Passenger Perceptions, Information Preferences, and Usability of Crowding Visualizations on Public Displays in Transit Stations and Vehicles

Large crowds in public transit stations and vehicles introduce obstacles for wayfinding, hygiene, and physical distancing. Public displays that currently provide on-site transit information could also provide critical crowdedness information. Therefore, we examined people's crowd perceptions and information preferences before and during the pandemic, and designs for visualizing crowdedness to passengers. We first report survey results with public transit users (n = 303), including the usability results of three crowdedness visualization concepts. Then, we present two animated crowd simulations on public displays that we evaluated in a field study (n = 44). We found that passengers react very positively to crowding information, especially before boarding a vehicle. Visualizing the exact physical spaces occupied on transit vehicles was most useful for avoiding crowded areas. However, visualizing the overall fullness of vehicles was the easiest to understand. We discuss design implications for communicating crowding information to support decision-making and promote a sense of safety. © 2023 ACM.

Embedded system vehicle based on multi-sensor fusion

As intelligent driving vehicles came out of concept into people’s life, the combination of safe driving and artificial intelligence becomes the new direction of future transportation development. Autonomous driving technology is developing based on control algorithms and model recognitions. In this paper, a cloud-based interconnected multi-sensor fusion autonomous vehicle system is proposed that uses deep learning (YOLOv4) and improved ORB algorithms to identify pedestrians, vehicles, and various traffic signs. A cloud-based interactive system is built to enable vehicle owners to master the situation of their vehicles at any time. In order to meet multiple application of automatic driving vehicles, the environment perception technology of multi-sensor fusion processing has broadened the uses of automatic driving vehicles by being equipped with automatic speech recognition (ASR), vehicle following mode and road patrol mode. These functions enable automatic driving to be used in applications such as agricultural irrigation, road firefighting and contactless delivery under new coronavirus outbreaks. Finally, using the embedded system equipment, an intelligent car was built for experimental verification, and the overall recognition accuracy of the system was over 96%. Author

Digital Transformation of Education Toward Successful Internships: A Methodology Developed Over Seven Years and Tested During COVID-19

Contribution: This article provides a teaching methodology which combines project-based learning, self-regulated learning (SRL), and design projects (DPs) to improve the preparedness of students for computing science-related internships. The methodology is supported by the implementation of the educational technology that transforms the way teaching and learning is transformed to benefit on-campus and off-campus students equitably, during the COVID-19 pandemic. Background: Success in the workspace is governed by the ability of an individual to learn on-the-job and independently. Online learning has led to a shift from instructor-led learning to SRL. This requires individuals to discipline themselves, and be in control of their learning and education. Outcome: The success of internships is improved with skills learnt in class through hands-on real-world projects. Both on/off-campus students gain equitable relevant experience. The teaching methodology developed over several years combines project-based learning, SRL, and DPs. Application Design: The methodology was applied using a flipped classroom approach. The educational technology was used to enhance SRL before in-class learning. This way, in-class rote learning was replaced with hands-on projects. Exam assessments were replaced with DPs where soft skills and technical skills are applied. Findings: The effectiveness of the developed methodology is measured through quantitative and qualitative evaluation tools. The evaluation demonstrates that combining well-designed education technology for SRL, with in-class project-based learning and DPs, can improve students' chances in getting high-impact internships.

Evaluating the Factors Affecting Electric Vehicles Adoption Considering the Sustainable Development Level

Electric vehicles are an important part of governments' environmental policies, and therefore understanding the factors affecting their market share is very important. So, this research is designed to investigate the factors affecting electric vehicle adoption, considering the effects of the COVID-19 pandemic and sustainable development level. Effective factors have been investigated in three categories. One is the characteristics of electric vehicles;the other is the impact of the COVID-19 pandemic on demand for these vehicles;and finally, the impact of the level of sustainable development of countries on adopting electric vehicles. Our analysis method is based on grey econometric and grey regression methods. The results show that vehicle dimensions, battery warranty conditions, battery life, and charging facilities are effective factors in the field of vehicle characteristics that can increase the adoption of electric vehicles. Also, the analysis shows that the COVID-19 pandemic has reduced the adoption of electric vehicles. Finally, we have shown that the market share of electric vehicles is higher in countries with a higher sustainable development level because of better economic, social, and cultural infrastructures.

