JP2691928B2 - Traffic flow detector - Google Patents
Traffic flow detectorInfo
- Publication number
- JP2691928B2 JP2691928B2 JP1166962A JP16696289A JP2691928B2 JP 2691928 B2 JP2691928 B2 JP 2691928B2 JP 1166962 A JP1166962 A JP 1166962A JP 16696289 A JP16696289 A JP 16696289A JP 2691928 B2 JP2691928 B2 JP 2691928B2
- Authority
- JP
- Japan
- Prior art keywords
- vehicle
- traffic flow
- traffic
- processing unit
- time
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
Description
【発明の詳細な説明】 （産業上の利用分野） 本発明は、自動車の走行する道路の状況を自動的に判
別し、交通流特性を把握するための交通流検出装置に関
するものである。Description: TECHNICAL FIELD The present invention relates to a traffic flow detection device for automatically determining the condition of a road on which an automobile runs and for grasping traffic flow characteristics.
（従来の技術） 従来、この種の交通流検出装置は、基本交通諸量（交
通量，平均速度，占有率）を１分間または５分間単位に
集計し、その値によって交通流の状況を規定してきた。
最近では、それらを時系列データとして扱い、信号理論
（相関函数）を適用し、新たなパラメータから交通流を
検出するようになってきた。(Prior Art) Conventionally, this type of traffic flow detection device collects basic traffic volumes (traffic volume, average speed, occupancy rate) in units of 1 minute or 5 minutes, and defines the status of traffic flow by the value. I've been
Recently, they have been treated as time series data, and signal theory (correlation function) has been applied to detect traffic flow from new parameters.
（発明が解決しようとする課題） 上記信号理論を適用した交通流検出装置でも交通流の
状況（たとえば渋滞のレベルが激しい場合）によって
は、交通流の特徴が出にくい（たとえば、渋滞時に発生
する渋滞波の伝搬周期が時系列データの自己相関関数か
ら明確にならない）ことが、欠点となっている。また、
信号理論を実システムに適用するには、リアルタイム性
が要求され、そのために特に数少ないデータから、どれ
だけ特徴抽出が可能となるかが課題であった。(Problems to be Solved by the Invention) Even in a traffic flow detection device to which the above signal theory is applied, the characteristics of the traffic flow are difficult to appear depending on the traffic flow situation (for example, when the traffic congestion level is intense) (for example, when traffic congestion occurs. The propagation period of a traffic jam wave is not clear from the autocorrelation function of time series data), which is a drawback. Also,
In order to apply the signal theory to a real system, real-time property is required, and for that reason, how much feature extraction is possible from a very small amount of data has been a problem.
本発明の目的は、従来の欠点を解消し、自由走行の状
態から渋滞のレベルが激しい状態を含めた交通流の状態
検出を可能とする優れた交通流検出装置を提供すること
である。An object of the present invention is to provide an excellent traffic flow detecting device that eliminates the conventional drawbacks and enables the detection of traffic flow states including a state of free running and a state of severe traffic congestion.
（課題を解決するための手段） 本発明の交通流検出装置は、車両の通過およびその車
両の特徴を検出する車両感知器と、この車両感知器から
の車両情報を演算して車両１台毎の車両通過情報を作成
する感知信号処理部と、前記車両通過情報に車両の特徴
別に設定した重み函数を重畳して時系列演算を行う処理
部とから構成され、交通量，速度，占有率等基本交通諸
量を時系列データとして出力することにより、交通流に
おける車群の識別レベルを高めることを特徴とする。(Means for Solving the Problems) A traffic flow detection apparatus of the present invention is a vehicle detector that detects passage of a vehicle and characteristics of the vehicle, and vehicle information from the vehicle detector is calculated to calculate each vehicle. Of the vehicle passage information, and a processing unit that superimposes a weighting function set for each vehicle characteristic on the vehicle passage information to perform a time-series calculation. Traffic volume, speed, occupancy rate, etc. It is characterized by increasing the identification level of the vehicle group in the traffic flow by outputting the basic traffic quantities as time series data.
