Adaptive fuzzy-network-based C-measure map-matching algorithm forcar navigation system

Most car navigation systems estimate the car position from dead reckoning and the Global Positioning System (GPS). However, because of the unknown GPS noise, the estimated position has an undesirable error. To solve this problem, a map-matching method is introduced, which uses a digital road map to correct the position error. In this paper, a novel adaptive-fuzzy-network-based C-measure algorithm is proposed, which can find the exact road on which a car moves. The C-measure algorithm is easy to calculate, and calculation time does not increase exponentially with the increase of junctions. For the experiments, a car navigation system is implemented with a small number of sensors. The real road experiments demonstrate the effectiveness and applicability of the proposed algorithm and the developed car navigation system     

Fusion of Map and Sensor Data in a Modern Car Navigation System

The main tasks of car navigation systems are positioning, routing, and guidance. This paper describes a novel, two-step approach to vehicle positioning founded on the appropriate combination of the in-car sensors, GPS signals, and a digital map. The first step is based on the application of a Kalman filter, which optimally updates the model of car movement based on the in-car odometer and gyroscope measurements, and the GPS signal. The second step further improves the position estimate by dynamically comparing the continuous vehicle trajectory obtained in the first step with the candidate trajectories on a digital map. This is in contrast with standard applications of the digital map where the current position estimate is simply projected on the digital map at every sampling instant.

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GPS/DR组合导航性能增强技术

为了提高全球定位系统(GPS)信号短时中断时地面车辆自主导航精确度,提出了GPS信号中断时采用车辆不完全约束条件和里程仪速度信息作为量测,辅助惯性导航系统实现车辆航位推算(DR)自主导航的方案;推导了该方案的GPS/DR组合导航的卡尔曼滤波方程;并进行了计算机仿真研究和地面车载试验,结果显示GPS信号中断90 s,DR自主导航误差为20 m,能够满足部分地面车辆短时高精确度自主定位要求。     

New Map‐Matching Algorithm Using Virtual Track for Pedestrian Dead Reckoning

In this paper, a map‐matching (MM) algorithm which combines an estimated position with digital road data is proposed. The presented algorithm using a virtual track is appropriate for a MEMS‐based pedestrian dead reckoning (PDR) system, which can be used in mobile devices. Most of the previous MM algorithms are for car navigation systems and GPS‐based navigation system, so existing MM algorithms are not appropriate for the pure DR‐based pedestrian navigation system. The biggest problem of previous MM algorithms is that they cannot determine the correct road segment (link) due to the DR characteristics. In DR‐based navigation system, the current position is propagated from the previous estimated position. This means that the MM result can be placed on a wrong link when MM algorithm fails to decide the correct link at once. It is a critical problem. Previous algorithms never overcome this problem because they did not consider pure DR characteristics. The MM algorithm using the virtual track is proposed to overcome this problem with improved accuracy. Performance of the proposed MM algorithm was verified by experiments.     

面向EVNS的电子地图的设计

分析研究车载导航信息系统电子地图算法,面向EVNS的导航系统中电子地图的建立,以及实现这些功能对电子地图数据库的基本要求及电子地图数据库的建立。以车载导航信息系统的导航电子地图和导航数据库作为重点研究对象．分析导航信息系统中导航电子地图的设计和电子地图的数据组织。     

Choosing the scale and extent of maps for navigation with mobile computing systems

Unlike most paper maps used for navigation, digital maps when displayed on handheld, personal navigation systems do not show the entire mapped extent in a single view, nor are they limited to a fixed map scale. The mapped extent, or footprint of the earth, that appears in any given view is dictated by scale, and there are as many scales as zoom steps. But what drives the choice of scale? We investigate this question first through an assessment of currently available navigation systems, to analyse the consistency or variation among current practices. The vast range of scales and zoom steps found across six software packages indicates an absence of design guidelines, the consequence of which is that users will have a very different experience, with respect to the map, depending on what program they use. Since map representation has been shown to influence spatial behaviour and decision-making, such differences arising from map scale may lead to unintended consequences for navigation system users. We argue that meaningful scales and map extents that incorporate temporal and behavioural aspects of travel as cued by global position system (GPS), can actually convey relevant information to map users. Drawing upon time-geography concepts and real-time data from GPS signals, we explore time-scale bars and isochrones as potential methods of spatiotemporal information delivery to users of personal navigation systems.     

