Method for constructing right-turning motor vehicle traffic capacity correction model under influence of non-motor vehicle line-crossing illegal parking

Abstract

The invention relates to a method for constructing a right-turn motor vehicle traffic capacity correction model under the influence of non-motor vehicle cross-line illegal parking, which comprises the following steps: taking two illegal parking characteristics of non-motor vehicle intrusion distance and illegal parking quantity as entry points, obtaining that two illegal parking factors both have influence on the speed of a right-turn motor vehicle through correlation analysis, and taking the right-turn speed as a dependent variable to obtain a right-turn motor vehicle traffic capacity correction model; and constructing a right-turn motor vehicle speed interference response model by taking the illegal parking quantity and the intrusion distance as independent variables. And based on the established speed interference response model, constructing a right-turn motor vehicle traffic capacity correction coefficient algorithm by applying a traffic wave theory and a gap acceptance theory, and integrating the right-turn motor vehicle traffic capacity correction coefficient algorithm into an HCM model to establish an improved HCM traffic capacity correction model. According to the method, the influence of the number, position and shape of non-motor vehicle cross-line illegal parking under different phases is considered, and reference is provided for traffic planning and road design.

Description

Technical Field

[0001] The present invention relates to a method for constructing a correction model for the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking, and belongs to the traffic control system. Background Art

[0002] In urban traffic management, the behavior of non-motor vehicle riders crossing the stop line and waiting for the green light at intersections has become a common phenomenon in some cities. Data shows that non-motor vehicle over-line illegal parking accounts for 30%-50% of non-motor vehicle violations. The non-motor vehicle lane is generally adjacent to the right-turn motor vehicle lane. If non-motor vehicles cross the line and wait at intersections, it will occupy the passing space of right-turning vehicles; in order to avoid non-motor vehicles, right-turning vehicles have to slowly detour at intersections, significantly reducing the passing speed and passing efficiency of vehicles. Some studies have found that at intersections with severe non-motor vehicle interference, the average speed of right-turning motor vehicles drops significantly, and in severe cases, it is almost halved. Although over-line illegal parking accounts for a relatively high proportion of non-motor vehicle violations and has a significant negative impact on the passing of right-turning motor vehicles, relevant research on over-line illegal parking is relatively scarce. Especially in the research field of exploring the relationship between over-line illegal parking and right-turn passing capacity, there are few studies involved. Therefore, studying the characteristics of non-motor vehicle over-line illegal parking and its impact on right-turn traffic flow is of great significance for improving road passing capacity.

[0003] Wang Tao et al. [1] Based on field observations, they respectively explored the influence of factors such as signal phase sequence, crossing width, and motor vehicle and non-motor vehicle flows at intersections on non-motor vehicle waiting behaviors. Li Yan [2] et al. established a risk model for crossing the line based on survival analysis to evaluate the influence of non-motor vehicle lane width and non-motor vehicle speed on the risk of electric bicycles crossing the line. The research found that both non-motor vehicle lane width and non-motor vehicle speed have a significant impact on the risk of crossing the line. However, the above research focuses on considering the reasons for illegal parking behaviors and less analyzes the characteristics of non-motor vehicle illegal parking.

[0004] Researchers have developed a variety of calculation models for the passing capacity of right-turning motor vehicles. Among them, the saturated flow rate method, the stop line method, and the conflict point method are the basic methods for calculating the passing capacity of intersections, and relatively strict preconditions usually need to be set in the calculation process, resulting in the calculation results may not conform to the actual situation. Therefore, considering the complex non-motor vehicle traffic characteristics in China, existing research believes that using measured data to correct the HCM is the most reliable method. Zhao Jing et al. [3] Adopted the method of regression analysis to correct the pedestrian and bicycle coefficient of the saturated flow rate of right-turning motor vehicles on the basis of considering different design modes and different phase conditions at intersections, but the influence of non-motor vehicle illegal parking on the passing capacity was not involved in the research. Lian Peikun et al. [4]Based on the conflict technology method, the influences of factors such as the mixed flow rate of non-motor vehicles and pedestrians, crossing time, and crosswalk width on the passing capacity of right-turning motor vehicles were evaluated. Qin Lihui, etc. [5] The coefficient of the number of bicycles on the roadside of urban arterial roads was corrected, and the regression analysis method was used to study the influence law of the number of roadside bicycles on the passing capacity of urban arterial roads. However, the consideration of illegal parking factors was not included in the research. At the same time, as a characteristic reflecting the change of vehicle density, traffic wave has been applied to the analysis of vehicle passing capacity. Chen Xiaoming, etc. [6] Using the traffic wave theory, the influence of non-motor vehicles passing through the conflict area on the right-turn conflict vehicle flow was calculated. Dong Ningning, etc. [7] Based on a two-phase signal intersection, the traffic wave theory was used to analyze the influence of the number of non-motor vehicles during the red light period on the right-turn vehicle speed, and the influence coefficient of non-motor vehicles on the passing capacity of right-turning vehicles was corrected. Although the existing research has considered the influence of non-motor vehicles on the passing capacity of right-turning motor vehicles to a certain extent, the research on the influence of non-motor vehicle illegal parking on the passing capacity is still insufficient, and the existing research fails to fully combine the traffic wave theory to analyze the influence of non-motor vehicle over-line illegal parking under different signal phases.

[0005] In summary, there are two problems in the current research on non-motor vehicle over-line illegal parking behavior and the passing capacity of right-turning motor vehicles: one is that in the relevant research on non-motor vehicle over-line illegal parking, only the reasons for the illegal parking behavior are considered, and the characteristics of non-motor vehicle over-line illegal parking are not considered; the other is that whether using the HCM model or the traffic wave theory to study the passing capacity of right-turning motor vehicles, the influence of non-motor vehicle over-line illegal parking is not taken into account. Based on this, it is necessary to provide a passing capacity model of right-turning motor vehicles under the influence of non-motor vehicle over-line illegal parking to provide a reference for traffic planning and road design.

[0006] [1] Wang Tao, Qin Guofeng, Yang Anlei, etc. Characteristics of Non-motor Vehicles Waiting to Go at Signalized Intersections [J]. Journal of Shandong Jiaotong University, 2016, 24(03): 36 - 42.

[0007] [2] Li Yan, Nan Srui, Hu Wenbin, etc. Risk Model of Electric Bicycles Crossing the Line on Roads Separated by Motor Vehicle and Non-motor Vehicle Markings [J]. Journal of Chongqing Jiaotong University (Natural Science Edition), 2021, 40(2): 13 - 20.

[0008] [3] Zhao Jing, Bai Yu, Yang Xiaoguang. Pedestrian and Bicycle Correction of Right-Turn Passing Capacity Based on Regression Analysis [J]. Journal of Highway and Transportation Research and Development, 2012, 29(2): 120 - 126, 153.

[0009] [4] Lian Peikun, Rong Jian, Lai Yuanwen. Actual Passing Capacity Model of Right-Turn Lanes at Diverting Island Signalized Intersections Based on Conflict Technology Method [J]. Journal of Beijing University of Technology, 2015, 41(09): 1415 - 1421.

[0010] [5] Qin Lihui, Pei Yulong, Bai Chongxi. Capacity and service level of urban arterial road sections under the interference of bicycles [J]. Journal of Harbin Institute of Technology, 2018, 50(9): 61-67.

[0011] [6] Chen Xiaoming, Shao Chunfu, Zhao Yi. Calculation model for the capacity of signalized intersections affected by non-motor vehicles [J]. Journal of Traffic and Transportation Engineering, 2008, 8(2): 101-105.

[0012] [7] Dong Ningning. Research on the capacity model and traffic organization of right-turn vehicles at signalized intersections affected by bicycles [D]. Xi'an: Chang'an University, 2019. Summary of the Invention

[0013] The present invention provides a method for constructing a correction model for the capacity of right-turn motor vehicles affected by non-motor vehicle over-line illegal parking, which considers the influence of non-motor vehicle over-line illegal parking characteristics under different phases and provides a reference for traffic planning and road design.

[0014] The technical solution adopted by the present invention to solve its technical problems is as follows:

[0015] A method for constructing a correction model for the capacity of right-turn motor vehicles affected by non-motor vehicle over-line illegal parking, comprising the following steps:

[0016] Step S1, data collection. At the location of a four-phase signalized intersection, through manual investigation and video investigation methods, obtain data on the intersection size, signal cycle, signal phase, motor vehicle lane width, non-motor vehicle lane width, critical gap, following time headway, right-turn motor vehicle traffic volume, non-motor vehicle traffic volume, non-motor vehicle arrival volume, non-motor vehicle over-line illegal parking quantity, illegal parking location, and the driving trajectory and speed of right-turn motor vehicles under illegal parking.

[0017] Step S2, based on the data collected in step S1, construct two models. First, conduct a correlation analysis on the data of non-motor vehicle arrival volume and non-motor vehicle illegal parking quantity, and establish an illegal parking quantity calculation model.

[0018] Second, according to the characteristics of the illegal parking location, classify the non-motor vehicle illegal parking shapes, convert the influence of non-motor vehicle illegal parking shapes on the capacity of right-turn motor vehicles into the influence of intrusion distance under the illegal parking shapes on the capacity of right-turn motor vehicles, and establish a probability model for intrusion distance of different shapes; continue to obtain an expected value calculation model for intrusion distance based on the intrusion distance probability model.

[0019] Step S3: Determine the correlation between the right-turn vehicle speed, the number of illegal parking, and the intrusion distance through correlation analysis. Then, taking the right-turn vehicle speed data as the dependent variable and the number of illegal parking and intrusion distance data as the independent variables, establish a regression model to obtain the function between the right-turn vehicle speed and the number of illegal parking and intrusion distance at different illegal parking positions. Integrate the illegal parking quantity calculation model and the expected value calculation model of the intrusion distance obtained in Step S2 with the obtained function to establish a right-turn motor vehicle speed interference response model.

[0020] Step S4: Based on the right-turn motor vehicle speed interference response model established in Step S3, for the four phases of Red 1, Red 2, Green 1, and Green 2 within the signal cycle, apply traffic wave theory and gap acceptance theory to respectively construct the right-turn motor vehicle passing capacity correction coefficient algorithms for the four phase stages, and integrate the correction coefficient algorithms for the four phase stages into the HCM model to establish an improved HCM passing capacity correction model.

[0021] Among them, Red 1 represents the straight-ahead red light phase, Red 2 represents the straight-ahead and left-turn red light phase, Green 1 represents the straight-ahead green light phase, and Green 2 represents the left-turn green light phase.

[0022] Furthermore, in Step S2, the established illegal parking quantity calculation model is:

[0023] Q e-bike =0.000174Q arrival 3 -0.0101Q arrival 2 +0.407Q arrival +0.366 (1)

[0024] In formula (1), Q e-bike is the number of illegal parkings of non-motor vehicles, with the unit of vehicle, and Q arrival is the arrival volume of non-motor vehicles at the intersection, with the unit of vehicle.

[0025] The steps to establish the intrusion distance probability model are as follows:

[0026] Step S221: The illegal parking positions of non-motor vehicles are divided into the inside of the trajectory and the outside of the trajectory according to the driving trajectory of right-turn motor vehicles. Among them, the illegal parking inside the trajectory means that the non-motor vehicle's over-line illegal parking positions are distributed at the position of the crosswalk on the same side, that is, on the right side of the motor vehicle's right-turn trajectory; the outside of the trajectory means that the non-motor vehicle's over-line illegal parking positions are mainly distributed on the left side of the motor vehicle's right-turn trajectory.

[0027] Step S222: Divide the shapes of non-motor vehicle illegal parkings. In the inside-of-trajectory working condition, the illegal parking shapes are divided into left-straight, front-convex, and right-straight triangle; in the outside-of-trajectory working condition, the illegal parking shapes are divided into rectangle and triangle.

