Spatial knowledge acquisition in mobile map-assisted navigation: a real-world longitudinal study

Spatial cognition has become an increasingly important area of study since it represents a major type of human knowledge with considerable practical significance. The general assumption is that people’s spatial knowledge forms people’s spatial behaviour, such as navigation, in the environment. However, there are some critical issues within this area, including: how such knowledge is represented and organised, the mechanisms by which it is activated, and the elementary and higher-level cognitive processes that function upon the knowledge base to produce new knowledge as well as the factors that are influential on acquiring spatial knowledge. The theories regarding spatial knowledge acquisitions have attempted to address these issues. This paper discusses these issues by reviewing the literature. As such, the paper firstly provides the research background on spatial knowledge acquisition and the theories of spatial knowledge development. Secondly, the paper debates the main factors affecting acquiring and forming knowledge about the environment. In doing that, the effects of two main factors are discussed: 1) the means of spatial knowledge acquisition (direct experience, physical map, and mobile maps), and 2) the role of different properties of physical environment.

Abstract. Recent years have witnessed the rapid development of navigation systems. They gradually become the default way of navigating in our daily life. Despite benefiting from their convenience, we may be negatively influenced by them (Parush et al. 2007). Current navigation systems usually draw too much of users' attention to the mobile devices, which leads to users’ lacking interaction with the environment. It is often the case that people easily forget travelled route and get lost without navigation systems (Reilly et al. 2008). Empirical study shows that by dividing attention, navigation systems impair users’ spatial memory, and thus impact their navigation skills (Gardony et al. 2013). Since a higher engagement with the environment can improve users’ spatial knowledge acquisition without decreasing efficiency (Brügger et al. 2017), navigation systems should incorporate important environmental features.As objects of visual, cognitive or structural importance (Sorrows & Hirtle 1999), landmarks have been extensively studied, and considered as an important environmental feature to be incorporated into navigation systems (Nuhn & Timpf 2018, Richter 2017, Duckham et al. 2010, Raubal & Winter 2002). They serve as references to provide users with more natural and pleasant navigating experience (Richter & Winter 2014). However, most of landmark-related studies are in outdoor environment. Although researchers have attempted to classify and assess indoor landmarks (Ohm 2014, Viaene 2014), it is still very difficult to determine suitable ones. As a subset of semantic indoor landmarks, existing navigational aids (e.g. signs and floor plans) are designed to assist navigation. Among them, signs are most preferred by users (Wang et al. 2017). Being the signs that give necessary information to route users to possible destinations, directional signs contribute most to wayfinding (Gibson 2009). With route information explicitly presented by them, they are relevant environmental features to be incorporated into indoor navigation systems.In this study, we therefore propose to incorporate directional signs into indoor navigation systems, in order to guide users’ attention back to the environment, to facilitate their spatial learning and improve their spatial knowledge acquisition.We incorporated directional signs into a proof-of-concept indoor navigation system. First, we integrated directional signs and their semantics into a graph-based model. A directional sign was modelled as a node. Each destination on the sign was linked with the sign by an edge. In order to differentiate it from the normal edge, it was marked as semantic edge. Thus, the semantics of the sign was modelled directly into the graph, instead of being stored as attributes in a previous version of our study (Wang & Gartner 2018). Then, a top-K shortest path algorithm was employed to find candidate routes (Yen 1971). In the end, the route with the largest coverage of semantic edges was suggested to the user. The users would then be explicitly guided to follow the directional signs in the environment.In the next step, we will evaluate the efficiency and effectiveness of the proposed navigation system by an empirical study with human subjects. Within the experiment, we will also investigate on whether this kind of guidance can succeed in drawing users’ attention back to the environment and support their spatial knowledge acquisition.

