A method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic

Abstract

The present invention discloses a method for constructing a vehicle micro-kinematic model for quantifying the ecological cost of road network traffic, and the steps are as follows: 1) a micro-motion characterization system for road section vehicles; 2) functional segment division of spatial resources for road sections between adjacent intersections; 3) modeling of following behaviors between vehicles in different functional segments; 4) modeling of lateral lane-changing behaviors between vehicles in interlaced lane-changing areas; 5) modeling of vehicle intersection driving decisions; 6) second-level calculation of the ecological cost of road section traffic, and calculating the second-level instantaneous operating parameters of the vehicle during operation as parameter input to calculate the ecological cost of road network traffic. The present invention not only solves the problem of unrecognizable and uncalculable objective functions of ecologically oriented optimization methods in the field of traffic control and management, but also proposes a set of high-precision and high-reliability measurement methods for micro-traffic flow delays, emissions and energy consumption based on operation sequential chains, and quantifies micro-behaviors such as driving action feedback responses of vehicles in the road network.

Description

Technical Field

[0001] The present invention relates to the field of traffic micro-simulation, and more specifically, to a method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic. Background Art

[0002] With the continuous development of urbanization and urban expansion, motorization and accessibility, urban traffic congestion, energy consumption, emissions and accidents have restricted the development of the economy and society. However, due to the high mobility, multiple emission entities and complex traffic behaviors, it is difficult to reduce carbon emissions, which has always been a global problem. Therefore, reducing vehicle delays and reducing traffic emissions and energy consumption has been one of the hot issues that have been continuously concerned in the field of traffic management and control in recent years.

[0003] With the introduction of the concept of intelligent transportation system, the exploration of using information, communication and control technology to deal with traffic congestion also began, focusing on safety, convenience, high carrying capacity and rapidity, but less on energy conservation and emission reduction. At the beginning of this century, the European Community, represented by the Netherlands, took the lead in proposing ecological driving, upgrading the focus to energy conservation and emission reduction of vehicles.

[0004] In recent years, relevant research results at home and abroad have mainly focused on:

[0005] (1) A simple index model based on delay ratio, energy consumption ratio and emission ratio was initially established, and this was used as the optimization target to consider the traffic optimization problem under complex environmental indicators. Its technical defect is that it ignores the display of the comprehensive cost-effectiveness of delay, energy consumption and emission.

[0006] (2) The delay, energy consumption and emissions are estimated by using the macroscopic road section vehicle status, which simply relies on the average speed or stop-start status of the road section to make numerical estimates at the macro level. Its technical defect is that it ignores the key influence of the vehicle's instantaneous working conditions (including constant speed-deceleration-idling-stationary, following, lane changing, driver-signal light feedback response and other microscopic behaviors).

[0007] (3) Using microscopic traffic simulators such as TRANSIMS to simulate vehicle driving, the vehicle movement data is obtained from the consumption and emission estimation modules built into the traffic simulation and signal optimization tools. The technical defect is that it ignores the adaptability to China's actual traffic scenarios.

[0008] In this regard, this paper will give a method for constructing a vehicle micro-kinematic model for quantifying the ecological cost of road network traffic, analyze the interference of factors such as traffic lights, neighboring vehicles, and road conditions when vehicles are running in the road network, reveal the spatial movement laws of vehicles at intersections and road sections, and extract key parameters and mathematical expressions for accurately calculating delays, energy consumption and emissions of fuel vehicles and electric vehicles. It abandons the traditional traffic control framework that ignores the benefits of energy conservation and emission reduction, and solves the problem of being unable to explicitly express the quantitative relationship between the objective function and the optimization parameters. Summary of the invention

[0009] The purpose of the present invention is to consider the comprehensive cost-effectiveness of delays, energy consumption and emissions generated during vehicle operation from a microscopic level, and to provide a method for constructing a vehicle micro-kinematic model for quantifying the ecological cost of road network traffic; specifically, while distinguishing the proportion of fuel vehicles and electric vehicles, the road sections between adjacent intersections are divided into detailed functional stages, the influence of the microscopic driving state of the vehicle under the driving conditions between the road sections on the overall traffic flow state is studied, a dynamic model of the vehicle between the intersection sections is established, the key parameters of the instantaneous working conditions at the second level during the operation of the vehicle (such as instantaneous speed, acceleration / deceleration, etc.) are accurately obtained, the entropy weight method is used to calibrate the weight coefficients of various indicators, and the ecological cost of the vehicle is calculated based on the weighted weights according to the converted pollution equivalent number, energy consumption and delay value.

