Route Navigation Research Articles

Smart Approach for Finding Indoor Navigation Using BLE for Visually Impaired Person

In day to day life, the problems faced by the visually impaired persons are increases due to the huge growth in urbanization in cities. Even normal person also gets confuse sometimes if they come across to the new locations, to handle this problem, in this paper, we have proposed a robust system which will gives help to user while navigating in huge complexes. This system uses BLE(bluetooth low energy) devices to communicate with the hardware present at user and then it will direct the route to the user. The process includes user interaction through voice for the input location after that system will find desired location of user by connecting the hardware to various BLE devices and depending upon the signal strengths from each BLE user will be get navigated. If the range of BLE devices get less than that means that user is going away from that BLE device and similarly if the range of particular device is getting increase then it means that user going towards the BLE device. Now to get accurate result we are implementing Three Dimensional Triangulation Technique where the hardware present at user will simultaneously connect with multiple BLE devices and then find the required route for navigation. Along with this we are providing IR(infra-red) SONAR sensors through which we can find any obstacle that comes between the user and its navigation. We have added buzzer and LED lights to notify the obstacle to others.

Direct Access Embolization of Intracranial Vascular Pathology: Preliminary Experience and Technical Notes

Abstract INTRODUCTION Transarterial embolization is widely used for definitive or adjunctive treatment of intracranial vascular pathology and is most commonly performed via the transfemoral approach. However, the ability to treat the lesion successfully depends significantly on the navigation of microcatheters into the distal circulation. Vascular tortuosity oftentimes precludes one's ability to position a microcatheter near the target lesion. In these cases, embolization relies on the ability of the embolysate to travel a fair distance before reaching the target lesion. METHODS We describe our preliminary experience with direct access embolization using a hybrid operating/bi-plane angiography suite. A craniotomy is performed to access and isolate the feeding artery. A microcatheter is inserted into the vessel and navigated to the target lesion. Embolization proceeds using bi-planar angiography. RESULTS Direct access embolization was attempted in 2 patients (45 M, 64 M) during treatment of a dural arteriovenous fistula and an arteriovenous malformation. Three treatments were performed (1 for dAVF, 2 for AVM) using Onyx (Medtronic; Dublin, Ireland) involving 4 vascular pedicles. The dAVF was successfully occluded via this approach. Significant nidal penetration/embolization was achieved in the AVM allowing for complete surgical resection. There were no complications related to this procedure. CONCLUSION Direct access embolization is an innovative technique combining both open and endovascular treatment of intracranial vascular pathology. It can be used in instances where difficult vascular anatomy preclude traditional transarterial routes of navigation. Further investigation is required to better define the safety, efficacy, and best practices of this novel technique.

Techno-economic analysis of PV systems integrated into ship power grid: A case study

The integration of a photovoltaic (PV) system into a ship power grid has recently become an important strategy of saving energy and reducing emissions from ships. Since the close relationship between the energy derived from the PV system and the navigation plans of ships including location, navigation routes and times, the techno-economic evaluation of the PV systems integrated into ship power grid is very important to ensure their proper application in ships. In this study, a ship-PV grid-connected power system incorporating in the COSCO TENGFEI pure car and truck carrier is selected as a case to conduct a comprehensive techno-economic analysis and an environmental performance assessment based on single and multi-criteria evaluation methods. Taking into account the uncertainty of navigation plan, the techno-economic efficiency of the power system along six main navigation routes are evaluated separately. The evaluation results show that the hybrid power system has high financial feasibility and environmental performance. Furthermore, the Asia-Malacca-Gibraltar-Europe navigation route has the best feasibility while the Asia-Bering-Europe navigation route has the worst feasible among the six main navigation routes. This case study provides a reliable reference for investment of hybrid power system.

