To Drive or to Be Driven? The Impact of Autopilot, Navigation System, and Printed Maps on Driver’s Cognitive Workload and Spatial Knowledge

The technical advances in navigation systems should enhance the driving experience, supporting drivers’ spatial decision making and learning in less familiar or unfamiliar environments. Furthermore, autonomous driving systems are expected to take over navigation and driving in the near future. Yet, previous studies pointed at a still unresolved gap between environmental exploration using topographical maps and technical navigation means. Less is known about the impact of the autonomous system on the driver’s spatial learning. The present study investigates the development of spatial knowledge and cognitive workload by comparing printed maps, navigation systems, and autopilot in an unfamiliar virtual environment. Learning of a new route with printed maps was associated with a higher cognitive demand compared to the navigation system and autopilot. In contrast, driving a route by memory resulted in an increased level of cognitive workload if the route had been previously learned with the navigation system or autopilot. Way-finding performance was found to be less prone to errors when learning a route from a printed map. The exploration of the environment with the autopilot was not found to provide any compelling advantages for landmark knowledge. Our findings suggest long-term disadvantages of self-driving vehicles for spatial memory representations.

The generalized spatial representation in the prefrontal cortex is inherited from the hippocampus

Hippocampal and neocortical neural activity is modulated by the position of the individual in space. While hippocampal neurons provide the basis for a spatial map, prefrontal cortical neurons generalize over environmental features. Whether these generalized representations result from a bidirectional interaction with, or are mainly derived from hippocampal spatial representations is not known. By examining simultaneously recorded hippocampal and medial prefrontal neurons, we observed that prefrontal spatial representations show a delayed coherence with hippocampal ones. We also identified subpopulations of cells in the hippocampus and medial prefrontal cortex that formed functional cross-area couplings; these resembled the optimal connections predicted by a probabilistic model of spatial information transfer and generalization. Moreover, cross-area couplings were strongest and had the shortest delay preceding spatial decision-making. Our results suggest that generalized spatial coding in the medial prefrontal cortex is inherited from spatial representations in the hippocampus, and that the routing of information can change dynamically with behavioral demands.

Retrosplenial cortex is necessary for spatial and non-spatial latent learning in mice

Latent learning occurs when associations are formed between stimuli in the absence of explicit reinforcement. Traditionally, latent learning in rodents has been associated with the creation internal models of space. However, increasing evidence points to roles of internal models also in non-spatial decision making. Whether the same brain structures and processes support the creation of spatially-anchored or non-spatial internal models via latent learning, is an open question. To address this question, we developed a novel operant box task that allows to test spatial and non-spatial versions of a flavour-based sensory preconditioning paradigm. We probed the role of the retrosplenial cortex, a brain area associated with spatial cognition and subjective value representation, in this task using precise, closed-loop optogenetic silencing during different task phases. We show that the retrosplenial cortex is necessary for both spatial and non-spatial latent learning in mice. We further demonstrate that the requirement of retrosplenial cortex is limited to the preconditioning phase of the task. Our results provide insight into the specific role of the retrosplenial cortex in latent learning, demonstrate that latent learning plays a general part in the creation of internal models, independent of spatial anchors, and provide a novel avenue for studying model-based decision making.

An Approach to Measuring Ship Design Complexity

Understanding different aspects of complexity and measuring them properly are important steps of handling ship design complexity effectively. The main objective of this article is to develop a practical and comprehensive method to measure ship design complexity. In engineering design, complexity is measured today by different indexes and methods. This paper initially explores the applicability of such measures in a ship design context supported by a review of different relevant user-cases. However, it is acknowledged that most of these measurement methods focus on product-related complexity aspects and rarely address or quantify complexities generated by the design process, the organisation of the firm, or the market situation. Therefore, this paper introduces a new and comprehensive model to measure ship design complexity including all these aspects. The model quantifies ship design complexity by means of the following nine different descriptive factors: directional, spatial, decision-making, structural, behavioral, contextual, perceptual, temporal, and technological complexity.

Cultural Landscapes: A Multi-Stakeholder Methodological Approach to Support Widespread and Shared Tourism Development Strategies

Starting from the most recent international debate on the theme of cultural landscape, this study explores the theme of landscape as a ‘common good’ and as a field of investigation and experimentation of an innovative model of long-term sustainable tourism development. In this context, the document illustrates a multi-stakeholder spatial decision-making process based on an evaluation approach that is useful to support decision-makers in defining improvement strategies for resilient landscapes. The methodology was experimented on and tested as part of the ‘Sila Labscape’ project conducted in Sila National Park (Southern Italy), a UNESCO site of excellence. The purpose of the study is to support the park’s community in acquiring a greater awareness of the values and resources present within the park and to stimulate co-design for the enhancement and management of environmental and cultural sites. Starting from the representation of the landscape perceived by users, it is possible to trace the values and meanings of the most attractive places. The most relevant results concern the identification of perceived landscape values, the recognition of shared values, and their consequent use to map ‘places of value’. The elaboration, structuring, and evaluation processes allow the tracing of new touristic routes and the expression of shared intersubjective perception that are useful for supporting decision-makers in the development of potential integrated development strategies and actions.

Coupling Fuzzy Multi-Criteria Decision-Making and Clustering Algorithm for MSW Landfill Site Selection (Case Study: Lanzhou, China)

The siting of Municipal Solid Waste (MSW) landfills is a complex decision process. Existing siting methods utilize expert scores to determine criteria weights, however, they ignore the uncertainty of data and criterion weights and the efficacy of results. In this study, a coupled fuzzy Multi-Criteria Decision-Making (MCDM) approach was employed to site landfills in Lanzhou, a semi-arid valley basin city in China, to enhance the spatial decision-making process. Primarily, 21 criteria were identified in five groups through the Delphi method at 30 m resolution, then criteria weights were obtained by DEMATEL and ANP, and the optimal fuzzy membership function was determined for each evaluation criterion. Combined with GIS spatial analysis and the clustering algorithm, candidate sites that satisfied the landfill conditions were identified, and the spatial distribution characteristics were analyzed. These sites were subsequently ranked utilizing the MOORA, WASPAS, COPRAS, and TOPSIS methods to verify the reliability of the results by conducting sensitivity analysis. This study is different from the previous research that applied the MCDM approach in that fuzzy MCDM for weighting criteria is more reliable compared to the other common methods.

A prototype of web-based PPGIS for municipal planning using open source software

Web-based Public Participation Geographic Information System (WebPPGIS) is inherently about empowering GIS and Web technology and enabling the public users to use the technology to capture their local knowledge and immerse them into the spatial decision making process. However, there have [sic] some common barriers to WebPPGIS implementation such as lack of communication mechanism for the public; lack of friendly use interface for the non-expert public users; and the cost of the GIS software packages etc. This thesis presents the results of a research project, aiming at overcoming the above barriers and implementing a practical WebPPGIS. General requirements of WebPPGIS are summarized based on the analysis of current researches and a prototype is implemented to demonstrate the feasibility of the approach. Also this thesis illustrates that Open Source Software (OSS) is a competetive solution for developing cost-effective WebPPGIS. Further, the evaluation of the prototype has been performed against the requirements