[0028] Step S223. The illegal parking distance directly reflects the degree of encroachment of illegally parked non-motor vehicles on the right-turn lane in various illegal parking shapes. Therefore, the intrusion distance is defined as D. y , inside the trajectory, for each illegal parking shape, the intrusion distance D y refers to the distance from the most forward illegal parking point close to the right-turn traffic flow to the stop line. Outside the trajectory, for each illegal parking shape, the intrusion distance D y refers to the distance from the last illegal parking point close to the right-turn traffic flow to the stop line.

[0029] Step S224. Based on the outer dimensions of the non-motor vehicle being 1.9 m in length and 0.6 m in width, and the static parking area of the non-motor vehicle being 1.3 - 1.8 m 2 , the intrusion distance is divided into units of 2 m. According to the traffic flow situation at the intersection, the intrusion distance is divided into four groups: 0 - 2 m, 2 - 4 m, 4 - 6 m, and 6 - 8 m. Using Bayesian theory, a probability model of the intrusion distance under different illegal parking shapes is established. The probability model of the intrusion distance under different illegal parking shapes is as follows:

[0030]

[0031] In formula (2), i is the intrusion distance group, with a group of 2 m; A j is the illegal parking shape of the non-motor vehicle; T is the phase stage P(D yi ) is the prior probability, that is, the probability of a certain group of intrusion distances occurring. n i is the frequency of occurrence of the i-th group of intrusion distances; M is the total number of samples; P(A j ,T|D yi ) is the likelihood probability, indicating the conditional factors for the occurrence of a certain group of intrusion distances of the non-motor vehicle. P(A j ,T) is the total probability, that is, considering all possible intrusion distances D yi cases, the total probability of the illegal parking shape A j and the phase stage T occurring; P(A j ,T) = ΣP(D yi )·P(A j ,T|D yi ); P(D yi |A j ,T) is the posterior probability, that is, given that the illegal parking shape A j and the phase stage T occur, the probability of the i-th group of intrusion distances D yi occurring.

[0032] Step S225. Use the probability model of the intrusion distance under different illegal parking shapes to calculate the expected value of the intrusion distance D y for each illegal parking shape. The calculation model of the expected value of the intrusion distance of the non-motor vehicle under different illegal parking shapes is expressed as:

[0033]

[0034] In formula (3), E(D y |A j , T) is the expected value of the non-motor vehicle intrusion distance D when the illegal parking shape A j and the phase stage T occur; x yi is the midpoint value of the intrusion distance of the i-th group; i

[0035] Furthermore, in step S3, based on the number of illegal parkings Q e-bike and the intrusion distance D under the non-motor vehicle illegal parking shape y , a right-turn motor vehicle speed interference response model is established to describe the change of the right-turn motor vehicle speed, and its expression is as follows:

[0036] u shape = b 0 + b 1 D y + b 2 Q e-bike + ξ (4)

[0037] In formula (4), u shape is the right-turn motor vehicle speed, with the unit of m / s, Q e-bike is the number of non-motor vehicle illegal parkings, with the unit of vehicle, calculated according to formula (1); D y is the length of the intrusion distance, with the unit of m, and the expected value of the intrusion distance under each illegal parking shape is calculated according to formula (3); ξ is the error term, b 0 is the model constant, b 1 is the coefficient of D y , b 2 is the coefficient of Q e-bike ;

[0038] Based on the general form of the right-turn motor vehicle speed interference response model, for different illegal parking shapes, a right-turn motor vehicle speed interference response model under each illegal parking shape is established, specifically including the inner side and the outer side of the trajectory, which are respectively:

[0039] Inner side of the trajectory:

[0040]

[0041] Outer side of the trajectory:

[0042]

[0043] Furthermore, in step S4, the steps to construct the right-turn motor vehicle passing capacity correction coefficient algorithm under four phase stages are as follows:​

[0044] Step S41: Analyze the impact of non - motor vehicle over - line parking on the right - turn traffic flow using the HCM algorithm. To more accurately evaluate the passing capacity of right - turn motor vehicles, a correction coefficient algorithm considering the impact of non - motor vehicle parking is designed as follows:

[0045] f Rpb = min(f Rp , f Rb ) (7)

[0046] In formula (7), f Rpb is the correction coefficient of the saturation flow rate of right - turn motor vehicles by non - motor vehicles and pedestrians, f Rb is the correction coefficient of the saturation flow rate of right - turn motor vehicles by non - motor vehicles considering the impact of non - motor vehicle parking; f Rp is the correction coefficient of the saturation flow rate of right - turn motor vehicles by pedestrians. At intersections where non - motor vehicles are the main factor affecting the driving of right - turn vehicles, pedestrians can quickly leave the potential conflict area and do not affect the passing of right - turn vehicles. Therefore, f Rp = 1; Thus, formula (7) is simplified to f Rpb = f Rb ;

[0047] Step S42: According to the intersection phase, the calculation of f Rb is divided into four parts, namely the red 1 phase, the red 2 phase, the green 1 phase, and the green 2 phase;

[0048] Step S43: During the red 1 phase, the change of traffic flow is divided into two processes. The first process is that the non - motor vehicles going straight across the street from the adjacent left - hand approach have not reached the conflict area, and at this time, right - turn motor vehicles can drive freely; the second process is that there is a traffic conflict between right - turn motor vehicles and non - motor vehicles going straight across the street from the adjacent left - hand approach, and at the same time, it is also affected by the non - motor vehicle over - line parking inside the trajectory. Therefore, the expression of the correction coefficient of the saturation flow rate of non - motor vehicles on right - turn motor vehicles during the red 1 phase is:

[0049]

[0050] In formula (8), f 1RRb is the correction coefficient of the saturation flow rate of non - motor vehicles on right - turn motor vehicles during the red 1 phase; f RRb1 is the correction coefficient of the right - turn saturation flow rate in the first process of the red 1 phase. In this phase, right - turn vehicles are not affected by left - hand non - motor vehicles, so f RRb1 = 1; P 1 is the proportion of the initial red - light duration T r1 in the red - light time T R1 of the red 1 phase, T R1is the red 1 phase time, with the unit of s, T r1 is the initial duration of the red light in the first process, with the unit of s, T r1 = L / v bs , where L is the distance that non-motor vehicles traveling straight across the street at the adjacent left entrance need to travel to reach the conflict area after entering the intersection, with the unit of m; v bs is the speed of non-motor vehicles traveling straight across the street at the adjacent left entrance when reaching the conflict area, with the unit of m / s. The free flow speed of non-motor vehicles is taken as 5.56 m / s; f RRb2 is the correction coefficient under the combined influence of the conflict of oncoming non-motor vehicles traveling straight across the street at the adjacent left entrance and the illegal parking beyond the inner line of the non-motor vehicle trajectory on this side during the second process of the red 1 phase; f R ′ Rb2 is the correction coefficient for the saturation flow rate of right-turning motor vehicles under the influence of the conflict of oncoming non-motor vehicles traveling straight across the street at the adjacent left entrance; f R ″ Rb2 is the correction coefficient for the saturation flow rate of right-turning motor vehicles under the influence of the illegal parking beyond the inner line of the non-motor vehicle trajectory on this side; P 2 is the time T of the second process R1 -T r1 accounts for the proportion of the red light time T of the red 1 phase R1 of

[0051] Step S44, in the red 2 phase, the right-turning motor vehicles do not conflict with oncoming vehicles from other directions and are only affected by the illegal parking beyond the inner line of the non-motor vehicle trajectory on this side. Therefore, the correction coefficient for the saturation flow rate of right-turning motor vehicles in the red 2 phase is:

[0052] f 2RRb = f R ″ Rb (9)

[0053] In formula (9), f 2RRb is the correction coefficient of non-motor vehicles for the saturation flow rate of right-turning motor vehicles in the red 2 phase; f R ″ Rb is the correction coefficient for the saturation flow rate of right-turning motor vehicles under the influence of the illegal parking beyond the inner line of the non-motor vehicle trajectory on this side in the red 2 phase;

[0054] Step S45, the green 1 phase is divided into two processes. In the first process, at the initial stage of the green light, a large number of non-motor vehicles traveling straight on this side enter and occupy the conflict area, and at this time, the right-turning motor vehicles need to stop and wait; in the second process, the right-turning motor vehicles conflict with the non-motor vehicles traveling straight on this side. In addition, the illegal parking behavior of non-motor vehicles beyond the outer line of the trajectory also interferes with the passage of right-turning motor vehicles. Therefore, the expression for the correction coefficient of non-motor vehicles for the saturation flow rate of right-turning motor vehicles during the green 1 phase is:

[0055]

[0056] In formula (10), f 1GRb is the correction coefficient of the saturated flow rate of non-motor vehicles in the green 1 phase for right-turning motor vehicles. f GRb1 is the correction coefficient of the saturated flow rate of right-turning vehicles in the first process of the green 1 phase. f GRb1 = 0; P 3 is the proportion of the time T g1 at the beginning of the green light in the green 1 phase to the time of the green 1 phase. T g1 is the duration of the initial stage of the green light in the first process, with the unit of s. λ B is the arrival rate of non-motor vehicles at the approach on this side of the intersection, with the unit of vehicle / s. T R is the red light time within a cycle, with the unit of s. N t is the saturated flow rate of the non-motor vehicle lane section at the intersection, with the unit of bicycle / (s·m). Its value is taken as 0.613 bicycle / (s·m). D is the width of the non-motor vehicle lane, with the unit of m. T G1 is the time of the green 1 phase, with the unit of s. f GRb2 is the correction coefficient under the combined influence of the conflict of straight-going non-motor vehicles crossing on this side and the interference of non-motor vehicles parked illegally beyond the outer line of the non-motor vehicle trajectory in the second process of the green 1 phase. f G ′ Rb2 is the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of the conflict of straight-going non-motor vehicles crossing on this side. f G ″ Rb2 is the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of non-motor vehicles parked illegally beyond the outer line of the non-motor vehicle trajectory on this side. P 4 is the proportion of the time T G1 -T g1 in the green 1 phase time T G1 of the green 1 phase.

[0057] Step S46, in the green 2 phase, the right-turning motor vehicles are not only affected by the conflict with left-turning non-motor vehicles, but also affected by the non-motor vehicles waiting to go straight inside the trajectory parking illegally beyond the line. Therefore, the correction coefficient of the saturated flow rate of right-turning motor vehicles in the green 2 phase is:

[0058] f 2GRb = f G ′ Rb ·f G ″ Rb (11)

[0059] In formula (11), f 2GRb is the correction coefficient of the saturated flow rate of non-motor vehicles in the green 2 phase for right-turning motor vehicles; f G′ Rb is the correction coefficient of the saturated flow rate of the right-turning motor vehicle affected by the conflict of left-turning non-motor vehicles; f G ″ Rb is the correction coefficient of the saturated flow rate of the right-turning motor vehicle affected by the illegal parking beyond the inner side of the non-motor vehicle track on this side;

[0060] Step S47, based on steps S43 - S46, the calculation formula for the traffic capacity of the signalized intersection is obtained as:

[0061]

[0062] In formula (12), S k is the saturated flow of the k-th phase stage, with the unit of vehicle / h, and k takes R1, R2, G1, and G2, corresponding to the red 1 phase stage, red 2 phase stage, green 1 phase stage, and green 2 phase stage respectively;

[0063] S 0 ′ = S 0 ·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT ; C is the signal cycle duration, with the unit of s;

[0064] Furthermore, since the illegal parking beyond the line of non-motor vehicles affects the right-turning motor vehicles in all four phase stages, therefore, the correction coefficient of the saturated flow rate of the right-turning motor vehicle affected by illegal parking in each phase stage is calculated, and the expression of the correction coefficient of the saturated flow rate of the right-turning motor vehicle affected by illegal parking in each phase stage is:

[0065] Red 1 phase

[0066] Red 2 phase

[0067] Green 1 phase

[0068] Green 2 phase

[0069] In formula (13), C′ R ′ 12 is the number of vehicles passing through the illegal parking area of non-motor vehicles at the approach within the red 1 time in one hour, with the unit of vehicle / h; T R1 -T r1 is the second process time of the red 1 phase;

