Rely-Guarantee Reasoning about Messaging System for Autonomous Vehicles

Differential Global Positioning System (DGPS) is a crucial component in the perception system of todays autonomous vehicle (AV). Traditional navigation technique takes advantage of the accurate positioning of DGPS and high-definition (HD) map to facilitate path tracking. However, HD map occupies large storage space due to its extensive information on the detailed structure of the environment, which is extremely costly to deploy onto in-vehicle computing devices. This work proposes a low-cost vector map based navigation framework. By recording the vector map offline, the framework initializes an optimal global route by giving any starting and ending position on the map. During runtime, the computer filters the real-time positioning data from DGPS and tracks the planned path according to geometric rules. Besides, when the Lidar/vision subsystem detects any obstacles, the method dynamically adjusts the local path to realize obstacle avoidance. Demonstrated on an AV testing platform, the proposed method calculates the angle of the steering wheel and transmits the actual commands through CAN bus interface.


 
 
 
 Global Positioning System (GPS) is a very popular outdoor positioning system. Due to the satellites’ errors signal, the Global Positioning System (GPS) receivers determine the accuracy of a current location with about 100 meters in latitude and 156 meters in longitude. In this few years, the technology on autonomous vehicles is rising. Autonomous vehicles need to navigate with high positioning accuracy for preventing any potential danger to road user. So in this paper, Differential Global Positioning System (DGPS) experiment will be introduced for improve the positioning accuracy. Differential Global Positioning System (DGPS) operations compose of Reference Station and Rover Station. Both of the station will use the GPS receiver for receiving the positioning data from GPS satellites and the positioning data collected from Reference Station will be used to calculate the positioning errors and the errors correction will then be transferred to Rover Station to improve the positioning accuracy. The results obtained will be discussed based on the average and range of errors in both latitude and longitude, number of satellites detected, Horizontal Dilution of Precision (HDOP), Vertical Dilution of Precision (VDOP) and the improvement on Differential Global Positioning System (DGPS) at the same time in different day. In four days’ results, it can be seen that the number of satellites detected will be affected by the Horizontal Dilution of Precision (HDOP) and Vertical Dilution of Precision (VDOP) which cause the positioning errors in latitude and longtitude. The average of positioning errors range between -4.165m and 2.925m in latitude and -0.618m and 1.998m in longitude.
 
 
 

Integrating Passive Millimeter Wave camera (PMMW), Global Positioning System (GPS), and Differential Global Positioning System (DGPS) provides a pilot with a visual precision approach and landing in inclement weather conditions conceivably down to CAT III conditions. A DARPA funded, NASA Langley managed Technology Reinvestment Program (TRP) consortium consisting of Honeywell, TRW, Boeing, and Composite Optics Corporations is demonstrating the PMMW camera. The TRW developed PMMW camera displays the runway through fog, smoke, and clouds in day or night conditions. The Global Air Traffic Program Office entered into a Cooperative Research and Development Agreement (CRDA) with Honeywell to demonstrate DGPS. The Honeywell developed DGPS provides precision navigational data to within 1 m error where GPS has 100 m of error. In inclement weather the runway approach is initiated using GPS data until a range where DGPS data can be received. The runway is presented to the pilot using the PMMW image viewed via a Heads Up Display (HUD) or Head Mounted Display (HMD). At a range where DGPS data is available, a precise runway and horizon symbology is computed in the Flight Display Computer and overlaid on the PMMW image. Image processing algorithms operate on the PMMW image to identify and highlight obstacles on the runway. The integrated system provides the pilot with an enhanced situation awareness of the runway approach in inclement weather. When a DGPS ground station is not available at the landing area, image processing algorithms (again operating on the PMMW image) generate the runway and horizon symbology. GPS provides the algorithm with initial conditions for runway location and perspective. The algorithm then locates and highlights the runway and any obstacles on the runway. Honeywell Technology Center is performing research in the area of integrating the PMMW, DGPS, and GPS technologies to provide the pilot with the most necessary features of each system; namely: visibility, accuracy, obstacle detection, runway overlay, horizon symbology and availability.© (1998) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.