[0010] The present invention discloses a method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic, comprising the following steps:

[0011] S1. Microscopic motion characterization system for road sections: Based on the spatial resource division of road sections, the driving behaviors of different vehicles are modeled, the characteristic parameters of vehicle motion are calculated, and the traffic ecological cost is calculated in seconds;

[0012] S2, road section spatial resource division: select the target road section between adjacent intersections through the segment prediction method to divide the spatial resource of vehicle movement trajectory;

[0013] S3. Modeling of vehicle-to-vehicle following behavior: Based on the motion characteristics between the leading vehicle and the following vehicle, a mathematical modeling and simulation method is used to determine an extended following model that fully considers the safe headway time between vehicles;

[0014] S4. Lane-changing behavior modeling between vehicles: Based on the longitudinal displacement and lateral displacement motion characteristics of the vehicle lane-changing, a mathematical modeling simulation method is used to fully consider the safe headway time to determine the lane-changing behavior model;

[0015] S5, Vehicle intersection driving decision modeling: Based on the signal control of the downstream intersection, a second-by-second calculation method is used to determine the decision model for vehicles passing through the stop line;

[0016] S6. Calculation of road section traffic ecological cost in seconds: Estimate the instantaneous operating parameters of the vehicle during operation based on the vehicle operation sequential chain kinematic model.

[0017] As a preferred technical solution: Step S1 is specifically as follows:

[0018] S101, dividing the road sections between adjacent intersections into detailed functional stages, and performing spatial trajectory analysis on the operation of vehicles based on different driving behaviors in each functional partition area; the functional stages are divided into: free driving area, weaving lane change area, prohibited lane change area, and conflict driving area;

[0019] S102, modeling the driving behaviors of different vehicles, analyzing vehicles under different operating conditions, and establishing an extended car-following model that maintains the sequential chain motion of vehicles based on the interaction mechanism between different vehicle types;

[0020] S103. Study the instantaneous state of vehicle motion from a microscopic perspective, and accurately calculate the key parameters of the instantaneous working condition of the vehicle in the second level during operation based on the position, speed and acceleration data of the vehicle throughout the entire process of passage;

[0021] S104, quantifying the calculated key parameters of the instantaneous working condition at the second level to calculate the traffic ecological cost at the second level.

[0022] As a preferred technical solution: Step S2 is specifically as follows:

[0023] S201. During the operation of the vehicles, the front vehicle between two longitudinally adjacent vehicles is defined as the leading vehicle, and the movement state of the rear vehicle is affected by the front vehicle, and the rear vehicle is defined as the following vehicle; on a road section without signal control, the following vehicle between two adjacent vehicles will follow the extended following model to follow the leading vehicle, and accelerate or decelerate within the speed range specified on the road section to ensure traffic efficiency while maintaining a safe following distance, and all vehicles merging into the main road section will gradually reach a stable movement state; taking the entrance of the main road section as the starting point, a road section of sufficient length is selected to be divided into a free driving area;

[0024] S202: The stable motion state of the vehicle will be disrupted by the forced lane change behavior. The vehicle that needs to change lanes will obtain a lateral acceleration at this stage to complete the lateral change of the vehicle. During the lane change process, the longitudinal movement process of the lane-changing vehicle is affected by the preceding vehicle located in a different lane, and the lane change behavior of the vehicle will also disrupt the original stable following behavior of the following vehicle located in a different lane. The road section where the vehicle takes and completes the forced lane change behavior is selected as the weaving lane change area.

[0025] S203, the vehicle is approaching a signalized intersection and cannot change lanes due to the double solid line restriction of the lane; the vehicle is judged whether it can pass through the intersection smoothly according to the green light time and the current vehicle speed, and the vehicle that cannot pass through will slow down and stop before the stop line and wait for the next green light release; the prohibited lane change section before the stop line is selected as the prohibited lane change area;

[0026] S204. After passing the stop line, the vehicle selects different driving directions according to the travel purpose. Due to the different diversion directions of vehicles, the time it takes for the vehicle to completely leave the intersection and enter the next lane is also different. Taking the stop line as the starting point, the road section where the vehicle takes and completes the turning behavior is divided into the conflict driving area.

[0027] As a preferred technical solution: Step S3 is specifically as follows:

[0028] S301. In the free driving area, the vehicle that is not affected by other vehicles is defined as the lead vehicle. The lead vehicle will move freely within the speed range specified on the urban road section. The lead vehicle will run at the expected speed V. When the real-time speed v n ft) When its speed is less than V, the leading vehicle will adopt uniform acceleration behavior, with a constant acceleration of a f , the vehicle motion in this process follows the free motion model:

[0029]

[0030] In the formula, a n (t) and v n (t) respectively represent the acceleration and real-time speed of the nth vehicle at time t, n = 1, 2, ..., N; N represents the number of vehicles; a f represents the constant acceleration of the nth vehicle; V represents the expected speed of the leading vehicle;

[0031] The movement of the following vehicle will be affected by the movement of the leading vehicle. Based on the full speed difference following model, an extended following model that fully considers the safe headway time between vehicles is proposed.

