TWI615816B - Mixed traffic flow control method - Google Patents
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本發明有關於一種交通號誌控制方法，特別是關於一種綜合考慮幹道車流的續進效率以及系統整體延遲的混合車流交通號誌控制方法。 The invention relates to a traffic signal control method, in particular to a hybrid traffic flow control method for comprehensively considering the continuous flow efficiency of the trunk traffic and the overall delay of the system.
都市中，各幹道的交叉路口是路網中最重要的環節，由於來自不同方向的車流將匯集在路口進行穿越、併入與分出等行為，因而在路口將產生各種潛在的衝突點；而為了消除路口的衝突、提升交通運輸效率以及增進道路的使用容量，交通工程人員需藉由號誌系統的交互更替來進行路權與時間的分配，以管制並引導車流行進。 In the metropolis, the intersection of the main roads is the most important link in the road network. Since the traffic from different directions will be collected at the intersection for crossing, incorporation and separation, various potential conflict points will be generated at the intersection; In order to eliminate conflicts at intersections, improve transportation efficiency, and increase the use capacity of roads, traffic engineers need to use the interaction of the number system to distribute the right and time to control and guide the car.
近年來，隨著科技的發展，交通號誌控制的策略已由原先的離線運算，進步到長短時段的彈性應變、觸動時相、以及動態查表等等技術；且號誌控制器更由原本只能儲存少數時制的機電式系統，進步為可儲存多種時制並依照道路交通需求來動態調整時制的微電腦控制器，關於這些號誌的控制，得要蒐集大量的路網偵測資料並進行動態運算，才能發展出即時的控制策略，進而因應路口需求。 In recent years, with the development of science and technology, the strategy of traffic signal control has been improved from the original offline operation to the elastic strain, the touch phase, and the dynamic look-up table for a long period of time; It can only store a few time-based electromechanical systems, and it is a microcomputer controller that can store multiple time systems and dynamically adjust the time system according to road traffic requirements. For the control of these signals, it is necessary to collect a large number of road network detection data and carry out dynamics. In order to develop an immediate control strategy, we can respond to the needs of intersections.
而號誌的控制系統是否能良好地發揮功能，主要係取決於時制計畫的設計，時制計畫包含有時相順序、每一 時相黃燈與全紅時段的規劃、週期長度的決定以及各時相有效的綠燈分配等，其中任何一部份考慮不周，就可能發生道路擁塞或路網癱瘓等情形。 Whether the control system of the slogan can function well depends mainly on the design of the time plan, and the time plan includes sometimes the order, each The planning of the phase yellow light and the full red period, the determination of the length of the period, and the effective green light distribution of each phase, etc., in which any part of the consideration is not well considered, road congestion or road network shackles may occur.
關於號誌時制的最佳化模式，已存在許多相關的研究或先前技術，包括獨立路口號誌設計、幹道續進問題、路網車流量指派等；而歷來的定時號誌控制系統皆著眼於兩大目標，其中一者為最大化續進帶寬，其優點為需要的資訊量較小，基本需要的只有道路幾何、旅行速率、綠燈時比等等，亦較符合大眾運輸的需求，因為許多的駕駛者都期望道路號誌續進能夠順暢，並以此作為觀察交通品質的基準。 Regarding the optimization model of the time system, there have been many related researches or prior technologies, including independent road number design, trunk road renewal, road network traffic assignment, etc. The traditional timing control system is focused on Two of the two goals, one of which is to maximize the continuous bandwidth, the advantage is that the amount of information required is small, the basic needs are only road geometry, travel speed, green light ratio, etc., and also meet the needs of mass transportation, because many Drivers expect the road number to continue smoothly and as a benchmark for observing traffic quality.
許多先前的研究(如Wagner、Gerlough & Bernes,1969)和實務經驗皆顯示帶寬系統係為相當有效的實用技術；其中，MAXBAND(Little,Kelton,and Gartner,1966&1981)為一續進帶寬的著名研究，其採用混合整數規劃法，可用於解決全域最佳時差、分時、週期長度、續進速率、左轉時相順序、以及幹道雙向帶寬權重等等交通問題，而此研究之模式亦被改良應用於相鄰多幹道路網之研究(Chang等人，1988)，而由於美國聯邦公路局自1980年代起積極於多個都會區推動交通號誌系統最佳化計畫，TRANSYT模式的引進與改良和SIGOP模式的發展等等遂應運而生。 Many previous studies (such as Wagner, Gerlough & Bernes, 1969) and practical experience have shown that bandwidth systems are quite effective practical techniques; among them, MAXBAND (Little, Kelton, and Gartner, 1966 & 1981) is a well-known study of the continuation bandwidth. It adopts mixed integer programming method, which can be used to solve the traffic problems such as the best time difference, time division, period length, continuation rate, left turn phase sequence, and trunk two-way bandwidth weight, etc., and the research mode is improved. Applied to the study of adjacent multi-dry road networks (Chang et al., 1988), and since the United States Federal Highway Administration has been active in multiple metropolitan areas since the 1980s to promote traffic signage system optimization programs, the introduction of the TRANSYT model and Improvements and the development of the SIGOP model have emerged.
即使TRANSYT-7F模式在降低道路擁擠與旅行時間上有相當成效，但基於今日都市的迅速疏散幹道尖峰車流之訴求下，許多交通管理者對其模式目標函數處理主幹道交通的能力仍嫌不足，咸認有加入號誌續進策略的必要；故近期延伸續進帶寬模式並以最大化續進帶寬為號誌時制求解目標的研究包含有：Gao(2008)、Peifeng(2011)、Xianyu(2012) 以及Yang(2014)等等。 Even though the TRANSYT-7F model has achieved considerable success in reducing road congestion and travel time, many traffic managers are still under-represented in their ability to handle trunk road traffic based on the rapid evacuation of peak traffic in today's cities. It is necessary to join the number continuation strategy; therefore, the recent study of extending the bandwidth mode and maximizing the continuous bandwidth as the ambition to solve the target includes: Gao (2008), Peifeng (2011), Xianyu (2012) ) And Yang (2014) and so on.