It is generally important to get a precise position information for autonomous unmanned vehicle(AUV) in order to run safely. The GPS for getting the position has been using to navigate a vehicle(or AUV). But it is difficult to precisely control the AUV due to large measuring error of the GPS. Therefore, this paper proposes a method to more precisely localize AUV using three low-cost differential global positioning systems (DGPS). The distance errors between each DGPS are minimized as using the least square method (LSM) and the Kalman filter to eliminate a Gaussian white noise. The selected DGPS is cheaper and easier to set up than the RTK-GPS. It is also more precise than the general GPS. The proposed method can correct the relatively position error according to stationary distance of the AUV. For evaluating the algorithm by simulation, the DGPS signal with the Gaussian white noise to any points is generated by the AR model. The corrected position signal can be used to localize and control the AUV on the road.

In order to resolve the problem that DGPS (differential global positioning system) can not be used in the HIL (hardware-in-loop) simulation of aerocraft, but only simulated by math modeling, a method how to use DGPS in HIL simulation was brought forward on the base of GSS7700GPS simulator and NovAtel DGPS receiver. The DGPS simulation system configuration fig of aerocarft was shown.The trial data of single GPS and DGPS was acquired and plotted in the table. Comparing single GPS trial data with DGPS trial data, it improved that DGPS has more positioning accuracy than single GPS. The method realized that the whole DGPS out-of-doors running process could be simulated realistically in static environment of laboratory. The accuracy and reliability of DGPS simulation of aerocraft were improved greatly by using the method.

Intelligent or Autonomous Vehicles are not visionary technologies that may be present in a far away future. From high tech military unmanned systems and automatic reverse parallel parking to cruise control and Antilock Brake Systems (ABS), these technologies are becoming embedded in people's daily life. The methodologies applied in these applications vary widely across areas, ranging from new hardware development to complex software algorithms. The purpose of this work is to present a survey about the benefits and applications of autonomous ground vehicles and to propose a new learning methodology, which provides the vehicle the capacity of learning maneuvers with a human driver. Four main areas will be discussed: system's topology, instrumentation, high level control, and computational vision. Section 1 will present the most common architecture of autonomous vehicles. The instrumentation used in intelligent vehicles such as differential global positioning system (DGPS), inertial navigation system (INS), radar, ladar and infrared sensor will be described in section 2, as well as the techniques used for simultaneous registration and fusion of multiple sensors. Section 3 presents an overview of some techniques and methods used for visual control in autonomous ground vehicles. Section 4 will describe the most efficient techniques for autonomous driving and parking, collision avoidance and cooperative driving. Finally, section 5 will propose a new algorithm based on Artificial Immune Systems, where a fuzzy system for autonomous maneuvering will be learnt by a data set of actions taken by a human driver. In order to validate the proposed method, the results of its application in an automatic parallel parking maneuver will be showed.

Localization of a vehicle is a key component for driving assistance or autonomous navigation. In this work, we propose a visual positioning system (VPS) for vehicle or mobile robot navigation. Different from general landmark-based or model-based approaches, which rely on some predefined known landmarks or a priori information about the environment, no assumptions on the prior knowledge of the scene are made. A stereo-based vision system is built for both extracting feature correspondences and recovering 3-D information of the scene from image sequences. Relative positions of the camera motion are then estimated by registering the 3-D feature points from two consecutive image frames. Localization of the vehicle is finally given by the reference to its initial position. I. INTRODUCTION Localization and tracking of a vehicle are major compo- nents for providing positions, directions and travel informa- tion to the driver. They also serve as key technologies for building autonomous navigation systems. Many approaches have been proposed for locating a mobile robot or a ve- hicle based on various techniques. The most commonly used methods include dead-reckoning techniques, navigation using active beacons, landmark-based navigation, map-based navigation, global positioning system (GPS), and vision- based positioning. Dead-reckoning is a procedure for determining the present location of a vehicle by advancing some previous position through known path and velocity information over a given period of time. Since an odometer and optical sensors for wheel direction detection are easily installed on a vehicle, dead-reckoning is usually a less expensive method for vehicle localization. However, the integration of incremental motion information over time will lead to accumulation of errors. In the case of long distance travel, accumulation of orientation error will make position errors diverge as the increase of driving time. Active beacons such as laser, sonar or radio can be used as media for vehicle or mobile robot navigation. These approaches use triangulation to measure the distance between a number of beacons and the mobile platform and then deter- mine the current location. The problems associated with this technique are the inaccuracy of the distance measurement caused by time-delay of the signals, and the installation and maintenance cost of a large number of beacons required for an area. Satellite based differential global positioning system (DGPS) is probably the most advanced and accurate method for identifying the position and orientation of an object. However, DGPS does not work well if the satellite signals are blocked. This situation commonly happens in the indoor environments, or urban areas with tall buildings, etc. In this work, we propose a visual positioning system (VPS) for vehicle or mobile robot navigation. Different from general landmark-based or model-based approaches which rely on some predefined known landmarks or ap rioriinfor- mation about the environment (e.g., 3-D models of buildings, objects, etc.), no assumptions on the prior knowledge of the scene are made. A stereo-based vision system is built for both extracting feature correspondences and recovering 3- D information of the scene from image sequences. A robust feature tracking method based on simultaneously considering the inter-frame images from the same camera and the stereo image pair from different cameras at a fixed time instant is developed. The relative position of the camera motion is then estimated by registering the 3-D feature points from two consecutive image frames. Our system includes the following basic modules:

