An Autonomous Modular Mobility Paradigm

In the United States, public transit vehicles have a very low average load factor (10.1-12.4%), resulting in an excessive waste of seat capacity and poor fuel economy per passenger mile served. This problem is gravely exacerbated by the COVID-19 pandemic, which at its peak had caused more than 70% reduction in transit ridership nationwide. On the other hand, the rapid uptake of e-commerce, also accelerated by the pandemic, has put tremendous pressure on last-mile delivery. A co-modality system that integrates transit services with last-mile logistics offers a promising solution to better utilization/sharing of vehicle capacity and supporting infrastructure. Here we show such a system may be implemented based on Autonomous Modular Vehicle Technology (AMVT). At the core of AMVT is the ability to operate a fleet of modular autonomous vehicles or pods that can be moved, stationed, joined, and separated in real time. Coupling modularity with autonomy is poised to enable co-modality and beyond. We describe an AMVT bimodality system that provides integrated public transit and last-mile logistics services with a fleet of pods and discuss relevant research challenges and opportunities, research approaches, and real-world adoption issues. © 2009-2012 IEEE.

Learning in the Pandemic: How the possibility to play video games during class and attend lessons without getting out of bed affects time-on-task

This Innovate Practice work-in-progress paper presents findings around how distance learning, due to the the COVID-19 pandemic, affected students as measured by time-on-task in programming.In this qualitative study, we examine a group of 36 second year upper-secondary students in Programming 1 during a nine week period in Spring 2021. During this time, they alternated between one whole week of distance learning followed by two weeks of in school instruction. For the Programming 1 lessons, students used an online platform to write, edit and run code in. We analyzed the log data from the platform to estimate time-on-task for each student for every lesson both at home and at school.We observed that students were affected differently by distance learning as measured by time-on-task. 12 students had more average time-on-task at school. 15 students had more average time-on-task at home. Nine students had less than five minutes difference on average.In addition to the analysis of time-on-task, students were given a survey in Fall 2021 to follow up on their experiences with in-school teaching and distance learning. In the survey, students were asked questions about their study environment at home during distance learning. From the responses, 13 students described their study environment as 'in bed' despite having access to a table and chair in a room for themselves and twenty-three students described their study environment as 'playing video games during online lectures'. Not surprisingly, students that said they were playing video games during online lectures had a lower average time-on-task by about ten minutes than their peers. Interestingly, students that said they participated in class in bed had a higher average time-on-task by about ten minutes than their peers.Correlating responses from the survey and time-on-task data, we reason about how students' study environments at home affected their time-on-task and how distance learning has affected students in the pandemic. © 2022 IEEE.

Comparison of Audio Quality of Teleconferencing Applications Using Subjective Test

The human need to communicate and connect during the Covid-19 pandemic has led to the increasing use of teleconferencing applications. Users naturally pay attention to audio quality in choosing a teleconference application from many available and easily accessible applications. Audio quality is partly affected by the audio coding method used and developed on the application and the noise introduced within the network. This work evaluates the audio quality of 5 popular teleconferencing applications using the subjective test. For complement, objective tests and Signal-to-Noise Ratio (SNR) assessments are also carried out. The standard used for the subjective test is ITU-R BS.1116-3: Methods for the Subjective Assessment of Small Impairments in Audio Systems, which aims to identify small differences between audio quality. The assessment is conducted by comparing the original and compressed audio. The original audio is recorded from the speaker side, while the compressed audio is recorded from the receiver side. Both are assessed using the subjective test method by 20 subjects. The assessment results of each audio teleconferencing application are different, even though some applications use the same codec. We also found that one of the most popular applications tends to have the lowest average score among the tested audio applications. © (2022) by the Audio Engineering Society All rights reserved.