JP2003242589A - Road running time predicting system - Google Patents
Road running time predicting systemInfo
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- JP2003242589A JP2003242589A JP2002084496A JP2002084496A JP2003242589A JP 2003242589 A JP2003242589 A JP 2003242589A JP 2002084496 A JP2002084496 A JP 2002084496A JP 2002084496 A JP2002084496 A JP 2002084496A JP 2003242589 A JP2003242589 A JP 2003242589A
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- traffic volume
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Abstract
Description
【０００１】[0001]
【発明が属する技術分野】本発明は、道路走行所要時間
を高い精度で予測する方法に関するものである。BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to a method of predicting a required road travel time with high accuracy.
【０００２】[0002]
【従来の技術】道路上に設置されている交通情報案内板
や警察によるＡＴＩＳ等の道路交通情報案内システムに
より、主要な道路区間の渋滞区間や走行所要時間情報が
ユーザーに提供されていることは従来から知られてい
る。しかし、これらの従来の走行所要時間情報は、いず
れも、現時点以前に走行した車両のプレートナンバーを
撮影し画像処理して照合（特願平６−１５９９４３、な
ど）した結果や、車両感知センサーによる走行速度観測
結果に基づいて計算した走行所要時間を提供するもので
ある。また、夏季や年末等のピーク期間の数週間前か
ら、道路公団により特に高速道路の渋滞見込みが情報提
供されていることも知られているが、これらの情報で
は、渋滞の発生予想時間帯と発生予想区間があまりにも
漠然としている。これらの従来の道路走行所要時間情報
は、全て、現時点より前の過去の計測結果を単に表示し
ていることが特徴である。このため、利用者が車で出発
しようとする現時点を基準として一定の時間が経過した
後の道路走行所要時間がどう変化するかを推計した情報
は現在では入手できず、利用者にとっては走行所要時間
の正確な予測や経路選択には、ほとんど参考になってい
ないとともに、実際に走行したら目的地まで随分時間が
かかってしまうとか、逆に随分早く着いてしまうという
欠点がある。2. Description of the Related Art It is known that users can be provided with information on traffic jams and travel times of major road sections by using a traffic information board installed on the road or a road traffic information guidance system such as ATIS by the police. Known from the past. However, all of these conventional travel time information are obtained by photographing the plate number of the vehicle that has traveled before the current time, performing image processing and collating (Japanese Patent Application No. 6-159943, etc.), and the vehicle detection sensor. It provides the travel time calculated based on the traveling speed observation results. It is also known that the highway public corporations have been providing information on the expected congestion of expressways, especially a few weeks before peak periods such as summer and the end of the year. The expected segment is too vague. All of these conventional road travel time information is characterized in that past measurement results before the present time are simply displayed. Therefore, it is not possible to obtain information on how the road travel time will change after a certain amount of time, based on the current time when the user is about to leave by car, and it is not possible for the user to travel. It does not serve as a reference for accurate time prediction and route selection, and has the drawback that it will take a long time to reach the destination if the vehicle actually travels, or on the contrary, it will arrive much earlier.
【０００３】また、車両感知器による該区間の走行車両
を検出する時間と該走行車の平均車長から走行速度を求
め、該区間延長を該走行速度で除して走行所要時間と
し、現時点以前のいくつかの所要時間算定結果を変数と
して自己回帰モデルを計算し、現時点以降の所要時間を
推計する方法が出願されている（特願平３−３０１２９
５、特開平０８−３０１０７３、特願平１０−６９６７
３、あるいは、特願平７−２１９２４８）。しかし、こ
の自己回帰方法によると、車両検出が断片的にしか出来
ないために、該区間の全体を走行した実際の所要時間と
は違うという理論的な問題を解決していないことが欠点
である。さらに、該自己回帰モデルによる推計値は、現
時点以降を対象として、一定時間間隔毎（たとえば５分
毎）の推計値を単に繰り返して計算する方法であるため
に、交通量の変化による走行速度あるいは走行所要時間
の変化を十分には考慮できないという問題があり、各道
路区間の交通量の変動特性を考慮できず、精度的に問題
が大きいという欠点がある。Further, the traveling speed is obtained from the time for detecting the traveling vehicle in the section by the vehicle detector and the average vehicle length of the traveling vehicle, and the section extension is divided by the traveling speed to obtain the traveling time, which is before the present time. A method of calculating an autoregressive model using several required time calculation results as a variable and estimating the required time after the present time has been applied (Japanese Patent Application No. 3-30129).