而歷來的定時號誌控制系統的另一大目標係為最小化交通的延誤、停等數及其他負面效果，其研究諸如Hillier(1966)、SIGOP(Traffic Research Corp.1966)、TRANSYT(Robertson,1969)、MITRAP(Gartner,Little與Gabbay,1975)、SIGOP-II(Liebertson與Woo,1976)等等；另外，Gao&Tian(2008)更認為求算號誌時制最佳解時，應考慮OD車流型態，因其研究之模擬結果顯示不同OD型態在相同號控時制下，將產生不同的績效。 Another major goal of the traditional timing control system is to minimize traffic delays, stop numbers, and other negative effects, such as Hillier (1966), SIGOP (Traffic Research Corp. 1966), and TRANSYT (Robertson, 1969), MITRAP (Gartner, Little and Gabbay, 1975), SIGOP-II (Liebertson and Woo, 1976), etc.; in addition, Gao & Tian (2008) thinks that the OD traffic type should be considered when seeking the best solution for the time system. State, because the simulation results of its research show that different OD types will produce different performance under the same number control time system.
除此之外，多目標演化演算法也常被用在交通號誌的規劃上，如Sun et al.(2003)、Abbas et al.(2007)、及Branke et al.(2007)等等研究，都是基於多目標演化演算法的觀念來計算交通號誌時制的設定。 In addition, multi-objective evolution algorithms are often used in the planning of traffic signs, such as Sun et al. (2003), Abbas et al. (2007), and Branke et al. (2007). It is based on the concept of multi-objective evolution algorithm to calculate the setting of traffic semaphore time system.
然而，比較上述各種研究，最大帶寬解的績效將較最小延誤解為佳，尤其是在高幹道交通量之前提下。 However, comparing the above various studies, the performance of the maximum bandwidth solution will be better than the minimum delay, especially before the high-traffic traffic volume.
檢視過去的這些交通號誌時制規劃的研究，其大多在求解單一目標的號誌設置問題，但若考慮兩種或兩種以上相互影響之交通管理目標，其研究與技術則是相對缺乏，因此，可知本領域亟需發展一套有能力處理交通路網的多重管理號控方法，本發明即是著眼於提高幹道車流的續進效率以及考慮系統整體延遲的目標來研發的。 Examining the past studies of these traffic chronographs, most of them are solving the problem of setting a single goal. However, if two or more traffic management objectives are considered, the research and technology are relatively lacking. It can be seen that there is an urgent need in the art to develop a multi-management number control method capable of handling traffic road networks. The present invention is developed with the aim of improving the continuation efficiency of trunk traffic and considering the overall delay of the system.
本發明混合車流交通號誌控制方法之步驟流程如下所示，主要係透過一分析伺服器執行至少包含下述步驟。 The flow of the steps of the hybrid traffic flow control method of the present invention is as follows, and is mainly performed by an analysis server to include at least the following steps.
步驟一，首先，以一幹道沿線包含有各路口為整體系統，透過交通工程中常用的CLV(Critical Lane Volume)演算法，以快速計算出該幹到上各路口的起始週期及綠燈時比。 In the first step, firstly, a road along the main road is included as a whole system, and the CLV (Critical Lane Volume) algorithm commonly used in traffic engineering is used to quickly calculate the starting period and the green time ratio of the dry to upper intersections. .
步驟二，在獲得各路口的起始週期與綠燈時比後，利用一第一區域搜尋法對起始週期相對較大的路口進行區域搜尋。 In the second step, after obtaining the initial period of each intersection and the green light time, a first area search method is used to perform area search on the intersection with a relatively large initial period.
其中，該第一區域搜尋法至少包含以下步驟：首先，判斷各路口的起始週期是否大於一週期門檻值，其中，週期門檻值可設為各路口初始的最大週期時間再減去各路口初始的週期時間標準差之值，僅有大於該週期門檻值之路口該分析伺服器才會對其進行區域搜尋，針對各個路口，在從其第一個時相開始進行區域搜尋前，須先判斷當前路口的週期時間是否已逾最大週期限制，其中，最大週期限制為各路口初始的最大週期時間；若已達最大週期限制，代表搜尋方向僅能朝降低綠燈時比方向前進，然而，路口的綠燈時比亦存在著最小綠燈限制，倘若調降綠燈時比後綠燈時比不低於最小綠燈限制，才能降低綠燈時比，反之，則代表無法對目前的該時相做改變，此時，可對其設定一個Flag1使其值等於1，設定的此Flag1將可避免分析伺服器對其執行不必要之模擬。若週期時間小於最大週期限制，則會以該時相的gRQ n,p 狀態做為是否要使用動態步幅的依據，其中，gRQ n,p 係代表在n路口的p時相中，完全紓解停等車隊的時間長度佔該時相總長度之百分比，其即表示了該路口的該時相在現行解的狀態下，對於路燈時間的渴望程度。 The first area search method includes at least the following steps: First, it is determined whether the initial period of each intersection is greater than a threshold value, wherein the threshold value can be set as the initial maximum period time of each intersection and then the initial interval of each intersection is subtracted. The value of the standard time difference of the cycle time, the analysis server will only perform regional search for the intersection that is greater than the threshold of the period. For each intersection, it is necessary to judge before starting the region search from the first phase. Whether the current cycle time of the intersection has exceeded the maximum cycle limit, wherein the maximum cycle limit is the initial maximum cycle time of each intersection; if the maximum cycle limit has been reached, the search direction can only advance toward the green light when lowering the direction, however, the intersection When there is a green light, there is also a minimum green light limit. If the green light is lower than the minimum green light when the green light is lower than the minimum green light limit, the green light time ratio can be lowered. Otherwise, it means that the current phase cannot be changed. It can be set to a Flag1 with a value equal to 1. The set Flag1 will prevent the analysis server from performing unnecessary simulations on it. If the cycle time is less than the maximum cycle limit, the gRQ n and p states of the phase are used as the basis for whether or not to use the dynamic stride, wherein gRQ n,p represents the p phase in the n intersection, completely 纾 The length of time for the team to be suspended, such as the percentage of the total length of the phase, indicates the degree of craving for the streetlight time for the phase of the intersection in the current solution state.