Reproducibility of a Real Case of an Oil Spill during Vessel Supply Operation in an Estuarine Zone

The global transportation of fossil fuels occurs mainly by sea and grows annually, along with the risks to the marine ecosystems, especially in the vicinity of navigation routes. Numerical simulations able to reproduce realistic oil spill scenarios can be utilised for planning risk mitigation actions. This study is based on simulating the behaviour and weathering rates recorded during the first 24 h after an oil spill that occurred in an estuarine region. The numerical system used is the ECOS (Easy Coupling Oil System) oil spill model coupled to the three-dimensional hydrodynamic model Telemac-3D. The hydrodynamic results were analysed considering wind velocity fields and currents, which are the dominant forces in the displacement and behaviour of the oil. The reproducibility of the oil leak was confirmed by comparing the results of the simulations with the official environmental emergency report of the accident. The strong correlation between the simulation and the report showcases the capacity of the simulation methodology to reproduce real case scenarios of oil spills.

Localization and Navigation in Autonomous Driving: Threats and Countermeasures

With the growing number of research studies on autonomous driving, a lot of new technologies for self-driving cars are also constantly emerging. While significantly promoting the development of autonomous vehicles, these emerging technologies also have potential vulnerabilities, which may bring up some nonnegligible security threats. Loopholes existing in localization and navigation technologies, which are the key elements of route planning and navigation, could be utilized by adversaries to manipulate autonomous driving navigation by hijacking valuable vehicles, goods, or even target characters. Toward this end, we provide in this article a basic guide summarizing the security threats and attack schemes, and we propose countermeasures specifically for localization and navigation technologies in autonomous vehicles. After that, we present a novel route spoofing attack that could also be implemented against future autonomous driving navigation. With such implementation, we demonstrate that effectively, routes of targeted drivers can be usurped and hence mislead drivers to take a wrong route, go by a malicious place, and even be tracked in real time.

Experiment on People’s Selection of Route Landmarks from Different Types of Geospatial Pictures

Abstract. Different types of geospatial pictures, such as maps and aerial imagery, have varying potential to provide spatial knowledge for the viewers. Our earlier review has assessed different common types of geopictures with regard to their support for acquiring different types of spatial knowledge (Kettunen et al., 2012). The assessment was based on previous literature about geopicture experiments as well as analytical itemization of the information available on the pictures as a function of picture characteristics, namely vantage point, number of visible vertical features, and visual realism. In addition to the actual assessment, the review concluded that there is an important shortage of empirical evaluations on spatial knowledge acquisition from geopictures, which lag we are addressing with the experiment described here.The aim of the experiment is to find out what kind of geospatial features, or landmarks (see Presson and Montello, 1988; Richter and Winter, 2014), people read from geopictures, does reading differ between pictures, and how does it differ. For the experimental task, we chose a common map activity of planning navigation for walking through an urban route. The stimuli are five different types of common geopictures with both aerial vertical and aerial oblique vantage points as well as with both abstract and photorealistic levels of visual realism (Figure 1). Five routes are to be planned in different areas of city of Helsinki so that a different geopicture type is shown for each route. The pictures are shown as corridors surrounding the shortest walking route.The participants have been recruited from expert and non-expert social media groups and e-mail lists, being called to be over 18 years old. The background questionnaire has asked about their age, gender, possible visual disorders, and frequency of use for each type of map in the experiment.The experimental design for measuring the effect of geopicture type was built randomized and between-participants so that each participant completes series of five pictures, each of different type, in randomized order, and from different geographical areas. Two rounds of five pictures are shown: first, to measure the actual selection of landmarks, and second, to investigate the level of recall of the selected landmarks later. The procedure of the experiment is the following (Figure 2): 1) Introduction, 2) Consent to participate, 3) Training trial of the landmark selection task (1 picture), 4) Testing trials of the landmark selection task (5 pictures), 5) Training trial of the selection recall task (1 picture), 6) Testing trials of the landmark selection task (5 pictures), 7) Background questionnaire, and 8) Thanks and feedback. The Start and End points of the routes are drawn on the pictures (Figure 1) and the participants are asked to plan the shortest route between the points along roads and paths, to point 3–7 features along the route in navigation route for being able to navigate the route, and to enter common names for the features after pointing each feature. Response times, pointed coordinates, and feature names are recorded in order to analyze the participants’ answers.The presentation at the ICC2019 conference will introduce preliminary results of the conducted experiment, reflect them on the previous studies on maps and routing and discuss their implications on the design of map contents from the viewpoint of route planning. The results will build empirical foundation about differences in reading of geospatial picture types, and for selecting appropriate features to be drawn on maps.

