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排序方式: 共有507条查询结果,搜索用时 31 毫秒
1.
基于图像处理的桥墩防撞预警系统的研究 总被引:1,自引:0,他引:1
利用图像处理硬件设备,通过摄像头将视频信息采入,送入DSP进行分析处理;专门视频信息处理软件,运用各种图像处理技术,进行实时处理分析,对船舶进行实时监控。当船舶进入预警区,经计算机判断处理,提醒监控人员并通过广播对船舶驾驶人员发出警告,避免事故发生。
在图像序列处理技术的开发中,采用软硬件分离的方法,先进行基于Visual C++的计算机软件设计研究;在软件中,研究了船舶检测、船舶跟踪与计算等内容。 相似文献
2.
基于红外搜索系统的被动测距技术研究 总被引:1,自引:0,他引:1
红外搜索系统是一种被动探测系统,量测数据中无目标的距离量;而评判来袭目标的威胁程度离不开其距离量。介绍了基于红外搜索系统的被动测距技术测量目标距离的算法、原理框图以及仿真试验与结果。 相似文献
3.
王庆武 《现代城市轨道交通》2012,(3):21-24
列车运行状态信息系统作为铁路调度生产和辅助决策的重要支撑手段,是提高机车运用效率、保障列车运行安全、充分发挥运用与检修一体化管理模式的优势、提高铁路运营管理能力的必不可少的重要环节。建立符合我国国情和安全装置现状要求并具有高度扩展性的"车对地"、"地对车"、"地对地"的机车运行安全监控闭环系统,全面实现列车实时状态追踪,为运输组织和机车管理提供及时、可靠的指挥依据,为维修、救援等提供决策支持,充分利用现代化的技术手段实现对列车运行状态的监控。收稿日期 相似文献
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5.
Kyuhyun Lee 《运输评论》2021,41(1):27-47
ABSTRACT Monitoring bicycle trips is no longer limited to traditional sources, such as travel surveys and counts. Strava, a popular fitness tracker, continuously collects human movement trajectories, and its commercial data service, Strava Metro, has enriched bicycle research opportunities over the last five years. Accrued knowledge from colleagues who have already utilised Strava Metro data can be valuable for those seeking expanded monitoring options. To convey such knowledge, this paper synthesises a data overview, extensive literature review on how the data have been applied to deal with drivers’ bicycle-related issues, and implications for future work. The review results indicate that Strava Metro data have the potential—although finite—to be used to identify various travel patterns, estimate travel demand, analyse route choice, control for exposure in crash models, and assess air pollution exposure. However, several challenges, such as the under-representativeness of the general population, bias towards and away from certain groups, and lack of demographic and trip details at the individual level, prevent researchers from depending entirely on the new data source. Cross-use with other sources and validation of reliability with official data could enhance the potentiality. 相似文献
6.
Estimation of urban network link travel times from sparse floating car data (FCD) usually needs pre-processing, mainly map-matching and path inference for finding the most likely vehicle paths that are consistent with reported locations. Path inference requires a priori assumptions about link travel times; using unrealistic initial link travel times can bias the travel time estimation and subsequent identification of shortest paths. Thus, the combination of path inference and travel time estimation is a joint problem. This paper investigates the sensitivity of estimated travel times, and proposes a fixed point formulation of the simultaneous path inference and travel time estimation problem. The methodology is applied in a case study to estimate travel times from taxi FCD in Stockholm, Sweden. The results show that standard fixed point iterations converge quickly to a solution where input and output travel times are consistent. The solution is robust under different initial travel times assumptions and data sizes. Validation against actual path travel time measurements from the Google API and an instrumented vehicle deployed for this purpose shows that the fixed point algorithm improves shortest path finding. The results highlight the importance of the joint solution of the path inference and travel time estimation problem, in particular for accurate path finding and route optimization. 相似文献
7.
This paper investigates crowding effect on the path choice of metro passengers. We show people reroute not only to avoid the delay from crowding but also to evade crowding itself. More specifically, a logit model fits best when it uses the transit delay from crowding as well as the passenger load of a connection in addition to the conventional explanatory variables. Also, we demonstrate that crowding decreases the overall welfare of metro passengers. The model is tested on the real path choice data acquired by the recent algorithm by Hong et al. (2015) known to detect the real path choice from Smart Card data in more than 90% of the cases. 相似文献
8.
[目的]智能船舶的航迹跟踪控制问题往往面临着控制环境复杂、控制器稳定性不高以及大量的算法计算等问题。为实现对航迹跟踪的精准控制,提出一种引入深度强化学习技术的航向控制器。[方法]首先,结合视线(LOS)算法制导,以船舶的操纵特性和控制要求为基础,将航迹跟踪问题建模成马尔可夫决策过程,设计其状态空间、动作空间、奖励函数;然后,使用深度确定性策略梯度(DDPG)算法作为控制器的实现,采用离线学习方法对控制器进行训练;最后,将训练完成的控制器与BP-PID控制器进行对比研究,分析控制效果。[结果]仿真结果表明,设计的深度强化学习控制器可以从训练学习过程中快速收敛达到控制要求,训练后的网络与BP-PID控制器相比跟踪迅速,具有偏航误差小、舵角变化频率小等优点。[结论]研究成果可为智能船舶航迹跟踪控制提供参考。 相似文献
9.
The Free-floating Flexible Dual-arm Space Robot is a highly nonlinear and coupled dynamics system. In this paper, the dynamic model is derived of a Free-floating Flexible Dual-arm Space Robot holding a rigid payload. Furthermore, according to the singular perturbation method, the system is separated into a slow subsystem representing rigid body motion of the robot and a fast subsystem representing the flexible link dynamics. For the slow subsystem, based on the second method of Lyapunov, using simple quantitative bounds on the model uncertainties, a robust tracking controller design is used during the trajectory tracking phase. The optimal control method is designed in the fast subsystem to guarantee the exponential stability. With the combination of the two above, the system can track the expected trajectory accurately, even though with uncertainty in model parameters, and its flexible vibration gets suppressed, too. Finally, some simulation tests have been conducted to verify the effectiveness of the proposed methods. 相似文献
10.
基于视频的交通流检测在智能交通系统中具有重要意义。本文针对广泛采用的低位摄像机,提出了一种交通流特性参数的检测分析方法。首先基于三级虚拟检测线和自适应更新率局部背景建模来快速提取车辆特征点并消除活动阴影对提取精度的影响;然后基于Adaboost(Adaptive Boosting,自适应增强)分类器实现特征点按车分组,并在跟踪过程中根据运动特征相关度消除分组误差,获取高精度的车辆轨迹;进而自动生成多车道轨迹时空图并提取各车道交通流的多种特性参数。实验结果验证了算法的高效性;同时,自动生成的多车道轨迹时空图也为更多的交通信息获取和更深入的交通流特性分析提供了有力支持。 相似文献