承上，若gRQ n,p 
而經歷這上述的步驟來決定該路口各時相調整綠燈時比的方向及步幅後，該分析伺服器便會執行模擬，若整體系統績效有改善，表示搜尋方向及步幅正確，即可重置所有Flag及動態步幅的程度，再回到該路口的第一個時相繼續進行搜尋更佳解；若是績效並未改善，首先判斷原先是否有使用動態步幅來調整(即為Flag2之值)，若有使用，則把動態步幅的程度降低，以確認是否因原先之搜尋步幅過大，導致搜尋不完整，而隨著步幅逐漸下降至0，則代表所有範圍皆搜尋完整，即可接續至下一個時相進行搜尋；另外，若原先未使用動態步幅，則須判斷先前搜尋方向是否有誤(即Flag3的值)，可將預設為減少綠燈時比的搜尋方向改為以增加綠燈時比為方向進行搜尋，然若仍舊未改善，則直接進行到下一個時相的搜尋；依此方法將該路口的所有時相皆被進行區域 搜尋後，便切換至下一個路口進行週期門檻值的判斷，以決定是否進行區域搜尋，直到完成所有路口的搜尋，該第一區域搜尋法完成。 After going through the above steps to determine the direction and stride of the green light when the intersection is adjusted, the analysis server will perform the simulation. If the overall system performance is improved, the search direction and the stride are correct. Reset the extent of all Flags and dynamic strides, and then return to the first phase of the intersection to continue searching for better solutions; if the performance has not improved, first determine whether the original dynamic stride is used to adjust (ie, Flag2) Value), if used, reduce the degree of dynamic stride to confirm whether the original search stride is too large, resulting in incomplete search, and as the stride gradually decreases to 0, it means that all ranges are searchable. , you can continue to search for the next phase; in addition, if you have not used dynamic stride, you must judge whether the previous search direction is wrong (ie, the value of Flag3), you can preset the search direction to reduce the green light ratio. Instead, search for the direction of increasing the green light, but if it still does not improve, go directly to the next phase of the search; in this way, all the phases of the intersection are zoned. After the search, it switches to the next intersection to judge the period threshold to determine whether to perform the area search until the search of all intersections is completed, and the first area search method is completed.
再來，該分析伺服器進行步驟三，將各路口中最大的週期時間訂為一共同週期，並將其餘路口之週期時間放大至該共同週期，而各路口的綠燈時間將會對應地根據綠燈時比進行放大；接著，若系統中有半週期路口，則依據綠燈時比將其原本的週期時間進行切割，進而為其轉換為半週期之時制計畫，若無半週期路口，則維持週期時間及綠燈時比。 Then, the analysis server performs step 3, and the maximum cycle time of each intersection is set to a common cycle, and the cycle time of the remaining intersections is enlarged to the common cycle, and the green time of each intersection is correspondingly according to the green light. The time ratio is amplified; then, if there is a half-cycle intersection in the system, the cycle time is cut according to the green light time, and then converted into a half-cycle time plan. If there is no half-cycle intersection, the cycle is maintained. Time and green light ratio.
步驟四，該分析伺服器接著針對未曾進行過區域搜尋的路口依一第二區域搜尋法進行搜尋，然而該第二區域搜尋法須受整體系統的共同週期限制。 In step four, the analysis server then searches for a second area search method for the intersection where the area search has not been performed. However, the second area search method is subject to the common period limitation of the overall system.
該第二區域搜尋法係為在為系統設置共同週期後，用以針對綠燈時比遭共同週期放大之路口進行綠燈時比的搜尋改良，該第二區域搜尋法係由該分析伺服器執行至少包含以下步驟：為維持共同週期不變，須挑出相對缺乏綠燈時間的時相與相對浪費綠燈時間的時相，並分別為前者增加綠燈時比及為後者減少綠燈時比，而做出的增加與減少綠燈須為等量，以維持共同週期不變。該分析伺服器判斷相對缺乏與浪費的依據分別係為路口的一時相之gRQ n,p 是否大於該路口的gRQ n,mean 或小於gRQ n,mean ，其中gRQ n,mean 為此路口n所有時相對於綠燈時間渴望程度的平均值。 The second area search method is a search improvement for a green light time ratio for a green light when compared to a common period enlarged intersection after setting a common period for the system, the second area search method is executed by the analysis server at least The following steps are included: in order to maintain the common cycle constant, it is necessary to pick out the phase of the relative lack of green time and the phase of the relative waste of green time, and respectively increase the green light ratio for the former and the green light ratio for the latter. The increase and decrease of the green light must be equal to maintain the common cycle. The analysis server determines whether the relative lack of waste and the basis of waste are respectively the gRQ n of the intersection of the intersection , whether p is greater than the gRQ n of the intersection , mean or less than gRQ n, mean , where gRQ n, mean is the intersection n The average of the degree of desire relative to the green time.
