發(fā)布時間：2018-06-01 01:12

  本文選題：人群仿真 + 路徑規(guī)劃�。� 參考：《北京交通大學》2017年碩士論文

【摘要】：人群仿真應用于學術、商業(yè)、娛樂等領域,近年來備受關注。人群仿真的目的是對人群建模,仿真人在群體中的行為。由于人群是個復雜的自組織系統(tǒng),影響行人運動的因素繁多,而且應用領域廣泛,實現(xiàn)高質(zhì)量的人群仿真效果存在著諸多挑戰(zhàn),這也體現(xiàn)了本文工作的價值。本文關注人群仿真的三個層次:全局路徑規(guī)劃、局部碰撞避免以及人體動畫實現(xiàn)。首先利用Delaunay三角劃分對場景建模,得到場景的靜態(tài)可達路徑,然后運用Dijkstra算法計算行人從起點到終點的最短路徑。由于在人群運動的場景中不僅僅存在靜態(tài)障礙物,所以還要考慮與周圍的人避免碰撞。為了達到真實又高效的碰撞避免效果,本文重點研究基于數(shù)據(jù)驅動的仿真方法。在局部碰撞避免方法中,本文利用行人運動軌跡,建立了范例數(shù)據(jù)庫;在仿真過程中,虛擬人物根據(jù)自身的狀態(tài),從數(shù)據(jù)庫中查找相似的范例;通過碰撞預測,從相似范例中選擇不會與其他虛擬人物或障礙物發(fā)生碰撞的行為,并使虛擬人物復制該行為。然而,此方法依賴于行人運動數(shù)據(jù),當數(shù)據(jù)量較少時易發(fā)生碰撞現(xiàn)象,并且在數(shù)據(jù)量過大的情況下,由于數(shù)據(jù)搜索量增大,存在仿真效率下降的問題。針對這兩個問題,本文引入計算無碰撞速度的規(guī)則和碰撞檢測及解除的算法,使得在數(shù)據(jù)未覆蓋仿真場景的情況下依然少有碰撞發(fā)生;利用運動軌跡數(shù)據(jù)訓練人工神經(jīng)網(wǎng)絡,對仿真?zhèn)�體的行為進行預測,能夠在仿真過程中擺脫對數(shù)據(jù)的依賴,使得仿真效率不受數(shù)據(jù)量的影響。最后利用運動捕捉數(shù)據(jù)和運動數(shù)據(jù)可視化方法生成人物的肢體動作,將行人運動軌跡擴展成人群行走動畫,使仿真效果更加真實完整。從仿真的效果來看,本文工作能夠有效地對場景建模,進行全局路徑規(guī)劃,在碰撞避免仿真方面較現(xiàn)有工作有很大的提升,并且為運動軌跡添加了人體動畫效果。另外開發(fā)了人群仿真系統(tǒng)原型,將全局路徑規(guī)劃、局部碰撞避免和人體動畫實現(xiàn)整合在一個系統(tǒng)中。原型系統(tǒng)實現(xiàn)了圖形用戶界面,使用戶或者研究人員更方便地了解該人群仿真系統(tǒng),直觀地看到各仿真階段的效果,方便開展未來的研究工作。
[Abstract]:Crowd simulation is applied in academic, commercial, entertainment and other fields, and has attracted much attention in recent years. The purpose of crowd simulation is to model and simulate the behavior of people in the crowd. Because the crowd is a complex self-organizing system, there are many factors affecting pedestrian movement, and the application field is extensive, there are many challenges to realize the high quality crowd simulation effect, which also reflects the value of the work in this paper. This paper focuses on three levels of crowd simulation: global path planning, local collision avoidance and human animation implementation. Firstly, the Delaunay triangulation is used to model the scene, and the static reachable path of the scene is obtained. Then, the Dijkstra algorithm is used to calculate the shortest path from the beginning to the end of the pedestrian. Since there are not only static obstacles in the crowd movement scene, it is also necessary to avoid collision with the people around. In order to achieve real and efficient collision avoidance, this paper focuses on data-driven simulation methods. In the method of local collision avoidance, this paper establishes a case database by using pedestrian trajectory. In the process of simulation, the virtual character looks up similar examples from the database according to his own state. Select from a similar example a behavior that does not collide with another virtual character or obstacle and make the virtual character copy the behavior. However, this method relies on pedestrian motion data. When the amount of data is small, collision will occur easily, and when the data is too large, the efficiency of simulation will decrease due to the increase of data search. Aiming at these two problems, this paper introduces the rules of calculating collision-free velocity and the algorithm of collision detection and resolution, so that there are few collisions when the data does not cover the simulation scene, and the artificial neural network is trained by moving track data. The behavior of simulation individuals can be predicted to get rid of the dependence on data in the process of simulation, so that the efficiency of simulation is not affected by the amount of data. Finally, the movement capture data and motion data visualization method are used to generate the body movements of the characters, and the pedestrian movement track is expanded into a crowd walking animation, which makes the simulation effect more real and complete. From the result of simulation, this paper can effectively model the scene, plan the global path, improve the simulation of collision avoidance greatly compared with the existing work, and add the human animation effect for the motion track. In addition, a prototype of crowd simulation system is developed, which integrates global path planning, local collision avoidance and human animation into one system. The prototype system realizes the graphical user interface, which makes the user or researcher understand the simulation system of the crowd more conveniently, see the effect of each simulation stage intuitively, and carry out the research work in the future.
【學位授予單位】：北京交通大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP391.41;TP183

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