Implementing the International GNSS Service 2021+ Strategic Plan: Vision and Use Cases

In this article, we address the central topic of the call for papers, childhood educates space, from the perspective of children’s and young people’s spatial knowledge. We argue that both childhood and youth educate as much as are educated by space. To shed light on this dynamic and complex interaction, we focus on the arenas and agencies at play within the production and acquisition of spatial knowledge. The term arena refers to the spatial conditions that delineate an area of activity related to the production and acquisition of spatial knowledge, and agency denotes the crucial means, agents, and tools that are instrumental in and buttress such area of activity. To render operative the analysis, we draw on two driving themes: (i) the gradual development of a comprehensive conception of space and (ii) its accompanying (and traversing) learning processes. Moreover, to substantiate the assertion that education between childhood and youth and space is mutually constitutive, we present a selection of findings from a qualitative meta-analysis conducted to reconstruct the evolution of young people’s spatial knowledge from the 1970s onwards. All in all, we claim that the process of production and acquisition of spatial knowledge forms the basis of, on the one hand, the keenness and depth of the perception that children and young people have of the physical world and, on the other, the ways they subjectively and symbolically characterize it.

Abstract. Mobile Mapping (MM) has gained significant importance in the realm of high-resolution data acquisition techniques. MM is able to record georeferenced street-level data in a continuous (laser scanners) and/or discrete (cameras) fashion. MM’s georeferencing relies on a conjunction of Global Navigation Satellite Systems (GNSS), Inertial Measurement Units (IMU) and optionally on odometry sensors. While this technique does not pose a problem for absolute positioning in open areas, its reliability and accuracy may be diminished in urban areas where high-rise buildings and other tall objects can obstruct the direct line-of-sight between the satellite and the receiver unit. Consequently, multipath measurements or complete signal outages impede the MM platform’s localisation and may affect the accurate georeferencing of collected data. This paper presents a technique to recover correct orientation parameters for MM imaging platforms by utilising aerial images as an external georeferencing source. This is achieved by a fully automatic registration strategy which takes into account the overall differences between aerial and MM data, such as scale, illumination, perspective and content. Based on these correspondences, MM data can be verified and/or corrected by using an adjustment solution. The registration strategy is discussed and results in a success rate of about 95 %.

Autonomous vehicles, which free drivers from driving, are gaining increasing interest for future travel needs. But the degradation of driver’s spatial knowledge will likely worsen when drivers no longer need to actively steer nor pay attention to the environment. This study extends the theory of visualising distant landmarks on mobile phone to windshield using Augmented Reality (AR), to support spatial learning. This study investigates the impact of AR distant landmarks (with vs. without AR landmarks) and road conditions (highway vs. local road) on acquiring spatial knowledge through an experiment using simulated videos of autonomous driving. Participants are randomly assigned to one of two scenarios to complete tasks which assessed their acquired spatial knowledge one the route-, directional, and configural levels. Results show that distant landmarks enhance the efficiency of acquiring route- and directional knowledge, although the effectiveness of acquiring route knowledge with AR landmarks is not significant on local road. Configurational knowledge is more likely impacted by the road type instead of the AR landmarks. The results indciate the necessity of carrying out follow-up studies on symbolising additional information in AR landmarks for supporting spatial learning and evaluate their impacts on the spatial knowledge at the configurational level.

People have to move between indoor and outdoor frequently in city scenarios. The global navigation satellite system signal cannot provide reliable indoor positioning services. To solve the problem, this article proposes a seamless positioning system based on an inverse global navigation satellite system signal, which can extend the global navigation satellite system service into the indoor scenario. In this method, a signal source is arranged at a key position in the room, and the inverse global navigation satellite system signal is transmitted to the global navigation satellite system receiver to obtain a preset positioning result. The indoor positioning service is continued with the inertial navigation system after leaving the key position. The inverse global navigation satellite system seamless positioning system proposed in this article can unify indoor and outdoor positioning using the same receiver. The receiver does not need to re-receive navigation information when the scene changes, which avoids the switching process. Through the design of signal layer coverage, the receiver is in a warm start state, and the users can quickly fix the position when the scenario changes, realizing quick access in a true sense. This enables the ordinary commercial global navigation satellite system receiver to obtain indoor positioning capability without modification, and the algorithm can perform accurate positioning indoors and outdoors without switching.

