CN108877244A - A kind of public transit vehicle intersection operation bottleneck method of discrimination based on dynamic data - Google Patents

Abstract

The invention discloses a dynamic data-based method for judging bottlenecks in the operation of bus intersections. Method steps of the present invention: S1, data preprocessing; S2, obtain the longitude and latitude data of intersection range, screen out the bus operation database within the intersection range from the bus GPS database; S3, use the speed-time integral model to estimate the bus The actual travel time of the vehicle at the intersection, and then calculate the intersection delay of each bus vehicle; S4, calculate the mean value of the average bus delay time at each intersection in the statistical interval; S5, use the grade of the intersecting road to judge the intersection type; S6, The cumulative frequency distribution of the average delay of each type of intersection is classified and counted, the threshold for determining the degree of bottleneck is determined, and the operational bottleneck of each type of intersection is dynamically identified. The invention can improve the operating efficiency of the public transport vehicle at the intersection, and has high universality.

Description

A method for judging bottlenecks of bus intersections based on dynamic data

Technical field:

The invention relates to a dynamic data-based method for judging bottlenecks in the operation of bus intersections, and belongs to the fields of smart bus technology, bus big data, and urban bus operation management.

Background technique:

Intersections are an important part of roads, and they are high-incidence locations for urban traffic delays. The flexibility of bus vehicles is poor. Due to the influence of social vehicles, unreasonable signal configuration, unscientific lane division, and lack of protection of bus rights of way at intersections, the delays of public vehicles are often greater than that of social vehicles, resulting in public transport. The waiting time at the entrance is too long, which affects the overall operating efficiency of public transport vehicles. Therefore, it is necessary to face the public transport system and study the intersection bottlenecks encountered by public transport vehicles during operation. Due to the influence of dynamic traffic flow, the bottleneck has the characteristics of time and space dynamics. At present, most of the bottlenecks are studied based on the influence of static facilities at intersections. Traditional manual survey methods are often used for the collection of intersection data. The analysis reveals a big limitation. It cannot make a dynamic judgment on the time, space, and degree of intersection bottlenecks, which is not conducive to the real-time and scientific nature of public transportation management and decision-making. In recent years, the development of intelligent public transportation systems, especially the vehicle-mounted GPS positioning system, can record the space-time location information of public transportation vehicles in real time, bringing a large amount of public transportation vehicle operation data. How to analyze and mine these data accurately and efficiently, quickly and accurately Identifying intersection bottlenecks in the operation of public transport vehicles is the key to solving the problems of public transport vehicle operation and management. The present invention proposes a dynamic data-based method for judging the operating bottleneck of bus intersections, making full use of the real-time GPS data of the bus and urban road information data to comprehensively analyze and grasp the operating status of the bus at each intersection in the urban traffic system , and dynamically identify the time and space where the bottleneck of the intersection facing the operation of public transport vehicles occurs, and judge the degree of the bottleneck. This method helps the traffic planning department, traffic management department, and public transport management department to accurately grasp the operation status of public transport vehicles at each urban intersection, and rationally allocate road resources through the design optimization and management optimization of the intersection. Operation optimization rationally allocates public transport resources, thereby improving the intersection bottleneck of public transport vehicles and improving the operating efficiency of public transport vehicles at the intersection.

Contents of the invention

The purpose of the present invention is to provide a dynamic data-based method for judging bottlenecks in the operation of bus intersections, which can improve the operating efficiency of buses at intersections, has high universality, and has great promotion prospects.

The above-mentioned purpose is achieved through the following technical solutions:

A method for discriminating bottlenecks in the operation of bus intersections based on dynamic data, the method comprising the following steps:

S1. Data preprocessing, including abnormal data discrimination, data cleaning, data fusion and intersection information supplementation;

S2. Obtain the longitude and latitude data of the intersection range, and filter out the bus operation database within the intersection range from the bus GPS database;

S3. Using the speed-time integral model to estimate the actual travel time of the bus at the intersection, and then calculate the intersection delay of each bus;

S4, calculate the mean value of the average delay time of public transport vehicles at each intersection in the statistical interval;

S5, judging the intersection type by using the grade of the intersecting road;

S6. The cumulative frequency distribution of the average delay of each type of intersection is classified and counted, the threshold for determining the degree of bottleneck is determined, and the operational bottleneck of each type of intersection is dynamically identified.