（作用） 本発明によれば、従来の交通諸量に、いくつかの方法
で得られる新しいパラメータを重畳することにより、自
由流における車群到達時間算出、渋滞流における渋滞波
伝搬周期の算出等を可能とし、リアルタイムで処理する
ことも可能にすることができる。(Operation) According to the present invention, by superposing new parameters obtained by some methods on the conventional traffic volume, calculation of vehicle group arrival time in free flow, calculation of congestion wave propagation cycle in congested flow, etc. And can be processed in real time.
（実施例） 本発明の一実施例を第１図ないし第５図に基づいて説
明する。(Embodiment) An embodiment of the present invention will be described with reference to FIGS.
第１図および第２図は本発明の交通流検出装置の構成
を示すものである。1 and 2 show the structure of the traffic flow detecting apparatus of the present invention.
第１図において、11,12はループ式車両検出器、13は
車両感知信号の作成と伝送機能を具えた車両感知器であ
り、交通流検出装置14と図示のように結合される。また
交通流検出装置14は、感知信号処理部15とデータ処理部
16、出力伝送部17から構成されている。In FIG. 1, 11 and 12 are loop type vehicle detectors, 13 is a vehicle detector having a function of generating and transmitting a vehicle detection signal, and is connected to a traffic flow detection device 14 as shown. The traffic flow detection device 14 includes a sensing signal processing unit 15 and a data processing unit.
16 and an output transmission unit 17.
第２図において、21はITV式車両検出器、22は伝送装
置、23は画像を受信し感知信号を作成する感知信号処理
部であり、16,17は第１図で示したと同じ機器部で16は
データ処理部、17は出力伝送部である。24は画像利用車
両検出器用感知信号処理装置である。In FIG. 2, 21 is an ITV type vehicle detector, 22 is a transmission device, 23 is a sensing signal processing unit that receives an image and creates a sensing signal, and 16 and 17 are the same equipment units as shown in FIG. Reference numeral 16 is a data processing unit, and 17 is an output transmission unit. Reference numeral 24 is a sensing signal processing device for an image-based vehicle detector.
次に動作について説明する。ループ式車両検出器11,1
2と車両感知器13により車両検出信号を作成し、交通流
検出装置14に伝送する。第２図の例では、ITV式車両検
出器21および伝送装置22により画像情報を画像利用車両
検出器用感知信号処理装置24に伝送する。交通流検出装
置14および感知信号処理装置24は受信した信号から交通
流の状態を判定し、他マンマシンや制御装置等へその結
果を出力する。Next, the operation will be described. Loop type vehicle detector 11,1
A vehicle detection signal is created by 2 and the vehicle detector 13 and transmitted to the traffic flow detection device 14. In the example of FIG. 2, the ITV type vehicle detector 21 and the transmission device 22 transmit the image information to the image-based vehicle detector detection signal processing device 24. The traffic flow detection device 14 and the sensing signal processing device 24 determine the state of the traffic flow from the received signals, and output the result to other man-machines, control devices and the like.