The Re-Scheme Project for the Mexican Cartography Plan

Abstract. The Mexican Navy is empowered by its current federal legislation to produce charts over military and civilian ports within Mexico. To fulfil this task, a National Nautical Cartography Program has been developed. The program currently consists on a production and maintenance scheme of 254 nautical charts at scale within general, coastal, approach, harbour and berthing usage bands. The design of the National Nautical Cartography Program is the result of port infrastructure and maritime traffic analysis that also follows the International Hydrographic Organization (IHO) recommendations published in the “Regulations for International (INT) Charts and Chart Specifications of the IHO” S-4. This paper will present details on the re-scheme project that includes Electronic Navigation Chart (ENC) cell footprints and their compilation scales in order to produce a seamless chart coverage along the coastlines of Mexico and a more efficient production workflow. The re-scheme project intends to provide more detail to existing charts and also provide current updates to ever-changing port infrastructure of the country and the emergence of new navigation routes for commerce and tourism. Additional benefits of the re-scheme project include: Providing an orderly design of ENC cell for program management, standardizing progressive scales with chart display, and establishing better international collaboration between Mexico and its neighbours on charts along the borders and INT charts.

Privacy Implication of Location-Based Service: Multi-Class Stochastic User Equilibrium and Incentive Mechanism

As a tool to assist traffic guidance and improve service quality, location-based service (LBS) platforms such as route navigation apps rely heavily on the collection and analysis of users’ location/trajectory information, which may evoke privacy concerns. Because of such privacy concerns, users may choose not to provide their information. In certain cases, this may lead to the problem of insufficient data for LBS applications (e.g., travel time estimation). To address this issue, the paper develops a modeling framework to quantify the levels of privacy for mixed user groups and proposes an incentive mechanism to encourage users to provide their location/trajectory information. It is assumed that LBS users have smaller travel time perception error but experience some extra privacy costs compared with the non-LBS users. A bi-level optimal incentive model with stochastic user equilibrium and elastic demand is developed to capture the mixed behavior of multi-class network users. The problem is solved using a meta-heuristic approach combined of genetic algorithm, successive average algorithm, and multiple behavior equilibrium assignment algorithm. The results reveal that the modeling framework can capture the mixed behavior of groups with different privacy levels. The proposed incentive mechanism is able to ensure sufficient data, and simultaneously minimize the required incentive.

Accurate Detection of Road Network Anomaly by Understanding Crowd's Driving Strategies from Human Mobility

There are thousands of road closures and changed traffic rules that impact vehicle routing every day. Detecting the road closures and traffic rule changes is essential for dynamic route planning and navigation serving. In this article, we propose a driving-behavior modeling-based method for accurately and effectively detecting the road anomalies. In the first step, we detect the areas of anomalies by using the deviation between drivers’ actual and expected behaviors. To discover the cause of anomalies, we explore the drivers’ short-term destination and find the crucial link pairs in anomalous areas through a novel optimized link entanglement search algorithm, namely, the Select Link Entanglements (SELES) algorithm. Finally, we analyze the crowd's driving patterns to explain the road network anomalies further. Experiments on a very large GPS dataset demonstrate that the proposed approach outperforms the existing methods in terms of both accuracy and effectiveness.

The Embodied Brain of SOVEREIGN2: From Space-Variant Conscious Percepts During Visual Search and Navigation to Learning Invariant Object Categories and Cognitive-Emotional Plans for Acquiring Valued Goals.