[0032]

[0033] In the formula, Δx n (t) = x n-1 (t)-x n (t) represents the longitudinal distance between the nth vehicle and the n-1th vehicle; Δv n (t) = v n-1 (t)-v n (t) represents the longitudinal speed difference between the nth vehicle and the n-1th vehicle at time t; the n-1th vehicle is the leading vehicle of the nth vehicle; V(Δx n (t)) represents the optimal speed of the nth vehicle; l cis the average length of the vehicle; V1, V2, c1, c2, λ, κ are constants.

[0034] As a preferred technical solution: Step S4 is specifically as follows:

[0035] S401. Based on the full speed difference model, an extended following model considering the potential lane change behavior of the leading vehicle is proposed, defining δ n (t) is a binary variable related to the braking response of the n-1th vehicle, reflecting whether the n-1th vehicle takes deceleration measures; θ n (t) is the disturbance coefficient caused by the braking reaction of the n-1th vehicle:

[0036]

[0037] In the formula, a lat，n-1 (t) is the lateral displacement acceleration of the n-1th vehicle at time t; δ n (t) is a binary variable related to the braking response of the n-1th vehicle;

[0038] S402. In the weaving lane change area, all vehicles that need to perform forced lane change behavior are following vehicles; the lane change behavior is divided into two steps: longitudinal displacement and lateral displacement; the longitudinal following behavior of the lane changing vehicle is described by the extended following model in S301, and the longitudinal acceleration is affected by the target lane and the leading vehicle in the current lane; for safety considerations, the minimum value calculated below is selected:

[0039] a lon (t) = minκ(V(Δx n (t))-v n (t))+λΔ n (t)+θ n (t)δ n (t) (4)

[0040]

[0041] In the formula, a lon (t) is the longitudinal acceleration at time f; l represents the set of lane types, where L c L is the lane the vehicle is currently in. t is the target lane for the lane-changing vehicle; when l=L c When Δx n，l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the current lane, Δv n，l (t) represents the speed difference between the two vehicles; when l = L t When Δx n，l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the target lane, Δv n，l(t) is the speed difference between the two vehicles;

[0042] S403: In the lane-changing prohibited area, if the leading vehicle cannot pass the stop line within the green light time, the following vehicle still follows the leading vehicle according to formula f2) in S301;

[0043] S404. In the conflict driving area, the diversion movement of the turning vehicle is simplified into two steps: longitudinal displacement and lateral displacement. The only difference between the turning vehicle and the straight-moving vehicle is that the latter has a lateral acceleration related to the pressure on the pedal and the steering wheel angle. When the vehicle leaves the stop line, the vehicle's motion state has the following two conditions:

[0044] S404-1, when there is a vehicle in front horizontally, the vehicle acts as a following vehicle, and its following behavior can be described by equation (2) in step S301;

[0045] S404-2. When there is no vehicle in front horizontally, the vehicle acts as the lead vehicle and accelerates to reach the expected running speed V according to the free motion model.

[0046] As a preferred technical solution: Step S5 is specifically as follows:

[0047] S501. In a lane-changing prohibited area, if the leading vehicle passes the stop line within the green light time, the following vehicle needs to determine whether it can pass the stop line within the green light time. The determination variable is defined as follows:

[0048]

[0049]

[0050] In the formula, S n (t) is a variable that determines whether the vehicle can pass the stop line within the green light time, 1 represents yes, 0 represents no; Represents the phase difference between intersection i-1 and i; represents the phase difference between intersections i and j; C is the cycle length; is the green light start and end time of the kth stage; t s is the time when the nth vehicle reaches the stop line; l s is the position of the stop line;

[0051] S502: If the nth vehicle can pass the stop line within the green light time, then according to formula (2) in step S301, it still follows the longitudinal motion behavior of the leading vehicle; if the nth vehicle cannot pass the stop line within the green light time, then its deceleration and parking process follows the parking motion model:

[0052]

[0053] As a preferred technical solution: Step S6 is specifically as follows:

[0054] S601. Analyze the coupling characteristics between vehicle running trajectory and traffic flow, driving behavior, and signal timing parameters, and perform numerical simulation of vehicle spatial trajectory at intersection based on micro-kinematics theory;

[0055] S602. Accurately and comprehensively obtain the position, speed and acceleration data of the vehicle during the entire process of passage at a microscopic perspective based on the simulation results, and then draw a vehicle spatial trajectory diagram to visualize the vehicle movement process, and establish a quantitative relationship between key parameters and travel delays, energy consumption and gas emissions.

[0056] The beneficial effects of the present invention are as follows:

[0057] 1) The present invention obtains the vehicle's instantaneous operating parameters through microscopic vehicle motion behavior analysis, which solves the problem of high cost and difficulty in calculating vehicle motion parameters at the macro level. By constructing a microscopic vehicle kinematic model and combining mathematical methods to deeply analyze the coupling characteristics between vehicle operation trajectory and traffic flow, driving behavior, and signal timing parameters, the present invention is more in line with reality.