承上，在以該第二區域搜尋法進行搜尋的過程中，會先針對路口的各時相之gRQ n,p 進行大小排序，以大於gRQ n,mean 中最大的時相為優先增加綠燈時比的對象，再挑出小於gRQ n,mean 中最小的時相作為等量減少綠燈時比的對象，若調 整後整體系統績效有改善，便依相同方向重新排序與搜尋；若未有改善，則維持大於gRQ n,mean 中最大的時相為優先增加對象，減少對象則改為小於gRQ n,mean 中次小的時相，若一直未改善，針對此大於gRQ n,mean 中最大時相的搜尋將會持續到不再有小於gRQ n,mean 的時相可以做減少對象為止，接著，便改由大於gRQ n,mean 中次大的時相做為優先增加綠燈時比的對象，減少對象則會再次從小於gRQ n,mean 的時相中，依序挑出最小、次小等等的時相來替換搜尋，直到針對該路口所有大於gRQ n,mean 時相進行完搜尋後，便完成該路口的區域搜尋，接著，再跳至下一路口進行搜尋，直到其餘路口都完成該第二區域搜尋法。 In the process of searching by the second region search method, the gRQ n,p of each time phase of the intersection is first sorted, and the green light is preferentially added when the maximum phase in the mean is greater than gRQ n The object of comparison is less than gRQ n, and the smallest phase in mean is the object of equal reduction in green light. If the overall system performance is improved after adjustment, it will be reordered and searched in the same direction; if there is no improvement, Then maintain greater than gRQ n, the largest phase in mean is the priority increase object, the reduction object is changed to less than gRQ n, the second time phase of mean , if it has not improved, for this greater than gRQ n, the maximum phase in mean The search will continue until there is no more than gRQ n, the phase of the mean can be reduced, and then the object that is greater than gRQ n and the second largest in the mean is used as the priority to increase the green light ratio. The object will replace the search from the phase less than gRQ n, mean , and select the minimum, the second, and so on, until all the gRQ n is greater than the gRQ n for the intersection. Complete the area search for the intersection, then jump to The next intersection is searched until the remaining intersections complete the second area search method.
步驟五，在對該幹道的整體系統經由該第一區域搜尋法以及該第二區域搜尋法決定時制計畫的週期與綠燈時比後，該分析伺服器將藉由MAXBAND演算法求解該幹道的最大續進綠寬帶，進而計算出各路口的時差(offset)，用以實施於該幹道上的交通號誌系統以進行控制，另外，亦可以將最後結果輸入混合車流模擬器，以模擬運算出整體系統的總延遲績效數值。 Step 5: After the overall system of the main road determines the period of the plan and the green time by the first area search method and the second area search method, the analysis server will solve the main road by the MAXBAND algorithm. The maximum continuous green broadband, and then calculate the time difference (offset) of each intersection, used to implement the traffic signal system on the main road for control, in addition, the final result can also be input into the hybrid vehicle flow simulator to simulate the calculation The total delayed performance value of the overall system.
本發明之混合車流交通號誌控制方法，即是透過上述步驟之執行所獲得結果，實施於幹道的交通號誌控制系統，提升幹道上車流的續進效率提升並使系統整體延遲降低，是一種高效的交通號誌控制方法。 The hybrid traffic flow control method of the present invention is a traffic sign control system implemented in the main road through the execution of the above steps, which improves the continuation efficiency of the traffic on the main road and reduces the overall delay of the system. Efficient traffic control method.
S100~S107‧‧‧步驟流程 S100~S107‧‧‧Step procedure
S201~S226‧‧‧步驟流程 S201~S226‧‧‧Step procedure
S301~S319‧‧‧步驟流程 S301~S319‧‧‧Step process
圖1為本發明混合車流交通號誌控制方法之步驟流程圖。 1 is a flow chart showing the steps of a method for controlling a mixed traffic flow number in the present invention.
圖2為本發明混合車流交通號誌控制方法之第一區域搜尋法的步驟流程圖。 2 is a flow chart showing the steps of the first area searching method for the hybrid traffic flow number control method of the present invention.
圖3為本發明混合車流交通號誌控制方法之第二區域搜尋法的步驟流程圖。 3 is a flow chart showing the steps of the second area searching method for the hybrid traffic flow number control method of the present invention.
圖4為一幹道交通系統之實施例示意圖。 4 is a schematic diagram of an embodiment of a trunk traffic system.
圖5為依據本發明混合車流交通號誌控制方法實施之第一範例表格。 Figure 5 is a first exemplary table of implementation of a hybrid traffic flow control method in accordance with the present invention.
圖6為依據本發明混合車流交通號誌控制方法實施之第二範例表格。 Figure 6 is a second exemplary form of implementation of a hybrid traffic flow control method in accordance with the present invention.
圖7為依據本發明混合車流交通號誌控制方法實施之第三範例表格。 Figure 7 is a third exemplary form of implementation of a hybrid traffic flow control method in accordance with the present invention.
圖8為依據本發明混合車流交通號誌控制方法實施之第四範例表格。 Figure 8 is a fourth exemplary form of implementation of a hybrid traffic flow control method in accordance with the present invention.
圖9為依據本發明混合車流交通號誌控制方法實施之第五範例表格。 Figure 9 is a fifth exemplary table for implementing the hybrid traffic flow control method in accordance with the present invention.