This article develops a model of how reactive and planned behaviors interact in real time. Controllers for both animals and animats need reactive mechanisms for exploration, and learned plans to efficiently reach goal objects once an environment becomes familiar. The SOVEREIGN model embodied these capabilities, and was tested in a 3D virtual reality environment. Neural models have characterized important adaptive and intelligent processes that were not included in SOVEREIGN. A major research program is summarized herein by which to consistently incorporate them into an enhanced model called SOVEREIGN2. Key new perceptual, cognitive, cognitive-emotional, and navigational processes require feedback networks which regulate resonant brain states that support conscious experiences of seeing, feeling, and knowing. Also included are computationally complementary processes of the mammalian neocortical What and Where processing streams, and homologous mechanisms for spatial navigation and arm movement control. These include: Unpredictably moving targets are tracked using coordinated smooth pursuit and saccadic movements. Estimates of target and present position are computed in the Where stream, and can activate approach movements. Motion cues can elicit orienting movements to bring new targets into view. Cumulative movement estimates are derived from visual and vestibular cues. Arbitrary navigational routes are incrementally learned as a labeled graph of angles turned and distances traveled between turns. Noisy and incomplete visual sensor data are transformed into representations of visual form and motion. Invariant recognition categories are learned in the What stream. Sequences of invariant object categories are stored in a cognitive working memory, whereas sequences of movement positions and directions are stored in a spatial working memory. Stored sequences trigger learning of cognitive and spatial/motor sequence categories or plans, also called list chunks, which control planned decisions and movements toward valued goal objects. Predictively successful list chunk combinations are selectively enhanced or suppressed via reinforcement learning and incentive motivational learning. Expected vs. unexpected event disconfirmations regulate these enhancement and suppressive processes. Adaptively timed learning enables attention and action to match task constraints. Social cognitive joint attention enables imitation learning of skills by learners who observe teachers from different spatial vantage points.

Enhancing Indoor Inertial Odometry with WiFi

Accurately measuring the distance traversed by a subject, commonly referred to as odometry, in indoor environments is of fundamental importance in many applications such as augmented and virtual reality tracking, indoor navigation, and robot route guidance. While theoretically, odometry can be performed using a simple accelerometer, practically, it is well-known that the distances measured using accelerometers suffer from large drift errors. In this paper, we propose WIO, a WiFi-assisted Inertial Odometry technique that uses WiFi signals as an auxiliary source of information to correct these drift errors. The key intuition behind WIO is that among multiple reflections of a transmitted WiFi signal arriving at the WiFi receiver, WIO first isolates one reflection and then measures the change in the length of the path of that reflection as the subject moves. By identifying the extent through which the length of the path of that reflection changes, along with the direction of motion of the subject relative to that path, WIO can estimate the distance traversed by the subject using WiFi signals. WIO then uses this distance estimate to correct the drift errors. While researchers have previously proposed to use WiFi signals to correct drift errors, prior schemes suffer from one or more of the following six limitations: they 1) do not work indoors, 2) require manual exhaustive fingerprinting, 3) are not resilient against changes in environment including human movements, 4) do not work on commodity WiFi devices, 5) require multiple access points, and/or 6) can measure distance traversed by humans but not by non-human subjects. WIO addresses all of these limitations. We implemented WIO using commodity devices, and extensively evaluated it in a wide variety of complex indoor scenarios on both human and robotic subjects. Our results demonstrate that WIO achieved an average error of just 6.28% in estimating the distances traversed by the subjects.

CONSTRUCTION OF OBSTACLE ELEMENT MAP BASED ON INDOOR SCENE RECOGNITION

Abstract. Route planning and navigation in indoor space have become a hot topic recently. To accomplish this task, a map and a real-time detection system are needed. Due to Lidar systems’ high efficiency in data acquisition, Lidar sensors have become an indispensable part of an object detection system. In this paper, we use Lidar points to generate obstacle maps. The obstacle maps can be used as a reference for route planning and navigation. To identify single objects more precisely, a deep network combined PointNet with Markov Random Field (MRF) is designed in our work to classify Lidar points. Then, single objects are segmented by using the Euclidean clustering method. After that, the prior rules and derived criteria we summarized from large amount images are used to determine objects’ kind between Influence Movement Obstacles (IMO) and Non-Influence Movement Obstacles (N-IMO). Finally, objects are projected into a 2D plane to generate obstacle maps. To evaluate the performance of our method, experiments were performed on the S3DIS dataset of Stanford University. The results show that our method greatly improves the overall accuracy compared to the original PointNet model, and can generate high-quality obstacle maps.