[0058] 2) The present invention can not only accurately obtain the delays, energy consumption and emission values ​​caused by vehicles passing through the target road network area, but also realize the unified indicator conversion of the values, accurately quantify the ecological cost of road network traffic, and realize the leap from numerical calculation to practical application.

[0059] 3) The present invention realizes the accurate calculation of ecological cost under offline control, and effectively solves the problem of uncalculatable objective function of ecologically oriented optimization methods in the field of traffic control and management (signal control, induced control, variable speed limit, etc.).

[0060] 4) The present invention proposes a high-precision and high-reliability measurement method for microscopic traffic flow delays, emissions and energy consumption based on an operation sequential chain, which quantifies the microscopic behaviors of vehicles in the road network, such as uniform speed-deceleration-idling-stationary, following, lane changing, and driver-signal light feedback response. BRIEF DESCRIPTION OF THE DRAWINGS

[0061] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0062] Figure 1 This is a flow chart of a method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic according to the present invention;

[0063] Figure 2 is a road network structure diagram of an embodiment of the present invention;

[0064] Figure 3 is a diagram of road network flow and signal control parameters according to an embodiment of the present invention;

[0065] Figure 4 is a diagram of the functional stage division structure of a road section according to an embodiment of the present invention;

[0066] Figure 5 is a vehicle kinematics model application diagram of this embodiment;

[0067] Figure 6 : is the vehicle space trajectory diagram obtained by simulation in this embodiment. DETAILED DESCRIPTION

[0068] In order to make those skilled in the art better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present application.

[0069] Reference to "embodiments" in this application means that a particular feature, structure, or characteristic described in conjunction with the embodiments may be included in at least one embodiment of the present application. The appearance of the phrase in various locations in the specification does not necessarily refer to the same embodiment, nor is it an independent or alternative embodiment that is mutually exclusive with other embodiments. It is explicitly and implicitly understood by those skilled in the art that the embodiments described in this application may be combined with other embodiments.

[0070] In a specific embodiment of the road network structure, such as Figure 2 As shown in Figure 1, it is known that there are two adjacent intersections with two-way four-lane traffic and their common signal cycle C is 120s. The traffic flow distribution and intersection signal control parameters within one cycle of the road network structure are shown in Figure 1. Figure 3 shown.

[0071] like Figure 1 As shown, this embodiment discloses a method for constructing a vehicle micro-kinematic model for quantifying the ecological cost of road network traffic, reveals the driving behaviors of different types of vehicles in mixed traffic flow, analyzes the coupling mechanism between various types of vehicles entering the road network from different directions, constructs numerical calculation and simulation of the spatial trajectory of road network vehicles, and efficiently and accurately estimates the position, speed and acceleration of the whole process, which specifically includes the following steps:

[0072] Step S1, specifically, according to the spatial resource division of the road section, the driving behaviors of different vehicles are modeled, the vehicle motion characteristic parameters are calculated, and the traffic ecological cost is calculated in seconds. The steps are as follows:

[0073] S101, such as Figure 4 As shown in the figure, the road sections between adjacent intersections are divided into detailed functional stages: free driving area, weaving lane change area, prohibited lane change area, and conflict driving area. In each functional partition area, the spatial trajectory analysis of the vehicle's operation is performed based on different driving behaviors.

[0074] S102. Modeling the driving behaviors of different vehicles, mainly analyzing vehicles under different operating conditions, and establishing an extended following model that maintains the sequential chain motion of vehicles based on the interaction mechanism between different vehicle types (leading vehicle, following vehicle).

[0075] S103. Study the instantaneous state of vehicle motion from a microscopic perspective, and accurately calculate the key parameters of the instantaneous operating conditions at the second level during the vehicle operation process based on the position, speed and acceleration data of the vehicle throughout the entire process of passage.

[0076] S104, quantifying the calculated key parameters of the instantaneous working condition at the second level to calculate the traffic ecological cost at the second level.

[0077] Step S2: dividing the road sections between adjacent intersections into detailed functional stages, and performing spatial trajectory analysis on the operation of vehicles in different divided stages based on different driving behaviors, the steps are as follows:

[0078] S201. During vehicle operation, the front vehicle between two longitudinally adjacent vehicles is defined as the leading vehicle, and the movement state of the rear vehicle is affected by the front vehicle, and the rear vehicle is defined as a following vehicle. On a road section without signal control, the following vehicle between two adjacent vehicles will follow the extended following model to follow the leading vehicle, accelerate or decelerate within the speed range specified on the road section, ensure traffic efficiency while maintaining a safe following distance, and all vehicles merging into the main road section will gradually reach a stable movement state. Take the entrance of the main road section as the starting point, and select a road section of sufficient length to divide it into a free driving area;

