The effects of different verbal route instructions on spatial orientation

Ponencias, comunicaciones y pósters presentados en el 17th AGILE Conference on Geographic Information Science "Connecting a Digital Europe through Location and Place", celebrado en la Universitat Jaume I del 3 al 6 de junio de 2014.Providing cognitively effective wayfinding instructions is an ongoing research agenda. In addition to providing instructions that are easy to follow, work has started to address instructions that can potentially facilitate spatial orientation and cognitive mapping. In this study, we use a type of verbal instructions that consists of not only landmarks at decision points but also additional landmarks along a route or in distance that are considered crucial for maintaining spatial orientation. The orientation-based route instructions are compared with machine-generated as well as skeletal instructions. Eleven participants were randomly assigned to use one of these three types of instructions to mentally walk a route that they are unfamiliar with and then performed a set of tasks. Preliminary results show that participants using the orientation instructions made fewest errors in their performance of direction estimation. Results from their drawn sketch maps also show more accuracy in global and local orientation. This type of instructions, not surprisingly, does not contribute to accurate estimation of distance. The machine-generated instructions which include distance information, however, are not found contributing to the best estimation of distance. This study supports the potentials of designing wayfinding instructions to facilitate spatial cognition. It also calls the necessity for more comprehensive studies on the effects of instructions on various aspects of wayfinding behaviors, as well as on the automatic generation of orientation-based instructions

Wayfinding in Unfamiliar Public Buildings - Factors in Landmark Recognition

This study was undertaken to help understand what helps people navigate into and within unfamiliar buildings. The aim is to arrive at a list of factors influencing wayfinding and to find which landmark and building element characteristics are most significant in the cognitive processes behind wayfinding. Three studies were conducted for this research. A case study and an experiment covered navigation provision and entrance recognition in existing buildings. An experiment in landmark recognition and wayfinding within buildings was also undertaken. For this, the participants were split into three groups: A, to find out which elements within the building were memorable (also used as control group); B, to find out which elements previously considered as landmarks were used as such when wayfinding; C, to find out which element characteristics prove useful in wayfinding. This information was analysed to establish characteristics of elements which identify landmarks. Consideration of how these elements can be emphasised will be put forward. In addition, it is hoped that the results will aid the understanding of wayfinding shortcomings in current building design and help provide pointers to ways of overcoming these

Usability analysis of 3D Maps for Pedestrian Navigation among different demographic profiles

3-Dimensional (3D) maps may provide the users with a more real-world like view in comparison with the 2-Dimensional (2D) maps. 3D maps offer more degree of freedom in movement to the users, a first-person perspective view and other dynamic details such as time of the day, weather could also be incorporated. This paper demonstrates the evaluation of the usability of 3D maps for navigation purposes, in several general aspects including recognizing landmarks and using these visual cues for navigation among different representative user-groups. The 3D model was designed to replicate the High Street, Stratford, London, UK. The participants of the survey were required to explore the model, identify and memorize the landmarks and form a mental map. They were also asked to reproduce the route they took in a 2D paper map and answer a questionnaire on their perception of their own cognitive abilities and their response on the performance of the 3D model. The results confirmed that the usability can vary among users of different demographic profiles – age, gender and language and familiarity with 3D technologies. It also showed that with some improvements in level of details incorporated in the model and design, 3D maps could become a useful tool for navigation purposes

Capturing cultural differences between UK and Malaysian drivers to inform the design of in-vehicle navigation systems

Attending to cultural diversity is important for products and technology intended for global placement, such as automobiles, yet many products (and associated interfaces) lack genuine cultural differentiation. For example, in-vehicle navigation systems are typically identical in form and function across world markets, differing only in the local language and map database. To capture and explore culturally-salient design factors, we utilised a scenario-based design methodology, involving 6 experienced drivers from the UK and Malaysia. Participants were asked to portray their ideal navigation system interface designs – by drawing pictograms and devising accompanying spoken messages – to direct drivers along 3 prescribed routes in the UK, Malaysia and Japan. Routes were presented using video and paper maps, with the order of presentation counterbalanced between groups; participants were not told in advance from which country each route was derived. Proposed designs highlight differences at a country level, which are consequently interpreted from a cultural perspective. For example, Malaysian drivers included a higher density of navigational elements in their designs, particularly in their home environment, compared to UK drivers. Malaysian drivers also created more incremental designs, particularly on the approach to a manoeuvre, suggesting a desire for greater navigational support at this point in the journey. Landmarks were consistently incorporated in designs, but differences were noted in cultural salience. Additionally, the phrasing of instructions (e.g. “go straight on”), nomenclature for road elements (e.g. ‘roundabout’) and distance declaration conventions (e.g. units) differed at a country level. The findings can be used to inform the design of culturally-attuned in-vehicle navigation systems