Geomagnetism-Based Indoor Navigation by Offloading Strategy in NB-IoT

Most indoor navigation technologies need to provide structure maps of buildings, but it is difficult to obtain these structure maps in practice. Therefore, we design a geomagnetism-based indoor navigation system without structure map of buildings by applying offloading strategy in narrow band Internet of Things. Why the geomagnetic signal can be used to achieve indoor navigation is due to its stability. We divide the indoor navigation into two parts: 1) the construction of signal fingerprint database and 2) the user navigation. First, the navigator carries out the signal acquisition of navigation route, and transfers the original signals to cloud server so as to construct the fingerprint database. Second, users can choose online navigation or offline navigation according to the actual situation. When choosing offline navigation, the users will employ dynamic time warping algorithm for fingerprint matching. When users would like to obtain better navigation results, they can choose online navigation. In this case, navigation system will offload the users’ sampling data to remote cloud, and then the cloud matches the fingerprint of geomagnetic signals by using particle filter algorithm and sends the computation results to the users so as to indicate the users’ moving direction. Experiment results demonstrate that our method is effective and the turning error is only 5 cm.

Navigation in Indoor Environments: Does the Type of Visual Learning Stimulus Matter?

This work addresses the impact of a geovisualization’s level of realism on a user’s experience in indoor navigation. The key part of the work is a user study in which participants navigated along a designated evacuation route previously learnt in a virtual tour or traditional 2D floor plan. The efficiency and effectiveness of completing the task was measured by the number of incorrect turns during navigation and completion time. The complexity of mental spatial representations that participants developed before and after navigating the route was also evaluated. The data was obtained using several qualitative and quantitative research methods (mobile eye tracking, structured interviews, sketching of cognitive maps, creation of navigation instructions, and additional questions to evaluate spatial orientation abilities). A total of 36 subjects (17 in the “floor plan” group and 19 in the “virtual tour” group) participated in the study. The results showed that the participants from both groups were able to finish the designated navigation route, but more detailed mental spatial representations were developed by the “virtual tour” group than the “floor plan” group. The participants in the virtual tour group created richer navigation instructions both before and after evacuation, mentioned more landmarks and could recall their characteristics. Visual landmark characteristics available in the virtual tour also seemed to support the correct decision-making.

Extracting urban landmarks from geographical datasets using a random forests classifier

ABSTRACTUrban landmarks are of significant importance to spatial cognition and route navigation. However, the current landmark extraction methods mainly focus on the visual salience of landmarks and are insufficient for obtaining high extraction accuracy when the size of the geographical dataset varies. This study introduces a random forests (RF) classifier combining with the synthetic minority oversampling technique (SMOTE) in urban landmark extraction. Both GIS and social sensing data are employed to quantify the structural and cognitive salience of the examined urban features, which are available from basic spatial databases or mainstream web service application programming interfaces (APIs). The results show that the SMOTE-RF model performs well in urban landmark extraction, with the values of recall, precision, F-measure and AUC reaching 0.851, 0.831, 0.841 and 0.841, respectively. Additionally, this method is suitable for both large and small geographical datasets. The ranking of variable importance given by this model further indicates that certain cognitive measures – such as feature class, Weibo popularity and Bing popularity – can serve as crucial factors for determining a landmark. The optimal variable combination for landmark extraction is also acquired, which might provide support for eliminating the variable selection requirement in other landmark extraction methods.

Modeling and forecasting of Neopanamax vessel transit time for traffic management in the Panama Canal

In response to an increased reliance on bigger, Neopanamax-sized vessels for shipping, the Panama Canal has been expanded. Whilst the way that vessels transit the newly expanded canal has stayed the same, maneuvering operations have changed. As a result, transit times have been affected. In accordance with the size and cargo of vessels, canal navigation rules restrict how access channels (Culebra Cut, Gatun Lake, and seaways) and new locks (Cocoli and Agua Clara) are used. Larger sized, Neopanamax vessels will benefit most from the expanded canal. Since the canal opened on 26 June 2016, data on transit times have been gathered. With these data, a thorough statistical analysis should be carried out. The most influential variables on overall time in transit (TET), such as pilot skill and Culebra Cut or Gatun Lake transit times, are identified. Formulae based on multivariate linear regression can be extracted that will make it possible to establish a conductive methodology for estimating the transit time of a Neopanamax vessel. Taking into account the results of the statistical analysis, a proposal is included for improving Neopanamax traffic management, with views to reduce the TET, from a transit policy point of view. This is the first work in scientific literature that analyzes in detail, from qualitative and statistical approaches, the total time in transit through the set of navigable routes and locks that compose the new expanded Panama Canal.