Joint Transmission Scheme and Coded Content Placement in Cluster-Centric UAV-Aided Cellular Networks

Recently, as a consequence of the COVID-19 pandemic, dependence on telecommunication for remote learning/working and telemedicine has significantly increased. In this context, preserving high Quality of Service (QoS) and maintaining low-latency communication are of paramount importance. In cellular networks, the incorporation of unmanned aerial vehicles (UAVs) can result in enhanced connectivity for outdoor users due to the high probability of establishing Line of Sight (LoS) links. The UAV's limited battery life and its signal attenuation in indoor areas, however, make it inefficient to manage users' requests in indoor environments. Referred to as the cluster-centric and coded UAV-aided femtocaching (CCUF) framework, the network's coverage in both indoor and outdoor environments increases by considering a two-phase clustering framework for Femto access points (FAPs)' formation and UAVs' deployment. Our first objective is to increase the content diversity. In this context, we propose a coded content placement in a cluster-centric cellular network, which is integrated with the coordinated multipoint (CoMP) approach to mitigate the intercell interference in edge areas. Then, we compute, experimentally, the number of coded contents to be stored in each caching node to increase the cache-hit-ratio, signal-to-interference-plus-noise ratio (SINR), and cache diversity and decrease the users' access delay and cache redundancy for different content popularity profiles. Capitalizing on clustering, our second objective is to assign the best caching node to indoor/outdoor users for managing their requests. In this regard, we define the movement speed of ground users as the decision metric of the transmission scheme for serving outdoor users' requests to avoid frequent handovers between FAPs and increase the battery life of UAVs. Simulation results illustrate that the proposed CCUF implementation increases the cache-hit-ratio, SINR, and cache diversity and decrease the users' access delay, cache redundancy, and UAVs' energy consumption.

Smart Ambulance Monitoring System Using Iot

A vehicle which is used to transport patients to hospitals is called as ambulance, this ambulance vehicle is equipped with some vital lifesaving equipment's and first aid medicines. With these medicines and equipment's, the patients are given first aid till it reaches the desired hospital. Whenever a patient is in life-threatening emergency, then the ambulance paramedics should act promptly and must update the status of the patient to their doctors. This type of treatment or service is called Emergency Medical Service (EMS). It deals with immediate treatment and timely movement of the patients. For implementing EMS in ambulance several solutions have been developed for faster means of communication between the equipment's used in ambulance and the doctors. But the solutions are not viable in emergency situations. In additions during Covid wave in 2020 there was a scarcity for hospitals beds, it was filled with many covid patients. In many hospitals there was a queue of ambulances with patients waiting outside the hospitals. In some cases, the patients even died before getting any treatment, to overcome such crucial situations we have come out with a new system combining IoT, Sensor system and Embedded Controllers. The system developed here has sensors to monitor patients' vital parameters and transmits to the hospital server, such that a doctor can know the live condition of the patient and he can give instructions to the paramedics to do emergency aids. The system is a compactable and connects to the server with a mobile hotspot. The information is updated every 10 seconds. By implementing this system in ambulances, it saves many valuable lives of the people.

Transformer notre avenir en un futur soutenable : pour une planification de la transition automobile

L'industrie automobile est dans une tourmente, conjoncturelle, tout d'abord, avec un marché profondément affecté par le Covid, des pénuries de matériaux et composants et des clients désorientés ;structurelle, ensuite, avec la transition â marche forcée vers l'électrification. Cette double crise est a haut risque pour l'industrie automobile, mais l'alignement de l'action de l'ensemble des parties prenantes devrait permettre â la filiere française de rester dans la course pour l'automobile du futur.