In the method for judging bottlenecks in the operation of bus intersections based on dynamic data, the data preprocessing described in step S1 specifically includes judging abnormal data objects that deviate from normal data and removing them, and simultaneously bus GPS data, AVL data and urban road intersection information are matched and fused, and whether there are traffic accidents, bus failures, and construction information at urban road intersections are supplemented, and updated in real time.

The described method for judging bottlenecks in the operation of bus intersections based on dynamic data, the specific method for calculating the intersection delay of each bus vehicle described in step S3 is:

S31. According to whether there are bus lanes with independent right-of-way arranged on the passenger flow corridor, it is judged that the type of passenger flow corridor is a conventional bus passenger flow corridor or a rapid transit passenger flow corridor. For the data with a value of 45km/h, the highest value is assigned to 45km/h; to define the smooth speed of the BRT passenger flow corridor as 40km/h, for the data whose instantaneous speed is greater than the highest value of 60km/h, the highest value is assigned to 60km/h;

S32. Obtain the latitude and longitude data of the intersection range, and filter out the bus operation database within the intersection range from the bus GPS database;

S33. Calculate the effective travel distance l of each bus vehicle at the intersection:

Among them, l is the effective distance traveled by the bus in the intersection, and the sequences t ₁ → t _n and v ₁ → v _n are the GPS time series and instantaneous speed series of the bus within the effective distance of the first to n time intervals respectively ;

S34, calculate the _actual travel time T of the bus vehicle at the intersection:

Among them, L is the distance that the public transport vehicles of an entrance road at the intersection should travel within the influence range of the intersection, and V is the average speed of all public transport vehicles traveling within the influence range of the intersection.

S35. Calculate the delay D _ij (t) of each bus vehicle at the intersection:

D _ij (t) refers to the delay of the jth bus vehicle passing through the i intersection in the time period t, T _refers to the time for the bus to travel at the intersection, and _v refers to the speed of the bus at the intersection, where the regular The unimpeded speed of the bus passenger flow corridor is 35km/h, and the unimpeded speed of the BRT passenger flow corridor is defined as 40km/h.

Beneficial effects produced by the present invention:

The present invention is a universal, practical and convenient processing method. By using the bus dynamic bottleneck identification method based on frequency accumulation, the advantages of bus big data can be effectively utilized, the basic information of urban roads can be fully integrated, the investment of investigators can be reduced, and data reliability can be improved. Degree, enhance applicability.

Description of drawings

Fig. 1 is a system frame diagram of a method for judging bottlenecks in the operation of bus intersections based on dynamic data;

Fig. 2 is a distribution diagram of intersection A of road section A in a certain city;

Fig. 3 is a specific situation diagram of each intersection A of a road section in a certain city;

Fig. 4 is a schematic diagram of GPS data of some public transport vehicles in a certain city;

Figure 5 is the cumulative distribution of delays at various types of intersections in section A of a certain city;

Figure 6 is a discrimination diagram of the operating status and bottleneck degree of various types of intersections in section A of a certain city;

Figure 7 is an analysis diagram of the operation status and bottleneck degree of each intersection of road section A in a certain city on a certain day;

Fig. 8 is a distribution diagram of intersection B of road section B in a certain city;

Fig. 9 is a specific situation diagram of each intersection of road section B in a certain city;

Figure 10 is a cumulative distribution diagram of delays at various types of intersections on road section B in a certain city;

Figure 11 is a discrimination diagram of the operating status and bottleneck degree of various types of intersections in section B of a certain city;

Fig. 12 is an analysis diagram of the operation status and bottleneck degree of each intersection of road section B in a certain city on a certain day.