ВЛИЯНИЕ ЛЬДА НА ФОРМИРОВАНИЕ СУДОХОДНЫХ МАРШРУТОВ В АКВАТОРИИ СЕВЕРНОГО МОРСКОГО ПУТИ

The article focuses on the processes of forming the shipping routes in the waters of the Northern Sea Route when passing from the summer navigation period to the winter navigation period. The main indicators characterizing the volume of freight carried out along the routes of the Northern Sea Route in 2018 are presented. There has been stated the change in the structure of the Arctic fleet and an increase in the share of large-tonnage vessels operating in the Kara Sea in the year-round navigation mode. The comparative data of monitoring the movement parameters of LNG-tankers (YamalMax type) obtained in January, March and September 2018 are given. The causes of changes in the trajectory of ships when sailing in ice have been revealed and analyzed. The results of the analytical review of works that are devoted to the study of the influence of the ice parameters on maneuverability of the vessels and the development of methods for finding the best routes along the Northern Sea Route are shown. To carry out studies of the ship speed, the tools of geo-information systems in geo-spatial formulation were use. The analytical model of the vessel navigation through the ice between two fixed points has been proposed. The main criteria for comparing shipping routes have been defined. The results of the comparative quantitative estimates of the vessel routes are given. Recommendations on using the results obtained in the theory and practice of Arctic shipping are given. The studies are carried out as part of an initiative project to develop a theory of sea transport flows in the Northern Sea Route water area, implemented at the Arctic Faculty of the Admiral Makarov State University of Maritime and Inland Shipping. The results of this paper can be use when searching for the best routes for navigation in the ice conditions, when planning hydrographic works and developing a promising network of shipping routes in the Arctic seas.

Crowdsourced Pothole Mapping and Route Navigation

Crowdsourced Pothole Mapping and Route Navigation

River-tide-storm surge interaction characteristics for the Hooghly estuary, East coast of India

ABSTRACT The head Bay of Bengal region that borders the North Indian Ocean is crisscrossed with numerous tidal creeks, riverine systems and channels that play an important role in storm surge studies. In particular, the storm surge resulting from the landfall of tropical cyclone over this region can interact with the river systems and thereby modify the characteristics of storm surge. Several studies were attempted to understand the behaviour of storm surges and associated inundation for the Indian coast; however, the role of hydrologic component in modifying storm surge received less attention. The present study considers a stretch of Hooghly River channel in West Bengal that provides the navigable route to two important national ports, and important in context to socio-economic implications. The state-of-art advanced circulation model (ADCIRC) hydrodynamic model used in this study incorporates the riverine stretch and investigates the effect of river discharge on storm surge propagation along the upstream reaches of the Hooghly River. In addition, the river-tide interaction was studied with differential river discharge volumes of 1000 and 3000 m3 s−1 that corresponds to the respective minimum and maximum discharges. Model simulations well represented the upstream tidal propagation as well the reversal of tidal currents in the river. Also the effect of variable river discharge volumes in modifying the limit of flood flow was clear from simulation. The results signify that limit of flood flow was seen nearly 70 km in the river upstream for discharge volume corresponding to 1000 m3 s−1 and reduced to 62 km on increasing the discharge to 3000 m3 s−1. The effect of wind stress on storm surge penetration into river was also investigated using the hypothetical Aila cyclone wind field. Moreover, the combined effect due to varying river discharge volumes and wind stress on storm surge characteristics was also studied. The study is an effort to understand the role of river-tide-storm surge interaction very useful in a real-time storm surge forecasting system.

Требования к допустимым условиям эксплуатации судов класса «М-СП4,5» и возможность их уточнения на примере Черного и Каспийского морей

This paper analyses operational requirements to M-SP4.5-class ships and shows that their acceptable operational conditions are mostly determined by global and local wave loads. Following their optimal navigation routes in the Black Sea and in the Caspian, these ships go somewhat farther from their shelters than recommended. The study confirms that M-SP4.5-class ships can be used at optimal shipping lanes between Russian Black Sea ports and the Bosporus and that their actual acceptable distance from shelters depends on wave directions. The paper suggests revision of Russian River Register rules in terms of global wave loads acceptable for M-SP4.5-class ships operation at arbitrary routes in the Caspian.