Land-vehicle navigation using GPS

The Global Positioning System (GPS) has made navigation systems practical for a number of land-vehicle navigation applications. Today, GPS-based navigation systems can be found in motor vehicles, farming and mining equipment, and a variety of other land-based vehicles (e.g., golf carts and mobile robots). Each of these applications is discussed and the reader is introduced to some of the issues involved with each one. One particular technical aspect of navigation for land vehicles is discussed. Specifically, the research discussed in this paper presents a quantitative examination of the impact that individual navigation sensors have on the perfomance of a land-vehicle navigation system. A range of navigation sensor performance levels and their influence on vehicle positioning accuracy are examined. Results show that, for a typical navigation system, positioning error is dominated by the accuracy of the position fixes provided by the GPS receiver when GPS position fixes are available and by the rate gyro's bias drift when GPS position fixes are not available. Furthermore, results show that the accuracy of the GPS position fixes has a significant impact on the relative contributions that each dead-reckoning navigation sensor error makes. The implications of these results for navigation system design and sensor design are discussed     

Less is more [intelligent speed adaptation for road vehicles]

The use of sophisticated in-car technology to enforce urban speed limits and improve road safety is an idea whose time could well have come. To the great majority of motorists, speed bumps are, at best, a 'necessary evil'. However, if the results of recent trials in Sweden involving intelligent speed adaptation (ISA) technology are anything to go by then the days of this contentious feature of our urban roads could well be numbered. Between 1999 and 2002 government funding of SEK75m (#5.64m) was provided to install ISA systems in 5000 test vehicles distributed amongst four Swedish municipalities (Borlange, Lidkoping, Lund and Umea), and the results of these trials have apparently greatly exceeded the expectations of even ISA technology's keenest proponents within the Swedish National Road Administration (SNRA). ISA systems are, a combination of several existing technologies being put together in a new way. Many cars at the expensive end of the market are now being provided with satellite navigation systems as standard, where each vehicle is fitted with a Global Positioning System (GPS) transmitter/receiver, so that the precise position of the vehicle can be determined, and a GSM mobile phone link, so that this position can be integrated with a detailed and accurate digital roadmap maintained by the satellite navigation service provider. ISA technology, simply put, merely adds data on speed limits to the digital road map, so that each vehicle 'knows' what the maximum legal speed is on any road that it happens to be travelling along.     

GPS辅助的被动成像导航系统的研究

本文介绍的是一种ＧＰＳ辅助的被动成像导航系统。该系统将ＧＰＳ接收机和被动成像传感器组合在一起，能提供完整的位置、速度、角速度和高度信息。在ＧＰＳ信息的辅助下，不仅解决了被动成像传感器所引起的高度／速度模糊问题，而且还大大简化了求解角速度的方程。本文给出了角速度估计和ＧＰＳ测量噪声对估计精度影响的理论分析和计算机仿真结果。仿真表明，即使在严重的ＧＰＳ测量噪声的影响下，运动参数仍可精确地计算出来。     

彩信与GPS汽车防盗器

系统利用GSM／GPRS模块结合GPS模块、蓝牙模块实行对汽车进行全方位防盗和导航。系统的整体设置通过电话拨打汽车防盗系统号码,接通系统后,将进行语音播报操作提示,实现系统设置与汽车定位,彩信等控制。系统具有震动传感、车边门传感、ACC传感与电平过低传感等触发源,当触发源被触发后,系统可循环拨打用户预设的报警电话,实现汽车报警。该系统具有独特的双电源控制,稳定性高。     

彩信与GPS汽车防盗器

系统利用GSM/GPRS模块结合GPS模块、蓝牙模块实行对汽车进行全方位防盗和导航.系统的整体设置通过电话拨打汽车防盗系统号码,接通系统后,将进行语音播报操作提示,实现系统设置与汽车定位,彩信等控制.系统具有震动传感、车边门传感、ACC传感与电平过低传感等触发源,当触发源被触发后,系统可循环拨打用户预设的报警电话,实现汽车报警.该系统具有独特的双电源控制,稳定性高.     

