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研究存在障碍物的三维空间的最短路径规划,并采用蚁群算法解决这一问题。路径规划问题是计算机领域内的经典问题。它可以描述为已知起始点、c以及环境信息,并确定一条从起始点到目标点的线路。一般来说,所规划的路径必须满足距离最短或代价最小的目标。路径规划技术有着广泛的应用,涉及我们的生活、工作、科研和娱乐等方面。 相似文献
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近年来,作为人工智能领域一个分支的最短路径探索仍值得做更进一步的讨论和研究,最短路径问题是给定的网络图中寻找出一条从起始点到目标点之间的最短路径。在最短路径的算法之中,各个算法也都具有各自的优点和适用性。针对Dijkstra算法、蚁群算法、A*算法的特点,经过分析与研究得出,A*算法在最短路径寻优方面比其它路径寻优效率更高,对A*算法的程序实现,为人工智能领域以及机器人路径应用方面提供了重要的实际应用参考价值。 相似文献
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研究了MIROSOT实时系统、二维的比赛环境中的蔽障路径规划问题,首先利用可视图法进行模型抽象,然后利用动态规划的思想,把路径规划转换成多阶段的决策问题,对于每个阶段的子问题,都可以用可视的搜索机制来求解,最后对求解结果进行评估,得到最短路径。对算法的设计及实现进行了仿真,仿真实验验证了该算法的可行性和有效性。 相似文献
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针对复杂工作环境中的自动化仓库路径规划和协作问题,根据蚁群算法在路径选择上可以很快找到最短路径的特征,提出运用蚁群算法,建立自动化仓库路径规划模型,并进行模拟研究,得到最短路径解,同时也进一步验证了蚁群算法的有效性和实用性。 相似文献
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本文介绍了GPS／GIS／GPRS技术在城市公交系统中的应用,并且引入了蚂蚁算法在最短路径算法中的应用一鉴于GPS／GIS／GPRS的功能以及最短路径算法的优势．把GPSIGIS／GPRS技术和最短路径算法引入城市公交系统中,能更容易地处理旅客发送的各个环节,并对其中涉及的问题进行有效管理和决策分析,使得城市公交系统得到优化 相似文献
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铺沙车在日常生活中利用较多,其路径的选择关系到铺沙工程的成本.为了降低成本,利用求解欧拉回路的改进方法,建立了求最短路径的单目标规划模型.设计了lingo优化算法,规划出一条最短路径.考虑到运沙车单次运输量的限制及车子载重量与费用之间的关系,设计了求解该问题的遗传算法,通过建立时应模型,从车辆数目、运输量、运输次数三方面,使铺沙车路径最短,在不同的条件下,求出对应的最优路径和最小费用. 相似文献
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提出一种基于多叉树Pareto最优解集的火灾扑救路径规划算法,对火灾现场的环境地图和火灾演化态势进行重构,实现对路径的优选,采用Pareto最优解集,构建基于多叉树Pareto最优解集的火源动态发展态势下的火灾扑救路径规划模型。实验结果表明,该模型能快速实现对火源热点的识别,并且规划路径能有效规避复杂建筑障碍物的干扰,实现对火灾扑救路径的最优选择。在动态未知环境中,对火灾扑救路径的规划和选择能达到最优,路径最短,分段较少,能有效地避免复杂建筑物的阻挡,有效节省了火灾扑救时间。 相似文献
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对于旅行商问题,即旅行者由起点出发,经过所有给定的点之后,最后再回到原点的问题,该问题属于最短路径问题。本文章通过建立0-1规划模型来对旅行商问题进行求解,根据问题的具体要求,列出约束的方程组,由lingo计算结果,求出最短路径并得到最短路程。 相似文献
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基于遗传算法的最短路径问题求解实现 总被引：1，自引：0，他引：1
文章应用遗传算法求解图论中的最短路径问题,并给出了该算法在解决这一问题的具体实现,使用该算法可以很快地求出一批最短路径集。 相似文献
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《Information processing & management》2023,60(3):103243
The detection and identification of traffic signs is a fundamental function of an intelligent transportation system. The extraction or identification of a road sign poses the same problems as object identification in natural contexts: conditions of illumination are variable and uncontrollable, and various objects frequently surround road signs. These difficulties make the extraction of features difficult. The fusion of time and space features of traffic signs is important for improving the performance of sign recognition. Deep learning-based algorithms are time-consuming to train based on a large amount of data. They are difficult to deploy on resource-constrained portable devices and conduct sign detection in real time. The accuracy of sign detection should be further improved, which is related to the safety of traffic participants. To improve the accuracy of feature extraction and classification of traffic signs, we propose MKL-SING, a hybrid approach based on multi-kernel support vector machine (MKL-SVM) for public transportation SIGN recognition. It contains three main components: a principal component analysis for image dimension reduction, a fused feature extractor, and a multi-kernel SVM-based classifier. The fused feature extractor extracts and fuses the time and space features of traffic signs. The multi-kernel SVM then classifies the traffic signs based on the fused features. Different kernel functions in the multi-kernel SVM are fused based on a feature weighting procedure. Compared with single-core SVM, multi-kernel SVM can better process massive data because it can project each kernel function into high-dimensional feature space to get global solutions. Finally, the performance of SVM-TSR is validated based on three traffic sign datasets. Experiment results show that SVM-TSR performs better than state-of-the-art methods in terms of dynamic traffic sign identification and recognition. 相似文献
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《Journal of The Franklin Institute》2023,360(7):4973-5000