Detailed ways

Below in conjunction with accompanying drawing and specific embodiment, further illustrate the present invention, should be understood that these embodiments are only for illustrating the present invention and are not intended to limit the scope of the present invention, after having read the present invention, those skilled in the art will understand various aspects of the present invention Modifications in equivalent forms all fall within the scope defined by the appended claims of this application.

As shown in Figure 1, it is a system framework diagram of a dynamic data-based bus intersection operation bottleneck discrimination method, which mainly includes:

Step 1. Data preprocessing, which mainly judges the abnormal data of the data from the bus data acquisition system, cleans the data, and then matches the bus GPS data, AVL data and urban intersection information from the urban road information system. Fusion;

Step 2. Obtain the longitude and latitude data of the intersection range, and filter out the bus operation database within the intersection range from the bus GPS database;

Step 3. Use the speed-time integral model to estimate the actual travel time of the bus at the intersection, and then calculate the intersection delay of each bus. The specific steps are as follows:

Firstly, according to whether there are bus lanes with independent right-of-way on the passenger flow corridor, the type of passenger flow corridor is judged——conventional bus passenger flow corridor or BRT passenger flow corridor. Passenger flow corridors are mostly arranged on the main roads of the city, but ground buses are divided into conventional buses and rapid transit buses, resulting in different levels of bus corridors, leading to large differences in the configuration of transportation facilities and operating speeds. Therefore, the unimpeded speed of the conventional bus passenger flow corridor is defined as 35km/h, and the highest value of 45km/h is assigned to the data whose instantaneous speed is greater than the highest value of 45km/h; the unimpeded speed of the BRT passenger flow corridor is defined as 40km/h, and for The data greater than the maximum value of 60km/h is given the maximum value of 60km/h;

Calculate the effective driving distance l of each bus vehicle at the intersection within the intersection range:

Among them, l is the effective distance traveled by the vehicle in the intersection, and the sequences t ₁ →t _n and v ₁ →v _n are the GPS time series and instantaneous speed series of all the buses within the effective distance of the first to n time segments, respectively.

Calculate the _actual travel time T of the bus at the intersection:

Among them, L is the distance that the public transport vehicles of an entrance road at the intersection should travel within the influence range of the intersection, is the average speed of all public transport vehicles traveling within the influence range of the intersection.

Calculate the delay D _ij (t) of each bus at the intersection:

D _ij (t) refers to the delay of the jth bus vehicle passing through the i intersection in the time period t, T refers to the _smooth travel time of the bus vehicle at the intersection, and v refers to the _smooth travel speed of the bus vehicle at the intersection (regular bus The unimpeded speed of the passenger flow corridor is 35km/h, and the unimpeded speed of the BRT passenger flow corridor is defined as 40km/h).

Step 4, calculating the mean value of the average delay time of public transport vehicles at each intersection in the statistical interval;

Step 5. Use the level of intersecting roads to judge the intersection type, and obtain the latitude and longitude data of the intersection range. The specific judgment method is shown in the following table:

Step 6. Classify and count the cumulative frequency distribution of the average delay of each type of intersection, determine the threshold for determining the degree of bottleneck, and dynamically identify the operating status and bottleneck of each type of intersection. The specific identification method is as follows;

Note: D ₁₅ , D ₃₀ , D ₅₀ , and D ₈₅ are the average delays of the 15th, 30%, 50%, and 85% intersections of different grades of intersections respectively

Below in conjunction with a certain city example, the present invention is further analyzed and explained from two aspects of conventional public transport and rapid transit:

Evaluate the operation status of intersections operated by regular public transport vehicles in section A of a certain city, and identify the operational bottlenecks of various intersections. The specific steps are as follows:

Step 1. Data preprocessing. The most important information in GPS data is business time, GPS speed, longitude, latitude and so on. The quality problem determination, cleaning and repairing methods of GPS data are as follows: ① For records with completely repeated field data, they should be eliminated; for records with partial field data repeated, they should be eliminated or repaired according to the specific situation; ② The GPS acquisition frequency is 10s According to the basis, it is determined whether the data bar is missing. If it is missing, the data needs to be repaired. The methods of data repair mainly include historical data prediction method and interpolation method; , BRT is 60km/h), or the displacement value of the bus vehicle in this period is greater than the threshold, it is judged as wrong data, and the wrong data needs to be repaired, and the repair method is the same as ②. Figure 2 shows the layout of intersections on road section A, Figure 3 shows the specific information of each intersection, and Figure 4 shows the GPS data of some buses.

Step 2, according to intersection specific information and GPS data, obtain the longitude and latitude data of each intersection range of road section A, then filter out the bus operation database within the intersection range from the bus GPS database;

Step 3. Use the speed-time integral model to estimate the actual travel time of the bus at the intersection, and then calculate the delay caused by each bus at the intersection;

Step 4, calculate statistical interval (the present invention sets statistical interval to be 15 minutes) the average bus delay time mean value of each crossing;

Step five, judge the type of intersection by using the level of the intersecting road. Road section A is mainly a regular bus operation section. Since the intersecting road sections C and D are secondary arterial roads, and the intersecting road sections E, road section F and road section B are main roads, it is judged that intersections ① and ④ are normal class C, and intersections ②, ③, ⑤ For the normal B category.

Step 6: Classify and count the cumulative frequency distribution of the average delay at each type of intersection, as shown in Figure 5, and determine the bottleneck threshold of each type of intersection based on the cumulative percentage. When intersecting with the main road (usually B type intersection), when the intersection delay is less than 24s, the bus runs smoothly; when the intersection delay is between 24s and 33s, it is basically smooth; when the intersection delay is between 33s and 48s When the intersection delay is between 48s and 77s, it is a moderate bottleneck; when the intersection delay exceeds 77s, it is a severe bottleneck. When intersecting with secondary arterial roads/branch roads (usually C-type intersections), when the intersection delay is less than 25s, the bus runs smoothly; when the intersection delay is between 25s and 34s, it is basically smooth; when the intersection delay is between When the intersection delay is between 34s and 44s, it is a mild bottleneck; when the intersection delay is between 44s and 68s, it is a moderate bottleneck; when the intersection delay exceeds 68s, it is a severe bottleneck, as shown in Figure 6. At the same time, it can dynamically identify the operational bottlenecks of various types of intersections. Specifically analyze the bottleneck status of each type of intersection at each time period on section A on May 30, 2017, and use different colors to represent different bottleneck levels, as shown in Figure 7;

Evaluate the operation status of the intersection of BRT vehicles in a certain city section B during a certain period of time, and identify the operation bottleneck;

Step 1, data preprocessing, same as section A processing method. Figure 8 shows the layout of the section B intersection, and Figure 9 shows the specific situation of each intersection;

Step 2. Obtain the longitude and latitude data of each intersection range of road section B, and filter out the bus operation database within the intersection range from the bus GPS database;

Step 3. Use the speed-time integral model to estimate the actual travel time of the bus at the intersection, and then calculate the intersection delay of each bus;

Step 4, calculate statistical interval (the present invention sets statistical interval to be 15 minutes) the average bus delay time mean value of each crossing;

Step five, judge the type of intersection by using the level of the intersecting road. Road section B is mainly a road section for BRT vehicles. Since the intersecting road section G is a secondary trunk road, and road sections A and H are main roads, it is judged that intersection ② is express category C, and intersections ① and ③ are express category B;

