JP7366866B2 - Train driving support system and train driving support method - Google Patents

Train driving support system and train driving support method Download PDF

Info

Publication number
JP7366866B2
JP7366866B2 JP2020147389A JP2020147389A JP7366866B2 JP 7366866 B2 JP7366866 B2 JP 7366866B2 JP 2020147389 A JP2020147389 A JP 2020147389A JP 2020147389 A JP2020147389 A JP 2020147389A JP 7366866 B2 JP7366866 B2 JP 7366866B2
Authority
JP
Japan
Prior art keywords
train
station
time
estimated
stop
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.)
Active
Application number
JP2020147389A
Other languages
Japanese (ja)
Other versions
JP2022042138A (en
Inventor
健太郎 牧
祥太 木村
潤 小池
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hitachi Ltd
Original Assignee
Hitachi Ltd
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Hitachi Ltd filed Critical Hitachi Ltd
Priority to JP2020147389A priority Critical patent/JP7366866B2/en
Publication of JP2022042138A publication Critical patent/JP2022042138A/en
Application granted granted Critical
Publication of JP7366866B2 publication Critical patent/JP7366866B2/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Images

Landscapes

  • Train Traffic Observation, Control, And Security (AREA)

Description

本発明は、鉄道の列車運転支援システムおよび列車運転支援方法に関する。 The present invention relates to a train driving support system and a train driving support method for railways.

地球環境問題や資源枯渇問題に対応するため、比較的エネルギー使用効率のよい鉄道分野においても、更なる省エネ化が必要とされている。その中で、鉄道の運行においては、駅間走行の速度パターンを適正化することで車両運行の省エネ化が可能である。 In order to respond to global environmental problems and resource depletion issues, further energy conservation is required even in the railway field, which has relatively high energy usage efficiency. Among these, in railway operation, it is possible to save energy in vehicle operation by optimizing the speed pattern of traveling between stations.

本技術分野に関連する先行技術として、特許文献１には、「車両側からリアルタイムに収集される車両の混雑度と、駅側でリアルタイムに収集される改札データ、ならびに事前に調査した当駅における曜日毎、時間毎の乗降客数のデータを用いて駅停車時間を予測し、予測した駅停車時間を反映させて列車ダイヤを作成する運行管理システムを得る」（段落［０００５］）点が開示されている。この先行技術によれば、乗降人数が想定以上に多く、先行列車の駅出発遅れが発生する際に、後続列車が先行列車に接近し過ぎることにより発生する機外停止や計画外のブレーキを抑制することができる。 As a prior art related to this technical field, Patent Document 1 states, "The congestion level of vehicles collected in real time from the vehicle side, the ticket gate data collected in real time at the station side, and the data at this station surveyed in advance. To obtain a traffic management system that predicts station stop times using data on the number of passengers boarding and alighting for each day of the week and each hour, and creates a train schedule that reflects the predicted station stop times.'' (Paragraph [0005]) is disclosed. ing. According to this prior art, when the number of passengers getting on and off the train is larger than expected and the preceding train is delayed in departing from the station, it is possible to suppress external stops and unplanned braking caused by the following train getting too close to the preceding train. can do.

特開２００８－１８９１８０号公報Japanese Patent Application Publication No. 2008-189180

特許文献１に開示されている駅停車時間は、駅における乗降に必要な時間（以降、「乗降時分」という）であり、乗降終了から列車が発車するまでの確認作業に必要な時間（以降、「確認時分」という）が含まれていない。この確認時分には、ドア挟みの解消や発車前の安全確認のための時間が含まれる。そのため、仮に駅で乗降が全く無い場合であっても確認時分は発生し、混雑状態で発着する列車においては数十秒の時間が必要となることもある。そうすると、確認時分を含まない駅停車時間の予測結果に基づいてダイヤ作成を行うと、後続列車の駅到着時刻を適切に設定できず、後続列車の機外停止や計画外のブレーキの抑制効果が限定的となる。 The station stopping time disclosed in Patent Document 1 is the time required for boarding and alighting at the station (hereinafter referred to as "boarding and alighting time"), and the time required for confirmation work from the end of boarding and alighting until the train departs (hereinafter referred to as "boarding and alighting time"). , "confirmation time") are not included. This confirmation time includes time for removing jammed doors and checking safety before departure. Therefore, even if there is no boarding or alighting at the station, a confirmation time will still be required, and it may take several tens of seconds for trains arriving and departing in crowded conditions. In this case, if a timetable is created based on the prediction result of the station stop time that does not include the confirmation time, the station arrival time of the following train cannot be set appropriately, and the effect of suppressing the off-board stop of the following train and unplanned braking. will be limited.

本発明は、駅停車時間として乗降時分に加えて確認時分も考慮し、先行列車の駅発車時刻の推定精度を向上させることで、後続列車の駅間走行に関して省エネ効果を安定的に発揮可能な列車運転支援システムを提供することを課題とする。 The present invention takes into account confirmation time in addition to boarding and alighting time as the station stop time, and improves the accuracy of estimating the station departure time of the preceding train, thereby stably achieving energy-saving effects for the following train's inter-station travel. The objective is to provide a train driving support system that is possible.

上記課題を解決するために、代表的な本発明の列車運転支援システムは、先行列車が停車駅で乗降を開始する前のタイミングで、先行列車の停車駅での乗降人数推定値を算出する乗降人数推定部と、車両定員に占める乗車人数の割合を乗車率として、先行列車が停車駅で乗降を開始する前に測定された先行列車の第１の乗車率と乗降人数推定値とを基にして、先行列車の停車駅での駅停車時間推定値を算出する駅停車時間推定部と、駅停車時間推定値と先行列車の停車駅での予定発着時刻とを基にして、先行列車の停車駅での発車時刻推定値を算出する先行列車発車時刻推定部と、発車時刻推定値に基づいて後続列車の停車駅への目標到着時刻を設定する後続列車目標到着時刻設定部と、後続列車が目標到着時刻を満足するための停車駅に至る駅間走行パターンを設定する後続列車駅間走行パターン設定部とを備え、駅停車時間推定部は、乗降人数推定値および第１の乗車率に基づく乗降時分推定値と先行列車の停車駅での乗降終了後の乗車率である第２の乗車率に基づく確認時分推定値との和を、駅停車時間推定値として算出することを特徴とする。 In order to solve the above problems, a typical train driving support system of the present invention calculates the estimated number of people getting on and off at the station where the preceding train stops before the preceding train starts boarding and alighting at the station where the preceding train stops. The number of people estimating unit is based on the first occupancy rate of the preceding train measured before the preceding train starts boarding and alighting at the stopping station and the estimated value of the number of passengers getting on and off, with the ratio of the number of passengers to the vehicle capacity as the occupancy rate. Based on the estimated station stop time and the scheduled departure and arrival times at the station where the preceding train stops, a preceding train departure time estimator that calculates an estimated departure time at a station; a subsequent train target arrival time setting unit that sets a target arrival time for the following train at a stopping station based on the estimated departure time; and a subsequent train inter-station travel pattern setting unit that sets an inter-station travel pattern leading to a stop station to satisfy the target arrival time, and the station stop time estimating unit is based on the estimated number of passengers getting on and off and the first occupancy rate. It is characterized by calculating the sum of the estimated boarding and alighting time and the estimated confirmation time based on the second occupancy rate, which is the occupancy rate after boarding and alighting at the station where the preceding train stops, as the estimated station stop time. do.

本発明によれば、後続列車における不要な機外停止や計画外のブレーキの抑制を、安定して機能させることができ、省エネ効果が向上する。
上記した以外の課題、構成および効果は、以下の実施例における説明により明らかにされる。 According to the present invention, it is possible to stably suppress unnecessary external stops and unplanned braking in a following train, and the energy saving effect is improved.
Problems, configurations, and effects other than those described above will be made clear by the explanations in the following examples.

実施例１および実施例２に係る列車運転支援システムの全体構成を示す図である。1 is a diagram showing the overall configuration of a train driving support system according to Examples 1 and 2. FIG. 実施例１に係る列車運転支援システムの内部構成を示す図である。1 is a diagram showing an internal configuration of a train driving support system according to a first embodiment. 実施例２に係る列車運転支援システムの内部構成を示す図である。FIG. 2 is a diagram showing an internal configuration of a train driving support system according to a second embodiment. 実施例３に係る列車運転支援システムの全体構成を示す図である。FIG. 3 is a diagram showing the overall configuration of a train driving support system according to a third embodiment. 実施例３に係る列車運転支援システムの内部構成を示す図である。FIG. 3 is a diagram showing an internal configuration of a train driving support system according to a third embodiment.

本発明を実施するための形態として、本発明に係る実施例１から３を示し、各実施例を図面を用いて以下に説明する。 Embodiments 1 to 3 according to the present invention will be shown as modes for carrying out the present invention, and each embodiment will be described below using the drawings.

実施例１では、停車駅における先行列車の乗降時分と確認時分の両方を考慮した上で、当該停車駅への後続列車の目標到着時刻が設定され、この目標到着時刻を満たすように前記後続列車は駅間で自動運転される、列車運転支援システムの例を説明する。 In the first embodiment, the target arrival time of the following train at the stopping station is set in consideration of both the boarding and alighting time and the confirmation time of the preceding train at the stopping station, and the above-mentioned arrival time is set so as to meet this target arrival time. An example of a train driving support system will be described in which following trains are automatically operated between stations.