[0079] S202: The stable motion state of the vehicle will be disrupted by the forced lane change behavior. The vehicle that needs to change lanes will obtain a lateral acceleration at this stage to complete the lateral change of the vehicle. During the lane change process, the longitudinal movement of the lane-changing vehicle is affected by the preceding vehicle in a different lane, and the lane change behavior of the vehicle will also disrupt the original stable following behavior of the following vehicle in a different lane. The road section where the vehicle takes and completes the forced lane change behavior is divided into the weaving lane change area;

[0080] S203, the vehicle is approaching a signalized intersection and cannot change lanes due to the double solid line restriction. The driver will determine whether the vehicle can pass through the intersection smoothly based on the green light time and the current speed. Vehicles that cannot pass through will slow down and stop before the stop line and wait for the next green light. The prohibited lane change section before the stop line is selected as the prohibited lane change area.

[0081] S204: After the vehicle passes the stop line, the driver will choose different driving directions according to the purpose of travel. Due to the different diversion directions of vehicles, the time it takes for the vehicle to completely leave the intersection and enter the next lane is also different. Starting from the stop line, the road section where the vehicle takes and completes the turning behavior is divided into the conflict driving area.

[0082] Step S3, specifically, analyzes vehicles under different operating conditions, and establishes an extended following model that maintains the sequential chain motion of vehicles based on the interaction mechanism between different vehicle types (leading vehicle, following vehicle), such as Figure 5 shown.

[0083] Furthermore, the specific steps of step S3 are as follows:

[0084] S301. In the free driving area, the vehicle that is not affected by other vehicles is defined as the lead vehicle, which will move freely within the speed range specified in the urban road section. The lead vehicle will run at the expected speed V. When its speed is less than V, the lead vehicle will adopt a uniform acceleration behavior, and the constant acceleration is a f , the vehicle motion in this process follows the free motion model:

[0085]

[0086] In the formula, a n (t) and v n (t) respectively represent the acceleration and real-time speed of the nth vehicle at time t, n = 1, 2, ..., N; N represents the number of vehicles; a f represents the acceleration of the nth vehicle at time t; V represents the expected speed of the leading vehicle.

[0087] Furthermore, the movement of the following vehicle will be affected by the movement of the leading vehicle. Based on the full speed difference following model, the present invention proposes an extended following model that fully considers the safe headway time between vehicles.

[0088]

[0089] In the formula, a n (t) and v n (t) respectively represent the acceleration and speed of the nth vehicle at time t, n = 1, 2, ..., N; N represents the number of vehicles; Δx n (t) = x n-1(t)-x n (t) represents the longitudinal distance between the nth vehicle and the n-1th vehicle; Δv n (t) = v n -1(t)-v n (t) represents the longitudinal speed difference between the nth vehicle and the n-1th vehicle at time t. The n-1th vehicle is the leading vehicle of the nth vehicle; V(Δx n (t)) represents the optimal speed of the nth vehicle; l c is the average length of the vehicle; V1, V2, c1, c2, λ, κ are constants.

[0090] Step S4: Analyze vehicles under different operating conditions. Based on different vehicle types, a mathematical modeling simulation method is used to fully consider the safe headway time to determine the lane changing behavior model according to the longitudinal displacement and lateral displacement motion characteristics of the vehicle lane changing. The specific steps are as follows:

[0091] S401. Based on the full speed difference model fFVD), an extended following model considering the potential lane change behavior of the leading vehicle is proposed, and δ n (t) is a binary variable related to the braking response of the n-1th vehicle, reflecting whether the n-1th vehicle takes deceleration measures; θ n (t) is the disturbance coefficient caused by the braking reaction of the n-1th vehicle.

[0092]

[0093] In the formula, a fat，n-1 (t) is the lateral displacement acceleration of the n-1th vehicle at time t; δ n (t) is a binary variable related to the braking response of the n-1th vehicle.

[0094] S402. In the weaving lane change area, the vehicles that need to perform forced lane change in the present invention are all following vehicles. Lane change behavior can be divided into two steps: longitudinal displacement and lateral displacement. The longitudinal following behavior of the lane change vehicle can be described by the extended following model in S201, and the longitudinal acceleration is affected by the target lane and the leading vehicle in the current lane. For safety reasons, the driver must choose the minimum value calculated below.

[0095] a lon (t) = minκ(V(Δx n (t))-v n (f))+λΔ n (t)+θ n (t)δ n (t) (4)

[0096]

[0097] In the formula, a lon (t) is the longitudinal acceleration at time f; l represents the set of lane types, where L c L is the lane the vehicle is currently in. t is the target lane for the lane-changing vehicle; when l=L c When Δx n，l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the current lane, Δv n，l (t) represents the speed difference between the two vehicles. t When Δx n，l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the target lane, Δv n，l (t) is the speed difference between the two vehicles.