[0070] In formula (14), C′R ′ 2 The number of vehicles passing through the non-motor vehicle illegal parking area of the approach lane during the red 2 time within one hour, with the unit of vehicle / h; T R2 is the red 2 phase time;

[0071] In formula (15), C′ G ′ 12 is the number of vehicles passing through the non-motor vehicle illegal parking area of the approach lane during the green 1 time within one hour, with the unit of vehicle / h; T G1 -T g1 is the second process time of the green 1 phase;

[0072] In formula (16), C′ G ′ 2 is the number of vehicles passing through the non-motor vehicle illegal parking area of the approach lane during the green 2 time within one hour, with the unit of vehicle / h; T G2 is the green 2 phase time;

[0073] During the red 1, green 1, and green 2 phase stages, the right-turning motor vehicles are affected by non-motor vehicle conflicts during operation. During the red 2 phase stage, the right-turning motor vehicles do not conflict with oncoming vehicles from other directions; therefore, for the red 1, green 1, and green 2 phase stages, it is necessary to calculate the correction coefficient of the saturated flow rate of right-turning motor vehicles under conflict influence, and the expression is as follows:

[0074] Red 1 phase

[0075] Green 1 phase

[0076] Green 2 phase

[0077] In formula (17), Q′ R12 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of oncoming straight non-motor vehicles from the left adjacent approach lane during the second process of the red 1 phase, with the unit of vehicle / h;

[0078] In formula (18), Q′ G12 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of straight non-motor vehicles crossing on the same side during the second process of the green 1 phase, with the unit of vehicle / h;

[0079] In formula (19), Q′ G2 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of left-turning non-motor vehicles during the green 2 phase, with the unit of vehicle / h;

[0080] Furthermore, during the red 1 phase, red 2 phase, green 1 phase, and green 2 phase, the traffic wave theory is applied to study the passing capacity of right-turning vehicles affected by non-motor vehicle illegal parking. Specifically, under the influence of non-motor vehicle over-line illegal parking, when there is no influence of non-motor vehicle illegal parking, let the average speed of the right-turning vehicle flow be u 1 , the flow of the right-turning vehicle flow is q 1 . When there is non-motor vehicle over-line illegal parking at the intersection, the area of the motor vehicle right-turn path becomes narrower, so that as the number of non-motor vehicle over-line illegal parkings increases, a bottleneck area of the right-turning vehicle flow appears, and the traffic wave is transmitted upstream. At this time, the average speed of the conflicting right-turning vehicle flow drops from u 1 without the influence of non-motor vehicle illegal parking to u 2 with the influence of non-motor vehicle illegal parking. The operating state of the right-turning vehicle changes from state A (u 1 , q 1 ) without the influence of non-motor vehicle illegal parking to the blocked state B (u 2 , q 2 );

[0081] At this time, there is a compression wave propagating from front to back in the conflicting vehicle flow, and the wave speed is:

[0082]

[0083] In formula (20): u 1 is the average speed of the upstream right-turning vehicles without the influence of non-motor vehicle illegal parking, with the unit of km / h, q 1 is the flow of the upstream right-turning vehicles without the influence of non-motor vehicle illegal parking, with the unit of vehicles / h; u 2 is the average speed of the downstream right-turning vehicles with the influence of non-motor vehicle illegal parking, with the unit of km / h, u 2 is calculated according to the right-turning motor vehicle interference response model u shape , q 2 is the flow of the downstream right-turning vehicles with the influence of non-motor vehicle illegal parking, with the unit of vehicles / h;

[0084] During the phase time within one hour, the number of vehicles passing through the non-motor vehicle illegal parking area of the approach is:

[0085] C″ = (u 1 - u w )k 1 = (u 2 - u w )k 2 (21)

[0086] In formula (21), C″ is the number of vehicles passing through the non-motor vehicle illegal parking area of the approach, with the unit of vehicles / h; k 1The density of upstream right-turning vehicles without parking violations, with the unit of km / vehicle; k 2 The density of downstream right-turning vehicles with parking violations, with the unit of km / vehicle;

[0087] Meanwhile, within the phase time of the same hour, the expression of the relationship between the right-turn traffic flow and the right-turn traffic speed is:

[0088] q(u) = 220.64u 0.7493 (22)

[0089] Substitute the wave speed formula (20) and formula (22) into formula (21), and we get:

[0090]

[0091] Furthermore, in the Red 1 phase, substitute the right-turn motor vehicle speed interference response model formula (4) under the influence of non-motor vehicle parking violations inside the track into formula (23), and we get:

[0092]

[0093] In formula (24), u shapei is the right-turn vehicle speed under the influence of non-motor vehicle parking violations inside the track, where i = 1, 2, 3;

[0094] Substitute formula (24) into formula (13) to obtain the correction coefficient of the right-turn motor vehicle saturation flow rate under the influence of parking violations in the Red 1 phase, and the expression is:

[0095] Red 1 phase

[0096] Based on the process analysis of the Red 1 phase, obtain the correction coefficients f R ″ Rb 、f G ″ Rb2 and f G ″ Rb ,

[0097] Red 2 phase

[0098] Green 1 phase

[0099] Green 2 phase

[0100] In formula (26), u shapei is the right-turn vehicle speed under the influence of non-motor vehicle parking violations inside the track in the Red 2 phase;

[0101] In formula (27), u shapej is the right-turn vehicle speed affected by the illegal parking of non-motor vehicles outside the trajectory of the green 1 phase. Among them, j = 4, 5;

[0102] In formula (28), u shapei is the right-turn vehicle speed affected by the illegal parking of non-motor vehicles inside the trajectory of the green 2 phase;

[0103] Furthermore, under the influence of the conflict of oncoming non-motor vehicles going straight across the street at the adjacent left entrance during the red 1 phase, the maximum number of right-turning vehicles Q′ R12 passing through the available gap is calculated by the formula:

[0104]

[0105] In formula (27), λ b is the arrival rate of non-motor vehicles at the left entrance during the red 1 phase, with the unit of vehicle / s; λ m1 is the arrival rate of right-turning vehicles at the conflict area during the red 1 phase, with the unit of vehicle / s; μ o is the passing gap when right-turning vehicles cross non-motor vehicles, with the unit of s. This parameter is obtained from the accepted gap and rejected gap statistically based on traffic measurement data using the RAFF method; μ f is the following headway when motor vehicles turn right, with the unit of s. This parameter is obtained by taking the average of the statistically measured following headways of right-turning motor vehicles;

[0106] Substituting formula (29) into formula (17), the correction coefficient f′ RRb2 of the saturated flow rate of right-turning motor vehicles affected by the conflict of oncoming non-motor vehicles going straight across the street at the adjacent left entrance can be calculated;

[0107] Furthermore, based on the analysis of the red 1 phase process, the maximum number of right-turning vehicles Q′ G12 passing through the available gap during the green 1 phase is obtained, and the calculation formula is:

[0108]

[0109] In formula (30), λ m2 is the arrival rate of right-turning vehicles at the conflict area during the green 1 phase, with the unit of vehicle / s;

[0110] Substituting formula (30) into formula (18), the correction coefficient f′ GRb2 of the right-turn saturated flow rate affected by the conflict during the green 1 phase can be calculated;

[0111] Based on the analysis of the red 1 phase process, the maximum number of right-turning vehicles Q′ G2 passing through the available gap during the green 2 phase is obtained, and the calculation formula is:

[0112]

[0113] In formula (31), λ m3 is the arrival rate of right-turning vehicles in the green 2 phase to the conflict area, with the unit of vehicle / s;

[0114] Substitute formula (31) into formula (19), and the correction coefficient f′ of the right-turn saturation flow rate under the influence of the conflict in the green 2 phase can be calculated; GRb ;

[0115] Furthermore, in formula (12), S 0 ′ = S 0 ·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT , S 0 is the saturation flow rate of the lane group under ideal conditions. The straight-through saturation flow rate is taken as 1650 pcu / h, and the right-turn motor vehicle saturation flow rate is taken as 1550 pcu / h;

[0116] N is the number of lanes in the lane group;

[0117] f w is the lane width correction coefficient, where W is the width of the motor vehicle lane, with the unit of m. W is taken as greater than 2.4 m. When W > 4.8 m, it is analyzed according to two lanes;

[0118] f HV is the correction coefficient for large vehicles; P HV is the percentage of large vehicles in the right-turn lane in the traffic flow. E HV is the conversion coefficient for large vehicles, taken as 2.0;

[0119] f g is the approach grade correction coefficient; G is the grade of the approach lane group, -0.06 ≤ G ≤ 0.10, and it is negative when going downhill;

[0120] f p is the correction coefficient for the number of stops in the adjacent lane, N m is the number of stops, with the unit of times / h; f bb is the bus blockage correction coefficient, N B is the number of bus stops within one hour, with the unit of vehicles / h; f ais the regional type correction coefficient, where for Shizhongtun and commercial areas, it is 0.9, and for other areas, it is 1.0;

[0121] f LU is the lane utilization reduction coefficient; f RT is the correction coefficient for the right-turn lane. When there is a dedicated right-turn lane, f RT = 0.85. When it is a shared through-right lane, f RT = 1 - 0.15P RT When there is only a single lane at the intersection approach, f RT = 1 - 0.135P RT P RT is the proportion of right-turning vehicles in the approach traffic flow.

[0122] Through the above technical solutions, compared with the prior art, the present invention has the following beneficial effects:

[0123] 1. The method for constructing a correction model for the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking provided by the present invention can accurately grasp the interaction between non-motor vehicles and right-turning motor vehicles under different signal phases through in-depth excavation of this first-hand data, enabling subsequent model construction and analysis to be based on a reliable real-world basis rather than theoretical derivation out of thin air, effectively avoiding the problem of being out of touch with reality;

[0124] 2. The method for constructing a correction model for the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking provided by the present invention incorporates multiple key factors such as the number of illegal parkings and the shape of illegal parkings into the research scope. According to the number of illegal parkings, a calculation model for the number of illegal parkings is established; from the perspective of the shape of illegal parkings, it is innovatively transformed into the study of intrusion distance, and a probability model is established to quantify its impact on the speed of right-turning motor vehicles; this comprehensive and detailed multi-factor consideration can more systematically and completely analyze complex traffic interference situations;

[0125] 3. The method for constructing a correction model for the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking provided by the present invention clarifies the differences in the applicable effects in different types of signalized intersections (right-turn dedicated phase and non-right-turn dedicated phase), providing a highly valuable decision-making basis for traffic management departments in aspects such as actual intersection planning and signal timing optimization, ensuring the feasibility of implementing the method. BRIEF DESCRIPTION OF THE DRAWINGS

[0126] The present invention will be further described below with reference to the drawings and embodiments.

[0127] Figure 1 is a schematic flow chart of the method for constructing a correction model for the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking provided by the present invention;

[0128] Figure 2It is a schematic diagram of traffic density change provided by the present invention;

[0129] Figure 3 It is a schematic diagram of the intrusion distance inside the trajectory provided by the present invention;

[0130] Figure 4 It is a schematic diagram of the intrusion distance outside the trajectory provided by the present invention;

[0131] Figure 5 It is a schematic diagram of the conflict area provided by the present invention. Detailed implementation manners

[0132] Now, the present invention will be further described in detail with reference to the accompanying drawings.

[0133] In the real urban road network, a large amount of non-motor vehicle traffic and frequent non-motor vehicle violations occur at signal intersections, especially the behavior of non-motor vehicles crossing the line and parking illegally, which causes problems such as increased delays of right-turning vehicles at intersections and reduced traffic efficiency of the entire intersection. The research on the right-turning traffic capacity at home and abroad can be divided into three categories: (1) Deriving and establishing a right-turning vehicle traffic capacity model according to the gap acceptance theory; (2) Based on actual investigations, statistically analyzing the measured data, obtaining various factors affecting the saturation flow rate, and calculating the right-turning vehicle traffic capacity through correction; (3) Obtaining the right-turning motor vehicle traffic capacity value through simulation. It is also pointed out in the background technology that, through the analysis of the database and the actual situation, the behavior of crossing the line and parking illegally, which exists in a relatively high proportion among violations, significantly has a negative impact on the motor vehicle traffic efficiency, but there is very little relevant research at home and abroad. Even if some scholars have conducted research, they also focus on exploring one of the factors.