実施例１によれば、前記先行列車の駅停車時間として、乗降時分に加えて確認時分も考慮することにより、前記先行列車の駅発車時刻の推定精度が向上し、それに伴う前記後続列車の目標到着時刻が適切に設定される。そのため、前記後続列車の駅間自動運転における無駄な加減速が抑制され、省エネな運転が可能となる。 According to the first embodiment, by considering the confirmation time in addition to the boarding and alighting time as the station stopping time of the preceding train, the accuracy of estimating the station departure time of the preceding train is improved, and the following train accordingly The target arrival time is set appropriately. Therefore, unnecessary acceleration and deceleration of the following train during inter-station automatic operation is suppressed, and energy-saving operation becomes possible.

図１は、実施例１に係る列車運転支援システムの全体構成を示す図である。
先行列車２１００と後続列車２２００それぞれは、運行管理装置２３００と無線で情報の送受信が可能な状態である。前記先行列車２１００は、自列車の位置、速度および乗車率を前記運行管理装置２３００へ送信する。前記後続列車２２００は、前記運行管理装置２３００から次駅２５００への目標到着時刻を受信する。 FIG. 1 is a diagram showing the overall configuration of a train driving support system according to a first embodiment.
The preceding train 2100 and the following train 2200 are each in a state where they can transmit and receive information wirelessly to the operation management device 2300. The preceding train 2100 transmits the position, speed, and occupancy rate of its own train to the operation management device 2300. The following train 2200 receives the target arrival time to the next station 2500 from the operation management device 2300.

また、前記次駅２５００には、駅人流監視装置２４００が備えられている。前記駅人流監視装置２４００は、前記次駅２５００における前記先行列車２１００への乗車人数推定値を算出し、前記運行管理装置２３００へ無線または有線で送信する。前記駅人流監視装置２４００における乗車人数推定としては、例えば、改札の通過人数計数結果や駅構内のカメラ画像分析結果を基にして推定する方法があるが、これらの方法に限定されるものではない。 Further, the next station 2500 is equipped with a station people flow monitoring device 2400. The station passenger flow monitoring device 2400 calculates the estimated number of passengers on the preceding train 2100 at the next station 2500 and transmits it to the operation management device 2300 wirelessly or by wire. For estimating the number of passengers in the station passenger flow monitoring device 2400, for example, there is a method of estimating based on the result of counting the number of people passing through the ticket gate or the result of analyzing camera images in the station premises, but the method is not limited to these methods. .

前記先行列車２１００から前記運行管理装置２３００への情報送信は、前記先行列車２１００が前駅（図示せず）を発車するタイミング以降で、前記次駅２５００へ到着するタイミング以前に行われる。また、前記情報送信は、前記前駅から前記次駅２５００までの駅間走行中に連続的に実施する必要はなく、少なくとも１回送信されればよい。 Information transmission from the preceding train 2100 to the operation management device 2300 is performed after the timing when the preceding train 2100 departs from the previous station (not shown) and before the timing when the preceding train 2100 arrives at the next station 2500. Further, the information transmission does not need to be performed continuously during inter-station travel from the previous station to the next station 2500, and may be transmitted at least once.

前記駅人流監視装置２４００から前記運行管理装置２３００への乗車人数推定値の送信は、前記先行列車２１００をさらに先行する列車（図示せず）が前記次駅２５００を発車したタイミング以降で、前記先行列車２１００が前記次駅２５００へ到着するタイミング以前に行われる。 The transmission of the estimated number of passengers from the station passenger flow monitoring device 2400 to the operation management device 2300 is performed after the timing at which a train (not shown) that further precedes the preceding train 2100 departs from the next station 2500. This is performed before the train 2100 arrives at the next station 2500.

前記運行管理装置２３００では、前記先行列車２１００から受信する情報と前記駅人流監視装置２４００から受信する情報とが揃った時点で、前記後続列車２２００の次駅への目標到着時刻を生成し、前記後続列車２２００に対して当該目標到着時刻を送信する。 When the information received from the preceding train 2100 and the information received from the station people flow monitoring device 2400 are complete, the operation management device 2300 generates a target arrival time for the following train 2200 at the next station, and The target arrival time is transmitted to the following train 2200.

図２は、実施例１に係る列車運転支援システムの内部構成を示す図である。各構成要素の動作態様を、図２を用いて説明する。
実施例１に係る列車運転支援システムが備える前記先行列車２１００内の装置構成は、先行列車車両情報管理装置２１０１、ドア制御器２１０２、速度発電機２１０３およびブレーキ制御装置２１０４である。なお、車両情報管理装置については、その呼称として、車両情報装置、車両情報制御装置、モニタ装置などもある。 FIG. 2 is a diagram showing the internal configuration of the train driving support system according to the first embodiment. The operation mode of each component will be explained using FIG. 2.
The device configuration in the preceding train 2100 included in the train driving support system according to the first embodiment includes a preceding train vehicle information management device 2101, a door controller 2102, a speed generator 2103, and a brake control device 2104. Note that the vehicle information management device is also referred to as a vehicle information device, a vehicle information control device, a monitor device, and the like.

先行列車速度・位置２１１３は、前記先行列車２１００から前記運行管理装置２３００への送信情報の一つである。前記先行列車車両情報管理装置２１０１が備える速度・位置検出部２１０５において、前記ドア制御器２１０２から受信するドア開情報２１１０と前記速度発電機２１０３から受信するパルス情報２１１１とを基にして前記先行列車速度・位置２１１３が算出される。 The preceding train speed/position 2113 is one piece of information transmitted from the preceding train 2100 to the operation management device 2300. The speed/position detection unit 2105 included in the preceding train vehicle information management device 2101 detects the preceding train based on the door opening information 2110 received from the door controller 2102 and the pulse information 2111 received from the speed generator 2103. Velocity/position 2113 is calculated.

前記パルス情報２１１１は、前記速度発電機２１０３から出力される車輪の回転数に比例した周期で発生するパルス信号である。前記パルス情報２１１１に対して当該周期と車輪径を考慮することで、前記先行列車速度・位置２１１３に含まれる列車の速度情報が計算される。 The pulse information 2111 is a pulse signal generated at a period proportional to the rotation speed of the wheel output from the speed generator 2103. By considering the period and wheel diameter for the pulse information 2111, the speed information of the train included in the preceding train speed/position 2113 is calculated.

前記ドア開情報２１１０は、車両内の各ドアの開閉状態を示す信号である。列車のドアが開くタイミングは、列車運行中は駅停車中のみであることから、前記ドア開情報２１１０の監視によって、列車が駅に到着したことが分かる。 The door opening information 2110 is a signal indicating the open/closed state of each door in the vehicle. Since the train doors open only when the train is in operation and stops at a station, it can be determined that the train has arrived at the station by monitoring the door opening information 2110.

前記先行列車速度・位置２１１３に含まれる列車の位置に関しては、前記ドア開情報２１１０の監視で判定した駅到着時に、駅の絶対位置をデータベース（図示せず）から取得し設定した上で、駅間走行中の位置を、列車速度の積分で計算した走行距離を前記駅の絶対位置に加算することにより計算する。 Regarding the position of the train included in the preceding train speed/position 2113, the absolute position of the station is acquired from a database (not shown) and set at the time of arrival at the station determined by monitoring the door opening information 2110, and then The position during the train is calculated by adding the travel distance calculated by integrating the train speed to the absolute position of the station.

次に、乗車率２１１４も、前記先行列車２１００から前記運行管理装置２３００への送信情報の一つである。前記先行列車車両情報管理装置２１０１が備える乗車率算出部２１０６において、前記ブレーキ制御装置２１０４から受信する空気ばね内圧２１１２を基にして前記乗車率２１１４を算出する。 Next, the occupancy rate 2114 is also one of the information transmitted from the preceding train 2100 to the operation management device 2300. The occupancy rate calculation unit 2106 included in the preceding train vehicle information management device 2101 calculates the occupancy rate 2114 based on the air spring internal pressure 2112 received from the brake control device 2104.

ここで、空気ばねは、車両と台車との間に装着されており、車輪から車両に伝わる振動を軽減する役目を果たす部品であり、乗り心地を良くするためのものである。空車から満車まで様々な荷重がかかる状況下で、車両の高さが維持されるようにその内圧が調整されるため、前記空気ばね内圧２１１２を基にして荷重の算出が可能である。算出された荷重から、空車状態での車体重量を差し引き、さらに一人当たりの重量で除算することで、乗車人数が推定できる。車両定員に占める乗車人数の割合が前記乗車率２１１４である。前記乗車率２１１４は、編成内の車両ごとに算出される。 Here, the air spring is a component that is installed between the vehicle and the truck, and serves to reduce vibrations transmitted from the wheels to the vehicle, and is intended to improve riding comfort. Since the internal pressure is adjusted so that the height of the vehicle is maintained under various loads from empty to full, the load can be calculated based on the air spring internal pressure 2112. The number of passengers can be estimated by subtracting the empty vehicle weight from the calculated load and then dividing by the weight per person. The ratio of the number of passengers to the vehicle capacity is the occupancy rate 2114. The occupancy rate 2114 is calculated for each vehicle in the formation.