5, JP-A-08-301073, Japanese Patent Application No. 10-6967
3 or Japanese Patent Application No. 7-219248). However, this autoregressive method has a drawback in that it cannot solve the theoretical problem that the actual time required to travel the entire section is different because the vehicle can be detected only in pieces. . Further, since the estimated value by the auto-regressive model is a method of simply calculating the estimated value for every fixed time interval (for example, every 5 minutes) from the present time point onward, the traveling speed or There is a problem in that the change in travel time cannot be fully taken into consideration, and the fluctuation characteristics of the traffic volume in each road section cannot be taken into consideration, which is a problem in that the problem is large in terms of accuracy.
【０００４】定時性を重んじる運輸業や、待ち合わせの
時刻までに目的地に着く必要がある利用者等にとって
は、現時点に出発するとかあるいは一定時間経過後に出
発する場合を含めて、道路走行所要時間の正確な予測値
や、目的地までの最短所要時間の経路情報は大事な情報
であり、利用者が道路を利用する任意の時間帯における
平均走行所要時間予測値を知りたいというニーズはかな
り高いと考えられる。また、道路全体の効率的な利用を
はかるために、他の空いている道路や経路の所要時間予
測値が提供されて有効に道路が利用されることは、社会
的要請が高いと考えられる。For the transportation business that values punctuality, and for users who need to arrive at their destination by the time of meeting, the time required for traveling on the road is included, including the case where the vehicle departs at the present time or after a certain time has elapsed. Accurate prediction value and route information of the shortest required time to the destination are important information, and there is a considerable need for users to know the average travel time predicted value in any time zone when using the road. it is conceivable that. In addition, it is considered that there is a high social demand for the road to be used effectively by providing the estimated time required for other vacant roads and routes in order to use the entire road efficiently.
【０００５】この改善策として、道路の走行所要時間あ
るいは走行速度は、その区間の道路交通量と関係が深い
ことと、各道路の混雑が毎日ほぼ同じような時間帯に生
じていることを考慮して、一定期間にわたって該区間の
走行所要時間と交通量の変動を調査収集しておくととも
に、該区間の現時点における走行所要時間あるいは交通
量の変動傾向を調査することにより、現時点に出発する
場合、あるいは現時点から一定時間経過して出発する場
合の走行所要時間を精度高く予測することが可能とな
る。As a countermeasure for this, it is considered that the required traveling time or traveling speed of the road is closely related to the road traffic volume of the section, and that the congestion of each road occurs in almost the same time zone every day. Then, when the departure time is reached by investigating and collecting the changes in the travel time and traffic volume of the section over a certain period and by investigating the trends in the travel time or traffic volume at the current point in the section. Alternatively, it is possible to accurately predict the required travel time when the vehicle departs after a certain time has passed from the present time.
【０００６】[0006]
【発明が解決しようとする課題】解決しようとする問題
点は、ある道路区間の現時点以前の走行所要時間観測結
果を提供する、あるいは案内表示する従来の道路走行所
要時間情報によっては、該道路区間を該現時点以降の一
定時間経過後に車で走行する場合の走行所要時間を、利
用者が正しく予測できない点である。The problem to be solved is to provide a result of observation of a required travel time of a certain road section before the present time, or to provide a guide display, depending on the conventional required travel time information of the road section. The point is that the user cannot correctly predict the required travel time when the vehicle travels after a certain period of time since the present time.