[0134] Based on this, to solve this problem, this application takes two illegal parking characteristics, namely the intrusion distance of non-motor vehicles and the number of illegal parking, as the starting point. Through correlation analysis, it is obtained that both illegal parking factors have an impact on the speed of right-turning motor vehicles. Taking the right-turn vehicle speed as the dependent variable and the number of illegal parking and the intrusion distance as the independent variables, a right-turning motor vehicle speed interference response model is constructed. Based on the established speed interference response model, applying the traffic wave theory and the gap acceptance theory to construct an algorithm for the correction coefficient of the right-turning motor vehicle traffic capacity, and integrating it into the HCM model to establish an improved HCM traffic capacity correction model.

[0135] Specifically, as Figure 1 shown, a method for constructing a correction model of the right-turning motor vehicle traffic capacity affected by non-motor vehicle crossing the line and parking illegally provided by this application includes the following steps:

[0136] Step S1, data collection, at the signal intersection, through manual survey and video survey methods, obtain the intersection size, signal cycle, signal phase, motor vehicle lane width, non-motor vehicle lane width, critical gap, vehicle headway, right-turn motor vehicle traffic volume, non-motor vehicle traffic volume, non-motor vehicle arrival volume, non-motor vehicle crossing the line illegal parking number, illegal parking location and right-turn motor vehicle driving trajectory and speed under illegal parking and other data; here, the video image of the observation area is processed by Tracker software to obtain speed data, critical gap and vehicle headway. The right-turn motor vehicle stop line is used as the observation starting point, and the exit lane stop line is used as the observation end point. The average speed of the right-turn motor vehicle passing this section of the journey is obtained by recording the time when the right-turn motor vehicle passes the observation surface; the critical gap can be obtained by using the Raff method based on the acceptance gap and rejection gap of the traffic measured data; the vehicle headway refers to the time interval between two adjacent vehicles in the queue of vehicles that pass through the intersection continuously.

[0137] In order to ensure the effectiveness and reliability of traffic data collection, a suitable intersection should be selected for video shooting. Therefore, the selected intersection should meet the following conditions as much as possible: the right-turn motor vehicle traffic volume and non-motor vehicle flow at the selected intersection should be large; there are many non-motor vehicles crossing the line and illegally parking; there is a dedicated lane for right-turn motor vehicles, and no intersection channelization facilities; the selected intersection has a small amount of pedestrian crossing traffic to reduce the impact of pedestrians on the traffic efficiency of the intersection; the selected intersection has the conditions for drone takeoff and landing, and there are few obstructions near the intersection, and the line of sight is good within the shooting range.

[0138] After analyzing a large amount of collected field data, it is found that illegal parking of non-motor vehicles across the line at intersections is common. The squeezing effect caused by high traffic volume will increase the possibility of illegal parking of non-motor vehicles across the line at intersections, and illegal parking of non-motor vehicles across the line at intersections will hinder the passage of right-turning vehicles and affect the speed and smoothness of right-turning vehicles. Therefore, studying the impact of illegal parking of non-motor vehicles across the line on right-turning vehicles is of great significance to improving traffic smoothness and efficiency.

[0139] Step S2, based on the data collected in step S1, construct two models. The first model is to conduct correlation analysis on the data of the number of non-motor vehicle arrivals and the number of non-motor vehicle illegal parking, and establish a model for calculating the number of illegal parking;

[0140] The second method is to classify the shapes of illegal parking of non-motor vehicles according to the characteristics of illegal parking locations, convert the impact of the shapes of illegal parking of non-motor vehicles on the traffic capacity of right-turn motor vehicles into the impact of the invasion distance under the illegal parking shape on the traffic capacity of right-turn motor vehicles, and establish an invasion distance probability model with different shapes; based on the invasion distance probability model, continue to obtain the expected value calculation model of the invasion distance.

[0141] This application first analyzes the relationship between the arrival volume of non-motor vehicles and the number of vehicles parked illegally across the line, and then studies the impact of the number of vehicles parked illegally across the line on the speed of right-turning vehicles. The Person correlation coefficient method is used to analyze the correlation between the arrival volume of non-motor vehicles and the number of illegally parked vehicles. The research finds that in the collected field data, the correlation between the arrival volume of non-motor vehicles and the number of illegally parked vehicles is strong. Based on the correlation analysis, the linear function, quadratic curve, and cubic curve are respectively used to fit the arrival volume Q of non-motor vehicles at the intersection arrival and the number Q of illegally parked non-motor vehicles e-bike for curve fitting, and the test fitting result R 2 shows that among many functions, the cubic function has the highest fitting degree. Therefore, this application establishes the calculation model for the number of illegally parked vehicles as:

[0142] Q e-bike = 0.000174Q arrival 3 - 0.0101Q arrival 2 + 0.407Q arrival + 0.366 (1)

[0143] In formula (1), Q e-bike is the number of illegally parked non-motor vehicles, with the unit of vehicle, and Q arrival is the arrival volume of non-motor vehicles at the intersection, with the unit of vehicle.

[0144] In this step, when continuing to analyze the illegal parking characteristics of non-motor vehicles, the illegal parking positions of non-motor vehicles at the intersection can be divided into those inside the trajectory of right-turning motor vehicles and those outside the trajectory. The so-called illegal parking inside the trajectory of right-turning motor vehicles means that in this case, the illegal parking positions of non-motor vehicles across the line are distributed at the position of the crosswalk on this side, that is, on the right side of the right-turning trajectory of motor vehicles, so it is called illegal parking inside the trajectory. The so-called illegal parking outside the trajectory of right-turning motor vehicles means that in this case, the illegal parking positions of non-motor vehicles across the line are mainly distributed on the left side of the right-turning trajectory of motor vehicles, so it is called illegal parking outside the trajectory. Since the illegal parking situations of non-motor vehicles are diverse, the specific shape is affected by factors such as lane width and traffic flow. Through investigation and research, it is found that Figure 3 as shown, in the case of illegal parking inside the trajectory, there are six illegal parking shapes, namely left straight triangle (a), forward convex triangle (b), right straight triangle (c), rectangle (d), trapezoid (e), and sector (f) shapes; Figure 4 as shown, in the case of illegal parking outside the trajectory, there are two illegal parking shapes, namely rectangle (g) and triangle (h). Since the illegal parking shapes are diverse, directly using the shapes for analysis will be very complicated. To simplify the analysis process, this application converts the impact of the illegal parking shape on the passing capacity of right-turning motor vehicles into the impact of the intrusion distance under the illegal parking shape on the passing capacity of right-turning.

[0145] Since the illegal parking distance directly reflects the degree of encroachment of illegally parked non-motor vehicles on the right-turn lane in various illegal parking shapes, the intrusion distance is defined as D y , under each illegal parking shape inside the trajectory, the intrusion distance D y refers to the distance from the most forward illegal parking point close to the right-turn traffic flow to the stop line. Under each illegal parking shape outside the trajectory, the intrusion distance D y refers to the distance from the last illegal parking point close to the right-turn traffic flow to the stop line; as a quantitative index, the intrusion distance can more intuitively reflect the impact of over-line illegal parking on the right-turn traffic capacity.

[0146] Considering that the outer contour dimensions of non-motor vehicles are generally 1.9 m in length and 0.6 m in width, and the static parking area of non-motor vehicles is 1.3 - 1.8 m 2 , the intrusion distance is divided into units of 2 m. According to the traffic flow conditions at the intersection, the intrusion distance is divided into four groups: 0 - 2 m, 2 - 4 m, 4 - 6 m, and 6 - 8 m. Bayes' theorem is a probability-based inference method. Its core idea is to calculate the updated posterior probability through Bayes' formula based on existing prior knowledge and new observation data, so as to make decisions or inferences. Compared with traditional frequency statistics, Bayesian statistics can not only provide rich posterior distribution information of parameters for statistical decisions, making the interpretation of results more intuitive and reasonable, but also reduce the subjectivity and rashness of decisions and avoid over-interpretation of research. Therefore, in this application, the expected value of the intrusion distance under each illegal parking shape is obtained by calculating the probability of different illegal parking shapes using Bayesian probability. Specifically, the probability model of the intrusion distance under different illegal parking shapes is as follows:

[0147]

[0148] In formula (2), i is the intrusion distance group, with a group of 2 m; A j is the illegal parking shape of non-motor vehicles; T is the phase stage P(D yi ) is the prior probability, that is, the probability of a certain group of intrusion distances occurring, n i is the frequency of the i-th group of intrusion distances occurring; M is the total number of samples; P(A j ,T|D yi ) is the likelihood probability, indicating the conditional factors for a certain group of intrusion distances of non-motor vehicles to occur, P(A j ,T) is the total probability, that is, considering all possible intrusion distances D yi cases, the total probability of the illegal parking shape A j and the phase stage T occurring; P(A j ,T) = ∑P(D yi )·P(A j ,T|D yi ); P(D yi|A j , T) is the posterior probability, that is, given the illegal parking shape A j and the occurrence of phase stage T, the intrusion distance D of the i-th group yi appears.

[0149] Based on formula (2), using the intrusion distance probability model under different illegal parking shapes to calculate the intrusion distance D under each illegal parking shape y expected value, the calculation model of the expected value of the intrusion distance of non-motor vehicles under different illegal parking shapes is expressed as:

[0150]

[0151] In formula (3), E(D y |A j , T) is the expected value of the intrusion distance D of non-motor vehicles given the illegal parking shape A j and the occurrence of phase stage T; x yi is the midpoint value of the i-th group of intrusion distances. i is the midpoint value of the i-th group of intrusion distances.

[0152] Under different illegal parking shapes, the expected values of the intrusion distances of non-motor vehicles are slightly different. Through the above formula, in the case of the fan-shaped (f) shape, the expected value of the intrusion distance of non-motor vehicles is the largest, which is 4.9 meters. The expected distances in the left straight triangle (a) and rectangle (d) illegal parking shapes are the smallest, which are 2.00 meters and 2.39 meters respectively.

[0153] Based on the research in step S2, in step S3, the correlation coefficient between the average speed of right-turning motor vehicles and the number of non-motor vehicle illegal parkings is calculated using the Spearman correlation coefficient method. Based on the illegal parking number calculation model and combined with the measured data analysis, it can be seen that there is a strong correlation between the number of non-motor vehicle illegal parkings and the average speed of right-turning motor vehicles, and it shows a negative correlation, indicating that as the number of illegal parkings at the intersection increases, the speed of right-turning vehicles decreases. Through correlation analysis, it is found that there is a strong correlation between the intrusion distances under different illegal parking shapes inside the trajectory and the speed of right-turning motor vehicles, and as the intrusion distance increases, the speed of right-turning motor vehicles gradually decreases; the correlation between the intrusion distances under the two illegal parking shapes outside the trajectory and the speed of right-turning motor vehicles also shows a strong correlation. Therefore, it is determined that there is a correlation between the right-turn speed and the number of illegal parkings and the intrusion distance. Then, taking the right-turn speed data as the dependent variable and the illegal parking number and intrusion distance data as the independent variables, a regression model is established to obtain the function between the right-turn speed at different illegal parking positions and the illegal parking number and intrusion distance, that is, a right-turning motor vehicle speed interference response model is established to describe the change of the right-turning motor vehicle speed, and its expression is as follows:

[0154] u shape = b 0 + b 1 Dy +b 2 Q e-bike +ξ (4)

[0155] In formula (4), u shape is the speed of the right-turning motor vehicle, with the unit of m / s, and Q e-bike is the number of illegally parked non-motor vehicles, with the unit of vehicle, and is calculated according to formula (1); D y is the length of the intrusion distance, with the unit of m, and the expected value of the intrusion distance under each illegally parked shape is calculated according to formula (3); ξ is the error term, and b 0 is the model constant, and b 1 is the coefficient of D y , and b 2 is the coefficient of Q e-bike .