前記駅人流監視装置２４００は、乗車人数推定部２４０１を備える。前記乗車人数推定部２４０１では、改札の通過人数計数結果や駅構内のカメラ画像分析結果等を基にして、前記先行列車２１００に乗車するために駅ホームに滞留する利用客の人数を推定し、乗車人数推定値２４１１を算出する。前記乗車人数推定値２４１１は、駅ホーム上における利用客の空間分布傾向を考慮して、編成の車両ごとに乗車人数の推定値が算出されることが望ましい。 The station passenger flow monitoring device 2400 includes a passenger number estimating section 2401. The number of passengers estimating unit 2401 estimates the number of passengers staying at the station platform to board the preceding train 2100 based on the results of counting the number of people passing through the ticket gate, the analysis of camera images inside the station, etc. An estimated number of passengers 2411 is calculated. As for the estimated number of passengers 2411, it is preferable that the estimated number of passengers is calculated for each vehicle in the formation, taking into consideration the spatial distribution tendency of passengers on the station platform.

前記運行管理装置２３００は、前記空気ばね内圧２１１２、前記乗車率２１１４および前記乗車人数推定値２４１１を基にして、後続列車目標到着時刻２３１５を算出し、前記後続列車２２００に送信する。前記運行管理装置２３００は、ダイヤ管理部２３０１、乗降人数推定部２３０２、駅停車時間推定部２３０３、先行列車発車時刻推定部２３０６および後続列車目標到着時刻設定部２３０７から構成される。また、前記駅停車時間推定部２３０３は、乗降時分推定部２３０４と確認時分推定部２３０５とから構成される。 The operation management device 2300 calculates a subsequent train target arrival time 2315 based on the air spring internal pressure 2112, the occupancy rate 2114, and the estimated number of passengers 2411, and transmits it to the subsequent train 2200. The operation management device 2300 is composed of a timetable management section 2301, a boarding/alighting number estimating section 2302, a station stop time estimating section 2303, a preceding train departure time estimating section 2306, and a following train target arrival time setting section 2307. Further, the station stop time estimating section 2303 includes a boarding/disembarking time estimating section 2304 and a confirmation time estimating section 2305.

前記ダイヤ管理部２３０１は、運行中の各列車の予定発着時刻を管理する。前記ダイヤ管理部２３０１が管理する予定発着時刻の内、予定発車時刻は、計画ダイヤ（図示せず）で定められた発車時刻であり、予定到着時刻は、前記先行列車速度・位置２１１３を基に推定される。予定到着時刻の推定方法の一例としては、前記先行列車２１００が走行中の駅間における一般的な走行速度パターンを仮定して、前記先行列車速度・位置２１１３の状態から前記次駅２５００までの所要時間を推定する方法が挙げられる。前記ダイヤ管理部２３０１は、前記先行列車２１００の前記予定発車時刻および前記予定到着時刻を、先行列車予定発着時刻２３１０として、前記先行列車発車時刻推定部２３０６に出力する。 The timetable management unit 2301 manages the scheduled departure and arrival times of each train in operation. Among the scheduled departure and arrival times managed by the timetable management section 2301, the scheduled departure time is the departure time determined by the planned timetable (not shown), and the scheduled arrival time is based on the preceding train speed and position 2113. Presumed. As an example of a method for estimating the scheduled arrival time, assuming a general traveling speed pattern between the stations where the preceding train 2100 is running, calculate the required time from the preceding train speed/position 2113 to the next station 2500. One example is a method of estimating time. The timetable management unit 2301 outputs the scheduled departure time and scheduled arrival time of the preceding train 2100 to the preceding train departure time estimation unit 2306 as the scheduled preceding train departure and arrival time 2310.

前記乗降人数推定部２３０２は、前記乗車率２１１４および前記乗車人数推定値２４１１を入力として、編成内の車両ごとに乗降人数推定値２３１１を算出し、前記駅停車時間推定部２３０３に出力する。前記乗降人数推定値２３１１は、前記乗車人数推定値２４１１と別途推定する降車人数推定値との和である。前記降車人数推定値の算出方法の一例としては、駅ごとに事前集計されている「曜日別・時間帯別の降車割合」の統計を基に、前記乗車率２１１４を考慮して算出する方法がある。例えば、前記次駅２５００に到着する列車に関して、「平日の朝７時台には乗客の１割が降車する」という統計がある場合、朝７時台に到着した先行列車２１００の乗車定員に前記乗車率２１１４を乗じた人数の１割が、前記降車人数推定値となる。前記降車人数推定値は、各車両の前記乗車率２１１４を基にして、車両ごとに算出されていることが望ましい。 The number of passengers getting on and off estimating section 2302 receives the occupancy rate 2114 and the estimated number of passengers 2411 as input, calculates an estimated number of people getting on and off for each vehicle in the formation, and outputs it to the station stop time estimation section 2303. The estimated number of passengers getting on and off the vehicle 2311 is the sum of the estimated number of passengers 2411 and a separately estimated number of people getting off the vehicle. An example of a method for calculating the estimated number of people getting off the train is a method in which the occupancy rate 2114 is taken into consideration based on the statistics of "alighting ratio by day of the week and time of day" that is compiled in advance for each station. be. For example, regarding the train arriving at the next station 2500, if there is a statistic that "10% of passengers get off the train by 7 a.m. on weekdays," then the passenger capacity of the preceding train 2100 that arrived at 7 a.m. will be 10% of the number of people multiplied by the occupancy rate 2114 becomes the estimated number of people getting off the train. It is preferable that the estimated number of people getting off the vehicle is calculated for each vehicle based on the occupancy rate 2114 of each vehicle.

前記駅停車時間推定部２３０３を構成する前記乗降時分推定部２３０４は、前記乗車率２１１４および前記乗降人数推定値２３１１を基にして、前記先行列車２１００の降車および乗車に必要な時間を推定し、乗降時分推定値２３１２として、前記先行列車発車時刻推定部２３０６に出力する。前記乗降時分推定値２３１２の算出方法の一例としては、予め用意された乗降時分算出式に、前記乗車率２１１４および前記乗降人数推定値２３１１を代入することで算出する方法がある。その際の前記乗降時分算出式の一例を下記する。
乗降時分＝ＭＡＸ（最小乗降時分、α・ｘ＋β・ｘ２＋γ・ｙ＋δ・ｙ２）
ここで、ＭＡＸ（ψ、φ）は、ψとφの内、大きい方を出力することを意味する。 The boarding/alighting time estimating unit 2304 configuring the station stop time estimating unit 2303 estimates the time required for alighting and boarding the preceding train 2100 based on the occupancy rate 2114 and the estimated number of passengers 2311. , is output to the preceding train departure time estimating section 2306 as an estimated boarding/alighting time value 2312. An example of a method for calculating the boarding/alighting time estimate 2312 is a method of calculating by substituting the occupancy rate 2114 and the boarding/alighting number estimated value 2311 into a boarding/alighting time calculation formula prepared in advance. An example of the equation for calculating the boarding and alighting time at that time will be described below.
Boarding and alighting time = MAX (minimum boarding and alighting time, α・x+β・x 2 +γ・y+δ・y 2 )
Here, MAX (ψ, φ) means outputting the larger one of ψ and φ.

乗降時分算出式のＭＡＸ（ψ、φ）のψに相当する「最小乗降時分」は、仮に乗降が全く無しでも最低限ドアを開けていなければならない時間を意味し、この時間が決まっている場合には決まっている値を使用し、決まっていない場合にはゼロとする。
乗降時分算出式ＭＡＸ（ψ、φ）のφに相当する多項式において、α、β、γおよびδは、係数であって、過去の乗降人数、乗車率および乗降時分の計測データ群から多変量回帰分析で求めるか、乗降行動を模擬したモデルシミュレーションによって求める。一方、変数ｘは前記乗降人数推定値２３１１、変数ｙは前記乗車率２１１４である。ここで、上記の多項式で、乗降人数のみならず乗車率の項が存在するのは、仮に同じ乗降人数であっても、乗車率の多寡すなわち列車内の混雑度によって乗降の速度が影響を受けるためである。 The "minimum boarding and alighting time", which corresponds to ψ in MAX (ψ, φ) in the boarding and alighting time calculation formula, means the minimum time that the door must be open even if there is no boarding and alighting, and this time is fixed. If so, use the fixed value, otherwise use zero.
In the polynomial corresponding to φ in the boarding and alighting time calculation formula MAX (ψ, φ), α, β, γ, and δ are coefficients that are calculated from the past measurement data group of the number of people getting on and off, the occupancy rate, and the boarding and alighting time. It is determined by variable regression analysis or by model simulation that simulates boarding and alighting behavior. On the other hand, the variable x is the estimated number of passengers getting on and off 2311, and the variable y is the occupancy rate 2114. Here, in the above polynomial, there is a term for not only the number of people getting on and off but also the boarding rate.The reason why there is a term for the boarding rate as well as the number of people getting on and off is that even if the number of people getting on and off is the same, the speed of boarding and alighting is affected by the number of boardings, that is, the degree of congestion in the train. It's for a reason.