Asystem to detectorbit errorsaffecting differential global positioning system integrity isdescribed.Themethod isbased on the use of carrier-phase ranging measurements madeby two or more ground-based referencereceivers separated by short baselines. A dual-frequency, geometry-free widelane approach is used to resolve cycle ambigu- ities present in the carrier-phase measurements. The performance of the proposed integrity monitor is evaluated relative to existing integrity requirements for aircraft landing navigation applications. The results show that real- time protection is achievable against all types of ephemeris errors that can ine uence aircraft precision approach and landing navigation. LTHOUGH initially developed to support military applica- tions, the global positioning system (GPS) has quickly grown into an important and versatile civil navigation utility. The differ- ential GPS (DGPS) technique, in particular, has provided improve- ments in positioning accuracy sufe cient for many demanding ap- plications, including aircraft navigation during precision approach andlandingphasesofe ight.However,forsuchdife cultapplications, highaccuracyisgenerallynotsufe cient.Thenavigationsystemmust also provide a means to ensure its own integrity by reliably detect- ing navigation system failures or anomalies. In this work, detailed consideration is given to the real-time detection of a specie c type of navigation failure: incorrect knowledge of a GPS satellite orbit. Each GPS satellite broadcasts orbit ephemerides so users can compute satellite locations at any time of interest. The satellite lo- cations, together with ranging measurements also obtained from the satellite signals, are used to compute user position. An error in knowledge of satellite position will, therefore, cause a resulting error in the computed user position. Nominally, these errors are negligibly small for DGPS users, but integrity considerations for aircraft precision landing navigation dictate that anomalous con- ditions must be quickly detected. Furthermore, the effects of orbit anomalies differ from those of other navigation failures, for exam- ple, GPS receiver failures, in that orbit errors ultimately cause nav- igation errors that are dependent on the time-varying displacement between the aircraft and ground-based DGPS reference receiver. Therefore, the impact of undetectable orbit errors on navigation must ultimately be assessed separately by each individual aircraft within the DGPS service volume. In this regard, the Federal Avia- tion Administration (FAA), RTCA, Inc., and the International Civil Aviation Organization (ICAO) are developing specie c ephemeris integrity performance standards for DGPS-based aircraft precision landing. The FAA' s local-area augmentation system (LAAS) will serve as the baseline DGPS architecture considered in this paper. Whenever the GPSdata broadcast by the satellites do not contain the correct satellite orbit parameters, an ephemeris anomaly is said to exist. Although there may be a variety of potential causes for such anomalies, for example, unscheduled maneuvers, incorrect or- bit uploads, and faulted data decoding in the receiver, all ephemeris

This article describes experimental results for a real-time, carrier phase, differential Global Positioning System (GPS) aided inertial navigation system (INS). The INS uses inexpensive solid state inertial sensors sampled and integrated at 150 Hz with differential GPS carrier phase measurements as corrections via a complementary filter at 1 Hz. Therefore, the implementation achieves 150 Hz, vehicle state estimates with position accuracy at the centimeter level. Such navigation systems have many application possibilities (e.g., aviation and precision flight, automated mining, precision farming, dredging, satellite attitude control, and automotive or train control). The experimental results described herein are the result of automated vehicle testing on the high occupancy vehicle lanes of the I-15 near San Diego in July 1999.