[0098] S403: In the lane-changing prohibited area, if the leading vehicle cannot pass the stop line within the green light time, the following vehicle still follows the leading vehicle according to formula (2) in S301.

[0099] S404. In the conflict driving area, the diversion movement of the turning vehicle is simplified into two steps: longitudinal displacement and lateral displacement. The only difference between the turning vehicle and the straight-moving vehicle is that the latter will have a lateral acceleration related to the pressure on the pedal and the steering wheel angle. When the vehicle leaves the stop line, the vehicle's motion state has the following two conditions.

[0100] 1) When there is a vehicle in front of the horizontal direction, the vehicle acts as a following vehicle, and its following behavior can be described by equation (2) in step S301.

[0101] 2) When there is no vehicle in front horizontally, the vehicle acts as the leading vehicle and accelerates to the desired running speed V according to the free motion model.

[0102] Step S5 specifically studies the instantaneous motion state of the vehicle under the influence of signal control from a microscopic perspective, and determines whether the vehicle can successfully pass the stop line within the periodic green light time.

[0103] Furthermore, the specific steps of step S5 are as follows:

[0104] S501. In a no lane change zone, if the leading vehicle passes the stop line within the green light time, the driver of the following vehicle needs to determine whether it can pass the stop line within the green light time. The determination variable is defined as follows.

[0105]

[0106]

[0107] In the formula, S n(t) is the variable that determines whether the vehicle can pass the stop line within the green light time (1 for yes, 0 for no); Represents the phase difference between intersection i-1 and i; represents the phase difference between intersections i and j; C is the cycle length; is the starting and ending time of the kth stage; t s is the time when the nth vehicle reaches the stop line; l s is the position of the stop line.

[0108] S502: If the nth vehicle can pass the stop line within the green light time, then according to formula (2) in step S201, it still follows the longitudinal motion behavior of the leading vehicle. If the nth vehicle cannot pass the stop line within the green light time, then its deceleration and parking process follows the parking motion model.

[0109]

[0110] Step S6 specifically studies the instantaneous state of vehicle motion from a microscopic perspective and accurately calculates the key parameters of the instantaneous operating conditions at the second level during vehicle operation.

[0111] Furthermore, the specific steps of step S6 are as follows:

[0112] S601. Analyze the coupling characteristics between vehicle running trajectory and traffic flow, driving behavior, and signal timing parameters, and perform numerical simulation of vehicle spatial trajectory at intersection based on micro-kinematics theory. The simulation time is one cycle C = 120s, and the time step Δt = 0.1s.

[0113] S602. Accurately and comprehensively obtain the position, speed and acceleration data of the vehicle's entire process of passage from a microscopic perspective based on the simulation results, so as to draw a vehicle spatial trajectory diagram and visualize the vehicle's movement process. The spatial trajectory diagram results of 25 vehicles passing through the target study area in one cycle are as follows: Figure 6 shown.

[0114] Furthermore, the calculated instantaneous operating parameters of some vehicles at the second level are shown in Table 1, Table 2, and Table 3 respectively.

[0115] Table 1 Instantaneous speed values ​​of 12 vehicles within 1s (unit: m / s)

[0116]

[0117] Table 2 Instantaneous acceleration values ​​of 12 vehicles within 1s (unit: m / s 2 )

[0118]

[0119] Table 3 Instantaneous positions of 12 vehicles within 1 second (unit: m)

[0120]

[0121] In addition, Tables 4 and 5 show the comparison of the simulation results based on the vehicle micro-kinematics model proposed in the present invention and the micro-simulation software PTVVissim 9 in terms of average delay and average road section travel time. Generally speaking, as the traffic volume increases, the delay and travel time tend to increase as expected. Under three traffic volumes (low, medium, and high), when the intersection spacing is 300 meters, 500 meters, and 700 meters, the simulation results of the vehicle micro-kinematics model are within the 10% error range of the Vissim simulation results.

[0122] Table 4 Average delay comparison table (unit: seconds)

[0123]

[0124] Table 5 Comparison of average travel time (unit: s)

[0125]

[0126] The simulation results show that the vehicle micro-kinematic model proposed in this paper can describe the typical following behaviors on different road sections, such as normal following behaviors on cruising sections, lane changing behaviors between lanes, and stop-and-go phenomena due to the presence of traffic lights. The vehicle instantaneous operating parameters (speed, acceleration, instantaneous position) are used as parameter inputs and substituted into the VT-Micro model to calculate the energy consumption and emissions generated by vehicle movement, and the ecological cost of road network traffic is estimated by introducing the time value coefficient.