また、前記乗降時分推定値２３１２の算出方法は、前記乗車率２１１４および前記乗降人数推定値２３１１を基にした算出方法であれば、上記した方法に限定されるものではない。算出方法によらず、乗降時分は編成内の車両ごとにその値を算出し、車両数分の乗降時分をまとめて前記乗降時分推定値２３１２として、前記先行列車発車時刻推定部２３０６に出力する。 Further, the method for calculating the estimated boarding/alighting time 2312 is not limited to the method described above, as long as it is a calculation method based on the occupancy rate 2114 and the estimated number of passengers 2311. Regardless of the calculation method, the value of the boarding and alighting time is calculated for each vehicle in the formation, and the boarding and alighting time for the number of vehicles is combined into the boarding and alighting time estimated value 2312 and sent to the preceding train departure time estimation unit 2306. Output.

前記駅停車時間推定部２３０３を構成する前記確認時分推定部２３０５は、前記乗車率２１１４および前記乗降人数推定値２３１１を基にして、前記先行列車２１００における乗降終了から発車までに必要な時間を推定し、確認時分推定値２３１３として前記先行列車発車時刻推定部２３０６に出力する。確認時分推定値２３１３の算出に当たっては、前記先行列車２１００における乗降終了後の乗車率（以降、「乗降後乗車率」という）を用いた算出式による方法が、有効である。なぜならば、確認時分は、ドア挟みの解消や発車前の確認作業に要する時間であるため、乗降行動そのものではなく、乗降後の乗車状態に影響されるからである。前記乗降後乗車率は、乗降前の状態である前記乗車率２１１４に対して前記乗降人数推定値２３１１を考慮し、前記乗車率２１１４と前記乗降人数推定値２３１１とを用いて算出できる。その際の前記乗降後乗車率を用いた前記確認時分推定値２３１３の確認時分算出式の一例を下記する。
確認時分＝ＭＡＸ（最小確認時分、γ’・ｚ＋δ’・ｚ２） The confirmation time estimating unit 2305, which constitutes the station stopping time estimating unit 2303, calculates the time required from the completion of boarding and alighting in the preceding train 2100 to departure based on the occupancy rate 2114 and the estimated number of passengers 2311. It is estimated and outputted as a confirmation time estimated value 2313 to the preceding train departure time estimating section 2306. In calculating the confirmation time estimated value 2313, it is effective to use a calculation formula using the occupancy rate after boarding and alighting in the preceding train 2100 (hereinafter referred to as "post-boarding and alighting occupancy rate"). This is because the confirmation time is the time required to eliminate door jamming and to confirm before departure, and is therefore affected by the riding condition after getting on and off, rather than the getting on and off behavior itself. The occupancy rate after getting on and off can be calculated using the occupancy rate 2114 and the estimated number of people getting on and off 2311 in consideration of the occupancy rate 2114 which is the state before getting on and off. An example of a formula for calculating the confirmation time and minute of the confirmation time estimated value 2313 using the occupancy rate after getting on and off at that time will be described below.
Confirmation time = MAX (minimum confirmation time, γ'・z+δ'・z 2 )

確認時分算出式のＭＡＸの第１項目の「最小確認時分」は、仮に乗降が全く無しで、乗車率がゼロの場合であっても、最低限必要な一定の確認時分があるため、その一定の値を使用する。第２項目の多項式中のγ’、δ’は、係数であって、過去の乗降人数、乗車率および確認時分の計測データ群から多変量回帰分析で求めるか、乗降行動を模擬したモデルシミュレーションによって求める。変数ｚは、前記乗降後乗車率である。 The first item of MAX in the confirmation time calculation formula, "minimum confirmation time," is because even if there is no boarding or alighting and the occupancy rate is zero, there is a certain minimum confirmation time required. , use that constant value. γ' and δ' in the polynomial of the second item are coefficients, which can be obtained by multivariate regression analysis from the past measured data of the number of people getting on and off, the occupancy rate, and the confirmation time, or by a model simulation that simulates the boarding and alighting behavior. Find it by The variable z is the occupancy rate after getting on and off.

すなわち、上記した確認時分算出式よれば、乗降後乗車率が、所定の閾値以下の場合には、左項の「最小確認時分」が大きいため、一定の最小確認時分が出力され、所定の閾値より大きい場合には、右項の「γ’・ｚ＋δ’・ｚ２」が大きくなり、右項の値が出力される。そして、乗降後乗車率が大きいほど、出力される確認時分も大きくなる。 That is, according to the above-mentioned confirmation time calculation formula, if the occupancy rate after boarding and alighting is less than or equal to a predetermined threshold, the "minimum confirmation time" in the left term is large, so a certain minimum confirmation time is output, If the value is larger than the predetermined threshold, the right term "γ'·z+δ'·z 2 " increases, and the value of the right term is output. The larger the occupancy rate after boarding and alighting, the larger the output confirmation time.

また、前記確認時分推定値２３１３の算出方法は、前記乗車率２１１４および前記乗降人数推定値２３１１を基にした算出方法であれば、上記した方法に限定されるものではない。算出方法によらず、確認時分は、編成内の車両ごとに値を算出し、車両数分の確認時分をまとめて前記確認時分推定値２３１３として、前記先行列車発車時刻推定部２３０６に出力する。 Further, the method for calculating the estimated confirmation time value 2313 is not limited to the method described above, as long as it is a calculation method based on the occupancy rate 2114 and the estimated number of passengers 2311. Regardless of the calculation method, the confirmation time is calculated for each vehicle in the formation, and the confirmation time and minutes for the number of vehicles are combined and sent to the preceding train departure time estimation unit 2306 as the confirmation time estimate 2313. Output.

前記先行列車発車時刻推定部２３０６では、前記先行列車予定発着時刻２３１０と前記乗降時分推定値２３１２と前記確認時分推定値２３１３とを基にして、先行列車発車時刻推定値２３１４を算出する。具体的には、先行列車の予定到着時刻に必要な駅停車時間を加えた時刻を算出し、算出した時刻が、予定発車時刻と比べて遅い場合には、当該時刻を前記先行列車発車時刻推定値２３１４とし、そうでない場合には、列車の早発は一般的になされないため、予定発車時刻を前記先行列車発車時刻推定値２３１４とする。ここで、必要な駅停車時間は、前記乗降時分推定値２３１２と前記確認時分推定値２３１３とから求める時間である。編成内の乗降時分推定値と確認時分推定値の中で、それぞれ最も大きい値の和を前記必要な駅停車時間とする。 The preceding train departure time estimating unit 2306 calculates an estimated preceding train departure time 2314 based on the preceding train scheduled departure and arrival time 2310, the estimated boarding and alighting time 2312, and the estimated confirmed time 2313. Specifically, the time is calculated by adding the necessary station stop time to the scheduled arrival time of the preceding train, and if the calculated time is later than the scheduled departure time, the time is used as the estimated departure time of the preceding train. If not, the estimated train departure time is set to the preceding train departure time estimate 2314 because trains generally do not depart early. Here, the required station stopping time is the time calculated from the boarding/alighting time estimated value 2312 and the confirmation time/minute estimated value 2313. The sum of the largest values of the estimated boarding and alighting times and estimated confirmation times in the train set is the required station stop time.

前記後続列車目標到着時刻設定部２３０７は、前記先行列車発車時刻推定値２３１４を基にして、前記後続列車目標到着時刻２３１５を算出し、前記後続列車２２００の自動列車運転装置２２０２に出力する。前記後続列車目標到着時刻２３１５の算出に当たっては、当該路線の信号システム、駅構内および周辺の軌道回路割り、前記次駅２５００への一般的な進入速度パターンなどを考慮に入れた上で、前記後続列車２２００が機外停止や計画外の減速をせずに前記次駅２５００に到着できる時刻を算出する。 The following train target arrival time setting unit 2307 calculates the following train target arrival time 2315 based on the preceding train departure time estimate 2314 and outputs it to the automatic train operation device 2202 of the following train 2200. In calculating the subsequent train target arrival time 2315, the following train The time at which the train 2200 can arrive at the next station 2500 without making an external stop or unplanned deceleration is calculated.

前記後続列車２２００において、実施例１の列車運転支援システムに関係する装置構成は、後続列車車両情報管理装置２２０１、前記自動列車運転装置２２０２および制駆動制御装置２２０３である。前記自動列車運転装置２２０２は、速度パターン計画部２２０４、データベース２２０５および制御指令生成部２２０６を有する。 In the following train 2200, the device configurations related to the train driving support system of the first embodiment are the following train vehicle information management device 2201, the automatic train driving device 2202, and the braking/driving control device 2203. The automatic train operation device 2202 includes a speed pattern planning section 2204, a database 2205, and a control command generation section 2206.