【０００７】[0007]
【課題を解決するための手段】本発明は、ある道路区間
において、一定期間に亙って該道路区間を走行する車の
平均走行所要時間及び自動車交通量の推移を調査した実
績を記録保存し、曜日等の同じ要因別に分類し平均推移
パターンを作成しておき、現時点と曜日等が同じ要因の
過去の平均走行所要時間および交通量の推移パターンの
実績を拠り所として、該区間における、現時点以降の一
定時間経過後を対象とする平均走行所要時間を予測する
ことを最も主要な特徴とする。SUMMARY OF THE INVENTION The present invention records and saves a record of a survey of changes in average travel time and vehicle traffic of a vehicle traveling on a road section over a certain period in the road section. , The average transition pattern is created by classifying by the same factor such as the day of the week, and the past average required travel time and the transition pattern of the traffic volume of the same factor at the present time and the day of the week are used as the basis, and after that point in the section. The main feature is to predict the average travel time required after a certain period of time.
【０００８】[0008]
【発明の実施の形態】予測対象道路区間の時刻別平均走
行所要時間及び交通量を一定期間に亙って調査した結果
をデータとして保存し、曜日等の要因別に該走行所要時
間及び交通量の推移を分類しておき、該道路区間の現時
点における平均走行所要時間及び交通量を調査収集した
結果を基準として、該区間における現時点以降の一定時
間経過後を対象とする平均走行所要時間を、精度高く予
測することを可能とした。BEST MODE FOR CARRYING OUT THE INVENTION The results of surveying the average required travel time and traffic volume by time of a road segment to be predicted are saved as data, and the required travel time and traffic volume are classified according to factors such as the day of the week. The transitions are categorized, and based on the results of survey and collection of the average travel time and the traffic volume at the present time of the road section, the average travel time required for a certain time after the present time in the section is calculated as the accuracy. It was possible to predict high.
【０００９】[0009]
【実施例】本発明の走行所要時間予測システムは、道路
の地点Ａから地点Ｂまでの道路区間を対象として、該区
間を走行する各車両の走行所要時間と交通量を計測算定
する走行所要時間計算部１と、予測に先立つ数週間から
約１年間程度の期間に亘って該道路区間の一定時間間隔
毎の平均走行所要時間と交通量を計算部１により計測算
定した結果を記録保存する保存部２と、保存した走行所
要時間及び交通量の推移パターンを曜日や天候等の要因
別に分類する分類計算部３と、予測する日の現時点まで
の走行所要時間及び交通量の推移結果を基準として現時
点以降の一定時間経過後の走行所要時間を予測する予測
計算部４とを備える。DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS The travel time prediction system of the present invention targets a road section from a point A to a point B of a road, and a travel time required to measure and calculate the travel time and the traffic volume of each vehicle traveling in the section. The calculation unit 1 and the result of measuring and calculating the average required travel time and the traffic volume of the road section at constant time intervals over a period of several weeks to about one year prior to the prediction and saving the results. Based on the part 2 and the classification calculation part 3 that classifies the saved transit time and traffic volume transition patterns by factors such as the day of the week and the weather, and the transit time and traffic volume transition results up to the current date of the forecast day. A prediction calculation unit 4 that predicts a required travel time after a certain time has elapsed since the present time.
