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使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 = = Implem...

王肇揚

使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 = = Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning /

Record Type:	Language materials, printed : Monograph/item
Title/Author:	使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 =/ 王肇揚.
Reminder of title:	Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning /
remainder title:	Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning.
Author:	王肇揚
Published:	雲林縣 :國立虎尾科技大學 , : 民113.07.,
Description:	[9], 54面 :圖, 表 ; : 30公分.;
Notes:	指導教授: 陳政宏.
Subject:	Dynamic Lane Change Trajectory Planning. -
Online resource:	電子資源

使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 = = Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning /
王肇揚

使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 =Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning /Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning.王肇揚. - 初版. - 雲林縣 :國立虎尾科技大學 ,民113.07. - [9], 54面 :圖, 表 ;30公分.

指導教授: 陳政宏.

碩士論文--國立虎尾科技大學電機工程系碩士班.

含參考書目.

隨著自動駕駛技術的發展，眾多車廠開始投入自駕技術的研發，並積極尋求更高等級的自動化。同時在自駕技術中車道變換系統以及同時定位與地圖建構(Simultaneous Localization and Mapping, SLAM)技術在自駕技術中也扮演著至關重要的角色。前者是使實驗車輛能夠準確獲取周圍環境訊息，並判斷是否適合進行車道變換，並確保車輛能夠準確地沿著變道路徑行駛，進而安全地執行該操作。而後者則是為實驗車輛提供了準確的定位和地圖構建的功能，使車輛能夠更好地感知周圍環境，從而更加可靠地執行車道變換等操作。本論文實驗主要在已知場域進行實驗，強調了基於模糊邏輯車道變換決策系統(Fuzzy Lane Change Decision System, FLCDS)和基於模糊邏輯航點追蹤系統(Fuzzy Waypoints Tracking System, FWTS)的設計與功能，並使這些系統能夠提高航點追蹤的準確性和能夠安全的車道變換。動態換道軌跡生成技術也是本論文的重點，確保了車輛在多變的駕駛環境中能夠安全地進行車道變換，也探討了模糊邏輯控制方法在自動駕駛中的應用，特別針對車道變換決策系統和航點追蹤系統。FLCDS則整合了來自3D和2D LiDAR感測器的高精度距離數據以及Realsense D435i深度攝影機的深度數據。該系統透過模糊邏輯控制器處理這些輸入數據，以做出安全有效的車道變換系統。FWTS設計是使用3D LiDAR數據用來確保車輛能夠準確地跟隨航點，從而防止偏離預定路徑。.

(平裝)Subjects--Topical Terms:

1451815
Dynamic Lane Change Trajectory Planning.

使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 = = Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning /
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245 1 0 $a 使用模糊控制結合SLAM和動態軌跡規劃實現車道變換 = $b Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning / $c 王肇揚.
246 1 1 $a Implementation of Lane Change Using Fuzzy Control Combined with SLAM and Dynamic Trajectory Planning.
250 $a 初版.
260 # $a 雲林縣 : $b 國立虎尾科技大學 , $c 民113.07.
300 $a [9], 54面 : $b 圖, 表 ; $c 30公分.
500 $a 指導教授: 陳政宏.
500 $a 學年度: 112.
502 $a 碩士論文--國立虎尾科技大學電機工程系碩士班.
504 $a 含參考書目.
520 3 $a 隨著自動駕駛技術的發展，眾多車廠開始投入自駕技術的研發，並積極尋求更高等級的自動化。同時在自駕技術中車道變換系統以及同時定位與地圖建構(Simultaneous Localization and Mapping, SLAM)技術在自駕技術中也扮演著至關重要的角色。前者是使實驗車輛能夠準確獲取周圍環境訊息，並判斷是否適合進行車道變換，並確保車輛能夠準確地沿著變道路徑行駛，進而安全地執行該操作。而後者則是為實驗車輛提供了準確的定位和地圖構建的功能，使車輛能夠更好地感知周圍環境，從而更加可靠地執行車道變換等操作。本論文實驗主要在已知場域進行實驗，強調了基於模糊邏輯車道變換決策系統(Fuzzy Lane Change Decision System, FLCDS)和基於模糊邏輯航點追蹤系統(Fuzzy Waypoints Tracking System, FWTS)的設計與功能，並使這些系統能夠提高航點追蹤的準確性和能夠安全的車道變換。動態換道軌跡生成技術也是本論文的重點，確保了車輛在多變的駕駛環境中能夠安全地進行車道變換，也探討了模糊邏輯控制方法在自動駕駛中的應用，特別針對車道變換決策系統和航點追蹤系統。FLCDS則整合了來自3D和2D LiDAR感測器的高精度距離數據以及Realsense D435i深度攝影機的深度數據。該系統透過模糊邏輯控制器處理這些輸入數據，以做出安全有效的車道變換系統。FWTS設計是使用3D LiDAR數據用來確保車輛能夠準確地跟隨航點，從而防止偏離預定路徑。.
520 3 $a The experiments in this manuscript are primarily conducted in a known environment. With the continuous development of autonomous driving technology, many car manufacturers have begun investing in the research and development of self-driving technologies, actively seeking higher levels of automation. In autonomous driving, lane change systems and Simultaneous Localization and Mapping (SLAM) technology play crucial roles. The former enables experimental vehicles to accurately acquire surrounding environmental information, determine the suitability of lane changes, and ensure that the vehicle can precisely follow the changed lane path to safely execute the maneuver. The latter provides precise positioning and map construction capabilities, allowing the vehicle to better perceive the surrounding environment and thereby perform lane changes and other operations more reliably. This manuscript emphasizes the design and functionality of the Fuzzy Lane Change Decision System (FLCDS) and the Fuzzy Waypoints System (FWTS), which enhance waypoint tracking accuracy and enable safe lane changes. Dynamic lane change trajectory generation technology is also a key focus of this paper, ensuring that vehicles can safely perform lane changes in variable driving environments. The paper explores the application of fuzzy logic control methods in autonomous driving, particularly for lane change decision systems and waypoint tracking systems. FLCDS integrates high-precision distance data from 3D and 2D LiDAR sensors and depth data from the Realsense D435i camera. This system processes these input data through a fuzzy logic controller to make safe and effective lane change decisions. FWTS is designed using 3D LiDAR data to ensure that the vehicle can accurately follow waypoints, thus preventing deviation from the planned route..
563 $a (平裝)
650 # 4 $a Dynamic Lane Change Trajectory Planning. $3 1451815
650 # 4 $a Lane Change Systems. $3 1451814
650 # 4 $a SLAM Technology. $3 1451813
650 # 4 $a Autonomous Driving. $3 1451790
650 # 4 $a Fuzzy Control. $3 1045763
650 # 4 $a 動態換道軌跡規劃. $3 1451812
650 # 4 $a 車道變換系統. $3 1451811
650 # 4 $a SLAM技術. $3 1451810
650 # 4 $a 自動駕駛. $3 1062046
650 # 4 $a 模糊控制. $3 995440
856 7 # $u https://handle.ncl.edu.tw/11296/27hp72 $z 電子資源 $2 http