前記後続列車車両情報管理装置２２０１は、後続列車位置・速度２２１０を生成して、前記自動列車運転装置２２０２へ出力する。前記後続列車車両情報管理装置２２０１は、前記先行列車車両情報管理装置２１０１と同じ装置であり、後続列車位置・速度２２１０の生成については、前記先行列車２１００の前記速度・位置検出部２１０５での説明と同じである。 The following train vehicle information management device 2201 generates the following train position and speed 2210 and outputs it to the automatic train operation device 2202. The following train vehicle information management device 2201 is the same device as the preceding train vehicle information management device 2101, and generation of the following train position/speed 2210 is explained in the speed/position detection unit 2105 of the preceding train 2100. is the same as

前記速度パターン計画部２２０４は、前記後続列車車両情報管理装置２２０１から取得する前記後続列車位置・速度２２１０を現在の位置および速度として、前記後続列車目標到着時刻２３１５を満たして前記次駅２５００に到着できるように駅間走行における目標速度パターン２２１１を計画する。当該計画の代表的な方法は、駅間走行のシミュレーションを用いて計画する方法である。その際には、前記データベース２２０５から取得する路線・車両・運行条件２２１２を考慮して、速度パターンの計画をする。ここで、路線条件の例としては、勾配、曲線、制限速度、トンネルおよび駅の位置情報などが挙げられる。車両条件の例としては、車両重量や出力可能な制駆動力の特性などが挙げられる。運行条件の例としては、運行種別や使用する番線情報などが挙げられる。前記目標速度パターン２２１１の表現方法としては、例えば、位置に応じた速度で表現する方法が挙げられる。 The speed pattern planning unit 2204 sets the following train position and speed 2210 acquired from the following train vehicle information management device 2201 as the current position and speed, and arrives at the next station 2500 satisfying the target arrival time 2315 of the following train. A target speed pattern 2211 for traveling between stations is planned so that the vehicle can travel between stations. A typical method for this planning is to use a simulation of running between stations. At that time, the speed pattern is planned in consideration of the routes, vehicles, and operation conditions 2212 acquired from the database 2205. Here, examples of route conditions include gradients, curves, speed limits, and location information of tunnels and stations. Examples of vehicle conditions include vehicle weight and characteristics of braking/driving force that can be output. Examples of operation conditions include operation type and line number information to be used. As a method of expressing the target speed pattern 2211, for example, a method of expressing the target speed pattern 2211 by a speed corresponding to a position can be mentioned.

前記制御指令生成部２２０６は、前記目標速度パターン２２１１に沿って前記後続列車２２００が走行できるように前記制駆動制御装置２２０３に対する制御指令２２１３を生成する。具体的な制御指令の生成例としては、前記後続列車位置・速度２２１０と前記目標速度パターン２２１１とを比較することによる速度偏差を入力として、当該速度偏差を減らすように比例制御で必要な制御指令を生成する方法が挙げられる。 The control command generation unit 2206 generates a control command 2213 to the braking/drive control device 2203 so that the following train 2200 can travel along the target speed pattern 2211. As a specific example of generation of a control command, a control command necessary for proportional control to reduce the speed deviation by inputting a speed deviation obtained by comparing the following train position/speed 2210 and the target speed pattern 2211 is given. One example is a method of generating .

前記制駆動制御装置２２０３は、受信した前記制御指令２２１３に基づいて、制動力または駆動力を出力させて前記後続列車２２００を走行させることになる。 The braking/driving control device 2203 causes the following train 2200 to run by outputting a braking force or a driving force based on the received control command 2213.

実施例２では、停車駅における先行列車の乗降時分と確認時分の両方を考慮した上で、当該停車駅への後続列車の目標到着時刻が設定され、前記後続列車の駅間運転がこの目標到着時刻を満たすように、運転士に対する運転操作の教示が行われることを特徴とする。 In Embodiment 2, the target arrival time of the following train at the stopping station is set, taking into consideration both the boarding and alighting time and confirmation time of the preceding train at the stopping station, and the inter-station operation of the following train is set based on this. It is characterized in that driving operations are taught to the driver so as to meet the target arrival time.

実施例２によれば、前記先行列車の駅停車時間として、乗降時分に加えて確認時分を考慮することで、前記先行列車の駅発車時刻の推定精度が向上し、それに伴う前記後続列車の目標到着時刻の設定が適切化される。これにより、運転士による前記後続列車の駅間運転において無駄な加減速が抑制され、省エネな運転が可能となる。 According to the second embodiment, by considering the confirmation time and minutes in addition to the boarding and alighting times as the station stopping time of the preceding train, the accuracy of estimating the station departure time of the preceding train is improved, and the following train accordingly The target arrival time is set appropriately. This suppresses unnecessary acceleration and deceleration during inter-station operation of the following train by the driver, allowing energy-saving operation.

実施例２に係る列車運転支援システムの全体構成については、図１に示す実施例１で説明したシステム構成と同じである。
図３は、実施例２に係る列車運転支援システムの内部構成と示す図である。各構成要素の動作態様を、図３を用いて説明する。 The overall configuration of the train driving support system according to the second embodiment is the same as the system configuration described in the first embodiment shown in FIG.
FIG. 3 is a diagram showing the internal configuration of the train driving support system according to the second embodiment. The operation mode of each component will be explained using FIG. 3.

前記先行列車２１００、前記運行管理装置２３００および前記駅人流監視装置２４００それぞれの各構成要素の動作態様は、実施例１における説明と同じである。
ただし、前記後続列車２２００において、実施例２に係る列車運転支援システムに関係する装置は、後続列車車両情報管理装置２２０１および運転支援装置３２０２である。前記運転支援装置３２０２は、速度パターン計画部２２０４、データベース２２０５および運転操作教示部３２０６を有する。 The operation mode of each component of the preceding train 2100, the operation management device 2300, and the station people flow monitoring device 2400 is the same as that described in the first embodiment.
However, in the following train 2200, the devices related to the train driving support system according to the second embodiment are the following train vehicle information management device 2201 and the driving support device 3202. The driving support device 3202 includes a speed pattern planning section 2204, a database 2205, and a driving operation teaching section 3206.

前記後続列車車両情報管理装置２２０１は、後続列車位置・速度２２１０を生成して、前記運転支援装置３２０２へ出力する。この生成方法については、実施例１における前記先行列車２１００の前記速度・位置検出部２１０５の説明と同じである。
また、前記速度パターン計画部２２０４の説明についても、実施例１における説明と同じである。 The following train vehicle information management device 2201 generates the following train position and speed 2210 and outputs it to the driving support device 3202. This generation method is the same as that described for the speed/position detection unit 2105 of the preceding train 2100 in the first embodiment.
Further, the explanation of the speed pattern planning section 2204 is also the same as that in the first embodiment.

前記運転操作教示部３２０６は、前記後続列車２２００が前記目標速度パターン２２１１に沿って走行できるように、運転士３２０３に対する操作教示内容３２１３を生成して出力する。前記操作教示内容３２１３の例としては、前記目標速度パターン２２１１に含まれる目標速度自体や、列車速度を前記目標速度パターン２２１１に近づけるための運転操作などが挙げられる。前記運転操作教示部３２０６による教示の例としては、前記運転士３２０３が目視する画面表示によって教示する方法や、音声鳴動によって教示する方法等が挙げられる。 The driving operation teaching section 3206 generates and outputs operation teaching contents 3213 for the driver 3203 so that the following train 2200 can travel along the target speed pattern 2211. Examples of the operation teaching content 3213 include the target speed itself included in the target speed pattern 2211, a driving operation for bringing the train speed closer to the target speed pattern 2211, and the like. Examples of the teaching by the driving operation teaching unit 3206 include a method of teaching using a screen display that the driver 3203 visually observes, a method of teaching using audio sound, and the like.

前記運転士３２０３は、前記操作教示内容３２１３に従って運転操作を行うことにより、前記後続列車２２００を走行させることになる。 The driver 3203 causes the following train 2200 to travel by performing a driving operation according to the operation instruction content 3213.

実施例３は、停車駅における先行列車の乗降時分と確認時分の両方を考慮した上で、前記先行列車の発車遅延予測が行われ、当該予測結果が駅員向けの端末表示を介して駅員に伝達されることを特徴とする。 In Embodiment 3, the departure delay of the preceding train is predicted by taking into consideration both the boarding and alighting times and confirmation times of the preceding train at the stopping station, and the prediction result is displayed on the station staff's terminal to inform the station staff. It is characterized by being transmitted to

実施例３によれば、前記先行列車の駅停車時間として、乗降時分に加えて確認時分を考慮することで、前記先行列車の駅発車時刻の推定精度が向上し、計画発車時刻からの遅れ有無の予測を精度よく駅員に提示することができる。その結果、前記先行列車の確認時分を短縮すべく、駅係員の配置や増員を適確に計画し、後続列車のスムーズな駅進入に寄与することで、前記後続列車の駅間自動運転における無駄な加減速が抑制され、省エネな運転が可能となる。 According to the third embodiment, by considering the confirmation time and minutes in addition to the boarding and alighting times as the stopping time of the preceding train, the accuracy of estimating the station departure time of the preceding train is improved, and it is possible to improve the estimation accuracy of the station departure time of the preceding train. Predictions of the presence or absence of delays can be presented to station staff with high accuracy. As a result, in order to shorten the time it takes to check the preceding train, we can accurately plan the allocation and increase of station staff, and contribute to the smooth entry of the following train into the station, thereby improving the automatic operation between stations of the following train. Unnecessary acceleration/deceleration is suppressed, enabling energy-saving operation.

