出租车作为城市公共交通工具的补充，为人们的交通出行提供了诸多方便，在城市交通运输中起着越来越重要的作用。然而由于出租车行业的粗放式管理模式以及落后的路边招手打车方式，致使出租车司机和乘客所掌握的信息不对称，进而导致了市民“打的难”而出租车空驶率却居高不下的问题，同时加重了交通拥堵，环境污染等诸多问题，人们的生活质量受到了严重的影响。而且目前所试行的电召及电话人工调度的出租车调度方式，叫车方式单一，调度方式效率低，成本高。因此，研究和实行新的高科技、高效率的出租车叫车系统显得尤为必要和迫切。 本文充分研究了国内外出租车调度技术的发展和应用情况，针对出租车行业的管理特点和技术需求，提出了以北斗定位技术（BD）、第三代移动通信技术（3G）、Google Maps API技术为基础的出租车调度管理系统设计方案。本系统主要包含车载终端、通信平台、呼叫中心、短信平台、调度平台和管理平台六大部分。系统基于B/S 模式设计，采用Windows Server 2003 为操作系统、SQL Server 2005 为数据库，使用Microsoft Visual Studio 2008集成开发环境，开发语言为ASP.NET+C#，并以Google Maps API作为开发地图模块的API。 本文的工作重点是出租车调度系统中最短路径求解算法的研究与改进。主要针对基本人工鱼群算法因参数视野固定不变而导致算法后期收敛速度慢、运算量大、易陷入局部最优的缺陷，根据静态最短路径问题的特点，对人工鱼群算法进行了改进。该改进算法只对人工鱼的觅食行为的视野进行调整，使其随着迭代次数的变化而自适应地变化，并设置了视野值的下限，以防视野过小，算法又陷入局部最小。实验结果表明，改进型人工鱼群算法的收敛速度、计算量、寻优精度和准确性均优于基本人工鱼群算法及基本蚁群算法，而且道路越复杂，节点越多，这种优势越显著。

Taxi, as a supplement to urban public transport vehicles, provides a lot of convenience for people, and plays an increasingly important role in urban transportation. However, the extensive taxi management model and the backward way people hail a taxi at the roadside have led to that the information obtained by the taxi drivers and passengers is asymmetrical, which makes people hard to take a taxi and causes the high rate of taxi empty crossing. Meanwhile, it has increased traffic congestion, environmental pollution and other problems, which have seriously affected the quality of life. The development and application at home and abroad of the taxi dispatch technology are full researched in this thesis. According the management characteristics and technical requirements of the taxi industry, a system framework for taxi scheduling and management is designed based on Beidou positioning technology (BD), the third generation mobile communication technology (3G), and Google Maps API technology. The system includes six parts: vehicle terminal, communications platform, call center, messaging platform, scheduling platform and management platform. The system is desighed as B/S mode. Windows Server 2003 operating system, SQL Server 2005 database, Microsoft Visual Studio 2008 integrated development environment, ASP.NET & C # development language and Google Maps API are used in this system. The focus of this thesis is the research and improvement of the shortest path algorithm for taxi dispatch system. To solve basic artificial fish-swarm algorithm(AFSA)’s drawbacks of low convergence rate in the latter stage, a large amount of computation and easiness of trapping in local optimal solution, which are all caused by the constant vision of the artificial fish, an improved artificial fish-swarm algorithm based on adaptive vision(AVAFSA) is proposed. In the improved algorithm, only the vision of the preying behavior of artificial fish is adjusted, inorder to make the vision gradually decrease with the increase of the number of iterations of the algorithm. When the value of the vision becomes less than half the initial value, it makes the value be equal to half the initial value. The proposed improved artificial fish swarm algorithm is applied to the static shortest path problem based on road network to provide customers with the best path. Simulation results depict the improved algorithm has a higher convergence rate and a smaller amount of calculation, and is more accurate and stable than the basic AFSA and ant colony optimization (ACO).