Promoting navigation system efficiency during GPS outage via cascaded neural networks: A novel AI based approach

Acquiring precise navigation data is a vital process to unmanned vehicles. Although Inertial Navigation System and Global Positioning System (INS/GPS) integrated system provides accurate and continuous navigation solution, the navigation solution accuracy degrades during GPS outages. In order to provide accurate and continuous navigation data during GPS outages, a novel architecture of a cascaded neural networks is proposed to estimate velocity and position errors during GPS signal blockage to handle the time dependency and non-linearity modeling. An ablation study is conducted to grasp the proposed model hyper parameters and their impacts on overall accuracy. Various scenarios are carried out by building and using different grades IMU models. These models are examined through two distinct trajectories for flying and ground platforms to assure the proposed algorithm applicability scope and efficiency. Furthermore, a comparative analysis is carried out based on a real-field test to evaluate the proposed algorithm efficiency and navigation accuracy during GPS outages. The proposed system proves its superiority against the legacy Extended Kalman Filter (EKF) and the advanced Recurrent Neural Network (RNN) based systems in terms of navigation performance during GPS outages periods.     

GPS导航系统中电子地图处理及匹配算法研究

针对传统的车载导航系统对于车辆位置的获取能力存在速度慢、精度低等诸多问题,从匹配算法和电子地图处理两个方面入手给出了相应的解决办法。结果表明,预处理后的电子地图结合我们提出的匹配算法能够极大改善匹配结果的实时性和准确性。     

The Optimal Traffic Information Process System by Using MIMO Algorithm

This paper presented dynamic vehicle information for wireless communication and safe systems by integrating radio frequency identification (RFID) technology. The systems provied different particular and advantage between RFID and other recognition technology. The car black box is the best choice and innovates specific application. It is not only the system can guard car but differentiate the responsibility for car accident event. Furthermore, the car black box is integrated the RFID, general packet radio service (GPRS), Bluetooth, personal digital assistant (PDA) and global positioning system (GPS). The proposed system has been trending the merger goal of digitization. Therefore, it is created a tremendous amount of commercial opportunity. The car black box is also combined multiple-user with real-time navigation information system. The system is integrated the independent real-time traffic information database and Geographical Information System (GIS) through data fusion method. We adopted a traffic information system offering advanced personalized route planning, including added services for traffic jam alerting by means of Short Message Service (SMS) in Global System for Mobile (GSM) communication network. It is shown small and low-cost GSM modules for data process by using the Multiple Input Multiple Output (MIMO), Ant colony optimization (ACO) algorithm, which developed a real-time software solution to help users and evaluation of user preferences for car traffic information system.     

基于ID卡定位的智能汽车自主导航系统设计

基于智能汽车的发展,本文设计了一种智能车的自主导航系统.该系统以ID卡定位为主导,模拟GPS系统来实现自主导航功能,以达到小车寻迹到达指定位置的目的.通过调试,小车可根据路面情况进行寻迹避障和定位,导航精度在3厘米之内.     

On Self-Interested Agents in Vehicular Networks With Car-to-Car Gossiping

As more and more cars are equipped with Global Positioning System (GPS) and Wi-Fi transmitters, it becomes easier to design systems that will allow cars to autonomously interact with each other, e.g., regarding traffic on the roads. Indeed, car manufacturers are already equipping their cars with such devices. Although, currently, these systems are a proprietary, we envision a natural evolution where agent applications will be developed for vehicular systems, e.g., to improve car routing in dense urban areas. Nonetheless, this new technology and agent applications may lead to the emergence of self-interested car owners, who will care more about their own welfare than the social welfare of their peers. These car owners will try to manipulate their agents such that they transmit false data to their peers. Using a simulation environment, which models a real transportation network in a large city, we demonstrate the benefits that are achieved by self-interested agents if no countermeasures are implemented. We then proceed to describe the mechanisms for minimizing the effect of the malicious agents on other agents in the network.      