図４は、実施例３に係る列車運転支援システムの全体構成を説明する図である。先行列車２１００は、運行管理装置５３００と無線で情報の送受信が可能な状態である。また、前記先行列車２１００は、自列車の位置、速度および乗車率を前記運行管理装置５３００へ送信する。次駅５５００は、駅人流監視装置２４００を備えている。 FIG. 4 is a diagram illustrating the overall configuration of a train driving support system according to the third embodiment. The preceding train 2100 is in a state where it can wirelessly transmit and receive information to and from the operation management device 5300. Further, the preceding train 2100 transmits the position, speed, and occupancy rate of its own train to the operation management device 5300. The next station 5500 is equipped with a station people flow monitoring device 2400.

前記駅人流監視装置２４００は、前記次駅５５００における前記先行列車２１００への乗車人数推定値を算出し、前記運行管理装置５３００へ無線または有線で送信する。前記駅人流監視装置２４００における乗車人数推定の方法としては、例えば、改札の通過人数計数結果や駅構内のカメラ画像分析結果を基にして推定する方法があるが、この方法に限定されるものではない。また、前記運行管理装置５３００から前記次駅５５００へは、無線または有線の通信によって発車遅延予測情報が送信される。 The station passenger flow monitoring device 2400 calculates the estimated number of passengers on the preceding train 2100 at the next station 5500, and transmits it to the operation management device 5300 wirelessly or by wire. As a method for estimating the number of passengers in the station passenger flow monitoring device 2400, for example, there is a method of estimating based on the result of counting the number of people passing through the ticket gate or the result of analyzing camera images in the station premises, but the method is not limited to this method. do not have. Further, departure delay prediction information is transmitted from the operation management device 5300 to the next station 5500 by wireless or wired communication.

図５は、実施例３に係る列車運転支援システムの内部構成を示す図である。各構成要素の動作態様を、図５を用いて説明する。
前記先行列車２１００および前記駅人流監視装置２４００の各構成要素の動作態様は、実施例１における説明と同じである。 FIG. 5 is a diagram showing the internal configuration of the train driving support system according to the third embodiment. The operation mode of each component will be explained using FIG. 5.
The operation mode of each component of the preceding train 2100 and the station people flow monitoring device 2400 is the same as that described in the first embodiment.

前記運行管理装置５３００は、前記先行列車２１００からの前記空気ばね内圧２１１２と前記乗車率２１１４、および、前記駅人流監視装置２４００からの前記乗車人数推定値２４１１を基にして、発車遅延有無予測結果５３１６を生成し、次駅５５００に送信する。ここで、前記運行管理装置５３００は、ダイヤ管理部２３０１、乗降人数推定部２３０２、駅停車時間推定部２３０３および先行列車発車遅延予測部５３０６から構成される。前記駅停車時間推定部２３０３は、乗降時分推定部２３０４および確認時分推定部２３０５を有する。 The operation management device 5300 predicts the presence or absence of a departure delay based on the air spring internal pressure 2112 and the occupancy rate 2114 from the preceding train 2100, and the estimated number of passengers 2411 from the station passenger flow monitoring device 2400. 5316 and transmits it to the next station 5500. Here, the operation management device 5300 includes a timetable management section 2301, a boarding/alighting number estimating section 2302, a station stop time estimating section 2303, and a preceding train departure delay predicting section 5306. The station stop time estimating section 2303 includes a boarding/alighting time estimating section 2304 and a confirmation time estimating section 2305.

前記ダイヤ管理部２３０１、前記乗降人数推定部２３０２および前記駅停車時間推定部２３０３それぞれの動作態様は、実施例１における説明と同じである。 The operating modes of the timetable management section 2301, the number of passengers estimating section 2302, and the station stop time estimating section 2303 are the same as those described in the first embodiment.

前記先行列車発車遅延予測部５３０６は、前記先行列車予定発着時刻２３１０、前記乗降時分推定値２３１２および前記確認時分推定値２３１３を基にして、前記発車遅延有無予測結果５３１６を生成する。具体的には、前記先行列車の予定到着時刻に対して必要な駅停車時間を加えた時刻を算出し、算出した時刻が予定発車時刻と比べて所定閾値時間以上遅い場合には、前記発車遅延有無予測結果５３１６を「遅延予測あり」とする。ここで、必要な駅停車時間は、前記乗降時分推定値２３１２と前記確認時分推定値２３１３とから求める時間である。編成内の乗降時分推定値と確認時分推定値の中で、それぞれ最も大きい値の和を前記必要な駅停車時間とする。 The preceding train departure delay prediction unit 5306 generates the departure delay prediction result 5316 based on the preceding train scheduled departure and arrival time 2310, the estimated boarding and alighting time 2312, and the estimated confirmed time 2313. Specifically, the time is calculated by adding the required station stop time to the scheduled arrival time of the preceding train, and if the calculated time is later than the scheduled departure time by more than a predetermined threshold time, the departure delay is determined. The presence/absence prediction result 5316 is set to "delay prediction". Here, the required station stopping time is the time calculated from the boarding/alighting time estimated value 2312 and the confirmation time/minute estimated value 2313. The sum of the largest values of the estimated boarding and alighting times and estimated confirmation times in the train set is the required station stop time.

前記次駅５５００は、駅員向け端末装置５５０１を備えている。前記駅員向け端末装置５５０１は、前記発車遅延有無予測結果５３１６を前記運行管理装置５３００から受信し、前記発車遅延有無予測結果５３１６が「遅延予測あり」の場合に、その旨を駅員５５０２に報知する。前記駅員５５０２は当該報知を受けて、前記先行列車２１００の確認時分を短縮すべく、駅係員の配置や増員を計画する。 The next station 5500 is equipped with a terminal device 5501 for station staff. The terminal device 5501 for station staff receives the train departure delay prediction result 5316 from the operation management device 5300, and when the train departure delay prediction result 5316 is “delay predicted”, it notifies the station staff 5502 to that effect. . Upon receiving the notification, the station staff 5502 plans the allocation or increase of station staff in order to shorten the time required to confirm the preceding train 2100.

これによって、遅延予測ありの報知が無く前記先行列車２１００の発車が計画から遅れた場合と比較して、前記後続列車２２００が前記次駅５５００へ進入する時に、機外停止や計画外の減速を強いられる可能性を低減できる。その結果、前記先行列車２１００自体の定時運行と前記後続列車２２００の省エネな運行に寄与できる。 As a result, when the following train 2200 approaches the next station 5500, external stops and unplanned decelerations are prevented, compared to a case where the departure of the preceding train 2100 is delayed as planned without notification of a predicted delay. It can reduce the possibility of being forced. As a result, it is possible to contribute to the on-time operation of the preceding train 2100 itself and the energy-saving operation of the following train 2200.

また、本発明は、以上の各実施例に限定されるものではなく、本発明の要旨を逸脱しない範囲において種々の変更が可能である。 Further, the present invention is not limited to the above embodiments, and various modifications can be made without departing from the gist of the present invention.

２１００…先行列車、２１０１…先行列車車両情報管理装置、２１０２…ドア制御器、
２１０３…速度発電機、２１０４…ブレーキ制御装置、２１０５…速度・位置検出部、
２１０６…乗車率算出部、２１１０…ドア開情報、２１１１…パルス情報、
２１１２…空気ばね内圧、２１１３…先行列車速度・位置、２１１４…乗車率、
２２００…後続列車、２２０１…後続列車車両情報管理装置、
２２０２…自動列車運転装置、２２０３…制駆動制御装置、
２２０４…速度パターン計画部、２２０５…データベース、２２０６…制御指令生成部、
２２１０…後続列車位置・速度、２２１１…目標速度パターン、
２２１２…路線・車両・運行条件、２２１３…制御指令、
２３００、５３００…運行管理装置、２３０１…ダイヤ管理部、
２３０２…乗降人数推定部、２３０３…駅停車時間推定部、２３０４…乗降時分推定部、２３０５…確認時分推定部、２３０６…先行列車発車時刻推定部、
２３０７…後続列車目標到着時刻設定部、２３１０…先行列車予定発着時刻、
２３１１…乗降人数推定値、２３１２…乗降時分推定値、２３１３…確認時分推定値、
２３１４…先行列車発車時刻推定値、２３１５…後続列車目標到着時刻、
２４００…駅人流監視装置、２４０１…乗車人数推定部、２４１１…乗車人数推定値、
２５００、５５００…次駅、３２０２…運転支援装置、３２０３…運転士、
３２０６…運転操作教示部、３２１３…操作教示内容、
５３０６…先行列車発車遅延予測部、５３１６…発車遅延有無予測結果、
５５０１…駅員向け端末装置、５５０２…駅員、５５１１…発車遅延予測情報 2100... Preceding train, 2101... Preceding train vehicle information management device, 2102... Door controller,
2103...Speed generator, 2104...Brake control device, 2105...Speed/position detection unit,
2106...Occupancy rate calculation unit, 2110...Door opening information, 2111...Pulse information,
2112...Air spring internal pressure, 2113...Preceding train speed/position, 2114...occupancy rate,
2200...Following train, 2201...Following train vehicle information management device,
2202... Automatic train driving device, 2203... Braking and driving control device,
2204... Speed pattern planning unit, 2205... Database, 2206... Control command generation unit,
2210...Following train position/speed, 2211...Target speed pattern,
2212...Route/vehicle/operating conditions, 2213...Control commands,
2300, 5300... Traffic management device, 2301... Timetable management department,
2302... Estimating the number of people getting on and off, 2303... Station stop time estimating section, 2304... Getting on and off time estimating section, 2305... Confirmation time estimating section, 2306... Preceding train departure time estimating section,
2307...Following train target arrival time setting section, 2310...Preceding train scheduled departure and arrival time,
2311... Estimated number of people boarding and alighting, 2312... Estimated boarding and alighting time, 2313... Estimated confirmation time,
2314...Preceding train departure time estimated value, 2315...Following train target arrival time,
2400...Station passenger flow monitoring device, 2401...Passenger number estimation unit, 2411...Passenger number estimated value,
2500, 5500...Next station, 3202...Driving support device, 3203...Driver,
3206... Driving operation teaching section, 3213... Operation teaching content,
5306... Preceding train departure delay prediction unit, 5316... Departure delay presence/absence prediction result,
5501...Terminal device for station staff, 5502...Station staff, 5511...Departure delay prediction information