[0127] The technical features of the above embodiments may be combined arbitrarily. To make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0128] The above embodiments are preferred implementation modes of the present invention, but the implementation modes of the present invention are not limited to the above embodiments. Any other changes, modifications, substitutions, combinations, and simplifications that do not deviate from the spirit and principles of the present invention should be equivalent replacement methods and are included in the protection scope of the present invention.

Claims

1. A method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic, characterized by: The following steps are involved: S1. Microscopic motion characterization system for road sections: Based on the spatial resource division of road sections, the driving behaviors of different vehicles are modeled, the characteristic parameters of vehicle motion are calculated, and the traffic ecological cost is calculated in seconds; S2, road section spatial resource division: select the target road section between adjacent intersections through the segment prediction method to divide the spatial resource of vehicle movement trajectory; S3. Modeling of vehicle-to-vehicle following behavior: Based on the motion characteristics between the leading vehicle and the following vehicle, a mathematical modeling and simulation method is used to determine an extended following model that fully considers the safe headway time between vehicles; S4. Lane-changing behavior modeling between vehicles: Based on the longitudinal displacement and lateral displacement motion characteristics of the vehicle lane-changing, a mathematical modeling simulation method is used to fully consider the safe headway time to determine the lane-changing behavior model; S5, Vehicle intersection driving decision modeling: Based on the signal control of the downstream intersection, a second-by-second calculation method is used to determine the decision model for vehicles passing through the stop line; S6. Calculation of road section traffic ecological cost in seconds: Estimate the instantaneous operating parameters of the vehicle during operation based on the vehicle operation sequential chain kinematic model; Step S3 is specifically as follows: S301. In the free driving area, the vehicle that is not affected by other vehicles is defined as the lead vehicle. The lead vehicle will move freely within the speed range specified on the urban road section. The lead vehicle will run at the expected speed V. When the real-time speed v n (t) When its speed is less than V, the leading vehicle will adopt uniform acceleration behavior, with a constant acceleration of a f , the vehicle motion follows the free motion model: In the formula, a n (t) and v n (t) respectively represent the acceleration and real-time speed of the nth vehicle at time t, n = 1, 2, ..., N; N represents the number of vehicles; a f represents the constant acceleration of the nth vehicle; V represents the expected speed of the leading vehicle; The movement of the following vehicle will be affected by the movement of the leading vehicle. Based on the full speed difference following model, an extended following model that fully considers the safe headway time between vehicles is proposed. In the formula, Δx n (t) = x n-1 (t)-x n (t) represents the longitudinal distance between the nth vehicle and the n-1th vehicle; Δv n (t) = v n-1 (t)-v n (t) represents the longitudinal speed difference between the nth vehicle and the n-1th vehicle at time t; the n-1th vehicle is the leading vehicle of the nth vehicle; V(Δx n (t)) represents the optimal speed of the nth vehicle; l c is the average length of the vehicle; V1, V2, c1, c2, λ, κ are constants, θ n (t) is the disturbance coefficient caused by the braking reaction of the n-1th vehicle, δ n (t) is a binary variable related to the braking response of the n-1th vehicle.

2. The vehicle micro-kinematics model construction method for quantifying the road network traffic ecological cost according to claim 1 is characterized by: Step S1 is specifically as follows: S101, dividing the road sections between adjacent intersections into detailed functional stages, and performing spatial trajectory analysis on the operation of vehicles based on different driving behaviors in each functional partition area; the functional stages are divided into: free driving area, weaving lane change area, prohibited lane change area, and conflict driving area; S102, modeling the driving behaviors of different vehicles, analyzing vehicles under different operating conditions, and establishing an extended car-following model that maintains the sequential chain motion of vehicles based on the interaction mechanism between different vehicle types; S103. Study the instantaneous state of vehicle motion from a microscopic perspective, and accurately calculate the key parameters of the instantaneous working condition of the vehicle in the second level during operation based on the position, speed and acceleration data of the vehicle throughout the entire process of passage; S104, quantifying the calculated key parameters of the instantaneous working condition at the second level to calculate the traffic ecological cost at the second level.

3. The method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic according to claim 2 is characterized by: Step S2 is specifically as follows: S201. During vehicle operation, a front vehicle between two longitudinally adjacent vehicles is defined as a leading vehicle, and a rear vehicle whose motion state is affected by the front vehicle is defined as a following vehicle. On a road section without signal control, the following car between two adjacent vehicles will follow the extended following model and move with the leading car, accelerating or decelerating within the speed range specified on the road section to ensure traffic efficiency while maintaining a safe following distance. All vehicles merging into the main road section will gradually reach a stable movement state; starting from the entrance of the main road section, a road section of sufficient length is selected to be divided into a free driving area; S202: The stable motion state of the vehicle will be disrupted by the forced lane change behavior, and the vehicle that needs to change lanes will obtain a lateral acceleration to complete the lateral change of the vehicle; during the lane change process, the longitudinal movement process of the lane-changing vehicle is affected by the preceding vehicle located in a different lane, and the lane change behavior of the vehicle will also disrupt the original stable following behavior of the following vehicle located in a different lane; The road sections where vehicles take and complete forced lane changes are divided into weaving lane change areas; S203, the vehicle is approaching a signalized intersection and cannot change lanes due to the double solid line restriction of the lane; the vehicle is judged whether it can pass through the intersection smoothly according to the green light time and the current vehicle speed, and the vehicle that cannot pass through will slow down and stop before the stop line and wait for the next green light release; the prohibited lane change section before the stop line is selected as the prohibited lane change area; S204. After passing the stop line, the vehicle selects different driving directions according to the travel purpose. Due to the different diversion directions of vehicles, the time it takes for the vehicle to completely leave the intersection and enter the next lane is also different. Taking the stop line as the starting point, the road section where the vehicle takes and completes the turning behavior is divided into the conflict driving area.