Introduction

L'industrie automobile est a la croisée des chemins, car elle est soumise a une conjonction d'externalités d'une ampleur et d'une intensité rarement vues : absorption de toutes les crises récentes, celles du Covid et des semi-conducteurs, mais aussi celle de la hausse des prix de l'énergie. C'est celui de parvenir å intégrer ces techniques afin de parvenir a réinventer l'automobile de demain, une automobile connectée, robotisée et traitant automatiquement de grands volumes de données afin de progresser en intelligence, et de mettre celle-ci au service de l'humain, pour un usage réinventé de l'automobile et pour instaurer un systéme de mobilité plus durable. Il appelle ainsi a mieux cibler l'accompagnement des fournisseurs pour faire émerger une nouvelle génération d'ETI et aussi l'apparition de grands équipementiers leaders dans le monde de l'électrique, de l'hydrogene et, plus globalement, de l'automobile de demain. Il demande aussi que l'Europe se donne du temps pour s'adapter a la transition en protégeant temporairement, a l'instar des États-Unis, son marché intérieur.

The French automotive industry faces the challenge of the ecological transition

[...]the vehicle of the future must be considered within the broader framework of the mobility of the future, taking into account the entire value chain. Transforming our future into a sustainable future: planning for the automotive transition Didier Sepulchre de Condé, Mechanical industry The automotive industry is in turmoil, firstly because of the economic situation, with a market deeply affected by Covid, shortages of materials and components and disoriented customers;and secondly because of the structural situation, with the forced transition to electrification. The four paradoxes of the ecological transition of the European car industry Alois Kirchner, Former Director of Cabinet of the Minister for Industry The energy transition in the automotive sector is essential for achieving French and European climate objectives. [...]the actions implemented come up against four paradoxes, which must be overcome if this transition is to succeed: * the regulation on the reduction of CO2 emissions from the tank to the wheel, to the exclusion of other sources which now represent the majority of emissions from new vehicles;* the steering of vehicle traffic restrictions based on Crit'air stickers, leading to the prohibition of access to certain cities for vehicles that are more virtuous than others that are still allowed to enter;* the inability to implement policies to support the production of vehicles on European soil that are sufficiently powerful to halt the fall in associated jobs;a situation that benefits production sites that are not subject to the same environmental standards;* and the rising price of "green" vehicles, leading to a slowdown in the renewal of the fleet and the maintenance of a high level of pollution and carbon emissions.

Carbon Dioxide Monitoring in Refuse Collection Vehicle Cabins to Reduce the Risk of SARS-CoV-2 Airborne Transmission

During the COVID-19 pandemic, essential workers such as waste collection crews continued to provide services in the UK, but due to their small size, maintaining social distancing inside waste collection vehicle cabins is impossible. Ventilation in cabins of 11 vehicles operating in London was assessed by measuring air supply flow rates and carbon dioxide (CO2) in the driver's cabin, a proxy for exhaled breath. The indoor CO2 indicated that air quality in the cabins was mostly good throughout a working day. However, short episodes of high CO2 levels above 1500 ppm did occur, mainly at the beginning of a shift when driving towards the start of their collection routes. This data indicated that the ventilation systems on the vehicles were primarily recirculating air and the fresh air supply made up only 10-20 % of the total airflow. Following recommendations to partly open windows during shifts and to maintain ventilation systems, a second monitoring campaign was carried out, finding on average, an improvement in ventilation on board the vehicles. © 2022 17th International Conference on Indoor Air Quality and Climate, INDOOR AIR 2022. All rights reserved.

Optimization of Contactless Distribution in the Post-COVID Era

During an emergency, timely and effective distribution of emergency supplies is critical in rescue. In the context of Covid-19, given the difficulties in distributing supplies to communities due to super infectious viruses, unmanned vehicle distribution is studied by taking into account the priority and satisfaction of communities to improve distribution safety and effectiveness of supplies. Furthermore, the influence of distribution time on the overall efficiency is also taken into account, thus ultimately establishing an unmanned distribution model with the shortest distribution time while meeting community satisfaction. The improved whale algorithm is used to solve the dual-objective model and compared with the basic whale optimization algorithm. The results show that the improved whale algorithm demonstrates better convergence, searchability, and stability. The constructed model can scientifically distribute daily necessities to communities while considering their priority and satisfaction. © 2022 IEEE.