[0156] Based on the general form of the interference response model of the right-turning motor vehicle speed, the illegally parked vehicle number calculation model and the expected value calculation model of the intrusion distance obtained in step S2 are integrated with the obtained function to establish an interference response model of the right-turning motor vehicle speed; it should be noted that under different illegally parked shapes on the inner side of the trajectory, Figure 3 the illegally parked shapes (a), (d), (e), and (f) in

[0157] Inner side of the trajectory:

[0158]

[0159] Outer side of the trajectory:

[0160]

[0161] It can be analyzed from Formula (5) and Formula (6) that under different illegal parking shapes inside the trajectory, as the intrusion distance increases, the speed of right-turning motor vehicles gradually decreases; while under different illegal parking shapes outside the trajectory, as the intrusion distance increases, the speed of right-turning motor vehicles gradually increases. This trend is closely related to the influence of the intrusion distance on the driving path of right-turning vehicles. For the illegally parked vehicles inside the trajectory, an increase in the intrusion distance to the stop line means that right-turning vehicles need more time and space to bypass these obstacles, resulting in a decrease in speed. On the contrary, for the illegally parked vehicles outside the trajectory, an increase in the intrusion distance has less impact on the path of the right-turning traffic flow, and it may even not require significant adjustment by right-turning vehicles. Therefore, the speed of right-turning vehicles will gradually increase. As the number of illegal parkings increases, the speed of right-turning motor vehicles gradually decreases. This is because a large number of non-motor vehicles are illegally parked at the intersection. To ensure driving safety, right-turning motor vehicles need to avoid these non-motor vehicles in a narrow passing space, resulting in a slowdown in speed.

[0162] The right-turn vehicle passing capacity model constructed in this application is under the influence of non-motor vehicles crossing the line and illegally parking. The widely used HCM2010 algorithm combines pedestrians and non-motor vehicles as a whole for research, and does not consider the influence of non-motor vehicles crossing the line and illegally parking on the right-turn traffic flow during the analysis process. Step S4, in order to more accurately evaluate the passing capacity of right-turning motor vehicles, a correction coefficient algorithm considering the influence of non-motor vehicle illegal parking is designed as: Rpb The pedestrians and non-motor vehicles are combined as a whole for research, and the influence of non-motor vehicles crossing the line and illegally parking on the right-turn traffic flow is not considered during the analysis process. Step S4, in order to more accurately evaluate the passing capacity of right-turning motor vehicles, a correction coefficient algorithm considering the influence of non-motor vehicle illegal parking is designed as:

[0163] f Rpb =min(f Rp ,f Rb ) (7)

[0164] In Formula (7), f Rpb is the correction coefficient of the saturation flow rate of non-motor vehicles and pedestrians for right-turning motor vehicles, f Rb is the correction coefficient of the saturation flow rate of non-motor vehicles for right-turning motor vehicles considering the influence of non-motor vehicle illegal parking; f Rp is the correction coefficient of the saturation flow rate of pedestrians for right-turning motor vehicles. At intersections where non-motor vehicles are the main factor affecting the driving of right-turning vehicles, pedestrians can quickly leave the potential conflict area and will not affect the passing of right-turning vehicles. Therefore, f Rp =1; Therefore, Formula (7) is simplified to f Rpb =f Rb .

[0165] Based on the analyzed data, this application targets the four phase stages within the signal cycle: Red 1 phase stage (straight red light phase), Red 2 phase stage (straight and left-turn red light phase), Green 1 phase stage (straight green light phase), and Green 2 phase stage (left-turn green light phase). Regarding the conflict area, such as Figure 5As shown, the gray box part in 5a is a schematic diagram of the conflict area in the red 1 phase, and the gray box part in 5b is a schematic diagram of the conflict area in the green 1 phase and the green 2 phase.

[0166] In the red 1 phase, the right-turning motor vehicles are affected by the conflict with oncoming non-motor vehicles from the left and the illegal parking of non-motor vehicles outside the track on their own side; in the red 2 phase, the right-turning motor vehicles are affected by the illegal parking of non-motor vehicles inside the track; in the green 1 phase, the right-turning motor vehicles are affected by the conflict with oncoming non-motor vehicles going straight and the illegal parking of non-motor vehicles outside the track, which affects the passage of right-turning motor vehicles; in the green 2 phase, the right-turning motor vehicles are affected by the conflict with left-turning non-motor vehicles coming from the opposite direction and the illegal parking of non-motor vehicles inside the track on their own side. Of course, under the influence of non-motor vehicles crossing the line and parking illegally, each factor is closely related to the right-turning vehicle speed. Especially when calculating the passing volume of right-turning vehicles, right-turning motor vehicles in all four phase stages are affected by non-motor vehicles crossing the line and parking illegally.

[0167] In the red 1 phase, the change of traffic flow is divided into two processes. The first process means that the non-motor vehicles going straight across the street from the adjacent left import lane have not reached the conflict area, and at this time the right-turning motor vehicles can drive freely; the second process means that there is a traffic conflict between the right-turning motor vehicles and the non-motor vehicles going straight across the street from the adjacent left import lane, and at the same time they are also affected by the illegal parking of non-motor vehicles crossing the line inside the track. Therefore, the expression of the correction coefficient of the saturated flow rate of non-motor vehicles on right-turning motor vehicles during the red 1 phase is:

[0168]

[0169] In formula (8), f 1RRb is the correction coefficient of the saturated flow rate of non-motor vehicles on right-turning motor vehicles in the red 1 phase; f RRb1 is the correction coefficient of the saturated flow rate of right-turning vehicles in the first process of the red 1 phase. In this stage, the right-turning vehicles are not affected by non-motor vehicles from the left, so f RRb1 = 1; P 1 is the proportion of the initial red light duration T r1 in the red light time T R1 of the red 1 phase, T R1 is the red 1 phase time, in seconds, T r1 is the initial red light duration of the first process, in seconds, T r1 = L / v bs , L is the distance that the non-motor vehicles going straight across the street from the adjacent left import lane need to travel to reach the conflict area after entering the intersection, in meters; v bs is the speed of the non-motor vehicles going straight across the street from the adjacent left import lane when they reach the conflict area, in m / s. The free flow speed of non-motor vehicles is taken as 5.56 m / s; f RRb2It is the correction coefficient under the combined influence of the oncoming non-motor vehicle conflict for going straight across the street at the left adjacent approach during the second process of the red 1 phase and the illegal parking by crossing the inner side of the non-motor vehicle track on this side; f′ RRb2 It is the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of the oncoming non-motor vehicle conflict for going straight across the street at the left adjacent approach; f″ RRb2 It is the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of the illegal parking by crossing the inner side of the non-motor vehicle track on this side; P 2 It is the time T of the second process R1 -T r1 It is the proportion of the red 1 phase red light time T R1 in

[0170] During the red 2 phase, the right-turning motor vehicles do not conflict with oncoming vehicles from other directions and are only affected by the illegal parking by crossing the inner side of the non-motor vehicle track on this side. Therefore, the correction coefficient of the saturated flow rate of right-turning motor vehicles in the red 2 phase is:

[0171] f 2RRb =f″ RRb (9)

[0172] In formula (9), f 2RRb is the correction coefficient of the saturated flow rate of right-turning motor vehicles by non-motor vehicles in the red 2 phase; f″ RRb is the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of the illegal parking by crossing the inner side of the non-motor vehicle track on this side in the red 2 phase.

[0173] The green 1 phase is divided into two processes. In the first process, at the initial stage of the green light, a large number of non-motor vehicles going straight on this side enter and occupy the conflict area, and at this time, the right-turning motor vehicles need to stop and wait. In the second process, the right-turning motor vehicles conflict with the non-motor vehicles going straight on this side. In addition, the illegal parking behavior of non-motor vehicles crossing the outer side of the track also interferes with the passage of right-turning motor vehicles. Therefore, the expression of the correction coefficient of the saturated flow rate of right-turning motor vehicles by non-motor vehicles during the green 1 phase is:

[0174]

[0175] In formula (10), f 1GRb is the correction coefficient of the saturated flow rate of right-turning motor vehicles by non-motor vehicles in the green 1 phase, f GRb1 is the correction coefficient of the saturated flow rate of right-turning in the first process of the green 1 phase, f GRb1 =0; P 3 is the time T at the initial stage of the green light in the green 1 phase g1 as the proportion of the green 1 phase time, T g1 is the duration of the initial stage of the green light in the first process, with the unit of s, λ Bis the arrival rate of non-motor vehicles at the approach on the same side of the intersection, with the unit of vehicle / s, T R is the red light time within a cycle, with the unit of s, N t is the saturated flow rate of the non-motor vehicle lane section at the intersection, with the unit of bicycle / (s·m), and its value is taken as 0.613 bicycle / (s·m), D is the width of the non-motor vehicle lane, with the unit of m; T G1 is the green 1 phase time, with the unit of s; f GRb2 is the correction coefficient under the combined influence of the straight-through non-motor vehicle crossing conflict on the same side and the interference of illegal parking beyond the line outside the non-motor vehicle trajectory during the second process of the green 1 stage; f′ GRb2 is the correction coefficient of the saturated flow rate of the right-turn motor vehicle under the influence of the straight-through non-motor vehicle crossing conflict on the same side; f″ GRb2 is the correction coefficient of the saturated flow rate of the right-turn motor vehicle under the influence of illegal parking beyond the line outside the non-motor vehicle trajectory on the same side; P 4 is the time T of the second process of the green 1 phase G1 -T g1 occupies the proportion of the green 1 phase time T G1 of,

[0176] During the green 2 phase, the right-turn motor vehicle is not only affected by the conflict with the left-turn non-motor vehicle, but also affected by the illegal parking of the non-motor vehicle waiting to go straight beyond the line inside the trajectory. Therefore, the correction coefficient of the saturated flow rate of the right-turn motor vehicle in the green 2 phase is:

[0177] f 2GRb =f′ GRb ·f″ GRb (11)

[0178] In formula (11), f 2GRb is the correction coefficient of the saturated flow rate of the right-turn motor vehicle by non-motor vehicles in the green 2 phase; f′ GRb is the correction coefficient of the saturated flow rate of the right-turn motor vehicle under the influence of the left-turn non-motor vehicle conflict; f″ GRb is the correction coefficient of the saturated flow rate of the right-turn motor vehicle under the influence of illegal parking beyond the line inside the non-motor vehicle trajectory on the same side.

[0179] Based on formulas (8)-(11), the calculation formula for the traffic capacity of the signalized intersection is obtained as:

[0180]

[0181] In formula (12), S k is the saturated flow of the kth phase stage, with the unit of vehicle / h, k takes R1, R2, G1, and G2, corresponding to the red 1 phase stage, red 2 phase stage, green 1 phase stage, and green 2 phase stage respectively; S 0 ′ = S0 ·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT ; C is the signal cycle duration, with the unit of s.

[0182] Next, solve for each variable in formula (12). Since the illegal parking of non-motor vehicles across the line affects the right-turning motor vehicles in all four phase stages, the saturation flow rate correction coefficient of right-turning motor vehicles affected by illegal parking in each phase stage is calculated. The expression for the saturation flow rate correction coefficient of right-turning motor vehicles affected by illegal parking in each phase stage is:

[0183] Red 1 phase

[0184] Red 2 phase

[0185] Green 1 phase

[0186] Green 2 phase

[0187] In formula (13), C″ R12 is the number of vehicles passing through the non-motor vehicle illegal parking area at the entrance during the red 1 time within one hour, with the unit of vehicles / h; T R1 -T r1 is the second process time of the red 1 phase;

[0188] In formula (14), C″ R2 is the number of vehicles passing through the non-motor vehicle illegal parking area at the entrance during the red 2 time within one hour, with the unit of vehicles / h; T R2 is the red 2 phase time;

[0189] In formula (15), C″ G12 is the number of vehicles passing through the non-motor vehicle illegal parking area at the entrance during the green 1 time within one hour, with the unit of vehicles / h; T G1 -T g1 is the second process time of the green 1 phase;

[0190] In formula (16), C″ G2 is the number of vehicles passing through the non-motor vehicle illegal parking area at the entrance during the green 2 time within one hour, with the unit of vehicles / h; T G2 is the green 2 phase time;

[0191] During the red 1, green 1, and green 2 phase stages, right-turning motor vehicles are affected by non-motor vehicle conflicts during operation. During the red 2 phase stage, right-turning motor vehicles do not conflict with oncoming vehicles from other directions. Therefore, for the three phase stages of red 1, green 1, and green 2, it is necessary to calculate the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of conflicts, and the expression is as follows:

[0192] Red 1 phase

[0193] Green 1 phase

[0194] Green 2 phase

[0195] In formula (17), Q′ R12 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of oncoming straight non-motor vehicles from the left adjacent approach during the second process of the red 1 phase stage, with the unit of vehicles / h;

[0196] In formula (18), Q′ G12 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of straight non-motor vehicles crossing on the same side during the second process of the green 1 phase stage, with the unit of vehicles / h;

[0197] In formula (19), Q′ G2 is the maximum number of right-turning vehicles passing through the available gap under the influence of the conflict of left-turning non-motor vehicles during the green 2 phase stage, with the unit of vehicles / h.