Spatial perception of landmarks assessed by objective tracking of people and space syntax techniques

This paper focuses on space perception and how visual cues, such as landmarks, may influence the way people move in a given space. Our main goal with this research is to compare people’s movement in the real world with their movement in a replicated virtual world and study how landmarks influence their choices when deciding among different paths. The studied area was a university campus and three spatial analysis techniques were used: space syntax; an analysis of a Real Environment (RE) experiment; and an analysis of a Virtual Reality (VR) environment replicating the real experiment. The outcome data was compared and analysed in terms of finding the similarities and differences, between the observed motion flows in both RE and VR and also with the flows predicted by space syntax analysis. We found a statistically significant positive correlation between the real and virtual experiments, considering the number of passages in each segment line and considering fixations and saccades at the identified landmarks (with higher visual Integration). A statistically significant positive correlation, was also found between both RE and VR and syntactic measures. The obtained data enabled us to conclude that: i) the level of visual importance of landmarks, given by visual integration, can be captured by eye tracking data ii) our virtual environment setup is able to simulate the real world, when performing experiments on spatial perception.info:eu-repo/semantics/publishedVersio

Elastic Step DQN: A novel multi-step algorithm to alleviate overestimation in Deep QNetworks

Deep Q-Networks algorithm (DQN) was the first reinforcement learning algorithm using deep neural network to successfully surpass human level performance in a number of Atari learning environments. However, divergent and unstable behaviour have been long standing issues in DQNs. The unstable behaviour is often characterised by overestimation in the $Q$-values, commonly referred to as the overestimation bias. To address the overestimation bias and the divergent behaviour, a number of heuristic extensions have been proposed. Notably, multi-step updates have been shown to drastically reduce unstable behaviour while improving agent's training performance. However, agents are often highly sensitive to the selection of the multi-step update horizon ($n$), and our empirical experiments show that a poorly chosen static value for $n$ can in many cases lead to worse performance than single-step DQN. Inspired by the success of $n$-step DQN and the effects that multi-step updates have on overestimation bias, this paper proposes a new algorithm that we call `Elastic Step DQN' (ES-DQN). It dynamically varies the step size horizon in multi-step updates based on the similarity of states visited. Our empirical evaluation shows that ES-DQN out-performs $n$-step with fixed $n$ updates, Double DQN and Average DQN in several OpenAI Gym environments while at the same time alleviating the overestimation bias

This is the tricky part: When directions become difficult

Automated route guidance systems, both web-based systems and en-route systems, have become commonplace in recent years. These systems often replace humangenerated directions, which are often incomplete, vague, or in error. However, humangenerated directions have the ability to differentiate between easy and complex steps through language in a way that is more difficult in automated systems. This article examines a set of human-generated verbal directions to better understand why some parts of directions are perceived as being more difficult than the remaining steps. Insights from this analysis will lead to recommendations to improve the next generation of automated route guidance systems

Computer models of saliency alone fail to predict subjective visual attention to landmarks during observed navigation

This study aimed to understand whether or not computer models of saliency could explain landmark saliency. An online survey was conducted and participants were asked to watch videos from a spatial navigation video game (Sea Hero Quest). Participants were asked to pay attention to the environments within which the boat was moving and to rate the perceived saliency of each landmark. In addition, state-of-the-art computer saliency models were used to objectively quantify landmark saliency. No significant relationship was found between objective and subjective saliency measures. This indicates that during passive observation of an environment while being navigated, current automated models of saliency fail to predict subjective reports of visual attention to landmarks