以下將以實施例結合圖式對本發明進行進一步說明，首先請參照圖1，其係為本發明混合車流交通號誌控制方法之步驟流程圖，其中，係透過一分析伺服器依序執行下列步驟，依序為：步驟S100以CLV法計算幹道上各路口的週期時間以及路口的時相綠燈時比；步驟S101進行第一搜尋法，來對起始週期小於起始週期限制但起始週期相對較大之路口進行區域搜尋並加以調整；步驟S102為整體幹道系統設定系統共同週期，共同週期為各路口的起始週期最大者；步驟S103進行第二搜尋法，對未經第一搜尋法調整且綠燈時比 受到週期調整而放大的路口綠燈時比進行相對調整；步驟S104，以透過上述調整的週期和綠燈時比制定幹道時制計畫；步驟S105以MAXBAND法對幹道時制計畫求解；步驟S106計算時制計畫求解後的系統時差，即可用以實施在幹道的交通號誌控制系統；另外，更可以進行步驟S107計算整體系統的延遲來瞭解調整後的效率。 The present invention will be further described in the following with reference to the drawings. First, please refer to FIG. 1 , which is a flow chart of the steps of the hybrid traffic flow control method of the present invention, wherein the following steps are sequentially performed through an analysis server. In sequence, step S100 calculates the cycle time of each intersection on the main road and the time-phase green light time ratio of the intersection by the CLV method; the first search method is performed in step S101, so that the start period is less than the start period limit but the start period is relatively The larger intersection performs regional search and adjustment; step S102 sets the system common period for the overall trunk system, and the common period is the maximum starting period of each intersection; step S103 performs the second search method, which is not adjusted by the first search method. And green light ratio When the intersection is enlarged and the green light is enlarged, the relative adjustment is performed; in step S104, the trunk time schedule is calculated by transmitting the adjusted period and the green time ratio; in step S105, the trunk time plan is solved by the MAXBAND method; and the step time is calculated by the step S106. The system time difference after the solution is drawn can be used to implement the traffic signal control system in the main road; in addition, the delay of the overall system can be calculated in step S107 to understand the adjusted efficiency.
再來，請參閱圖2，係為本發明混合車流交通號誌控制方法之第一區域搜尋法的步驟流程圖，其中，第一區域搜尋法係以分析伺服器執行步驟流程如下：步驟S201：先確認路口n之初始週期C n 大於週期門檻值，超過週期門檻值才繼續搜尋，確認結果為是則進入步驟S202，否則進入步驟S203；步驟S202：對路口n進行搜尋，先搜尋路口的第一時相，設定p=1；步驟S203：設定n=n+1，找尋下一路口，進入步驟S226；步驟S204：確認路口n的初始週期C n 是否已逾最大起始週期限制Max C，若結果為否，進入步驟S205，若結果為是，進入步驟S206；步驟S205：確認路口n的第一時相對綠燈時比的渴望程度gRQ n,p 是否大於等於百分之一百，若結果為是，進入步驟S221，若結果為否，進入步驟S223，步驟S206：確認路口n的第一時相目前綠燈時比G n,p -1是否會小於最小綠燈時比限制Min G n,p ，若是，則進入步驟S207，若否，進入步驟S208；步驟S207：將第一時相Flag 1之值設定為1，避免分析伺服器對其執行不必要之模擬； 步驟S208：路口n的初始週期C n 減1，將路口n第一時相的綠燈時比亦降低1；步驟S209：確認Flag 1之值是否為1，是則進入步驟S210，否則跳入步驟S211；步驟S210：確認Flag 1值為0，進行模擬；步驟S211：當前調整是最佳解，進入步驟S214；步驟S212：確認模擬後目標是否有改善，未改善則進入步驟S211，改善的話，進入步驟S213；步驟S213：將最佳值設定為當前值，重置Flag跟動態步幅，進入步驟S202，再度調整路口n的第一時相；步驟S214：確認動態步幅程度的Flag 2是否為0，若為0，進入步驟S215，若不為0，進入步驟S216；步驟S215：判斷先前搜尋方向是否有問題，確認關於搜尋方向的Flag 3是否為0，若為0，再度回到步驟S204，若不為0，進入步驟S219；步驟S216：DSS=DSS-1，調降動態步幅程度；步驟S217：確認DSS是否為0，若為是，則代表動態步幅已歸零，進入步驟S218，若為否，再度回到步驟S204；步驟S218：重置所有Flag跟動態步幅，進入步驟S219；步驟S219：設定p=p+1，代表欲開始搜尋路口n下一個時相；步驟S220：確認p是否已超過路口n的時相個數，若為否，再度回到步驟S204，若為是，進入步驟S203，找尋下一路口；步驟S221：確認Max C減去初始週期C n 後是否大於等於動態步幅的最大值Max DSS，若是，則進入步驟S222，若 否，進入步驟S225；步驟S222：將初始週期C n 依動態步幅調升，將綠燈時比G n,p 亦依據動態步幅調升，將動態步幅程度的Flag 2設為1，進入步驟S209；步驟S223：確認Flag3是否為零，若為0，進入步驟S224，若不為0，進入步驟S225；步驟S224：設定Flag3為1，調整搜尋方向，進入步驟S206；步驟S225：將初始週期C n 調升1，並將綠燈時比G n,p 亦調升1，進入步驟S209；步驟S226：確認n是否仍小於等於路口總數，以確認是否搜尋完畢，若為是，回到步驟S201繼續搜尋，若為否，結束第一搜尋法。 Referring to FIG. 2, it is a flow chart of the first area searching method of the hybrid traffic flow number control method of the present invention, wherein the first area searching method is performed by the analysis server, and the flow of the steps is as follows: Step S201: First, it is confirmed that the initial period C n of the intersection n is greater than the period threshold, and the search is continued after the period threshold is exceeded. If the result of the confirmation is yes, the process proceeds to step S202. Otherwise, the process proceeds to step S203. Step S202: searching for the intersection n , first searching for the intersection temporary phase, set p = 1; step S203: setting n = n +1, find the next intersection, proceeds to step S226; step S204: confirm intersection C n n initial period if the maximum timed initial period limit Max C, If the result is no, proceed to step S205, if the result is YES, proceed to step S206; and step S205: confirm whether the first degree of the intersection of the intersection n is relative to the green light ratio , whether the degree of desire gRQ n,p is greater than or equal to one hundred percent, if the result is If yes, go to step S221, if the result is no, go to step S223, step S206: confirm whether the first phase of the intersection n is greener than G n, p -1 is smaller than the minimum green light when the limit is Min G n,p If If yes, go to step S207, if no, go to step S208; step S207: set the value of the first phase phase Flag 1 to 1, to avoid unnecessary simulation of the analysis server; Step S208: initial cycle of the intersection n C n minus 1, the green time ratio of the first phase of