Библиографическое описание:

Калмыков Б. Ю., Скудина А. А., Дмитриенко Н. А. Using intellectual transport systems in monitoring transport streams // Молодой ученый. — 2015. — №7. — С. 141-144.

In article features of application of the theory of transport streams in intellectual transport systems, and also a method of monitoring of characteristics of a transport stream by means of floating data cars (FDC) are resulted. Results of an experimental research on a high system of city with use of «floating» cars are offered.

Key words: characteristics of traffic flow, floating cars, the discreteness of the information received, the incident.

 

Development of methods of management of transport streams is the most important direction of researches in the field of organizing traffic safety. Traffic control is, first of all the solution of problems of information processing in real time, feasible by means of intellectual transport systems. One of the main directions of developing intellectual transport systems is information support of participants of the traffic movement. It is possible to distinguish the dynamic management of a route allowing to reduce road jams as main elements of a transport network by means of the redirecting transport streams to less loaded streets from functionality of intellectual transport systems. The operational personified road information is provided by means of signs with the changing messages (ZIS). [1, 3р.]

In the course of modeling traffic as a way of identification of optimum model of a route choice of the movement a dynamic distribution of transport streams is introduced, it was established that the parameter of estimating the capacity of a site of a road network has special impact. Changing values of this parameter, it is possible to reveal with the help of influencing criteria to a movement route choice at a given time: the condition of a street road network determining a choice of the smallest by time or the shortest route in distance, a delay of vehicles and length of turn on entrances to traffic light objects, or driver’s desire to move only on highways of the city.

For search of effective strategy of transport streams management, and the organization of traffic needs a wide range of characteristics of a transport stream is to be considered, regularity of influence of external and internal factors on dynamic characteristics of a mixed transport stream. [2, 38 p.]

Therefore one of the actual directions of developing functions of intellectual transport systems is researching methods of monitoring the characteristics of transport streams by means of «floating» cars. Information received from «floating» cars can be included data on location of the car and its speed, weather conditions, characteristics of transport streams, hindrances, and jam situations. After the corresponding processing and generalization of transport information have been done it can be used for management of traffic and transfer to other participants of the movement. Information concerning the volume and efficiency of its processing allow us to apply this method as traffic control in the real mode of time.

Thus, «floating» cars can be considered as means of improving information support of traffic. Functionality of intellectual transport systems allows us to make essential changes in methods of monitoring of transport streams characteristics and to increase the quality of road and transport information as a management traffic process.

For initial assessment of reliability of the received information by means of «floating» cars it is necessary to check, at what discreet and shares of «floating» cars essential distinctions occurred between the received speed after modeling «floating» cars and average speed on a stage. This task can be interpreted as one of typical tasks of the dispersive analysis, whether when it is required to establish influence of various factors or their interactions on parameters impacts on processes which is considered to be essential measure against casual deviations.

For realization of this task a lot researches on means of micro modeling on a street road network were conducted. The program AIMSUN complex was applied to modeling it. (Figure 1)

The studied site of a street road network is characterized by the rectangular scheme with a detour. It includes 20 crossings in one level.

The street road network can be characterized as city value. The general extent of streets of the studied site of a network is 24,05 km.

Modeling period is 1 hour. Experiment was made for all levels of service.

The main objective of research was consisted in definition of necessary number of the «floating» cars which are constantly estimated in the street area and sufficient deviation from obtained information of «floating» cars. The analysis of the obtained data was carried out by means of the dispersive analysis.

Comparing the received F-values of criterion for the studied sources of obtaining information as the main characteristics of a transport stream and tabular value of criterion for acceptance of a zero hypothesis, it is possible to draw a conclusion that a choice of «floating» cars as the source of obtaining information doesn't influence on an assessment of the main characteristics of a transport stream. [3, 56р.]

The descriptive reasons results are given in table 1

Table 1

Influence of Data, received by means of «floating» cars as indicators of reliability of received information

Level of service

A share of «floating» cars in a stream, %

An interval of obtaining information from «floating» cars

12

24

40

60

120

А

2

-

-

-

-

-

3

-

-

-

-

-

5

-

-

-

-

-

10

+

+

+

-

-

20

+

+

+

-

-

50

+

+

+

+

+

В

1

-

-

-

-

-

2

-

-

-

-

-

3

-

-

-

-

-

5

+

-

-

-

-

10

+

+

+

+

-

20

+

+

+

+

+

50

+

+

+

+

+

C

5

+

+

-

-

-

10

+

+

+

+

-

20

+

+

+

+

+

50

+

+

+

+

+

D

5

-

-

-

-

-

10

+

+

-

-

-

20

+

+

+

+

-

50

+

+

+

+

+

E

5

-

-

-

-

-

10

+

+

+

-

-

20

+

+

+

+

+

50

+

+

+

+

+

F

5

-

-

-

-

-

10

+

+

-

-

-

20

+

+

+

+

+

50

+

+

+

+

+

- — the source influences reliability of the received information

+ — the source doesn't influence reliability of the received information

 

Figure 1 Obtaining information from floating cars in the simulation

 

For level of service D is the characteristic speed of traffic flow in urban environments from 18 to 23 km/h. In these conditions for obtaining reliable information from «floating» car following conditions are required: if the share of floating cars 10 %, then the discreteness of the information received should not exceed 24 S., at 20 % to 60 C., at 50 % to 120 C. 5 % floating cars is not sufficient, since in this case there is uneven coverage of the investigated road network floating cars.

At levels of service E and F to obtain reliable information from «floating» car (i.e. the source does not affect the accuracy) are sufficient for the following conditions: if the share of floating cars 10 %, then the discreteness of the information received should not exceed 24 p., when the number of floating cars from 20 to 50 % to 120 C. 5 % floating cars is not sufficient, since in this case there is uneven coverage of the investigated road network floating cars.

Conclusions which can be made by results of the dispersive analysis a set of results of supervision with various a share of «floating» cars are done and deviation in measurements for various levels of conveniences of the movement are performed that it is possible to carry out a speed assessment at a share of «floating» cars from 10 % to 50 % and deviation of measurement from 12s to 60s.

At the stage of research it is necessary to check at which discrete measurements and the share of floating cars become significant differences between speed, under normal conditions and скоростьюs in the formation of the incident. In other words, you receive the possibility of determining the incident at different levels of facilities.

The results show that service levels b and C have the ability to determine congestion. For the other levels of service, this is not possible, because at levels D, E, F traffic conditions close to congestion, making it impossible to identify the incident. At the service level And the flow moves freely and when an incident occurs the velocity of the flow is not reduced on average.

 

References:

 

1.                  Zyrianov V., Kocherga V., Estimation of efficiency of urban network operation with usage of floating vehicles. Proceedings of the international congress ITS in Europe. Bilbao, 2001, 18

2.                  Tarnoff P. A virtual case. Do we need operations centers?«Traffic technology international». Oct/Nov, 1998, 138 p.

3.                  Prigogine I., Herman R. Kinetic theory of velueulai tial'li. American Elsevier NY 1991. 112 p

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