Claims (12)

先行列車が停車駅で乗降を開始する前のタイミングで、前記先行列車の前記停車駅での乗降人数推定値を算出する乗降人数推定部と、
車両定員に占める乗車人数の割合を乗車率として、前記先行列車が前記停車駅で乗降を開始する前に測定された前記先行列車の第１の乗車率と、前記乗降人数推定値とを基にして、前記先行列車の前記停車駅での駅停車時間推定値を算出する駅停車時間推定部と、
前記駅停車時間推定値と前記先行列車の前記停車駅での予定発着時刻とを基にして、前記先行列車の前記停車駅での発車時刻推定値を算出する先行列車発車時刻推定部と、
前記発車時刻推定値に基づいて後続列車の前記停車駅への目標到着時刻を設定する後続列車目標到着時刻設定部と、
前記後続列車が前記目標到着時刻を満足するための前記停車駅に至る駅間走行パターンを設定する後続列車駅間走行パターン設定部と
を備え、
前記駅停車時間推定部は、前記乗降人数推定値および前記第１の乗車率に基づく乗降時分推定値と、前記先行列車の前記停車駅での乗降終了後の乗車率である第２の乗車率に基づく確認時分推定値との和を、前記駅停車時間推定値として算出する
ことを特徴とする列車運転支援システム。 a number of passengers estimating the number of people getting on and off at the stop station of the preceding train at a timing before the preceding train starts boarding and alighting at the stop station;
Based on the first occupancy rate of the preceding train measured before the preceding train starts boarding and alighting at the stop station and the estimated value of the number of passengers getting on and off, the ratio of the number of passengers to the vehicle capacity is taken as the occupancy rate. a station stop time estimation unit that calculates an estimated station stop time at the stop station of the preceding train;
a preceding train departure time estimation unit that calculates an estimated departure time of the preceding train at the stopping station based on the estimated station stop time and the scheduled departure and arrival time of the preceding train at the stopping station;
a subsequent train target arrival time setting unit that sets a target arrival time of the subsequent train at the stop station based on the estimated departure time;
a subsequent train station-to-station travel pattern setting unit that sets an inter-station travel pattern for the subsequent train to reach the stop station so that the subsequent train satisfies the target arrival time;
The station stop time estimating unit calculates the estimated boarding and alighting time based on the estimated number of passengers and the first occupancy rate, and a second boarding rate that is the occupancy rate after the boarding and alighting of the preceding train at the stop station. A train driving support system characterized in that the sum of a confirmation time and minute estimated value based on a rate is calculated as the station stop time estimated value. 請求項１に記載の列車運転支援システムであって、
前記先行列車発車時刻推定部は、前記先行列車の予定到着時刻に前記乗降時分推定値および前記確認時分推定値を加えた時刻と、前記先行列車の予定発車時刻とを比較し、より遅い方の時刻を前記発車時刻推定値として出力する
ことを特徴とする列車運転支援システム。 The train driving support system according to claim 1,
The preceding train departure time estimating unit compares the scheduled arrival time of the preceding train with the estimated boarding and alighting time and the estimated confirmation time and the scheduled departure time of the preceding train, and determines whether the scheduled departure time of the preceding train is later. A train driving support system characterized in that the train driving support system outputs the time of the train as the estimated departure time. 請求項１または２に記載の列車運転支援システムであって、
前記後続列車駅間走行パターン設定部で設定される前記駅間走行パターンに沿って、前記後続列車が搭載する制駆動制御装置に対して制動または駆動に関する制御指令を出力する
ことを特徴とする列車運転支援システム。 The train driving support system according to claim 1 or 2,
A train characterized in that a control command regarding braking or driving is output to a braking/driving control device mounted on the following train in accordance with the inter-station traveling pattern set by the following train inter-station traveling pattern setting unit. Driving assistance system. 請求項１または２に記載の列車運転支援システムであって、
前記後続列車駅間走行パターン設定部で設定される前記駅間走行パターンに沿って、前記後続列車を手動運転するための運転操作を教示する
ことを特徴とする列車運転支援システム。 The train driving support system according to claim 1 or 2,
A train driving support system characterized by teaching driving operations for manually driving the following train in accordance with the inter-station traveling pattern set by the following train inter-station traveling pattern setting unit. 先行列車が停車駅で乗降を開始する前のタイミングで、前記先行列車の前記停車駅での乗降人数推定値を算出する乗降人数推定部と、
車両定員に占める乗車人数の割合を乗車率として、前記先行列車が前記停車駅で乗降を開始する前に測定された前記先行列車の第１の乗車率と、前記乗降人数推定値とを基にして、前記先行列車の前記停車駅での駅停車時間推定値を算出する駅停車時間推定部と、
前記駅停車時間推定値と前記先行列車の前記停車駅での予定発着時刻とを基にして、前記先行列車の前記停車駅での発車遅延有無を予測する先行列車発車遅延予測部と
を備え、
前記駅停車時間推定部は、前記乗降人数推定値および前記第１の乗車率に基づく乗降時分推定値と、前記先行列車の前記停車駅での乗降終了後の乗車率である第２の乗車率に基づく確認時分推定値との和を、前記駅停車時間推定値として算出する
ことを特徴とする列車運転支援システム。 a number of passengers estimating the number of people getting on and off at the stop station of the preceding train at a timing before the preceding train starts boarding and alighting at the stop station;
Based on the first occupancy rate of the preceding train measured before the preceding train starts boarding and alighting at the stop station and the estimated value of the number of passengers getting on and off, the ratio of the number of passengers to the vehicle capacity is taken as the occupancy rate. a station stop time estimation unit that calculates an estimated station stop time at the stop station of the preceding train;
a preceding train departure delay prediction unit that predicts whether or not there will be a departure delay of the preceding train at the stopping station, based on the estimated station stop time and the scheduled departure and arrival time at the stopping station of the preceding train;
The station stop time estimating unit calculates the estimated boarding and alighting time based on the estimated number of passengers and the first occupancy rate, and a second boarding rate that is the occupancy rate after the boarding and alighting of the preceding train at the stop station. A train driving support system characterized in that the sum of a confirmation time and minute estimated value based on a rate is calculated as the station stop time estimated value. 請求項５に記載の列車運転支援システムであって、
前記先行列車発車遅延予測部は、前記先行列車の予定到着時刻に前記乗降時分推定値および前記確認時分推定値を加えた出発準備終了予想時刻と、前記先行列車の予定発車時刻とを比較し、前記出発準備終了予想時刻が前記予定発車時刻よりも遅い場合に、前記先行列車の発車遅延有りの予測結果を出力する
ことを特徴とする列車運転支援システム。 The train driving support system according to claim 5,
The preceding train departure delay prediction unit compares the expected departure preparation end time obtained by adding the estimated boarding and alighting time and the estimated confirmation time to the scheduled arrival time of the preceding train, and the scheduled departure time of the preceding train. The train driving support system is characterized in that, when the expected departure preparation end time is later than the scheduled departure time, a prediction result indicating that the preceding train will be delayed in departure is output. 請求項５または６に記載の列車運転支援システムであって、
前記停車駅に端末装置を更に備え、
前記端末装置は、前記先行列車発車遅延予測部の予測結果に基づく前記停車駅での発車遅延予測情報を提示する
ことを特徴とする列車運転支援システム。 The train driving support system according to claim 5 or 6,
further comprising a terminal device at the stop station,
The train driving support system is characterized in that the terminal device presents departure delay prediction information at the stop station based on the prediction result of the preceding train departure delay prediction unit. 請求項１から７のいずれか１項に記載の列車運転支援システムであって、
前記第１の乗車率は、前記先行列車が搭載する機器で測定され、前記駅停車時間推定部へ送信される
ことを特徴とする列車運転支援システム。 The train driving support system according to any one of claims 1 to 7,
The train driving support system, wherein the first occupancy rate is measured by a device mounted on the preceding train and transmitted to the station stop time estimating unit. 請求項１から８のいずれか１項に記載の列車運転支援システムであって、
前記第２の乗車率は、前記第１の乗車率と前記乗降人数推定値とを用いて算出される
ことを特徴とする列車運転支援システム。 The train driving support system according to any one of claims 1 to 8,
The train driving support system, wherein the second occupancy rate is calculated using the first occupancy rate and the estimated number of passengers getting on and off the train. 請求項１から９のいずれか１項に記載の列車運転支援システムであって、
前記停車駅に駅人流監視装置を更に備え、
前記乗降人数推定部は、前記駅人流監視装置が取得する乗車人数推定値、前記第１の乗車率および統計的に事前集計された前記停車駅の降車人数傾向に基づいて、前記乗降人数推定値を算出する
ことを特徴とする列車運転支援システム。 The train driving support system according to any one of claims 1 to 9,
The stop station is further equipped with a station people flow monitoring device,
The number of people getting on and off the train is configured to estimate the number of people getting on and off the train based on the estimated number of people getting on and off the train acquired by the station people flow monitoring device, the first occupancy rate, and the trend of the number of people getting on and off at the stop station that is statistically pre-compiled. A train driving support system that calculates the following: 請求項１から１０のいずれか１項に記載の列車運転支援システムであって、
前記第２の乗車率が所定の閾値以下の場合、前記確認時分推定値は一定であり、前記第２の乗車率が所定の閾値より大きい場合、前記第２の乗車率が大きいほど前記確認時分推定値も大きくなる
ことを特徴とする列車運転支援システム。 The train driving support system according to any one of claims 1 to 10,
When the second occupancy rate is less than or equal to a predetermined threshold, the confirmation time estimate is constant, and when the second occupancy rate is greater than the predetermined threshold, the larger the second occupancy rate is, the more the confirmation time is fixed. A train driving support system characterized by increasing the estimated time and minute values. 先行列車が停車駅で乗降を開始する前のタイミングで前記先行列車の前記停車駅での乗降人数推定値を算出する乗降人数推定ステップと、
車両定員に占める乗車人数の割合を乗車率として、前記先行列車が前記停車駅で乗降を開始する前に測定された前記先行列車の第１の乗車率と、前記乗降人数推定値とを基にして、前記先行列車の前記停車駅での駅停車時間推定値を算出する駅停車時間推定ステップと、
前記駅停車時間推定値と前記先行列車の前記停車駅での予定発着時刻とを基にして、前記先行列車の前記停車駅での発車時刻推定値を算出する先行列車発車時刻推定ステップと、
前記発車時刻推定値に基づいて後続列車の前記停車駅への目標到着時刻を設定する後続列車目標到着時刻設定ステップと、
前記後続列車が前記目標到着時刻を満足するための前記停車駅に至る駅間走行パターンを設定する後続列車駅間走行パターン設定ステップと
を有し、
前記駅停車時間推定ステップは、前記乗降人数推定値および前記第１の乗車率に基づいて乗降時分を推定するステップと、前記先行列車の前記停車駅での乗降終了後の乗車率である第２の乗車率に基づく確認時分を推定するステップと、推定した前記乗降時分の値と推定した前記確認時分の値との和を求めて前記駅停車時間推定値として算出するステップとから成る
ことを特徴とする列車運転支援方法。 a step of estimating the number of people getting on and off at the stop station of the preceding train at a timing before the preceding train starts getting on and off at the stop station;
Based on the first occupancy rate of the preceding train measured before the preceding train starts boarding and alighting at the stop station and the estimated value of the number of passengers getting on and off, the ratio of the number of passengers to the vehicle capacity is taken as the occupancy rate. a station stop time estimating step of calculating an estimated value of the station stop time at the stop station of the preceding train;
a preceding train departure time estimating step of calculating an estimated departure time of the preceding train at the stopping station based on the estimated station stop time and the scheduled departure and arrival time of the preceding train at the stopping station;
a subsequent train target arrival time setting step of setting a target arrival time of the following train at the stop station based on the estimated departure time;
a subsequent train inter-station travel pattern setting step of setting an inter-station travel pattern for the subsequent train to reach the stop station so that the subsequent train satisfies the target arrival time;
The station stop time estimating step includes a step of estimating the boarding and alighting time based on the estimated number of people getting on and off and the first occupancy rate, and a step of estimating the boarding and alighting time based on the estimated number of people getting on and off and the first occupancy rate; 2, estimating the confirmation time based on the occupancy rate, and calculating the sum of the estimated value of the boarding and alighting time and the estimated value of the confirmation time to calculate the estimated value of the station stop time. A train driving support method characterized by:
JP2020147389A 2020-09-02 2020-09-02 Train driving support system and train driving support method Active JP7366866B2 (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
JP2020147389A JP7366866B2 (en) 2020-09-02 2020-09-02 Train driving support system and train driving support method