【００１０】走行所要時間計算部１は、走行する車両を
撮影した画像からナンバーを認識した結果をＡ，Ｂ地点
間で比較照合することにより走行所要時間および交通量
を算定する、あるいは、カーナビに搭載したＧＰＳ測位
システムを用いて車の位置情報と時刻情報を収集して
Ａ，Ｂ地点間の走行所要時間及び交通量を算定する。但
し、走行所要時間は、その分だけ戻した時刻を出発時刻
とする。保存部２は、日々の一定時間間隔毎に計算した
走行所要時間及び交通量のデータを、記録装置に蓄積保
存していく。分類計算部３は、蓄積保存した日々の時刻
別走行所要時間および交通量の推移パターンを相互に比
較する（たとえば、χ２乗検定で）ことにより、類似し
たパターン同士を集め、曜日や天候、あるいは季節や月
単位で、複数のグループに分類して、各分類毎の時刻別
平均走行所要時間および交通量の推移パターンを作成し
ておくとともに、各分類ごとに、一定時間間隔ごとの交
通量と走行所要時間（実際の計算では逆数の走行速度を
使う）との相関関係を作成し保存する。なお、この交通
量Ｑと走行速度Ｖの相関関係をＱＶカーブと呼ぶ。The required travel time calculation unit 1 calculates the required travel time and the traffic volume by comparing and collating the result of recognizing the number from the image of the traveling vehicle between the points A and B, or using the car navigation system. The on-board GPS positioning system is used to collect vehicle position information and time information to calculate the travel time and traffic volume between points A and B. However, the required traveling time is the time returned by that amount as the departure time. The saving unit 2 accumulates and saves the data of the required travel time and the traffic volume calculated at a constant time interval every day in a recording device. The classification calculation unit 3 collects similar patterns from each other by comparing the accumulated travel times of the daily traveling time required by time and the transit patterns of the traffic volume (for example, by the χ2 test) to determine the day of the week, the weather, or the like. It is classified into multiple groups according to the season or month, and a transition pattern of the average required travel time and traffic volume for each time is created for each category. Create and save the correlation with the travel time (use the inverse travel speed in the actual calculation). The correlation between the traffic volume Q and the traveling speed V is called a QV curve.
【００１１】予測計算部４は、２つの機能を持つ。最初
の機能は、予測しようとする当日の現時点までの交通量
推移を計算部１で求めておき、その日と同じ所属分類の
交通量の推移パターンを基準として、現時点あるいは現
時点を含むいくつかの一定時間間隔の幅における、当日
の交通量Ｃ１と所属分類の交通量Ｃ０の比率Ｒを求め、
予測しようとする時刻ｔ（現時点あるいは現時点以降の
ある時刻）における所属分類の同じ幅の交通量Ｑｔに、
該交通量の変動比率Ｒを乗じた結果を、予測対象時刻に
おける予測交通量Ｐｔとする。もうひとつの機能は、該
予測交通量Ｐｔを、該所属分類のＱＶカーブに当てはめ
て平均走行速度Ｖｔを得ることにより、該区間の距離を
該平均走行速度Ｖｔで除して、平均走行所要時間の予測
値とする。（図−１、図−２、図−３）The prediction calculation section 4 has two functions. The first function is to calculate the traffic volume transition up to the present time of the day to be predicted by the calculation unit 1, and use the transition pattern of the traffic volume of the same affiliation classification as that day as a reference to set some constants including the current time or the current time. The ratio R of the traffic volume C 1 of the day and the traffic volume C 0 of the belonging classification in the width of the time interval is calculated,
At the time t (current time or some time after the current time) to be predicted, in the traffic volume Q t of the same width of the belonging classification,
The result obtained by multiplying the variable ratio R of the traffic, the predicted traffic amount P t in the prediction target time. Another function, the predicted traffic amount P t, by obtaining an average travel speed V t by applying the QV curves of the affiliation classification, by dividing the distance between the compartment at the average running speed V t, the average This is the estimated value of the required travel time. (Figure-1, Figure-2, Figure-3)
【図１】道路区間の走行所要時間と交通量推移の観測結
果[Fig.1] Results of observation of travel time and traffic volume changes in road sections
【図２】道路区間の過去の交通量推移と、予測対象時刻
における予測交通量[Fig.2] Past traffic volume change of road section and predicted traffic volume at prediction target time
【図３】道路区間の交通量と走行速度との相関関係[Fig. 3] Correlation between traffic volume and traveling speed in a road section