Step 6: Classify and count the cumulative frequency distribution of the average delay at each type of intersection, as shown in Figure 10, and determine the bottleneck threshold of each type of intersection based on the cumulative percentage. When intersecting with the main road (fast type B intersection), when the intersection delay is less than 8s, the bus runs smoothly; when the intersection delay is between 8s and 14s, it is basically smooth; when the intersection delay is between 14s and 23s When the intersection delay is between 23s and 50s, it is a moderate bottleneck; when the intersection delay exceeds 50s, it is a severe bottleneck. When intersecting with secondary arterial roads/branch roads (fast C-type intersections), when the intersection delay is less than 4s, the bus runs smoothly; when the intersection delay is between 4s and 8s, it is basically smooth; when the intersection delay is between When the intersection delay is between 12s and 28s, it is a moderate bottleneck; when the intersection delay exceeds 28s, it is a severe bottleneck, as shown in Figure 11. At the same time, it can dynamically identify the operational bottlenecks of various types of intersections. Specifically analyze the bottleneck status of various types of BRT intersections in a section B on May 30, 2017, and use different colors to represent different bottleneck levels, as shown in Figure 12.

Claims (3)

1. a method for judging bottlenecks in the operation of bus intersections based on dynamic data, is characterized in that, the method comprises the steps: S1. Data preprocessing, including abnormal data discrimination, data cleaning, data fusion and intersection information supplementation; S2. Obtain the longitude and latitude data of the intersection range, and filter out the bus operation database within the intersection range from the bus GPS database; S3. Using the speed-time integral model to estimate the actual travel time of the bus at the intersection, and then calculate the intersection delay of each bus; S4, calculate the mean value of the average delay time of public transport vehicles at each intersection in the statistical interval; S5, judging the intersection type by using the grade of the intersecting road; S6. The cumulative frequency distribution of the average delay of each type of intersection is classified and counted, the threshold for determining the degree of bottleneck is determined, and the operational bottleneck of each type of intersection is dynamically identified. 2. the method for judging bottlenecks in the operation of bus intersections based on dynamic data according to claim 1, wherein the data preprocessing described in step S1 specifically includes judging abnormal data objects that deviate from normal data and Carry out elimination, and at the same time, match and integrate bus GPS data, AVL data and urban road intersection information, and supplement whether there are traffic accidents, bus failures, and construction information at urban road intersections, and update them in real time. 3. according to claim 1 or 2 described method based on the bottleneck discrimination method of bus intersection operation of dynamic data, it is characterized in that, the concrete method of the intersection delay of calculating every bus vehicle described in step S3 is: S31. According to whether there are bus lanes with independent right-of-way arranged on the passenger flow corridor, it is judged that the type of passenger flow corridor is a conventional bus passenger flow corridor or a rapid transit passenger flow corridor. For the data with a value of 45km/h, the highest value is assigned to 45km/h; to define the smooth speed of the BRT passenger flow corridor as 40km/h, for the data whose instantaneous speed is greater than the highest value of 60km/h, the highest value is assigned to 60km/h; S32. Obtain the latitude and longitude data of the intersection range, and filter out the bus operation database within the intersection range from the bus GPS database; S33. Calculate the effective travel distance l of each bus vehicle at the intersection: Among them, l is the effective distance traveled by the bus in the intersection, and the sequences t ₁ → t _n and v ₁ → v _n are the GPS time series and instantaneous speed series of the bus within the effective distance of the first to n time intervals respectively ; S34, calculate the _actual travel time T of the bus vehicle at the intersection: Among them, L is the distance that the public transport vehicles of an entrance road at the intersection should travel within the influence range of the intersection, and V is the average speed of all public transport vehicles traveling within the influence range of the intersection. S35. Calculate the delay D _ij (t) of each bus vehicle at the intersection: D _ij (t) refers to the delay of the jth bus vehicle passing through the i intersection in the time period t, T _refers to the time for the bus to travel at the intersection, and _v refers to the speed of the bus at the intersection, where the regular The unimpeded speed of the bus passenger flow corridor is 35km/h, and the unimpeded speed of the BRT passenger flow corridor is defined as 40km/h.