It is the foundation of intelligent inland waterway management to collect the location information of aids to navigation (AtoN) with high precision. Differential Global Positioning System (DGPS) is an effective approach to improve the accuracy of the Global Positioning System (GPS). This paper provides an accurate positioning method for AtoN through applied the DGPS and ZigBee. In this system, via ZigBee in ZigBee network, AtoN transmits its own GPS data to the GPRS AtoN which has a GPRS module. The GPS reference station receives and decodes the local DGPS data. Then, the GPS data of AtoN and the local DGPS data are broadcasted to the supervision center of AtoN management through GPRS. The accurate position of AtoN is computed in supervision center. This system will improve the positioning accuracy of AtoN in nearby area of reference station. It can be used for alarm of AtoN drift and improve the navigation safety of inland vessels.

Massive investment in 'intelligent' vehicle technologies is going to turn autonomous vehicles into reality in a few years. The insertion of this intelligence at the road vehicles is expected to cause a reduction in traffic accidents due to the mitigation of human drivers errors and imperfections by computerized autopilots. However, autonomous vehicles shall mitigate the existing hazards at the roadway transportation systems while not creating new hazards. Thus, some critical aspects need to be better considered, such as how to ensure safety in this new vehicle paradigm. There is no specific method to analyze and assure the safety levels of the autonomous vehicle system. Despite the ISO 26262 - a new safety standard that specifies requirements and activities throughout the road vehicles development lifecycle - it cannot be applied to the autonomous road vehicles scope. This paper proposes a design strategy that may be used at the architecture design level of autonomous vehicles that may facilitate the development, analysis and, consequently, safety level assuring. The main idea is to implement an independent module - the Autonomous Vehicle Control (AVC) - that is going to both interact with the vehicle's systems and create a protection layer that is independent of the way the vehicle's system was developed. So, the AVC could be used with any autonomous vehicle system and could be tested individually. This strategy is based on both recommended practices published by Society of Automotive Engineers (SAE) and on approaches used on other transportation system domains. Another important point is that the proposed module will be intended, in principle, for fully autonomous cars (high levels of driving automation). So, it is expected that, in the future, the proposed module can be used to develop a safety software standard or to suit the existing ones to the needs of autonomous road vehicles.

GPS is a technique that has become very popular for outdoor positioning. Due to the error in satellite signal, the GPS receivers determine the accuracy of a current location with about 100 m in latitude and 156 m in longitude. Autonomous vehicles depend on positioning accuracy in navigation tracking. Inaccuracy of positioning will cause the autonomous vehicles moving in dangerous way. So in this paper, Differential Global Positioning System (DGPS) experiment will be introduced to improve the accuracy of the positioning data. In the experiment, reference station and rover station will receive the positioning data from GPS satellites and the positioning data collected from reference station will be used to calculate the errors and the errors correction will then be transferred to rover station to improve the accuracy of positioning data. The results obtained will be discussed based on the range and average of positioning errors and the Differential Global Positioning System (DGPS) improvement at different time.