With the continuing spread of distributed measurement and control systems (e.g. Cyber-Physical Systems, Industry 4.0) there is an increased need to implement synchronized sampling and actuation over the components of a distributed system. To achieve this goal, the clocks of the system must be synchronized, including the ones doing sampling and actuation. In most cases local synchronization alone is not enough; It is also needed to keep in sync with a global reference time in order, for example, to be able to implement timestamps based on global time and simultaneous sampling across system components that are spatially distributed (operate on different sites). This global reference time mostly means one which is provided by a GNSS (Global Navigation Satellite System) service, such as GPS. In these systems, it is the master clock which is responsible for attaining (e.g. via a GNSS receiver) and keeping the global reference time. It can then pass it on in the local communication network, usually using IEEE 1588 (Precision Time Protocol). It follows, that thus, the characteristics of such systems are heavily limited by the precision, accuracy and reliability of the used GNSS receiver. Our paper thus is about the examination of potentially promising GNSS receivers for which we developed a custom measurement system. This includes the design of a test PCB, the writing of a PC data collecting program, the formulation of MATLAB scripts which process the collected data, and the validation of the data collecting system via GNSS receivers simulated by TI evaluation boards. We also conducted measurements with the system on the Quectel L86 GNSS receiver, the results of which are presented in the paper.

Positioning, Navigation and Timing (PNT) services based on the Global Navigation Satellite System (GNSS) have a number of known drawbacks that makes them prone to suffer a disruption. These flaws can be exploited to disable this service in critical infrastructures. Therefore, the hybridization of GNSS and 5G measurements enabling Assured PNT (APNT) services is growing up and gaining attention by governmental bodies. 5G signals emitted by terrestrial networks and by Low Earth Orbit (LEO) satellites can complement GNSS, enhancing their reliability, security and accuracy. For example, the larger Signal-to-Noise Ratio (SNR) of a terrestrial system makes them more difficult to suffer a jamming attack as compared to GNSS signals. A joint data and positioning signal enhances the security and reliability of the APNT solution with, for example, the successful decoding of encrypted data, this could be used for system authentication. Moreover, a larger signal bandwidth increases the accuracy of the PNT solution. All of these benefits can be extracted from the 5G terrestrial and non-terrestrial networks that transmit the Positioning Reference Signal (PRS). The rationale for these benefits rely on the flexibility of this pilot signal in terms of bandwidth or symbols used for the APNT service. This paper aims to analyse how this flexibility can be optimized to achieve a specific level of accuracy, minimizing the resources used under certain constrains of bandwidth or latency. The results present the optimal parameters to design a 5G PRS waveform with a target scenario constrains. Then, we compare it with the GNSS service and how to benefit when using them in combination. Finally, the paper concludes with the future research lines proposing a joint communications and positioning system as a closed loop. In such scenario, the user achieved accuracy is sent back to the infrastructure, and using the dynamic PRS flexibility, the system increases or reduces the PRS resources in order to meet the user accuracy requirements.

Water vapour radiometers (WVR) provide information about temperature and humidity in the troposphere, with high temporal resolution when compared to the radiosonde (RS) observations. This technique can provide an additional reference data source for the zenith tropospheric delay (ZTD) estimated with the use of the Global Navigation Satellite System (GNSS). In this work, the accuracy of two newly installed radiometers was examined by comparison with RS observations, in terms of temperature (T), absolute humidity (AH), and relative humidity (RH), as well as for the ZTD. The impact of cloud covering and heavy precipitation events on the quality of WVR measurements was investigated. Also, the WVR data were compared to the GNSS ZTD estimates. The experiment was performed for 17 months during 2020 and 2021. The results show agreement between RS and WVR data at the level of 2◦C in T and 1 gm-3 in AH, whereas for RH larger discrepancies were noticed (standard deviation equal to 21%). Heavy precipitation increases WVR measurement errors of all meteorological parameters. In terms of ZTD, the comparison of WVR and RS techniques results in bias equal to –0.4 m and a standard deviation of 7.4 mm. The largest discrepancies of ZTD were noticed during the summer period. The comparison between the GNSS and WVR gives similar results as the comparison between the GNSS and RS (standard deviation 7.0–9.0 mm).

