基于Android的大型地下停车场反向寻车系统设计与实现
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摘要
针对国内大型地下停车场反向寻车技术中需要建造大型设备和携带卡或条形码等辅助定位物品的不足,提出一种以手机为媒介,基于Android系统的用于车位引导与反向寻车导航的APP.以最短路径理论A*算法为基础,将起始点至目的地的路线转化为起始点相应停车位至目的地停车位的路径进行计算,分析路障现状,规划出最优路径并为车主提供实时路径寻车导航;以Android Studio为开发工具,以Java为开发语言.
In view of parking lots equipped with large-scale equipment and parker carrying auxiliary positioning items such as cards or barcodes during the reverse car-seeking at the large-scale underground parking lots in China,this paper proposes a mobile phone as the tool based on Android system for parking space guidance and reverse search for car. Based on the shortest path theory A * algorithm,this paper transforms the route from starting point to the destination into the path from the original parking space to the destination parking space,then analyzes the current situation of large underground parking lot roadblocks,plans the optimal path. Real-time navigation is provided for users. This paper uses Android Studio as a development tool and Java as the development language to develop a reverse search vehicle for large underground parking lots based on Android.
In view of parking lots equipped with large-scale equipment and parker carrying auxiliary positioning items such as cards or barcodes during the reverse car-seeking at the large-scale underground parking lots in China,this paper proposes a mobile phone as the tool based on Android system for parking space guidance and reverse search for car. Based on the shortest path theory A * algorithm,this paper transforms the route from starting point to the destination into the path from the original parking space to the destination parking space,then analyzes the current situation of large underground parking lot roadblocks,plans the optimal path. Real-time navigation is provided for users. This paper uses Android Studio as a development tool and Java as the development language to develop a reverse search vehicle for large underground parking lots based on Android.
引文
[1]陈伟程,吉,肖寒,等.全国机动车保有量分析:《中国机动车环境管理年报(2017)》第Ⅰ部分[J].环境保护,2017,45(12):33-34.
[2]高广银,丁勇,姜枫,等.基于BP神经网络的停车诱导泊位预测[J].计算机系统应用,2017,26(1):236-239.
[3]Cao J,Menendez M.System dynamics of urban traffic based on its parking-related-states[J].Transportation Research Part B,2015,81:718-736.
[4]安旭,许凌云,刘松.基于RFID的智能立体停车场管理系统的设计与实现[J].电子设计工程,2017,25(7):119-122.
[5]杨澜,康宁,艾玉亮,等.基于双重匹配位置指纹的室内停车场定位方法[J].测控技术,2017,36(6):24-28.
[6]高通,范道尔吉,贾成果,等.基于机器视觉与RFID智能引导停车场[J].计算机系统应用,2017,26(7):71-77.
[7]王辉,朱龙彪,王景良,等.基于Dijkstra-蚁群算法的泊车系统路径规划研究[J].工程设计学报,2016,23(5):489-496.
[8]Wu Y,Li X.Numerical simulation of the propagation of hydraulic and natural fracture using Dijkstra’s Algorithm[J].Energies,2016,9(7):519.
[9]Moscibrodzka M,Das T K,Czerny B.The pattern of accretion flow onto Sgr A*[J].Monthly Notices of the Royal Astronomical Society,2018,370(1):219-228.
[2]高广银,丁勇,姜枫,等.基于BP神经网络的停车诱导泊位预测[J].计算机系统应用,2017,26(1):236-239.
[3]Cao J,Menendez M.System dynamics of urban traffic based on its parking-related-states[J].Transportation Research Part B,2015,81:718-736.
[4]安旭,许凌云,刘松.基于RFID的智能立体停车场管理系统的设计与实现[J].电子设计工程,2017,25(7):119-122.
[5]杨澜,康宁,艾玉亮,等.基于双重匹配位置指纹的室内停车场定位方法[J].测控技术,2017,36(6):24-28.
[6]高通,范道尔吉,贾成果,等.基于机器视觉与RFID智能引导停车场[J].计算机系统应用,2017,26(7):71-77.
[7]王辉,朱龙彪,王景良,等.基于Dijkstra-蚁群算法的泊车系统路径规划研究[J].工程设计学报,2016,23(5):489-496.
[8]Wu Y,Li X.Numerical simulation of the propagation of hydraulic and natural fracture using Dijkstra’s Algorithm[J].Energies,2016,9(7):519.
[9]Moscibrodzka M,Das T K,Czerny B.The pattern of accretion flow onto Sgr A*[J].Monthly Notices of the Royal Astronomical Society,2018,370(1):219-228.