본 논문에서는 국제해사기구(IMO), 국제항로표지협회(IALA) 등 국제기구의 DGNSS 서비스 요구성능 증가에 기술적으로 대처하고, 해상교통안전 증대를 위하여 선박자동식별시스템(AIS)의 기지국 시스템에서 DGPS 기준국 기능을 수행할 수 있는 효과적인 방안을 제안한다. 본 논문에서 제안하는 방식은 DGPS 기준국에서 제공하는 보정 정보를 네트워크를 통하여 AIS 기지국에서 수신하고, 수신된 보정정보를 단순히 해상 선박의 AIS 단말기에 중계하는 방법이 아니라 AIS 기지국에서 커버리지 내의 선박에 최적화된 보정정보를 생성하여 전송하는 방법이다. 이를 구현하기 위하여, 본 논문에서는 먼저 DGPS 기준국과 네트워크를 통해 연결되는 AIS 기준국을 설계하고, AIS 기준국에서 보정정보를 생성하기 위한 알고리즘을 제안한다. 그리고 DGPS 기준국 보정정보의 실측 데이터를 기반으로 제안한 알고리즘의 성능평가를 수행하고 그 결과를 제시한다. 마지막으로 제안한 시스템의 효율적 적용 방안에 대해 논의한다. In order to prepare for increasing performance requirement for Differential Global Navigation Satellite System (DGNSS) services of International Maritime Organization (IMO) and International Association of Lighthouse Authorities (IALA), this paper focuses on design of network-based Automatic Identification System (AIS) reference station system that can perform the functionality of Differential Global Positioning System (DGPS) reference station in an AIS base station system. AIS base station receives the differential corrections from the DGPS reference station, and it is not a method for transmitting the received differential corrections to onboard AIS units, but it is a method for generating the optimized differential corrections for onboard AIS units in AIS coverage. Therefore this paper proposes an algorithm for generating the differential corrections at AIS reference station, and performs the performance assessment of the proposed algorithm based on DGPS correction data measured from a DGPS reference station. Finally this paper discusses the test results and efficiency of the proposed system.

A Control survey is a survey operation that is carried out in order to establish position of points with a high degree of accuracy in order to support activities like mapping and map revisions, property boundary surveys, construction projects and so on. Control densification is a continuous exercise in the field of geomatics. This forms the basis upon which other geomatics and engineering activities geared toward development are referenced. This study is aimed at determining the coordinates of existing control points network along Ayetoro / Egbeda Atuba road using dual frequency GPS and Total Station with a view to comparing the accuracies of DGPS and Total Station using statistical analysis to determine which one has better accuracy. The Objectives of the study are to locate the existing control points, to collect the information/coordinates of the existing control points, and to carry out the observation using DGPS and Total station and process/compute the final coordinates and compare the results by using statistical analysis. The methodology that are adopted for this project is Satellite Positioning Technology using Differential Global Positioning System (DGPS) and Total Station. And the acquired data was processed and adjusted. The statistical analysis was used to compare the result obtained from DGPS and Total Station with the data collected from the Ministry of Land and Housing. The result of the analysis shows that DGPS has better accuracy. It is recommended that whenever more suitable and accurate method of measurement is to be employed, the DGPS method should be selected as this study has demonstrated and compared the accuracy of the two methods and showed that the DGPS method is better.

Several techniques for the implementation of Differential Global Positioning System (DGPS) have been developed and demonstrated to significantly improve the positioning accuracy of the GPS system. The concept of Wide Area DGPS (WADGPS) has provided a practical approach for the development of a world wide network of the DGPS schemes. Current plans are to implement WADGPS under the auspices of Wide-Area Augmentation System (WAAS) in the United States of America and as the Future Air Navigation System (FANS) throughout the rest of the world under the sponsorship of the International Civil Aviation Organization (ICAO). The operations of the WAAS and FANS systems entail the set up of additional infra structure, and a commitment of significant financial and other resources. For small countries like Singapore, a preferred approach embodied in the concept of Small Area DGPS (SADGPS) has been suggested. The SADGPS aims to develop an autonomous DGPS controller which will eliminate the need for transmission of DGPS corrections in real time and thus provide a more robust as well as economical method to improve the performance of the basic GPS system. The investigation of SADGPS has been ongoing at the Nanyang Technological University in Singapore. Earlier, it was demonstrated that limited success for the SADGPS could be obtained by the application of constant corrections to the coordinates of points located within a small area. However, performance was sensitive to the brands of the commercial GPS receivers used. For some types of GPS receivers, significant improvement in accuracy was possible, whereas, for others no discernible improvement could be demonstrated. This paper presents the design of an intelligent SADGPS system based on the technology of artificial neural networks (ANNs). This SADGPS controller reduces the errors of basic GPS system below 10 meters and performs equally well for different brands of the GPS user equipment. To the author's knowledge this is the first published application of ANNs to DGPS.