Initial trust formation on shared autonomous vehicles: Exploring the effects of personality-, transfer- and performance-based stimuli

Building initial trust is critical for the acceptance of shared autonomous vehicles (SAVs). Initial trust determines whether this emerging mobility solution will be accepted when it is available in the market. This study examines the initial trust formation process in the context of SAVs using the elaboration likelihood model and trust transfer theory. It investigates the effects of different personality-based, transfer-based, and performance-based factors on initial trust and adoption intention. A structural equation modelling is conducted in Singapore based on valid survey design principles, sampling protocols, and data analysis procedures. Results show that among three trust-building paths, the performance-based factors which include SAV capability and interaction quality are the most important. The transfer-based (i.e., trust in shared mobility) and personality-based factor (i.e., trust propensity) rank second and third, respectively. Six moderators such as covid history and shared mobility experience are also tested to investigate significant differences in the results. Based on these findings, this study offers theoretical and policy implications for scholars and practitioners.

A New Big Data Approach to Understanding General Traffic Impacts on Bus Passenger Delays

This paper presents a new method to quantify the potential user time savings if the urban bus is given preferential treatment, changing from mixed traffic to an exclusive bus lane, using a big data approach. The main advantage of the proposal is the use of the high amount of information that is automatically collected by sensors and management systems in many different situations with a high degree of spatial and temporal detail. These data allow ready adjustment of calculations to the specific reality measured in each case. In this way, we propose a novel methodology of general application to estimate the potential passenger savings instead of using simulation or analytical methods already present in the literature. For that purpose, in the first place, a travel time prediction model per vehicle trip has been developed. It has been calibrated and validated with a historical series of observations in real-world situations. This model is based on multiple linear regression. The estimated bus delay is obtained by comparing the estimated bus travel time with the bus travel time under free-flow conditions. Finally, estimated bus passenger time savings would be obtained if an exclusive bus lane had been implemented. An estimation of the passenger's route in each vehicle trip is considered to avoid average value simplifications in this calculation. A case study is conducted in A Coruña, Spain, to prove the methodology's applicability. The results showed that 18.7% of the analyzed bus trips underwent a delay exceeding 3 min in a 2,448 m long corridor, and more than 33,000 h per year could have been saved with an exclusive bus lane. Understanding the impact of different factors on transit and the benefits of a priority bus system on passengers can help city councils and transit agencies to know which investments to prioritize given their limited budget.

Investigation of Employee Related Airport Ground Access Strategies from a Post-COVID Perspective

Until recently, addressing the environmental externalities associated with the use of the private car and single occupancy vehicles has been the focus of the airport ground access policies worldwide. However, with the emerging unprecedented challenges of the COVID-19 pandemic, which have already changed the way we live, work, and travel, encouraging a change in commuter behavior has become even more important. This has necessitated that existing strategies be reconsidered in favor of adapting to a highly uncertain ‘‘COVID-19 world.'' Historically, there has been a dearth of literature relating to airport employees' ground access even though as a group employees represent an important segment of airport users with complex access requirements. This paper therefore focuses on airport employee related airport ground access strategies considering an emerging understanding of the future impacts of COVID-19 on global air travel. Pre-COVID strategies are investigated by conducting a documentary analysis of the most recent ground access strategies of 27 UK airports. The findings reveal that airport ground access strategies were mainly focused on setting targets and producing policy measures in favor of reducing car use and increasing the use of more sustainable transport modes including public transport, car sharing, and active travel (walking, cycling). However, measures encouraging public transport and car sharing will be more difficult to implement because of social distancing and fear of proximity to others. Instead, initiatives encouraging remote working, active travel, and improved staff awareness will be at the forefront of the future ground access strategy development. © National Academy of Sciences: Transportation Research Board 2021.

Reputation of Electric Vehicles in the Environment of Carbon Reduction and Accelerated Digitization