[0198] During the red 1 phase stage, red 2 phase stage, green 1 phase stage, and green 2 phase stage, the traffic wave theory is applied to study the passing capacity of right-turning vehicles under the influence of non-motor vehicle illegal parking; Figure 2 As shown, under the influence of non-motor vehicle over-line illegal parking, assuming that when there is no influence of non-motor vehicle illegal parking, the average speed of the right-turning vehicle flow is u 1 , and the traffic flow of the right-turning vehicle flow is q 1 . When there is non-motor vehicle over-line illegal parking at the intersection, the right-turning vehicle path area becomes narrower, so that as the number of non-motor vehicle over-line illegal parkings increases, a bottleneck area of the right-turning vehicle flow appears, and the traffic wave is transmitted upstream accordingly. At this time, the average speed of the conflicting right-turning vehicle flow drops from u 1 without the influence of non-motor vehicle illegal parking to u 2 with the influence of non-motor vehicle illegal parking, and the running state of the right-turning vehicle changes from state A (u 1 , q 1 ) without the influence of non-motor vehicle illegal parking to the blocked state B (u 2 , q 2 );

[0199] At this time, there is a compression wave propagating from front to back in the conflicting vehicle flow, and the wave speed is:

[0200]

[0201] In formula (20): u 1 is the average speed of the upstream right-turning vehicles without the influence of non-motor vehicle illegal parking, with the unit of km / h, and q 1 is the flow of the upstream right-turning vehicles without the influence of non-motor vehicle illegal parking, with the unit of vehicles / h; u 2 is the average speed of the downstream right-turning vehicles with the influence of non-motor vehicle illegal parking, with the unit of km / h, and u 2 can be calculated according to formula (4), and q 2 is the flow of the downstream right-turning vehicles with the influence of non-motor vehicle illegal parking, with the unit of vehicles / h;

[0202] During the phase time within one hour, the number of vehicles passing through the non-motor vehicle illegal parking area of the approach is:

[0203] C″ = (u 1 - u w )k 1 = (u 2 - u w )k 2 (21)

[0204] In formula (21), C″ is the number of vehicles passing through the non-motor vehicle illegal parking area of the approach, with the unit of vehicles / h; k 1 is the density of the upstream right-turning vehicles without the influence of illegal parking, with the unit of km / vehicle; k 2 is the density of the downstream right-turning vehicles with the influence of illegal parking, with the unit of km / vehicle;

[0205] Meanwhile, during the phase time within the same hour, the expression of the relationship between the right-turning traffic flow and the right-turning traffic speed is:

[0206] q(u) = 220.64u 0.7493 (22)

[0207] Substituting wave speed formula (20) and formula (22) into formula (21), we get:

[0208]

[0209] During the red 1 phase, substituting the right-turning motor vehicle speed interference response model formula (4) under the influence of non-motor vehicle illegal parking on the inner side of the trajectory into formula (23), we get:

[0210]

[0211] In formula (24), u shapei is the right-turning vehicle speed under the influence of non-motor vehicle illegal parking on the inner side of the trajectory, where i = 1, 2, 3;

[0212] Substituting formula (24) into formula (13) gives the correction coefficient of the saturated flow rate of right-turning motor vehicles under the influence of illegal parking during the red 1 phase, and the expression is:

[0213] Red 1 phase

[0214] Based on the process analysis of the red 1 phase, the correction coefficients f R ″ Rb 、f G ″ Rb2 and f G ″ Rb ,

[0215] Red 2 phase

[0216] Green 1 phase

[0217] Green 2 phase

[0218] In formula (26), u shapei is the right-turning vehicle speed under the influence of illegal parking of non-motor vehicles inside the track during the red 2 phase;

[0219] In formula (27), u shapej is the right-turning vehicle speed under the influence of illegal parking of non-motor vehicles outside the track during the green 1 phase, where j = 4, 5;

[0220] In formula (28), u shapei is the right-turning vehicle speed under the influence of illegal parking of non-motor vehicles inside the track during the green 2 phase.

[0221] The maximum number of right-turning vehicles Q′ R12 passing through the available gap under the influence of the conflict of oncoming non-motor vehicles going straight across the adjacent approach on the left during the red 1 phase is calculated by the formula:

[0222]

[0223] In formula (27), λ b is the arrival rate of non-motor vehicles at the left approach during the red 1 phase, with the unit of vehicle / s; λ m1 is the arrival rate of right-turning vehicles at the conflict area during the red 1 phase, with the unit of vehicle / s; μ 0 is the passing gap when right-turning vehicles cross non-motor vehicles, with the unit of s, and this parameter is obtained by using the RAFF method based on the accepted gaps and rejected gaps statistically analyzed from traffic measurement data; μ fis the following-distance time when a motor vehicle turns right, with the unit of s. This parameter is obtained by taking the average of the following-distance times of the right-turning motor vehicles through statistics;

[0224] Substituting formula (29) into formula (17), the correction coefficient f of the saturated flow rate of the right-turning motor vehicle under the influence of the oncoming non-motor vehicle conflicts in the straight-through crosswalk of the adjacent approach on the left can be calculated R ′ Rb2 。

[0225] Based on the analysis of the red 1 phase process, the maximum number of right-turning vehicles Q′ passing through the available gap in the green 1 phase is obtained G12 ,and the calculation formula is:

[0226]

[0227] In formula (30), λ m2 is the arrival rate of right-turning vehicles in the green 1 phase to the conflict area, with the unit of vehicle / s;

[0228] Substituting formula (30) into formula (18), the correction coefficient f of the saturated flow rate of right-turning vehicles under the influence of conflicts in the green 1 phase can be calculated G ′ Rb2 ;

[0229] Based on the analysis of the red 1 phase process, the maximum number of right-turning vehicles Q′ passing through the available gap in the green 2 phase is obtained G2 ,and the calculation formula is:

[0230]

[0231] In formula (31), λ m3 is the arrival rate of right-turning vehicles in the green 2 phase to the conflict area, with the unit of vehicle / s;

[0232] Substituting formula (31) into formula (19), the correction coefficient f of the saturated flow rate of right-turning vehicles under the influence of conflicts in the green 2 phase can be calculated G ′ Rb 。

[0233] In formula (12), regarding S 0 ′=S 0 ·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT ,S 0$S_0$ is the saturated flow rate of the lane group under ideal conditions. The saturated flow rate for straight-through vehicles is taken as 1650 pcu / h, and the saturated flow rate for right-turning motor vehicles is taken as 1550 pcu / h;

[0234] $N$ is the number of lanes in the lane group;

[0235] $f$ w is the lane width correction coefficient, where $W$ is the width of the motor vehicle lane, in m. $W$ is taken to be greater than 2.4 m. When $W \gt 4.8$ m, it is analyzed as a two-lane road;

[0236] $f$ HV is the correction coefficient for large vehicles; $P$ HV is the percentage of large vehicles in the traffic flow in the right-turn lane. $E$ HV is the conversion coefficient for large vehicles, taken as 2.0;

[0237] $f$ g is the approach slope correction coefficient; $G$ is the slope of the approach lane group, $-0.06 \leq G \leq 0.10$. It is negative when going downhill;

[0238] $f$ p is the correction coefficient for the number of stops in adjacent lanes, $N$ m is the number of stops, in times / h; $f$ bb is the correction coefficient for bus blockage, $N$ B is the number of bus stops within one hour, in vehicles / h; $f$ a is the correction coefficient for area type. Among them, for urban centers and commercial areas, it is taken as 0.9, and for other areas, it is taken as 1.0;

[0239] $f$ LU is the lane utilization reduction coefficient; $f$ RT is the correction coefficient for the right-turn lane. Among them, when there is a dedicated right-turn lane, $f$ RT $ = 0.85$. When it is a shared straight-through and right-turn lane, $f$ RT $ = 1 - 0.15P$ RT When there is only a single lane at the intersection approach, $f$ RT $ = 1 - 0.135P$ RT $P$ RT is the proportion of right-turning vehicles in the approach of the intersection in the traffic flow.

[0240] Examples and comparative examples:

[0241] In order to verify the superiority and feasibility of the method for constructing the correction model of the passing capacity of right-turning motor vehicles affected by non-motor vehicle over-line illegal parking provided by this application,

[0242] In the embodiment, a cross-shaped intersection is selected, with four-phase signal control and a signal cycle of 160 s. The non-motor vehicle flow at the east approach is 916 vehicles / h, the non-motor vehicle flow at the south approach is 824 vehicles / h, the non-motor vehicle flow at the west approach is 1115 vehicles / h, the non-motor vehicle flow at the north approach is 786 vehicles / h, the width of the non-motor vehicle lane is 2.2 m, the width of the right-turn lane is 3.2 m, and the critical gap μ 0 is 3.6 s, and the following distance of right-turning motor vehicles μ f is 2.3 s. The basic saturated flow of right-turns is 1550 pcu / h. According to the improved traffic capacity model, the traffic capacities of right-turning vehicles under the red 1 phase, red 2 phase, green 1 phase, and green 2 phase are 900 veh / h, 1040 veh / h, 510 veh / h, and 625 veh / h respectively.

[0243] In the comparative example, a T-shaped intersection is selected, with four-phase signal control. There is a right-turn lane at the west approach and a dedicated right-turn phase is set, and the signal cycle is 150 s. The non-motor vehicle flow at the east approach is 1244 vehicles / h, the non-motor vehicle flow at the south approach is 695 vehicles / h, the non-motor vehicle flow at the west approach is 905 vehicles / h, the width of the non-motor vehicle lane is 2.4 m, the width of the right-turn lane is 3.2 m, and the critical gap μ 0 is 3.6 s, and the following distance of right-turning motor vehicles μ f is 2.3 s. Since there is a dedicated right-turn phase at the west approach, only the traffic capacity when right-turning motor vehicles have the right of way is calculated, that is, the green 1 and red 2 phases. According to the improved traffic capacity model, the traffic capacities of right-turning vehicles under the green 1 phase and red 2 phase are 571 veh / h and 903 veh / h respectively.

[0244] The traffic capacities of the two intersections are calculated respectively by the HCM method (HCM model), the improved model of Dong Ningning in [8] in the background technology, and the improved model of this paper (reference model). The numerical values and algorithm errors of each calculation model are shown in Table 1.

[0245] Table 1 Comparison table of right-turn traffic capacities at each intersection (pcu / h)

[0246]

[0247] The HCM reduces based on the saturated flow rate under ideal conditions, without considering the impact of conflicts between motor vehicles and non-motor vehicles and illegal parking of non-motor vehicles on the right-turning vehicle flow; the reference model only considers the impact of the number of non-motor vehicles on the right side during the red light on the right-turning vehicle flow, ignoring the impact of the behavior of non-motor vehicles crossing the line and illegal parking. Therefore, as can be seen from Table 1, the passing capacity of right-turning motor vehicles calculated by the improved model provided in this application is relatively close to the measured passing capacity of right-turning motor vehicles, and the accuracy has been greatly improved compared with the other two algorithms. Moreover, the error between the results of the improved model and the measured results is within 10%, and it has good applicability when there is a dedicated right-turn signal phase at the intersection.

