Social-Aware Driver Assistance Systems for City Traffic in Shared Spaces

Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specifically delimited areas. This makes the traffic they comprise challenging for automated systems. The information traditionally considered (e.g., streets, and obstacle positions and speeds) is not enough to build suitable models of the environment. The required explanatory and anticipation capabilities need additional information to improve them. Social aspects (e.g., goal of the displacement, companion, or available time) should be considered, as they have a strong influence on how people move and interact with the environment. This paper presents the Social-Aware Driver Assistance System (SADAS) approach to integrate this information into traffic systems. It relies on a domain-specific modelling language for social contexts and their changes. Specifications compliant with it describe social and system information, their links, and how to process them. Traffic social properties are the formalization within the language of relevant knowledge extracted from literature to interpret information. A multi-agent system architecture manages these specifications and additional processing resources. A SADAS can be connected to other parts of traffic systems by means of subscription-notification mechanisms. The case study to illustrate the approach applies social knowledge to predict people&rsquo s movements. It considers a distributed system for obstacle detection and tracking, and the intelligent management of traffic signals. Document type: Articl

IoT Smart Collect - Routing Process and Driver Guidance

Waste collection is a traditional process that involves a driver collecting waste from a set of designated deposits based on a pre-determined route. The authors present a new approach that utilizes Artificial Intelligence to define the route based on the occupancy volume of the deposits. The new process involves the use of a mobile application to assist the driver during the journey. The application communicates with the central system to receive information on the next route, calculates the best possible route considering traffic laws and road conditions, and guides the driver throughout the journey. The application also provides real-time updates on the driver’s progress and allows the driver to provide feedback All collected data is stored and can be consulted and explored through lists, graphs, and filtering options. The authors believe that the new approach will improve the efficiency of waste collection and provide a better experience for the driver.info:eu-repo/semantics/publishedVersio

Social-Aware Driver Assistance Systems for City Traffic in Shared Spaces

Shared spaces are gaining presence in cities, where a variety of players and mobility types (pedestrians, bicycles, motorcycles, and cars) move without specifically delimited areas. This makes the traffic they comprise challenging for automated systems. The information traditionally considered (e.g., streets, and obstacle positions and speeds) is not enough to build suitable models of the environment. The required explanatory and anticipation capabilities need additional information to improve them. Social aspects (e.g., goal of the displacement, companion, or available time) should be considered, as they have a strong influence on how people move and interact with the environment. This paper presents the Social-Aware Driver Assistance System (SADAS) approach to integrate this information into traffic systems. It relies on a domain-specific modelling language for social contexts and their changes. Specifications compliant with it describe social and system information, their links, and how to process them. Traffic social properties are the formalization within the language of relevant knowledge extracted from literature to interpret information. A multi-agent system architecture manages these specifications and additional processing resources. A SADAS can be connected to other parts of traffic systems by means of subscription-notification mechanisms. The case study to illustrate the approach applies social knowledge to predict people’s movements. It considers a distributed system for obstacle detection and tracking, and the intelligent management of traffic signals

Sustaining critical transport infrastructure space in megacities: multimodal assessment of railway and road systems in Kano & Lagos — Nigeria

Globalisation has the most tremendous negative effects on the changing landscapes of many cities because of the roles of cities as the de facto economy and haven of liveable socioeconomic advantages. As the urban population grows, particularly in developing countries' mega-cities where transport development faces the most complex challenges, a more sophisticated framework of assessment of critical transportation infrastructure and transportation planning is required. This research aims to investigate transport effects of the complex web of interactions of urban chain processes to bring about a more sustainable (and resilient) transport infrastructure development of mega-cities. The interdisciplinary research concepts which incorporate the development of scenario-based applications and prediction techniques involving qualitative and quantitative frameworks were applied to the two Nigerians most populous cities (Lagos and Kano). The framework includes the analysis of spatial-temporal relationship of transport space and urban land use change, congestion and accessibility, sustainability paradigm and themes and ordering of priorities of the intervention policies based on transportation demand management objectives. Data sources include Landsat images, traffic and demographic data, transportation infrastructure inventories, and collaborative engagement with stakeholders and policymakers via questionnaires, interviews, and checklists. First, spatial-temporal analysis was carried out using remote sensing GIS software for land use classification and CA-Markov model implemented in IDRISI SELVA for temporal prediction and its suitability quality. Next is the assessment of accessibility and congestion pattern of the two cities using a surrogate multi-layer feed-forward and back-propagation model involving input-output and curve fitting (NFTOOL) implemented in artificial neural network wizard of MATLAB. Also, the sustainable paradigm and themes were carried using questionnaire and interview instruments and analysed respectively using SPSS and NVivo softwares. Finally, the priorities of intervention policy decision and quality of infrastructure and services were analysed using hybrid SERVQUAL-AHP models. The spatial-temporal analysis of the two cities produced patterns of rising trends for transport and built-up areas while the other land use classes are receding. For example, Kano transport space had grown from 137km$^2$ in 1984 to 290km$^2$ in 2019 while that Lagos grew from 337km$^2$ to 535km$^2$ in the same period. The dynamics model predicts spatial land requirement of Kano city for transport to reach 410km$^2$ in 2050 while Lagos will be needing 692km$^2$ in the same period. Future prediction of the two cities will be highly unsustainable for transport infrastructure. The congestion profile results put the two cities within congestion indices ranging from 7.5 to 10 on a maximum scale of 10, indicating extreme traffic congestion regimes and inaccessibility in the two cities. The sustainability paradigm comprising literacy, sustainable choices and indicators of sustainable transport are below average exposing poor development in the area. Also, the thematic analysis revealed the preponderance of more negative sentiments from the interview over statements of optimism and progress and it corroborates the findings of sustainability paradigm. Finally, satisfaction quality assessment produced low quality scores of 48% and 49% for Kano and Lagos cities respectively. AHP equally allocated more weight to tangibility which defines infrastructure and service qualities. These values are suggestive of the necessity to infrastructure, public transit systems and management of transport demand in the decision policy making. To deal with rising urbanization trends in Nigerian cities and maintain liveable and accessible urban environments, aggressive push—and—pull policies that improve and increase transport infrastructure quality and drive sustainable transport, promote modal split, reduced motorization, and access control is recommended