the intersection n is also decreased by 1; step S209: confirming whether the value of Flag 1 is 1, if yes, proceeding to step S210, otherwise jumping to step S211; step S210: confirming Flag 1 The value is 0, and the simulation is performed; step S211: the current adjustment is the optimal solution, and the process proceeds to step S214; step S212: confirm whether the target is improved after the simulation, if not, the process proceeds to step S211, if not, the process proceeds to step S213; and the step S213: The optimal value is set to the current value, the flag and the dynamic stride are reset, and the process proceeds to step S202 to adjust the first phase of the intersection n again; step S214: confirm whether the flag 2 of the dynamic stride level is 0, and if it is 0, enter Step S215, if not 0, proceed to step S216; step S215: determine whether there is a problem in the previous search direction, confirm whether Flag 3 is 0 in the search direction, and if it is 0, return to step S204 again, if not 0, enter Step S219; step Step S216: DSS=DSS-1, adjust the dynamic stride degree; step S217: confirm whether the DSS is 0, if yes, the dynamic stride has been reset to zero, proceed to step S218, and if no, return to the step again. S204: Step S218: reset all Flags and dynamic strides, go to step S219; Step S219: Set p = p +1, which means to start searching for the next phase of the intersection n; Step S220: Confirm whether p has exceeded the intersection n The number of phases, if not, returns to step S204 again, if yes, proceeds to step S203 to find the next intersection; step S221: confirms whether Max C is greater than or equal to the maximum value of the dynamic step after subtracting the initial period C n Max DSS, if yes, go to step S222, if no, go to step S225; step S222: increase the initial period C n according to the dynamic step, and adjust the green time ratio G n,p according to the dynamic step, and the dynamic Step 2 of the stride level is set to 1, proceeding to step S209; step S223: confirming whether Flag3 is zero, if it is 0, proceeding to step S224, if not, proceeding to step S225; step S224: setting Flag3 to 1, adjusting the search Direction, proceeding to step S206; step S225: initial cycle C n is incremented by 1, and the green light is further increased by 1 than G n,p , and the process goes to step S209; step S226: confirm whether n is still less than or equal to the total number of intersections to confirm whether the search is completed, and if yes, return to step S201 to continue. Search, if no, end the first search method.
再來，請參閱圖3，係為本發明混合車流交通號誌控制方法之第二區域搜尋法的步驟流程圖，其中，第二區域搜尋法係以分析伺服器針對未經第一區域搜尋法之路口執行步驟流程如下：步驟S301：設定n=1，自第一個路口開始判斷；步驟S302：確認路口的綠燈時比是否受調整的共同週期影響而放大，若為是，進入步驟S303，若為否，進入步驟S304；步驟S303：將路口的時相依據綠燈時比的渴望程度gRQ n,p 進行遞減排序，並依渴望程度由大到小賦予index值i，i的範圍為自1到I，其中，index值為1的係具有最大gRQ n,p 的時相，index值為2的係具有次大gRQ n,p 的時相，而index值為I的係具有最小index值為的時相；步驟S304：設定n=n+1，開始進入下一個路口； 步驟S305：設定i=1，以具有最大gRQ n,p 的i時相做為目標；步驟S306：確認i時相的gRQ n,f(i)是否大於等於gRQ n,mean ，即是否大於等於路口內時相的平均綠燈渴望程度，若為是，進入步驟S307，若為否，進入步驟S304；步驟S307：設定一值j=1；步驟S308：確認j+i是否小於I，即為確認i時相是否是搜尋到index中排序最後一位，若為是，進入步驟S309，若為否，進入步驟S310；步驟S309：確認gRQ n,f(I+1-j)是否小於gRQ n,nean ，若為是，進入步驟S311，若為否，進入步驟S310；步驟S310：設定i=i+1，調整index指向次序下一位，即gRQ n,f(i)更小者；步驟S311：確認G n,f(I+1-j)-1之值是否大於等於Min G n,f(I+1-j)，即確認等量調整後是否另一時相會小於綠燈時比最小限制，若為是，進入步驟S312，若為否，進入步驟S317；步驟S312：G n,f(i)調增1，相對應地，G n,f(I+1-j)調降1，進入步驟S313；步驟S313：執行模擬，進入步驟S314；步驟S314：確認目標是否改善，若為是，進入步驟S315，若為否，進入步驟S316；步驟S315：設定最佳值為當前值；步驟S316：設定當前值為最佳值；步驟S317：設定j=j+1，即為嘗試調整index指向次序下一位；步驟S318：確認i是否小於等於I，即為確認是否已依據 index搜尋完畢，若為是，進入步驟S306，若為否，進入步驟S304；步驟S318：確認n是否小於路口總數，以確認是否將剩餘路口搜尋完畢，若為是，進入步驟S302，尋找下一路口，若為否，則第二區域搜尋法結束。 Referring to FIG. 3, it is a flow chart of the second region search method of the hybrid traffic flow number control method of the present invention, wherein the second region search method is based on the analysis server for the first region search method. The flow of the intersection execution step is as follows: Step S301: setting n =1, starting from the first intersection; step S302: confirming that the green light of the intersection is enlarged compared with whether or not the green period of the adjustment is affected, and if yes, proceeding to step S303, If not, proceed to step S304; step S303: decrement the time phase of the intersection according to the degree of craving gRQ n,p of the green light ratio, and assign the index value i according to the degree of eagerness, i , the range of i is 1 To I , wherein the index value of 1 has the largest gRQ n, the phase of p , the index value of 2 has the second largest gRQ n, p phase, and the index value I has the smallest index value. Step S304: setting n = n +1, starting to enter the next intersection; Step S305: setting i =1, aiming at the i- phase having the maximum gRQ n,p ; step S306: confirming the i- phase Whether gRQ n,f ( i ) is greater than or equal to gRQ n,mean , that is, whether it is large And equal to the average green light