Claims

1. A method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line, characterized by: The following steps are involved: Step S1, data collection, at the four-phase signalized intersection, through manual survey and video survey methods, obtain the intersection size, signal cycle, signal phase, motor vehicle lane width, non-motor vehicle lane width, critical gap, following vehicle time, right-turn motor vehicle traffic volume, non-motor vehicle traffic volume, non-motor vehicle arrival volume, non-motor vehicle crossing the line illegal parking number, illegal parking location and right-turn motor vehicle driving trajectory and speed data under illegal parking; Step S2, based on the data collected in step S1, construct two models. The first model is to conduct correlation analysis on the data of the number of non-motor vehicle arrivals and the number of non-motor vehicle illegal parking, and establish a model for calculating the number of illegal parking; The second method is to classify the shapes of illegal parking of non-motor vehicles according to the characteristics of illegal parking positions, and convert the impact of the shapes of illegal parking of non-motor vehicles on the traffic capacity of right-turn motor vehicles into the impact of the intrusion distance under the illegal parking shape on the traffic capacity of right-turn motor vehicles, and establish an intrusion distance probability model with different shapes; based on the intrusion distance probability model, the expected value calculation model of the intrusion distance is further obtained; Step S3, determining the correlation between the right-turn speed and the number of illegal parking and the intrusion distance through correlation analysis, then establishing a regression model with the right-turn speed data as the dependent variable and the number of illegal parking and the intrusion distance data as the independent variables, and obtaining the function between the right-turn speed and the number of illegal parking and the intrusion distance at different illegal parking positions; integrating the illegal parking number calculation model and the expected value calculation model of the intrusion distance obtained in step S2 with the obtained function, and establishing a right-turn motor vehicle speed interference response model; Step S4, based on the right-turn motor vehicle speed disturbance response model established in step S3, for the four phases of red 1, red 2, green 1 and green 2 in the signal cycle, apply traffic wave theory and gap acceptance theory to respectively construct the right-turn motor vehicle capacity correction coefficient algorithms under the four phase stages, integrate the correction coefficient algorithms under the four phase stages into the HCM model, and establish an improved HCM capacity correction model; Among them, red 1 represents the phase of the red light for going straight, red 2 represents the phase of the red light for turning left when going straight, green 1 represents the phase of the green light for going straight, and green 2 represents the phase of the green light for turning left.

2. The method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 1 is characterized by: In step S2, the established illegal parking quantity calculation model is: Q e-bike =0.000174Q arrival 3 -0.0101Q arrival 2 +0.407Q arrival +0.366 (1) In formula (1), Q e-bike is the number of illegal parking of non-motor vehicles, in units of vehicles, Q arrival is the number of non-motor vehicles arriving at the intersection, in vehicles; The steps to establish the intrusion distance probability model are: Step S221, the illegal parking position of non-motor vehicles is divided into the inner side of the track and the outer side of the track according to the driving track of the right-turning motor vehicle, wherein the illegal parking position on the inner side of the track refers to the illegal parking position of non-motor vehicles crossing the line and distributed at the pedestrian crossing position on this side, that is, the right side of the right-turning track of the motor vehicle; the illegal parking position on the outer side of the track refers to the illegal parking position of non-motor vehicles crossing the line and mainly distributed on the left side of the right-turning track of the motor vehicle; Step S222, classifying the illegal parking shapes of non-motor vehicles. In the inner track condition, the illegal parking shapes are divided into left straight shape, front convex shape and right straight triangle shape. In the outer track condition, the illegal parking shapes are divided into rectangle and triangle shape. Step S223: The illegal parking distance directly reflects the degree of encroachment of the right-turn lane by the illegally parked non-motor vehicle under various illegal parking shapes. Therefore, the intrusion distance is defined as D y , under each illegal parking shape inside the track, the intrusion distance D y It refers to the distance from the frontmost illegal parking point near the right-turn traffic flow to the stop line. Under each illegal parking shape outside the trajectory, the intrusion distance D y It refers to the distance from the rearmost illegal parking point close to the right-turn traffic flow to the stop line; Step S224: Based on the outer dimensions of the non-motor vehicle being 1.9 m long and 0.6 m wide, the non-motor vehicle static parking area is 1.3-1.8 m 2 , the invasion distance is divided into 2m units, and the invasion distance is divided into four groups of 0-2m, 2-4m, 4-6m, and 6-8m according to the traffic conditions at the intersection; the probability model of the invasion distance under different illegal parking shapes is established using Bayesian theory. The probability model of the invasion distance under different illegal parking shapes is as follows: In formula (2), i is the intrusion distance group, 2 meters per group; A j It is the shape of illegal parking of non-motor vehicles; T is the phase stage P(D yi ) is the prior probability, that is, the probability of a certain set of intrusion distances appearing, n i is the frequency of the invasion distance of the i-th group; M is the total number of samples; P(A j ,T|D yi ) is the likelihood probability, which represents the conditional factors for the occurrence of a certain group of intrusion distances of non-motor vehicles, P(A j ,T) is the total probability, that is, considering all possible intrusion distances D yi In the case of illegal parking shape A j and the total probability of phase T occurring; P(A j ,T)=∑P(D yi )·P(A j ,T|D yi ); P(D yi |A j ,T) is the posterior probability, that is, when the illegal parking shape A is known j When phase T occurs, the invasion distance D of the i-th group yi Probability of occurrence; Step S225, using the intrusion distance probability model under different illegal parking shapes to calculate the intrusion distance D under each illegal parking shape y Expected value, the expected value calculation model of the intrusion distance of non-motor vehicles under different illegal parking shapes is expressed as: In formula (3), E(D y |A j ,T) is the known illegal parking shape A j When the phase T occurs, the non-motor vehicle intrusion distance D yi The expected value of x i is the midpoint value of the invasion distance of the i-th group.

3. The method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 1 is characterized in that: In step S3, based on the number of illegal parking lots Q e-bike And the intrusion distance D under the illegal parking shape of non-motor vehicles y , a right-turn motor vehicle speed disturbance response model is established to describe the change of the right-turn motor vehicle speed, and its expression is as follows: in shape =b0+b1D y +b2Q e-bike +ξ (4) In formula (4), u shape is the speed of the right-turning vehicle in m / s, Q e-bike is the number of illegal parking of non-motor vehicles, in units of vehicles, calculated according to formula (1); D y is the intrusion distance length, in meters. The expected value of the intrusion distance under each illegal parking shape is calculated according to formula (3); ξ is the error term, b0 is the model constant, and b1 is D y The coefficient of b2 is Q e-bike The coefficient of Based on the general form of the right-turn motor vehicle speed disturbance response model, for different illegal parking shapes, a right-turn motor vehicle speed disturbance response model under each illegal parking shape is established, specifically including the inner and outer sides of the track, which are: Inside the track: Outside of track:

4. The method for constructing a corrected model for the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 1 is characterized in that: In step S4, the steps of constructing the right-turn motor vehicle capacity correction coefficient algorithm in four phase stages are as follows: Step S41, using the HCM algorithm to analyze the impact of non-motor vehicles crossing the line and illegally parking on the right-turn traffic flow without considering it. In order to more accurately evaluate the right-turn motor vehicle traffic capacity, the correction coefficient algorithm considering the impact of non-motor vehicles illegally parking is designed and set as follows: f Rpb =min(f Rp ,f Rb ) (7) In formula (7), f Rpb is the correction coefficient of the saturation flow rate of non-motor vehicles and pedestrians to right-turn motor vehicles, f Rb f is the correction coefficient of the saturated flow rate of non-motor vehicles to right-turning motor vehicles under the influence of illegal parking of non-motor vehicles; Rp is the correction coefficient of pedestrians to the saturation flow rate of right-turning vehicles. At the intersection where non-motor vehicles are the main factor affecting the movement of right-turning vehicles, pedestrians can quickly leave the potential conflict area and will not affect the passage of right-turning vehicles. Therefore, f Rp =1; Therefore, formula (7) is simplified to f Rpb =f Rb ; Step S42: according to the intersection phase, f Rb The calculation is divided into four parts, namely, red 1 phase stage, red 2 phase stage, green 1 phase stage and green 2 phase stage; Step S43, in the Red 1 phase, the change of traffic flow is divided into two processes. The first process refers to the non-motorized vehicles crossing the street on the left adjacent entrance road have not yet reached the conflict zone, and the right-turning motor vehicle can travel freely at this time; the second process refers to the traffic conflict between the right-turning motor vehicle and the non-motorized vehicles crossing the street on the left adjacent entrance road, and at the same time, it is also affected by the illegal parking of the non-motorized vehicles on the inner side of the track. Therefore, during the Red 1 phase, the correction coefficient expression of the saturation flow rate of the non-motorized vehicles to the right-turning motor vehicle is: In formula (8), f 1RRb f is the correction coefficient of the saturated flow rate of non-motor vehicles to right-turning motor vehicles in the red 1 phase; RRb1 is the correction coefficient of the right-turn saturation flow rate in the first process of the red 1 stage. In this stage, the right-turning vehicle is not affected by the non-motor vehicle on the left, so f RRb1 =1; P1 is the initial duration of the red light in the first process T r1 Occupancy red light time of red 1 phase T R1 The proportion of T R1 is the red 1 phase time, in seconds, T r1 The initial duration of the red light in the first process, in seconds, T r1 =L / v bs , L is the distance that a non-motor vehicle that crosses the street straight through the adjacent entrance on the left side needs to travel after entering the intersection to reach the conflict zone, in meters; v bs is the speed of non-motor vehicles crossing the street in the adjacent entrance lane on the left to the conflict zone, in m / s, and the free flow speed of non-motor vehicles is 5.56 m / s; RRb2 f′ is the correction coefficient for the combined influence of the conflict between the non-motor vehicle crossing the street in the adjacent entrance lane on the left and the illegal parking on the inner side of the non-motor vehicle trajectory on this side; RRb2 It is the saturation flow rate correction coefficient of right-turning motor vehicles under the influence of the conflict between non-motor vehicles crossing the street in the adjacent entrance lane on the left; f″ RRb2 is the saturation flow rate correction coefficient of the right-turning motor vehicle under the influence of illegal parking on the inner side of the non-motor vehicle track; P2 is the second process time T R1 -T r1 Occupancy red light time of red 1 phase T R1 The proportion of Step S44, in the Red 2 phase, the right-turning motor vehicle does not conflict with vehicles coming from other directions, and is only affected by the illegal parking of non-motor vehicles on the inner side of the trajectory. Therefore, the correction coefficient of the saturation flow rate of the right-turning motor vehicle in the Red 2 phase is: f 2RRb =f″ RRb (9) In formula (9), f 2RRb f″ is the correction coefficient of the saturated flow rate of non-motor vehicles to right-turning motor vehicles in the red 2 phase; RRb is the saturation flow rate correction coefficient of the right-turning motor vehicle under the influence of illegal parking on the inner side of the non-motor vehicle trajectory during the red 2 phase; Step S45, the green 1 phase stage is divided into two processes. In the first process, which refers to the early stage of the green light, a large number of straight non-motor vehicles on this side enter and occupy the conflict area. At this time, the right-turning motor vehicle needs to stop and wait; in the second process, the right-turning motor vehicle conflicts with the straight non-motor vehicle on this side. In addition, the illegal parking behavior of non-motor vehicles outside the track also interferes with the passage of right-turning motor vehicles; therefore, the correction coefficient expression of the saturation flow rate of non-motor vehicles to right-turning motor vehicles during the green 1 phase is: In formula (10), f 1GRb f is the correction coefficient of the saturation flow rate of non-motor vehicles to right-turning motor vehicles in the green 1 phase, GRb1 is the correction coefficient of the right-turn saturation flow rate in the first process of green 1 stage, f GRb1 =0; P3 is the initial time T of green light in green 1 phase g1 The proportion of green 1 phase time, T g1 The initial duration of the green light in the first process, in seconds. λ B is the non-motor vehicle arrival rate at the entrance of the intersection, in vehicles / s. The arrival rate of non-motor vehicles conforms to the negative binomial distribution. R is the red light time in one cycle, in seconds, N t is the saturated flow rate of the non-motor vehicle lane section at the intersection, in bicycle / (s·m), and its value is 0.613bicycle / (s·m); D is the width of the non-motor vehicle lane, in m; T G1 Green 1 phase time, unit is s; f GRb2 f′ is the correction coefficient under the combined influence of the conflict of non-motor vehicles going straight on this side and the interference of illegal parking outside the non-motor vehicle track during the second process of green 1 stage; GRb2 is the saturation flow rate correction coefficient of the right-turning motor vehicle under the influence of the straight non-motor vehicle crossing conflict on this side; f″ GRb2 is the saturation flow rate correction coefficient of the right-turning motor vehicle under the influence of illegal parking outside the non-motor vehicle track on this side; P4 is the second process time T of the green 1 phase G1 -T g1 Green 1 phase time T G1 The proportion of Step S46, in the Green 2 phase, the right-turning motor vehicle is not only affected by the conflict with the left-turning non-motor vehicle, but also by the non-motor vehicle waiting to go straight on the inner side of the track crossing the line and illegally parking. Therefore, the saturation flow rate correction coefficient of the right-turning motor vehicle in the Green 2 phase is: f 2GRb =f′ GRb ·f″ GRb (11) In formula (11), f 2GRb f′ is the correction coefficient of the saturated flow rate of non-motor vehicles to right-turning motor vehicles in the green 2 phase; GRb is the saturation flow rate correction coefficient of right-turning motor vehicles under the influence of left-turning non-motor vehicles conflict; f″ GRb is the saturation flow rate correction coefficient of the right-turning motor vehicle under the influence of illegal parking on the inner side of the non-motor vehicle track; Step S47, based on steps S43 to S46, the calculation formula for the signalized intersection capacity is obtained as follows: In formula (12), S k is the saturated flow rate in the kth phase stage, in units of vehicles / h, k is R1, R2, G1 and G2, corresponding to the corresponding red 1 phase stage, red 2 phase stage, green 1 phase stage and green 2 phase stage respectively; S0′=S0·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT ; C is the signal cycle length, in seconds.