In recent years, regional traffic congestion has become increasingly frequent, which seriously affects the safety and efficiency of urban vehicles. Therefore, traffic flow prediction methods based on artificial intelligence are widely used in traffic management. However, the existing traffic flow prediction methods need to collect raw data, which involves risks of vehicle privacy leakage. Federated learning, which shares model updates without exchanging local data, has gradually become an effective solution to achieve privacy protection. A federated learning traffic flow prediction model for regional transportation systems is proposed in this paper. At the same time, due to the emergence of highly intelligent automatic driving vehicles, a vehicle scheduling system, which can control the departure and routes of vehicles in urban regions is developed in the proposed approach. A road weight measurement method combined with real time traffic information is introduced to optimize the driving routes of vehicles to reduce the average travel time. Additionally, departure strategy, is another factor that has a great influence on traffic efficiency, but is usually ignored in the past, and is also carefully compared and studied in this paper. The numerical results illustrate that the proposed schemes can effectively improve the privacy protection ability of model updates, reduce the scheduling completion time by using the traffic flow prediction model, and realize the comparative research between departure strategies, which provides a reference for developing a safe and efficient regional transportation system. 相似文献
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武汉理工大学交通运输专业主要就业方向为国际航运业。文章通过对国际航运业中重要指数—指数——BDI和该校交通运输专业就业情况的分析研究,发现BDI指数与交通运输专业就业两者之间存在正相关关系。通过对BDI指数的合理预测,为交通运输专业的就业提出了建议和意见,以期能够帮助该专业学生就业。 相似文献
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生态交通系统以人流物流为核心,讲究车、路、站、能源、管理等要素与人、经济、自然的协调,其目标是生态安全、绿色出行、和谐交通。居民以"慢行+公交"生态出行理念的实现,需从规划、技术上扩充步行、自行车与公共交通的生态位,同时采用限行、收费方式压缩轿车的生态位。效仿公交式的物流配送网络建设,既是对轴辐式配送网络的完善,也是货运从独立经营到共同配送的良性生态演化。客运与货运的生态位重叠,可通过时、空维数的部分分离来减缓竞争。 相似文献
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《Information processing & management》2022,59(1):102750
In the last few years, intelligent transport systems (ITS) have drawn growing attention, and these applications would have a clear and more comfortable experience for transportation. ITS provides applications with a chance to address the future condition on the route beforehand. The major issues in ITS to accomplish a precise and effective traffic flow prediction system are essential. Therefore, in this paper, a machine learning-assisted intelligent traffic monitoring system (ML-ITMS) has proposed improving transportation protection and reliability to tackle several challenges. The suggested ML-ITMS uses mathematical models to improve the accuracy estimation of traffic flow and nonparametric processes. The Machine Learning-based (ML) method is one of the best-known methods of nonparametric. It requires less prior information about connections between various traffic patterns, minor estimation limitations, and better suitability of nonlinear traffic data features. Human-Robot Interaction (HRI) helps resolve crucial issues concurrently on both the customers and service supplier levels at both ends of the transport system. Thus the experimental results show the proposed ML-ITMS to enhance traffic monitoring to 98.6% and better traffic flow prediction systems than other existing methods. 相似文献
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我国智能交通系统专利状况分析 总被引：1，自引：1，他引：0
专利信息能够从一个侧面反映技术发展的趋势变化。通过中国专利检索系统(CPRS)中公开收录的专利数据,对智能交通系统主要是城市道路智能交通系统中的交通信息采集技术、交通信息处理技术、交通管理技术和交通信息服务技术等4个重点领域的专利申请情况分别进行研究。文章通过对专利申请态势、国内技术分布和国外来华专利布局进行对比分析,发现ITS领域存在的专利机会和风险,提出技术布局策略和发展建议。 相似文献
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识别中国交通碳排放影响因素，将其分解为能源结构、（交通）能源强度、交通强度、经济城市化、人口城市化、土地城市化6个驱动因素，分析不同脱钩状态下各因素驱动效果尤为关键，其中，所采用的广义费雪指数（GFI）因素分解法具有消除残值、分解更完全的优势。研究发现，中国交通碳排放持续增长，但理想脱钩状态省份从0个上升到8个；经济和土地城市化是阻碍碳减排最关键因素，人口城市化、交通强度、能源结构促进碳减排；能源强度、交通强度是形成不同脱钩状态主因。构建“高效、紧凑、智能”城市交运体系有助于交通部门更早实现碳达峰。 相似文献
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城市混合交通流诱导系统的研究 总被引：4，自引：0，他引：4
借鉴国外发达国家关于交通流诱导系统的成功经验,结合我国城市交通特点,提出了在我国开展城市交通机非混行的交通流诱导系统研究的内容,结构以及进行诱导模型与算法研究的新思路,为进一步研究我国城市交通机非混合的交通流诱导系统进行必要的基础准备。 相似文献