craving degree of the phase in the intersection, if yes, go to step S307, if no, go to step S304; step S307: set a value j =1; step S308: confirm whether j + i is less than I , ie To confirm whether the i phase is the last bit of the searched index, if yes, go to step S309, if no, go to step S310; step S309: confirm whether gRQ n,f ( I +1- j ) is less than gRQ n,nean , if yes, go to step S311, if no, go to step S310; step S310: set i = i +1, adjust index to the next order, ie gRQ n, f ( i ) is smaller; Step S311: Confirm whether the value of G n,f ( I +1- j ) -1 is greater than or equal to Min G n,f ( I +1- j ) , that is, whether the other phase is smaller than the green light after the equal adjustment is confirmed. The minimum limit, if yes, proceeds to step S312, if not, proceeds to step S317; step S312: G n,f ( i ) is incremented by 1, correspondingly, G n,f ( I +1- j ) is lowered 1. Go to step S313; step S313: execute simulation, go to step S314; step S314: confirm whether the target is improved, if yes, go to step S315, if no, go to step Step S316: Step S315: setting the optimal value as the current value; Step S316: Setting the current value as the optimal value; Step S317: Setting j = j +1, that is, trying to adjust the index pointing order to the next bit; Step S318: Confirming Whether i is less than or equal to I , that is, to confirm whether the index search has been completed, if yes, go to step S306, if no, go to step S304; step S318: confirm whether n is smaller than the total number of intersections, to confirm whether the remaining intersections are searched If yes, go to step S302 to find the next intersection, and if no, the second area search method ends.
圖4為一幹道交通系統之實施例示意圖，圖中橫向道路為運用本發明的主幹道，而圖中垂直的道路則為支幹道，其中，各方向箭頭分別代表幹道及沿線與各支幹道交會路口可允許的車流續進方向。 4 is a schematic view of an embodiment of a trunk road traffic system. The horizontal road in the figure is a main road using the present invention, and the vertical road in the figure is a branch road, wherein each direction arrow represents a trunk road and a line along with each trunk road. At the intersection, the allowed traffic flow continues.
其中，在實施例中，路口1與路口2沿主幹道的東西方向以直進車流為主，流量皆高達2000輛以上，車流組成以機車和小客車為主，但機車偏高；由支幹道出來的車輛，若干受交通規則之限制皆為汽車，轉向以直線前進為主，但右轉比例較高；另外，在路口3，沿主幹道的東西向以直進流量為主，但流量下降至1000~1500輛，由路口3上側支幹道出來的車流組成以機車為主，直進與右轉車輛分別為2050輛和1834輛，這當中，直進機車高達2001輛，右轉機車則為1774輛，左轉流量幾乎趨近於無，而由下方支幹道出來的車輛較少，各轉向車輛皆小於200輛；最後，則是路口4，由西向東向的車流量較少，以直進車流為主，流量為614輛，向東向的車流組成以機車和小客車為主，主要轉向則以左轉和右轉為主，轉向北的方向進入園區的車輛以小客車為主，方向性則以直進和右轉為主，流量分別為1853輛和1068輛，另外則是轉向南行進的車流，將本實施例之交通流量以本發明進行求解以進行控制。 In the embodiment, the intersection 1 and the intersection 2 are mainly in direct traffic flow along the east-west direction of the main road, and the flow rate is up to 2000 or more, and the traffic flow is mainly composed of a locomotive and a small passenger car, but the locomotive is high; The vehicles, some of which are restricted by traffic rules are cars, the steering is mainly in a straight line, but the right turn ratio is higher; in addition, at the intersection 3, the east-west direction along the main road is mainly direct flow, but the flow rate drops to 1000. ~1500 vehicles, the traffic flow from the upper trunk road of the intersection 3 is mainly composed of locomotives. The direct-in and right-turn vehicles are 2050 and 1834 respectively, among which, the direct-moving locomotive is as high as 2001, and the right-turning locomotive is 1774, left. The transfer flow is almost no, and there are fewer vehicles coming out from the lower trunk roads, and each of the steering vehicles is less than 200. Finally, it is intersection 4, with less traffic from west to east, with direct traffic, traffic. For the 614 vehicles, the eastbound traffic consists mainly of locomotives and small passenger cars. The main steering is mainly left and right turn. The vehicles that turn to the north are mainly small passenger cars. The direction is straight forward and right. turn Mainly, the flow rate is 1853 and 1068, respectively, and the other is the traffic flow to the south, and the traffic flow of the embodiment is solved by the present invention for control.
首先，經由將實施例中各路口的流量資訊輸入分 析伺服器，以利用CLV運算法演算解出各路口初始號誌時制設定，結果範例如圖5所示，圖中單位為秒，而此時的系統總延遲為1293236.859(輛/秒)。 First, by inputting the traffic information of each intersection in the embodiment The server is analyzed to calculate the initial number of the intersections using the CLV algorithm. The result is shown in Figure 5. The unit in the figure is seconds, and the total system delay at this time is 1,123,326.859 (cars/second).
再透過第一區域搜尋法，搜尋改善號誌時制設定，並演算解出各路口改善後之號誌時制設定，結果範例如圖6所示，圖中單位為秒，而此時的系統總延遲為1216490.21(輛/秒)。 Through the first area search method, the search improves the time-based setting, and calculates the solution of the time-of-day setting after the improvement of each intersection. The result is shown in Figure 6. The unit in the figure is seconds, and the total system delay at this time. It is 1216490.21 (vehicles per second).