5. The method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 4 is characterized in that: Since non-motor vehicles crossing the line and illegally parking have an impact on right-turning vehicles in the four phases, the saturated flow rate correction coefficient of right-turning vehicles under the influence of illegal parking in each phase is calculated. The expression of the saturated flow rate correction coefficient of right-turning vehicles under the influence of illegal parking in each phase is: Red 1 Phase Red 2 Phase Green 1 Phase Green 2 Phase In formula (13), C″ R12 is the number of vehicles passing through the non-motor vehicle illegal parking area on the entrance road during the Red 1 time within one hour, in vehicles / h; T R1 -T r1 It is the second process time of red 1 phase; In formula (14), C″ R2 is the number of vehicles passing through the non-motor vehicle illegal parking area on the entrance road during the Red 2 time within one hour, in vehicles / h; T R2 is the red 2 phase time; In formula (15), C″ G12 T is the number of vehicles passing through the non-motor vehicle illegal parking area on the entrance road during the Green 1 time within one hour, in vehicles / h; G1 -T g1 It is the second process time of green 1 phase; In formula (16), C″ G2 T is the number of vehicles passing through the non-motor vehicle illegal parking area on the entrance road during the Green 2 time within one hour, in vehicles / h; G2 It is the green 2 phase time; In the red 1, green 1 and green 2 phases, right-turning motor vehicles are affected by non-motor vehicle conflicts during operation. In the red 2 phase, right-turning motor vehicles do not conflict with vehicles coming from other directions. Therefore, for the three phases of red 1, green 1 and green 2, it is necessary to calculate the saturation flow rate correction coefficient of right-turning motor vehicles under the influence of conflicts. The expression is as follows: Red 1 Phase Green 1 Phase Green 2 Phase In formula (17), Q′ R12 The maximum number of right-turning vehicles passing through the traversable gap under the influence of the conflict between the straight-moving non-motorized vehicles on the adjacent entrance lane on the left side in the second process of the Red 1 phase, in vehicles / h; In formula (18), Q′ G12 The maximum number of right-turning vehicles passing through the traversable gap under the influence of the straight-moving non-motor vehicle crossing conflict on this side in the second process of the green 1 phase, in vehicles / h; In formula (19), Q′ G2 It is the maximum number of right-turning vehicles that can pass through the traversable gap under the influence of left-turning non-motor vehicle conflicts in the Green 2 phase, in vehicles / h.

6. The method for constructing a corrected model for the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 5 is characterized in that: In the red 1 phase stage, the red 2 phase stage, the green 1 phase stage and the green 2 phase stage, the traffic wave theory is applied to study the right-turn vehicle capacity under the influence of non-motor vehicle illegal parking; specifically, under the influence of non-motor vehicle illegal parking, when there is no non-motor vehicle illegal parking, the average speed of the right-turn traffic is u1, and the right-turn traffic flow is q1. When there is non-motor vehicle illegal parking at the intersection, the right-turn path area of ​​the motor vehicle becomes narrower, so that as the number of non-motor vehicle illegal parking increases, the bottleneck area of ​​the right-turn traffic appears, and thus the traffic wave is transmitted upstream. At this time, the average speed of the conflicting right-turn traffic is reduced from u1 without the influence of non-motor vehicle illegal parking to u2 with the influence of non-motor vehicle illegal parking, and the running state of the right-turn vehicle changes from state A (u1, q1) without the influence of non-motor vehicle illegal parking to state B (u2, q2) when blocked; At this time, there is a compression wave propagating from front to back in the conflicting traffic flow, and the wave speed is: In formula (20), u1 is the average speed of upstream right-turning vehicles without the influence of illegal non-motor vehicle parking, in km / h; q1 is the flow rate of upstream right-turning vehicles without the influence of illegal non-motor vehicle parking, in vehicles / h; u2 is the average speed of downstream right-turning vehicles with the influence of illegal non-motor vehicle parking, in km / h. u2 is calculated based on the interference response model u shape Calculated, q2 is the flow of right-turning vehicles downstream affected by illegal parking of non-motor vehicles, in units of vehicles / h; During the one-hour phase, the number of vehicles passing through the non-motor vehicle illegal parking area on the entrance road is: C″=(u1-u w )k1=(u2-u w )k2 (21) In formula (21), C″ is the number of vehicles passing through the illegal parking area of ​​non-motor vehicles on the entrance road, in units of vehicles / h; k1 is the density of right-turning vehicles upstream without the influence of illegal parking, in units of km / vehicle; k2 is the density of right-turning vehicles downstream with the influence of illegal parking, in units of km / vehicle; At the same time, in the phase time within the same hour, the relationship between the right-turn traffic flow and the right-turn traffic speed is expressed as: q(u)=220.64u 0.7493 (22) Substituting the wave speed formula (20) and formula (22) into formula (21), we obtain:

7. The method for constructing a corrected model for the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 6 is characterized in that: In the red 1 phase, the speed disturbance response model formula (4) of the right-turning motor vehicle under the influence of illegal parking of non-motor vehicles on the inner side of the trajectory is substituted into formula (23), and the result is: In formula (24), u shapei is the right-turn speed under the influence of illegal parking of non-motor vehicles on the inner side of the trajectory, where i = 1, 2, 3; Substituting formula (24) into formula (13) to obtain the saturation flow rate correction coefficient of right-turning motor vehicles under the influence of illegal parking in the red 1 phase, the expression is: Red 1 Phase Based on the analysis of the red 1 phase process, the right-turn saturated flow rate correction coefficient f″ under the influence of non-motor vehicle crossing the line and illegal parking in the red 2 phase, green 1 phase and green 2 phase is obtained. RRb , f″ GRb2 and f″ GRb , Red 2 Phase Green 1 Phase Green 2 Phase In formula (26), u shapei The right-turn speed under the influence of illegal parking of non-motor vehicles on the inner side of the trajectory during the red 2 phase; In formula (27), u shapej is the right-turn speed under the influence of illegal parking of non-motor vehicles outside the trajectory in the green 1 phase, where j = 4, 5; In formula (28), u shapei It is the right-turn speed under the influence of illegal parking of non-motor vehicles on the inner side of the trajectory in the green 2 phase.

8. The method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 7 is characterized in that: The maximum number of right-turning vehicles Q′ that can pass through the gap under the influence of the conflict between non-motor vehicles crossing the street in the adjacent entrance lane on the left side R12 The calculation formula is: In formula (27), λ b is the non-motor vehicle arrival rate at the left entrance lane in the red 1 phase, in vehicles / s; m1 is the arrival rate of right-turning vehicles in the red 1 phase to the conflict zone, in units of vehicles / s; μ0 is the crossing gap when a right-turning vehicle crosses a non-motor vehicle, in units of seconds. This parameter is obtained using the RAFF method based on the acceptance gap and rejection gap statistics of actual traffic data; μ f The following distance when a motor vehicle turns right, in seconds, is obtained by taking the average of the following distances of motor vehicles turning right. Substituting formula (29) into formula (17), we can calculate the saturation flow rate correction coefficient f′ of right-turning motor vehicles under the influence of the conflict between non-motor vehicles crossing the street in the adjacent entrance lane on the left side: RRb2 .

9. The method for constructing a model for correcting the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 8, characterized in that: Based on the process analysis of the Red 1 phase, the maximum number of right-turning vehicles Q′ passing through the traversable gap in the Green 1 phase is obtained. G12 , the calculation formula is: In formula (30), λ m2 is the arrival rate of right-turning vehicles in the green 1 phase to the conflict zone, in vehicles / s; Substituting formula (30) into formula (18), the right turn saturation flow rate correction coefficient f′ under the influence of green 1 phase conflict can be calculated: GRb2 ; Based on the process analysis of the red 1 phase, the maximum number of right-turning vehicles Q′ passing through the traversable gap in the green 2 phase is obtained. G2 , the calculation formula is: In formula (31), λ m3 is the arrival rate of right-turning vehicles in the green 2 phase to the conflict zone, in vehicles / s; Substituting formula (31) into formula (19), the right turn saturation flow rate correction coefficient f′ under the influence of green 2 phase conflict can be calculated: GRb .

10. The method for constructing a corrected model for the traffic capacity of right-turning motor vehicles under the influence of illegal parking of non-motor vehicles crossing the line according to claim 4, characterized in that: In formula (12), S0′=S0·N·f W ·f HV ·f g ·f p ·f bb ·f a ·f LU ·f RT , S0 is the saturated flow rate of the lane group under ideal conditions, the straight-moving saturated flow rate is 1650 pcu / h, and the right-turning motor vehicle saturated flow rate is 1550 pcu / h; N is the number of lanes in the lane group; f w is the lane width correction factor, Where W is the width of the motor vehicle lane, in meters, and W is greater than 2.4 meters. When W>4.8 meters, the analysis is conducted as a dual-lane lane. f HV is the correction factor for large vehicles; P HV is the percentage of large vehicles in the right-turn lane in the traffic flow, E HV is the conversion factor for large vehicles, which is taken as 2.0; f g is the inlet slope correction factor; G is the slope of the entrance track group, -0.06≤G≤0.10, and it is negative when going downhill; f p is the correction factor for the number of stops in the adjacent lane, N m is the number of parking lots, in times / h; f bb is the bus congestion correction factor, N B is the number of buses stopping within an hour, in units of vehicles / h; f a is the area type correction coefficient, where the city center and commercial area take 0.9, and other areas take 1.0; f LU is the lane utilization reduction factor; f RT is the correction factor for the right-turn lane, where f RT = 0.85, when the straight right shared lane, f RT =1-0.15P RT , when the intersection entrance road has only a single lane, f RT =1-0.135P RT , P RT It is the proportion of right-turning vehicles on the entrance ramp to the traffic flow.

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