A Particle Filtering Approach for Joint Detection/Estimation of Multipath Effects on GPS Measurements

Multipath propagation causes major impairments to global positioning system (GPS) based navigation. Multipath results in biased GPS measurements, hence inaccurate position estimates. In this paper, multipath effects are considered as abrupt changes affecting the navigation system. A multiple model formulation is proposed whereby the changes are represented by a discrete valued process. The detection of the errors induced by multipath is handled by a Rao-Blackwellized particle filter (RBPF). The RBPF estimates the indicator process jointly with the navigation states and multipath biases. The interest of this approach is its ability to integrate a priori constraints about the propagation environment. The detection is improved by using information from near future GPS measurements at the particle filter (PF) sampling step. A computationally modest delayed sampling is developed, which is based on a minimal duration assumption for multipath effects. Finally, the standard PF resampling stage is modified to include an hypothesis test based decision step     

MEMS IMU Based Pedestrian Indoor Navigation for Smart Glass

In open air environment, Global Positioning System (GPS) receiver can determine its position with very high accuracy. Inside a building the GPS signal is degraded, the position estimation from the GPS receiver is very erroneous and of no practical use. In this paper, we present an indoor navigation system to track the position of a pedestrian by using built-in inertial measurement unit (IMU) sensors of a smart eyeglass. The device used for this project was an intelligent eye-wear “JINS MEME”. Here algorithm for step detection, heading and stride estimation are used to estimate the position based on the known locations of the walker using Pedestrian Dead Reckoning method (PDR). We have used extended Kalman filters as sensor fusion algorithm, where measurements of acceleration and orientation from IMU are used to track user’s movement, pace, and heading. The results showed that the level of accuracy was entirely acceptable. Average deviancy between the estimated and real position was less than 1.5 m for short range of walk was accomplished. There are some ideas for further development. Increasing the accuracy of the position estimation by palliation of stride length estimation error was identified as the most essential.     

GPS模块在便携式导航系统中的应用

GPS是全球定位系统的简称，目的是在全球范围内对地面或空中目标进行准确定位和监测。文章讨论了GPS模块TU-30的工作原理，介绍了其在便携式导航系统中的应用，给出了这种GPS模块与单片机的接口电路。     

Pedestrian navigation with augmented reality,voice and digital map: final results from an in situ field study assessing performance and user experience

This paper reports on a field study comparing navigation performance and user experience of voice, digital map and augmented reality (AR) interfaces for electronic assistance in the context of pedestrian navigation. The in situ study was conducted with two subsequent experiments in the city of Salzburg along a pre-defined route using a self-implemented smartphone application running on Apple's iPhone 4. The study involved 48 participants aged between 22 and 66 years with different experiences in using smartphones and navigation systems. Navigation performance was measured on a micro-level including information on effectiveness (number and reasons of stops, global positioning system (GPS accuracy), efficiency (walking and task completion time, duration of stops) and satisfaction (NASA Task Load Index, System Usability Scale). A final questionnaire completed the study. Between the first and the second experiment, the application was adapted considering user feedback and the previous findings. Results show that in the context of GPS-enhanced pedestrian navigation, digital map and voice-only interfaces lead to significantly better navigation performance and user experience in comparison to AR interfaces. The study also reveals similar results for digital map and voice-only interfaces given that voice instructions are carefully composed. Results lead to the conclusion that AR is still suffering from usability and hardware issues leading to higher uncertainty of navigating persons. Best navigation performance and user experience can be achieved by combining digital maps and accurate voice instructions.