Accuracy assessment of integrated GNSS measurements with LIDAR mobile mapping data in urban environments

Recent results of our team showed that parental spatial training before fertilization improves the offspring's spatial memory. However, the process of spatial learning (short-term/working and long-term memories, mnesic consolidation and procedures) in the offspring has not been fully clarified yet. Therefore, this study aimed at specifically analyzing whether maternal learning of a spatial task before fertilization can impact on the process of spatial learning in the female offspring. In the present study, 8-week-old female Wistar rats that had been spatially trained (or not) in the Morris Water Maze (MWM) were mated with conspecific standard-reared male rats, and their 4-week-old female offspring were spatially tested in the same MWM to evaluate their learning and memory processes. Results showed that the female offspring of trained mothers significantly displayed lower escape latencies, higher swimming speed, shorter total distance swum, longer percentage of time spent in the target quadrant and better localization memory in comparison to the female offspring of not trained mothers. Further, MWM performances of mothers trained and their female offspring significantly correlated. These findings indicate that the maternal spatial training before fertilization improves the spatial learning and memory consolidation process of the female offspring.

Navigation assistance systems have become integral to our daily routines, helping us to find our way through unfamiliar environments. However, their use may come at a price, as empirical evidence suggests a potentially harmful impact of these systems on our spatial abilities, including the acquisition of spatial knowledge. This could be remedied by giving users more freedom and involving them in the decision-making process. Therefore, we present a navigation system that combines augmented reality and Beeline Navigation (BeeAR). Here, the location of the destination is overlaid with a digital landmark and permanently displayed to the user via a visual, translucent AR display (without a map). Since the digital content is integrated into the real world, no mapping between the device and reality is required, potentially lowering the workload. Making one's own decisions along the route is expected to increase engagement with the environment, leading to increased acquisition of spatial knowledge. We compare BeeAR with findings from a previous study comparing Free Choice Navigation (FCN) and Turn-by-Turn (TBT) navigation conducted along the same routes on the outskirts of Vienna, Austria. Although BeeAR and FCN do not provide users with a map, BeeAR users could better retrace the walked route and remembered more points of interest along the route than FCN users. Participants of all three navigation conditions achieved a high configuration similarity between drawn points of interest and their true locations, albeit only one navigation condition included a map.

Evaluating the effects of collaboration and competition in navigation tasks and spatial knowledge acquisition within virtual reality environments

Cycle slips are discontinuity events in a receiver’s phase lock on a Global Navigation Satellite System (GNSS) signal. If cycle-slip events are not detected and repaired, the quality of positioning using carrier phase processing suffers. In this paper, we present an algorithm for flagging cycle slips during data preprocessing. This new algorithm is part of a new GNSS software that replaces a legacy software at the National Geodetic Survey (NGS). It uses the Hatch–Melbourne–Wübbena (HMW), ionosphere-free and geometry-free linear combinations to detect cycle slips. The use of the three observables in parallel helps improve sensitivity to cycle slips and overcome the challenge of detecting cycle slips of equal size and same sign on both/multiple frequencies. Different detection threshold values were evaluated in a well-controlled environment using GNSS data acquired from continuously operating reference stations (CORS) networks and artificially simulated cycle slips that were introduced into the datasets. The goal of evaluation was to determine the optimal values for cycle-slip detection parameters. In the absence of formal confidence limits, the results of the study show that, in a worst-case scenario involving small slips of magnitudes ranging from 1 to 3 cycles, there is a range of parameter values that resulted in at least 97% success rate without any false detections. Based on these and other findings, we provide a set of optimal values from which the results are an improvement of at least 34% in cycle-slip detection, compared to results from the legacy algorithm’s settings. The results of the study will support the National Oceanic and Atmospheric Administration’s (NOAA) GNSS services and tools for the public, such as the Online Positioning User Service (OPUS).