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
JP2020147389A JP7366866B2 (en) 2020-09-02 2020-09-02 Train driving support system and train driving support method

Publications (2)

Publication Number Publication Date
JP2022042138A JP2022042138A (en) 2022-03-14
JP7366866B2 true JP7366866B2 (en) 2023-10-23

Family

ID=80629430

Family Applications (1)

Application Number Title Priority Date Filing Date
JP2020147389A Active JP7366866B2 (en) 2020-09-02 2020-09-02 Train driving support system and train driving support method

Country Status (1)

Country Link
JP (1) JP7366866B2 (en)

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002037076A (en) 2000-07-27 2002-02-06 Kawasaki Heavy Ind Ltd Method and device for simulating train operation
JP2008189180A (en) 2007-02-06 2008-08-21 Mitsubishi Electric Corp Train operation management system
JP2014144754A (en) 2013-01-30 2014-08-14 Mitsubishi Electric Corp Railway train control system and automatic railway train driving device
JP2015107687A (en) 2013-12-03 2015-06-11 株式会社東芝 Train operation control device, control method, and control program
JP2015182623A (en) 2014-03-25 2015-10-22 株式会社日立製作所 Automatic train operation system, train operation support system, and train service management system
WO2017168585A1 (en) 2016-03-29 2017-10-05 三菱電機株式会社 Train traffic control system and train traffic control method
JP2020137227A (en) 2019-02-18 2020-08-31 株式会社東芝 Train control device, and train control system and method

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2002037076A (en) 2000-07-27 2002-02-06 Kawasaki Heavy Ind Ltd Method and device for simulating train operation
JP2008189180A (en) 2007-02-06 2008-08-21 Mitsubishi Electric Corp Train operation management system
JP2014144754A (en) 2013-01-30 2014-08-14 Mitsubishi Electric Corp Railway train control system and automatic railway train driving device
JP2015107687A (en) 2013-12-03 2015-06-11 株式会社東芝 Train operation control device, control method, and control program
JP2015182623A (en) 2014-03-25 2015-10-22 株式会社日立製作所 Automatic train operation system, train operation support system, and train service management system
WO2017168585A1 (en) 2016-03-29 2017-10-05 三菱電機株式会社 Train traffic control system and train traffic control method
JP2020137227A (en) 2019-02-18 2020-08-31 株式会社東芝 Train control device, and train control system and method

Also Published As

Publication number Publication date
JP2022042138A (en) 2022-03-14

Similar Documents

Publication Publication Date Title
US8774992B2 (en) Operation support device and automatic operation device
US8751073B2 (en) Method and apparatus for optimizing a train trip using signal information
EP3437957B1 (en) Train traffic control system and train traffic control method
JP6141035B2 (en) Train control system and automatic train operation device
EP2923913B1 (en) Automatic train operation system
US9150209B2 (en) System and method for monitoring braking effort
US20070233335A1 (en) Method and apparatus for optimizing railroad train operation for a train including multiple distributed-power locomotives
JP5930846B2 (en) Vehicle system
Al-Mudhaffar et al. Bus stop and bus terminal capacity
WO2019013852A1 (en) Method and system for monitoring and evaluating a performance of a driver of a vehicle
WO2008073546A2 (en) Method and apparatus for optimizing railroad train operation for a train including multiple distributed-power locomotives
CN111401643B (en) Urban rail transit passenger flow loop self-adaptive intelligent train scheduling method
CN113184024B (en) Tramcar-oriented arrival time static prediction method and system
JP7366866B2 (en) Train driving support system and train driving support method
JPH11192948A (en) Railway control device
Zieger et al. Opportunities and challenges for the demand-responsive transport using highly automated and autonomous rail units in rural areas
JP4448363B2 (en) Train operation management system
JP2019089449A (en) Device, method and program for train travel control
JP7179576B2 (en) Operation control device, operation control system and operation control method
CN113572805A (en) Subway rail transit passenger flow monitoring system and method based on weighing data
Xun et al. An optimization approach for real-time headway control of railway traffic
KR20210066816A (en) Methods for Governing Multimode Transport Networks
JP7467241B2 (en) Train Operation System
AU2016202936B2 (en) Method and apparatus for optimizing railroad train operation for a train including multiple distributed-power locomotives
Hafezi et al. Bus scheduling model: a literature review

Legal Events

Date Code Title Description
A621 Written request for application examination

Free format text: JAPANESE INTERMEDIATE CODE: A621

Effective date: 20230303

TRDD Decision of grant or rejection written
A977 Report on retrieval

Free format text: JAPANESE INTERMEDIATE CODE: A971007

Effective date: 20230929

A01 Written decision to grant a patent or to grant a registration (utility model)

Free format text: JAPANESE INTERMEDIATE CODE: A01

Effective date: 20231003

A61 First payment of annual fees (during grant procedure)

Free format text: JAPANESE INTERMEDIATE CODE: A61

Effective date: 20231011

R150 Certificate of patent or registration of utility model

Ref document number: 7366866

Country of ref document: JP

Free format text: JAPANESE INTERMEDIATE CODE: R150