Claims (14)
区間において、該区間を走行する車群の流れに従って車
両にて走行するに際して、現時点以降の、任意の時間経
過後に走行する場合に要する走行所要時間を、該区間の
現時点までの走行所要時間及び交通量を調査した結果を
拠り所として、予測するシステム1. In a road section from a point A to a point B of a certain road, when traveling by a vehicle according to the flow of a vehicle group traveling in the section, it is required when traveling after an arbitrary time has elapsed since the present time point. A system that predicts the required travel time based on the results of surveys of the required travel time and traffic volume up to the present time of the section
年間程度の長い期間に亙って、道路の地点Ａから地点Ｂ
までの道路区間において、走行する車群の平均走行所要
時間を、走行車両を撮影した画像からナンバーを認識し
て両地点相互に照合して算定した走行所要時間結果、あ
るいはＧＰＳによる位置側位結果の比較から分析した走
行所要時間結果を保存装置に収集保存し、該走行所要時
間データを曜日や季節等の要因別に、該区間の時刻別走
行所要時間の推移パターンとして分類しておき、その分
類した走行所要時間推移データを拠り所にして、該区間
の現時点以降の、任意の時間経過後の走行所要時間を予
測する、請求項１の予測システム2. A period of at least several weeks, preferably 1
Over the long period of about a year, from point A to point B on the road
In the road section up to, the average travel time required for the traveling vehicle group was calculated by recognizing the number from the image of the traveling vehicle and comparing the two points with each other. The traveling time results analyzed from the comparison are collected and stored in a storage device, and the traveling time data is classified according to the factors such as the day of the week and the season as a transition pattern of the traveling time by time of the section, and the classification is performed. The prediction system according to claim 1, wherein the travel required time transition data is used as a basis to predict the travel required time after the lapse of an arbitrary time after the present time of the section.
において、過去に調査保存した複数の時刻別道路走行所
要時間及び時刻別交通量調査結果の推移と、該区間にお
けるその日の現時点までの道路走行所要時間及び交通量
の調査結果の推移との比較から、その日の現時点以降の
任意時間経過後の、該区間の道路走行所要時間を予測す
る、請求項１の予測システム3. In the road section from the point A to the point B of the road, changes in a plurality of time-dependent road travel required times and time-dependent traffic volume survey results that have been researched and saved in the past and up to the present time of the day in the section. The prediction system according to claim 1, which predicts the road travel time of the section after a lapse of an arbitrary time after the present time of the day, by comparison with the transition of the road travel time and the traffic volume survey result.
時刻別走行所要時間推移を、月別、曜日別などの要因に
より分類した時刻別平均走行所要時間推移形を算定し、
分類項目を「月別曜日別」などとする平均走行所要時間
推移パターンを複数作成して、該区間と同じ要因分類に
属するパターンを拠り所として、任意の時間経過後の走
行所要時間を予測する、請求項２の予測システム4. The average travel required time transition form for each time is calculated by classifying the travel required travel time by time collected in the past for road sections by factors such as month and day of the week,
Create a plurality of average travel required time transition patterns with classification items such as "by month and day of the week" and use the patterns that belong to the same factor category as the section as a basis to predict the travel required time after an arbitrary time has passed. Prediction system of Item 2
する一定時間間隔毎に、道路区間の地点Ａから地点Ｂま
でを走行する車群の走行所要時間調査結果を平均して、
現時点からその走行所要時間分戻った時刻を地点Ａの出
発時刻として、最新の一定時間間隔における該道路区間
の地点Ａから地点Ｂまでの平均走行所要時間と定義す
る、請求項１の予測システム5. An average of traveling time required survey results of a group of vehicles traveling from a point A to a point B of a road section is averaged at regular time intervals of about several minutes (for example, 5 minutes).
The prediction system according to claim 1, wherein the time when the travel required time has returned from the present time is defined as the departure time of the point A, and is defined as the average travel required time from the point A to the point B of the road section in the latest constant time interval.