The accelerated digitization of the third decade of the twenty-first century poses a challenge both for science and for practice. The study presents partial results of continuous research on online reputation management of entities operating in the environment of low-carbon economy. The aim of the study is the application of a standardized methodology for calculating the Total level of Online Reputation (TOR) to determine the market position of selected Electric Vehicles (EVs) compared to the market position of conventional Vehicles with Internal Combustion Engines (ICEVs) in the online environment. The research sample consists of the ten best-selling Vehicles and the ten best-selling Electric Vehicles in the world by sales in the year 2021. Based on the measurement results and the subsequent analysis of the context, it can be concluded that the EV market shows the parameters of a developing market not only from the point of view of sales but also in terms of the overall level of Online Reputation as such. At the same time, it is possible to point out a high geographical specificity and significant disproportionality of the EV market compared to ICEVs. From the overall market perspective, the future of cars in the EV category is still unclear, as building trust in low-carbon products is limited by historical tradition. The main representatives of the EV industry thus represent the first forays of the onset of the low-carbon era in individual transport. The description of the issue will require the monitoring of status indicators over time. The results of the presented study can thus serve as a baseline and methodological framework for further research of the adoption of low-carbon policies in common practice.

Freight Distribution in Small Islands: Integration between Naval Services and Parcel Lockers

Freight transportation in urban areas represents an essential activity from the standpoint of economic development;in recent years, the spread of e-commerce (also accelerated by COVID-19) has contributed to increasing the demand for freight distribution over short distances. In most cities, the approaches and measures are often based on new technologies. Nevertheless, today there are contexts wherein delivery operations represent critical tasks to be solved. Furthermore, low accessibility areas, such as small islands, present further problems due to their exclusive dependence on maritime links (and often low-reliability services). This paper tackles this topic, formulating and solving a distribution problem by linking shipping services with last-mile distribution operated by means of an automatic delivery service (parcel lockers). A test application is proposed by considering the small island of Lipari in the archipelago of the Aeolian islands (Sicily, Southern Italy). The results show that such a type of service could reduce the user's waiting time when compared to traditional home deliveries.

Advanced Technologies for Geosite Visualization and Valorization: A Review

This review attempts to summarize contributions by authors who, in the last decade, have dedicated their efforts to making geoheritage accessible to the public. Geoheritage is composed of geosites, which are, nowadays, real milestones on which field-based geological education can be conducted. However, the COVID-19 pandemic in particular has made it clear that a new paradigm is needed;a series of tools must be introduced and increasingly used to make it possible for potential users, be they academics, students, or the lay public, to experience geosites from locations that can be thousands of kilometers away. All these have been achieved over time by a wide range of evolving techniques and advanced technologies such as GIS tools, virtual reality applications and further innovative technologies such as WebGIS platforms accompanied by appropriate navigation tools (VR headsets and thumbsticks). The viewers, in this way, are provided with a complete view of a virtual geosite, which enables visualizing its characteristics at different scales. VR technologies, especially, have revealed a high degree of satisfaction, based on feedback collected from VR geosite visualization events, both by scientists, students and the general public, and could be the forefront of geosite visualization and valorization in the near future.

Digital Twins in the Marine Industry

The ocean holds abundant resources, but the utilization of those resources for the marine economy presents a complex and dynamic industrial situation. Exploring sustainable development in this industry is of practical value, as it involves the rational use of marine resources while protecting the environment. This study provides an innovative review of the current application status of Digital Twins Technology (DTT) in various sectors of the marine industry, including the ship-building industry (SBI), Offshore Oil and Gas Industry, marine fishery, and marine energy industry. The findings reveal that DTT offers robust support for full life cycle management (LCM) in SBI, including digital design, intelligent processing, operation, and error management. Furthermore, this work delves into the challenges and prospects of DTT application in the marine industry, aiming to provide reference and direction for intelligent systems in the industry and guide the rational development and utilization of marine resources in the future.

Data-Driven Analysis and Optimization for Urban Energy Systems Equitable Resilience

Electric vehicles (EVs) can be leveraged as power resources to support the grid operation in challenging scenarios, e.g., natural disasters or health crises such as the COVID-19 pandemic. This paper aims to enhance equity of power resilience in urban energy systems by means of strategic allocation of EV charging infrastructure. We first use data-driven approaches to infer the relationships between communities' power resilience equity and available EV charging infrastructure as well as other prominent social-demographic factors. This inference leads to the development of a machine learning model for power resilience inequity prediction. We further develop an optimization frame-work that jointly considers equitable resiliency and resource utilization to guide the optimized EV charging infrastructure allocation across the city. Case studies demonstrate the capability of the devised approach in enhancing power resilience equity in marginalized communities. © 2023 IEEE.