above; z σ Indicates the use of 1 / v i Linearized auxiliary 0-1 decision variables, σ=1,2,3, corresponding to the three speed intervals mentioned above; then 1 / v i The expression is as follows: Adopting the above linearization method makes the model solvable by branch and bound method or commercial solvers; The final solution is the recommended operating speed v for BRT vehicles in each section of the line. i , and the optimal residence time T at each station j , that is, to generate a BRT bus dynamic scheduling plan that jointly controls vehicle speed and station stops.