4. The method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic according to claim 1 is characterized by: Step S4 is specifically as follows: S401. Based on the full speed difference model, an extended following model considering the potential lane change behavior of the leading vehicle is proposed, defining δ n (t) is a binary variable related to the braking response of the n-1th vehicle, reflecting whether the n-1th vehicle takes deceleration measures; θ n (t) is the disturbance coefficient caused by the braking reaction of the n-1th vehicle: In the formula, a lat,n-1 (t) is the lateral displacement acceleration of the n-1th vehicle at time t; δ n (t) is a binary variable related to the braking response of the n-1th vehicle; S402. In the weaving lane change area, all vehicles that need to perform forced lane change behavior are following vehicles; the lane change behavior is divided into two steps: longitudinal displacement and lateral displacement; the longitudinal following behavior of the lane changing vehicle is described by the extended following model in S301, and the longitudinal acceleration is affected by the target lane and the leading vehicle in the current lane; for safety considerations, the minimum value calculated below is selected: a lon (t)=minκ(V(Δx n (t))-v n (t))+λΔv n (t)+θ n (t)δ n (t) (4) In the formula, a lon (t) is the longitudinal displacement acceleration at time t; l represents the set of lane types, where L c L is the lane the vehicle is currently in. t is the target lane for the lane-changing vehicle; when l=L c When Δx n,l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the current lane, Δv n,l (t) represents the speed difference between the two vehicles; when l = L t When Δx n,l (t) is the longitudinal headway between the nth vehicle and the leading vehicle in the target lane, Δv n,l (t) is the speed difference between the two vehicles; S403: In the lane-changing prohibited area, if the leading vehicle cannot pass the stop line within the green light time, the following vehicle still follows the leading vehicle according to formula (2) in S301; S404. In the conflict driving area, the diversion movement of the turning vehicle is simplified into two steps: longitudinal displacement and lateral displacement. The only difference between the turning vehicle and the straight-moving vehicle is that the latter has a lateral acceleration related to the pressure on the pedal and the steering wheel angle. When the vehicle leaves the stop line, the vehicle's motion state has the following two conditions: S404-1, when there is a vehicle in front horizontally, the vehicle acts as a following vehicle, and its following behavior is described by equation (2) in step S301; S404-2 When there is no vehicle in front horizontally, the vehicle acts as the lead vehicle and accelerates to reach the expected running speed V according to the free motion model.

5. The method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic according to claim 4 is characterized by: Step S5 is specifically as follows: S501. In a lane-changing prohibited area, if the leading vehicle passes the stop line within the green light time, the following vehicle needs to determine whether it can pass the stop line within the green light time. The determination variable is defined as follows: In the formula, S n (t) is a variable that determines whether the vehicle can pass the stop line within the green light time, 1 represents yes, 0 represents no; Represents the phase difference between intersection i-1 and i; represents the phase difference between intersections i and j; C is the cycle length; is the green light start and end time of the kth stage; t s is the time when the nth vehicle arrives at the stop line; l s is the position of the stop line; S502: If the nth vehicle can pass the stop line within the green light time, then according to formula (2) in step S301, it still follows the longitudinal motion behavior of the leading vehicle; if the nth vehicle cannot pass the stop line within the green light time, then its deceleration and parking process follows the parking motion model:

6. The method for constructing a vehicle micro-kinematics model for quantifying the ecological cost of road network traffic according to claim 5 is characterized by: Step S6 is specifically as follows: S601. Analyze the coupling characteristics between vehicle running trajectory and traffic flow, driving behavior, and signal timing parameters, and perform numerical simulation of vehicle spatial trajectory at intersection based on micro-kinematics theory; S602. Accurately and comprehensively obtain the position, speed and acceleration data of the vehicle's entire travel process from a microscopic perspective based on the simulation results, and then draw a vehicle spatial trajectory diagram to visualize the vehicle's movement process, and establish a quantitative relationship between key parameters and travel delays, energy consumption and gas emissions.

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