再來，以各路口中最大的週期時間設定為共同週期，其中，共同週期為200秒，設定後解出之各路口改善號誌時制設定，結果範例如圖7所示，圖中單位為秒，以及此時系統總延遲為1225239.47(輛/秒)。 Then, the maximum cycle time among the intersections is set as the common cycle, wherein the common cycle is 200 seconds, and the intersections of the intersections that are solved after the setting are set to improve the time system setting. The result is shown in Fig. 7, and the unit is seconds. And the total system delay at this time is 1225239.47 (cars / sec).
接著，由於本實施例中路網中無半週期設定，故分析伺服器直接進入第二區域搜尋法，搜尋改善後之號誌時制設定並求解，結果範例如圖8所示，圖中單位為秒，此時系統總延遲1225239.47(輛/秒)。 Then, since there is no half-cycle setting in the road network in this embodiment, the analysis server directly enters the second area search method, and searches for the improved time-based time setting and solves the solution. The example of the result is shown in FIG. 8 , and the unit is seconds. At this time, the total delay of the system is 1225239.47 (vehicles/second).
最後，分析伺服器經由MAXBAND演算解出之各路口改善號誌時制設定，結果範例如圖9所示，圖中單位為秒。由圖9結果可分析出，最後經由MAXBAND演算出之號誌時制設定與先前之差別在於各路口的Offset時差，而其最大化西向東綠燈續進帶寬係為0.185×200=37(秒)，而最大化東向西的綠燈續進帶寬係為0.09156×200=18.312(秒)，如此調整，即可將本發明的混合車流交通號誌控制方法應用於該主幹道上，以提升駕駛者體驗以及順暢車流。 Finally, the analysis server optimizes the number of time intervals created by the MAXBAND calculation. The result is shown in Figure 9. The unit is seconds. From the results of Fig. 9, it can be analyzed that the last difference between the time and time set by MAXBAND is the Offset time difference of each intersection, and the maximum westbound green light continuation bandwidth is 0.185×200=37 (seconds). The maximum green-light bandwidth of the east-west is 0.09156×200=18.312 (seconds). With this adjustment, the hybrid traffic flow control method of the present invention can be applied to the main road to improve the driver experience and Smooth traffic.
綜上所述，本發明於技術思想上實屬創新，也具備先前技術不及的多種功效，已充分符合新穎性及進步性之法定發明專利要件，爰依法提出專利申請，懇請 貴局核准 本件發明專利申請案以勵發明，至感德便。 In summary, the present invention is innovative in terms of technical ideas, and also has various functions that are not in the prior art, and has fully complied with the statutory invention patent requirements of novelty and progressiveness, and has filed a patent application according to law, and is requested to approve it. This invention patent application is to invent invention, to the sense of virtue.
S100~S107‧‧‧步驟流程 S100~S107‧‧‧Step procedure
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002150481A (en) * | 2000-11-14 | 2002-05-24 | Mitsubishi Electric Corp | Subordinate device |
| US20090167561A1 (en) * | 2007-12-26 | 2009-07-02 | Aochengtongli S&T Development ( Beijing ) Co., Ltd | Intelligent traffic light control system |
| US20090167562A1 (en) * | 2007-12-26 | 2009-07-02 | Aochengtongli S&T Development ( Beijing ) Co., Ltd | Traffic light control system for a high flow intersection |
| CN101763735A (en) * | 2010-02-01 | 2010-06-30 | 王茜 | Method for controlling dynamic signal control system having negative system loss time |
| WO2014019461A1 (en) * | 2012-08-02 | 2014-02-06 | 中兴通讯股份有限公司 | Arterial traffic light optimization and control method and device |
-
2016
- 2016-12-14 TW TW105141330A patent/TWI615816B/en active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2002150481A (en) * | 2000-11-14 | 2002-05-24 | Mitsubishi Electric Corp | Subordinate device |
| US20090167561A1 (en) * | 2007-12-26 | 2009-07-02 | Aochengtongli S&T Development ( Beijing ) Co., Ltd | Intelligent traffic light control system |
| US20090167562A1 (en) * | 2007-12-26 | 2009-07-02 | Aochengtongli S&T Development ( Beijing ) Co., Ltd | Traffic light control system for a high flow intersection |
| CN101763735A (en) * | 2010-02-01 | 2010-06-30 | 王茜 | Method for controlling dynamic signal control system having negative system loss time |
| WO2014019461A1 (en) * | 2012-08-02 | 2014-02-06 | 中兴通讯股份有限公司 | Arterial traffic light optimization and control method and device |
Non-Patent Citations (4)
| Title |
|---|
| 國立交通大學,"號誌控制技術研究計畫（1/4）",<http://www.motc.gov.tw/ch/home.jsp?id=714&parentpath=0%2C2%2C711&mcustomize=multimessages_view.jsp&dataserno=201412310002&aplistdn=ou=data,ou=technology,ou=chinese,ou=ap_root,o=motc,c=tw&toolsflag=Y&imgfolder=img%2Fstandard>,交通部, 公開時間：2014年12月31日 |
| 國立交通大學,"號誌控制技術研究計畫（1/4）",<http://www.motc.gov.tw/ch/home.jsp?id=714&parentpath=0%2C2%2C711&mcustomize=multimessages_view.jsp&dataserno=201412310002&aplistdn=ou=data,ou=technology,ou=chinese,ou=ap_root,o=motc,c=tw&toolsflag=Y&imgfolder=img%2Fstandard>,交通部, 公開時間：2014年12月31日 * |
| 葉志韋,"以改良格位傳遞模式構建混合車流狀況之適應性號誌控制邏輯",國立成功大學,紙本公開時間：2014年 * |
| 邱裕鈞,"混合車流下之綠色適應***通號誌控制模式研究成果報告(精簡版)",行政院國家科學委員會專題研究計畫 成果報告,公開時間：2012年101月4日 * |
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