次に本実施例における交通流の判定への信号処理につ
いて、第３図および第４図に基づいて説明する。感知信
号処理部15,23では車両検出信号や画像信号から上流側
車両検出信号31および下流側車両検出信号32、車両検出
信号41のようなパルス信号が形成される。ONの状態は車
が通過した場合であり、OFFの状態は車がない場合であ
る。これらの信号から、交通量，平均速度，占有率を算
出する。さらに２つの車両検出器がある場合は、大型，
小型の識別が一台毎に算出される。また第４図の実施例
では、画像情報から第３図の実施例に加えて色の識別情
報が１台毎に算出される。データ処理部16では感知信号
処理部15,23で得られた信号を重畳する。重み函数33,42
は新たなパラメータを重畳する際の重みづけの例であ
り、従来の方法による交通量の算出が従来の交通量算出
式34に対し本発明の交通量算出式35,43は重畳した場合
の算出式である。このようなデータ処理部16において
は、新たな時系列信号を作り、それに対して信号理論を
適用し、渋滞・非渋滞の識別、渋滞波の伝搬特性や伝搬
時間等の算出を行う。Next, the signal processing for determining the traffic flow in this embodiment will be described with reference to FIGS. 3 and 4. In the detection signal processing units 15 and 23, pulse signals such as the upstream vehicle detection signal 31, the downstream vehicle detection signal 32, and the vehicle detection signal 41 are formed from the vehicle detection signal and the image signal. The ON state is when the vehicle has passed, and the OFF state is when there is no vehicle. The traffic volume, average speed, and occupancy rate are calculated from these signals. If you have two more vehicle detectors,
A small identification is calculated for each device. Further, in the embodiment shown in FIG. 4, color identification information is calculated for each vehicle from the image information in addition to the embodiment shown in FIG. The data processing unit 16 superimposes the signals obtained by the sensing signal processing units 15 and 23. Weight function 33,42
Is an example of weighting when superimposing a new parameter, the calculation of the traffic volume by the conventional method is the traffic volume calculation formulas 35 and 43 of the present invention in comparison with the conventional traffic volume calculation formula 34. It is an expression. In the data processing unit 16 as described above, a new time-series signal is created, signal theory is applied to it, and congestion / non-congestion is identified, and the propagation characteristics and propagation time of a congestion wave are calculated.
第５図は、渋滞時における車両感知信号の自己相関函
数算出の例である。渋滞波が約４分の周期で伝わること
が算出されるが、51は交通量から求めた場合であり、52
は占有率から求めた場合である。十分な時系列データを
使うことによって、さらに交通量よりは、車の大きさを
加味した占有率データの方がより交通流を表わすことが
わかっている。53は本発明の新たなパラメータを重畳し
た場合想定される相関函数である。鋭い特性表示がされ
るため、時系列データ数の短縮化が可能となりリアルタ
イム性が可能となる。FIG. 5 is an example of calculating an autocorrelation function of a vehicle detection signal during a traffic jam. It is calculated that the traffic jam will be transmitted in a cycle of about 4 minutes, but 51 is calculated from the traffic volume and 52
Is the case obtained from the occupancy rate. By using sufficient time series data, it has been found that the occupancy rate data in which the size of the car is taken into consideration more represents the traffic flow than the traffic volume. 53 is a correlation function that is assumed when a new parameter of the present invention is superimposed. Since sharp characteristics are displayed, the number of time-series data can be shortened and real-time performance can be realized.
（発明の効果） 本発明によれば、従来、交通状況によっては信号理論
を適用しても、特徴抽出ができなかった場合でも、本発
明の交通量検出装置の時系列データを利用することによ
り、車群の識別レベルが向上することで、交通流におけ
る車群到達時間算出、渋滞流における渋滞波伝搬周期の
算出等が可能となり、その結果、少ない時系列データで
も交通流の特徴を抽出することが可能になることで、リ
アルタイムに交通流の判定を行うことができ、その実用
上の効果は大である。(Effect of the Invention) According to the present invention, conventionally, even when the signal theory is applied depending on the traffic situation and the feature extraction cannot be performed, the time-series data of the traffic detection device of the present invention is used. By improving the vehicle group identification level, it becomes possible to calculate the vehicle group arrival time in a traffic flow, calculate the traffic jam propagation period in a traffic jam, etc. As a result, the characteristics of the traffic flow can be extracted even with a small amount of time series data. As a result, the traffic flow can be determined in real time, and its practical effect is great.