点Ａを現時点に出発するとした場合、あるいは、該地点
Ａを現時点以降の任意の時間（たとえば１時間等）経過
後に出発する場合を対象として、該地点Ａから該地点Ｂ
までの平均走行所要時間を予測する、請求項１の予測シ
ステム6. A case where the point A is to be departed from the point A of the road toward the point B at the present time, or the point A is to be departed after an arbitrary time (for example, 1 hour) after the present time elapses. As a target, from the point A to the point B
The prediction system according to claim 1, which predicts an average travel time to
傍において、あるいは地点Ａから地点Ｂまでの区間のな
かで最大交通量となると考えられる地点Ｃにおいて交通
量を観測し、過去の同じ分類にて保存した同じ地点にお
ける単位時間間隔別交通量と地点Ａから地点Ｂまでの該
単位時間間隔の時刻別走行所要時間との相関関係（交通
量Ｑと走行所要時間Ｖとの関係で、ＱＶカーブと称す
る）をもとに、現時点の交通量に対する走行所要時間を
算定した結果を、現時点に地点Ａを出発して地点Ｂまで
走行する場合にかかる走行所要時間予測値とする、請求
項１の予測システム7. At the present time, the traffic volume is observed in the vicinity of the point A of the road section or at the point C, which is considered to be the maximum traffic volume in the section from the point A to the point B, and is classified into the same classification in the past. Correlation between the traffic volume by unit time interval and the travel time required by time of the unit time interval from the point A to the point B at the same point saved as (the relationship between the traffic volume Q and the travel time V, QV curve Based on the above), the result of calculating the travel time required for the current traffic volume is used as the travel time estimated value required to travel from point A to point B at the present time. Prediction system
ら地点Ｂまでの道路走行所要時間を予測する場合に、地
点Ａの近傍、あるいは地点Ａから地点Ｂまでの区間のな
かで最大交通量となると考えられる地点Ｃにおいて現時
点まで観測した交通量と、過去の同じ分類における交通
量の比率を算定し、予測対象時刻における過去の交通量
に、該比率を乗じた結果を、該予測時刻における交通量
と設定して、該ＱＶカーブにより走行所要時間を予測す
る、請求項７の予測システム8. The maximum traffic volume in the vicinity of the point A or in the section from the point A to the point B when predicting the road travel time from the point A to the point B after a certain time has passed since the present time point. The ratio of the traffic volume observed up to the present time at the point C, which is considered to be, and the traffic volume in the same classification in the past are calculated, and the past traffic volume at the prediction target time is multiplied by this ratio to obtain the result at the prediction time. The prediction system according to claim 7, wherein the travel time is predicted based on the QV curve by setting the traffic volume.
間程度の長い期間におけるできるだけ多くの日を対象と
して、渋滞が恒常的に発生している時間帯を含むできる
だけ長い時間帯にわたって、単位時間間隔毎の地点Ａか
ら地点Ｂまでの平均走行所要時間及び該地点Ａあるいは
該地点Ｃの交通量を連続して調査した結果を保存し、同
じ分類別の交通量と走行所要時間の相関関係（ＱＶカー
ブと称する）を作成する、請求項７、８の予測システム9. A unit time interval for a road section is as long as possible, including a time zone in which congestion is constantly occurring, targeting as many days as possible over a long period of several weeks to one year. The average traveling time from point A to point B for each time and the result of continuously investigating the traffic volume at the point A or the point C are saved, and the correlation between the traffic volume and the traveling time (QV The prediction system according to claim 7 or 8, which creates a curve).
高い測位システム）あるいは携帯電話の基地局を利用す
る測位システムにより車の位置情報を収集できる車載装
置を利用して、道路走行中の位置情報を通信により収集
した結果、あるいは該装置内の保存装置に記録した結果
の中から、一定期間、該道路区間の地点Ａから地点Ｂま
での時刻別走行所要時間を計算及び保存して要因別に分
類し、該道路区間の任意の時間経過後の走行所要時間予
測に使うための要因別所要時間推移パターンを作成して
おく、請求項１，２，４の予測システム10. A position on a road while using a vehicle-mounted device capable of collecting position information of a vehicle by a GPS function (high-accuracy positioning system using artificial satellites) or a positioning system using a mobile phone base station. From the result of collecting information by communication or the result of recording in a storage device in the device, the traveling time required for each time from the point A to the point B of the road section is calculated and stored for a certain period, and the factors are classified according to factors. The prediction system according to claim 1, 2, or 4, which classifies and creates a required time transition pattern by factor for use in predicting a required travel time after the passage of an arbitrary time of the road section.
で、明らかにどれも代替的によく利用される関係にある
と考えられる２つまたはそれ以上の主要な道路がある場
合に、同じ時間帯における該代替道路別交通量の増減傾
向を調査把握して、同じ分類条件の日であれば、代替経
路の交通量の合計はほぼ一定となると想定して各代替経
路別の交通量を精度高く予測した上で、該代替道路別の
平均走行所要時間を予測する、請求項７，８の予測シス
テム11. The same time zone when there are two or more major roads that are apparently in a relationship that is often used as an alternative between areas where the demand for traveling by car is high. The increase / decrease trend of the traffic volume by alternative road in the above is investigated and grasped, and if it is the day of the same classification condition, it is assumed that the total traffic volume of the alternative routes will be almost constant and the traffic volume by each alternative route will be highly accurate. 9. The prediction system according to claim 7, wherein, after the prediction, the average travel time required for each of the alternative roads is predicted.
走行速度を調査収集して、該調査結果を単純に平均した
所要時間、あるいは、該調査結果の最頻値から大きく外
れた最小値周辺または最大値周辺等の特異値を除いて平
均した所要時間を対象とする、請求項１の予測システム12. A travel time of a plurality of traveling vehicles traveling on a road section is surveyed and collected, and a required time obtained by simply averaging the survey results, or a minimum value greatly deviated from a mode of the survey results. 2. The prediction system according to claim 1, wherein the average time required excluding singular values such as around the maximum value is targeted.
と、過去の類似要因分類における同じ時間帯の交通量合
計との比率を算定し、同じ分類の過去の所要時間推移形
に該比率を加味することにより、その日の現時点以降の
該道路区間の走行所要時間の推移を予測する、請求項
７，８の予測システム。13. A ratio between the total traffic volume of several hours before the present time and the total traffic volume of the same time zone in the past similar factor classification is calculated, and the ratio is calculated in the past required time transition type of the same classification. 9. The prediction system according to claim 7, wherein the transition of the required travel time of the road section after the present time on that day is predicted by adding the factors.
推移と、同じ分類における過去の平均的な該推移パター
ンとを比較して、急激な変化が起きた場合に、対象道路
区間の管轄警察署に事故等の原因と、事故等の処理が済
むまでの所要時間を確認または過去の事故発生時の延滞
時間の実績を参考として、現時点以降の走行所要時間の
推計値をその分加算することにより、その日の現時点以
降の該道路区間の走行所要時間の推移を予測する、請求
項１の、予測システム。14. The time required or the traffic volume transition up to the present time is compared with the past average transition pattern in the same classification, and when a sudden change occurs, the police station in charge of the target road section is notified. By confirming the cause of the accident and the time required to complete the processing of the accident, or by referring to the past delay time when the accident occurred in the past, by adding the estimated value of the required travel time after the current time, The prediction system according to claim 1, which predicts a transition of a required travel time of the road section after the present time on that day.
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|---|---|---|---|
| JP2002084496A JP2003242589A (en) | 2002-02-18 | 2002-02-18 | Road running time predicting system |
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| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| JP2002084496A JP2003242589A (en) | 2002-02-18 | 2002-02-18 | Road running time predicting system |
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|---|---|---|---|---|
| JP2006163495A (en) * | 2004-12-02 | 2006-06-22 | Aisin Aw Co Ltd | Data processing unit, information display unit and database generation method |
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| JP2006163495A (en) * | 2004-12-02 | 2006-06-22 | Aisin Aw Co Ltd | Data processing unit, information display unit and database generation method |
| JP4506440B2 (en) * | 2004-12-02 | 2010-07-21 | アイシン・エィ・ダブリュ株式会社 | Data processing apparatus, information display apparatus, and database creation method |
| JP2006268137A (en) * | 2005-03-22 | 2006-10-05 | Fujitsu Ltd | Congestion state guiding device |
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