第１図，第２図は本発明の一実施例における交通流検出
装置の構成図、第３図，第４図は新しいパラメータの重
畳方法を示したもの、第５図は自己相関函数を示すグラ
フである。 11,12…ループ式車両検出器、13…車両感知器、14…交
通流検出装置、15,23…感知信号処理部、16…データ処
理部、17…出力伝送部、21…ITV式車両検出器、22…伝
送装置、24…感知信号処理装置、31…上流側車両検出信
号、32…下流側車両検出信号、33,42…重み函数、34…
従来の交通量算出式、35,43…本発明の交通量算出式、4
1…車両検出信号。FIGS. 1 and 2 are block diagrams of a traffic flow detecting apparatus in one embodiment of the present invention, FIGS. 3 and 4 show a new parameter superimposing method, and FIG. 5 shows an autocorrelation function. It is a graph. 11, 12 ... Loop type vehicle detector, 13 ... Vehicle detector, 14 ... Traffic flow detection device, 15, 23 ... Sensing signal processing unit, 16 ... Data processing unit, 17 ... Output transmission unit, 21 ... ITV type vehicle detection 22 ... Transmission device, 24 ... Sensing signal processing device, 31 ... Upstream vehicle detection signal, 32 ... Downstream vehicle detection signal, 33, 42 ... Weight function, 34 ...
Conventional traffic volume calculation formula, 35, 43 ... Traffic volume calculation formula of the present invention, 4
1 ... Vehicle detection signal.
Claims (1)
る車両感知器と、この車両感知器からの車両情報を演算
して車両１台毎の車両通過情報を作成する感知信号処理
部と、前記車両通過情報に車両の特徴別に設定した重み
函数を重畳して時系列演算を行う処理部とから構成さ
れ、交通量，速度，占有率等基本交通諸量を時系列デー
タとして出力することにより、交通流における車群の識
別レベルを高めることを特徴とする交通流検出装置。1. A vehicle detector that detects passage of a vehicle and characteristics of the vehicle, and a detection signal processing unit that calculates vehicle information from the vehicle detector to create vehicle passage information for each vehicle. The vehicle passing information is composed of a processing unit that superimposes a weighting function set for each characteristic of the vehicle to perform a time-series calculation, and outputs basic traffic amounts such as traffic volume, speed, and occupancy as time-series data. , A traffic flow detection device characterized by increasing the identification level of a vehicle group in a traffic flow.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP1166962A JP2691928B2 (en) | 1989-06-30 | 1989-06-30 | Traffic flow detector |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP1166962A JP2691928B2 (en) | 1989-06-30 | 1989-06-30 | Traffic flow detector |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| JPH0334100A JPH0334100A (en) | 1991-02-14 |
| JP2691928B2 true JP2691928B2 (en) | 1997-12-17 |
Family
ID=15840850
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| JP1166962A Expired - Fee Related JP2691928B2 (en) | 1989-06-30 | 1989-06-30 | Traffic flow detector |
Country Status (1)
| Country | Link |
|---|---|
| JP (1) | JP2691928B2 (en) |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102226930A (en) * | 2011-05-27 | 2011-10-26 | 迈锐数据（北京）有限公司 | Method for processing vehicle detection information |
Families Citing this family (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104064035A (en) * | 2014-06-18 | 2014-09-24 | 米振宇 | Traffic flow detection device |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JPS513033A (en) * | 1974-06-27 | 1976-01-12 | Uchida Seisakusho Kk | SANSOFUSOK UNITAISHOSURUNENSHOKI |
-
1989
- 1989-06-30 JP JP1166962A patent/JP2691928B2/en not_active Expired - Fee Related
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102226930A (en) * | 2011-05-27 | 2011-10-26 | 迈锐数据（北京）有限公司 | Method for processing vehicle detection information |
Also Published As
| Publication number | Publication date |
|---|---|
| JPH0334100A (en) | 1991-02-14 |
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Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| LAPS | Cancellation because of no payment of annual fees |