Investing in existing passenger rail and building new high-speed services will help to decarbonize America’s transportation

In the U.S. today, driving is easy, accessible, relatively affordable, and convenient. But Americans’ reliance on the car has huge impacts on CO2 emissions and encourages unsustainable urban sprawl. Camille Kamga writes that making better and more efficient cars is not the answer to these problems; he argues that more, better, faster rail services are needed. These kinds of investments will take advantage of emerging trends away from driving and car ownership and will help to decarbonize America’s transportation

Transit Signal Priority in Smart Cities

Giving priority to public transport vehicles at traffic signals is one of the traffic management strategies deployed at emerging smart cities to increase the quality of service for public transit users. It is a key to breaking the vicious cycle of congestion that threatens to bring cities into gridlock. In that cycle, increasing private traffic makes public transport become slower, less reliable, and less attractive. This results in deteriorated transit speed and reliability and induces more people to leave public transit in favor of the private cars, which create more traffic congestion, generate emissions, and increase energy consumption. Prioritizing public transit would break the vicious cycle and make it a more attractive mode as traffic demand and urban networks grow. A traditional way of protecting public transit from congestion is to move it either underground or above ground, as in the form of a metro/subway or air rail or create a dedicated lane as in the form of bus lane or light rail transit (LRT). However, due to the enormous capital expense involved or the lack of right-of-way, these solutions are often limited to few travel corridors or where money is not an issue. An alternative to prioritizing space to transit is to prioritize transit through time in the form of Transit Signal Priority (TSP). Noteworthy, transit and specifically bus schedules are known to be unstable and can be thrown off their schedule with even small changes in traffic or dwell time. At the same time, transit service reliability is an important factor for passengers and transit agencies. Less variability in transit travel time will need less slack or layover time. Thus, transit schedulers are interested in reducing transit travel time and its variability. One way to reach this goal is through an active intervention like TSP. In this chapter a comprehensive review of transit signal priority models is presented. The studies are classified into different categories which are: signal priority and different control systems, passive versus active priority, predictive transit signal priority, priority with connected vehicles, multi-modal signal priority models, and other practical considerations

Slowing the spread of COVID-19: Review of “Social distancing” interventions deployed by public transit in the United States and Canada

This paper presents a review of social distancing measures deployed by transit agencies in the United States and Canada during the COVID-19 pandemic and discusses how specific operators across the two countries have implemented changes. Challenges and impacts on their operations are also provided. Social distancing is one of the community mitigation measures traditionally implemented during influenza pandemics and the novel coronavirus pandemic. Research has shown that social distancing is effective in containing the spread of disease. This is applicable to the current situation with the novel coronavirus, given the lack of effective vaccines and treatments in the United States and Canada in the first eight months of the pandemic. Moreover, social distancing is particularly useful in settings where community transmission is substantial. Directives for social distancing were issued in several states and public transit operators were charged with how to provide for physical distance of six feet between passengers on their property including physical infrastructure such as station buildings and rolling infrastructure (rolling stock) including trains, subway cars and buses. Operational changes were also required due to physical distancing, e.g. adding train cars to provide for opportunities to physically distance on the train. Examples of some measures discussed in this research includes taping off every other seat on buses, increasing the total length of trains by adding cars, separating bus drivers from passengers with plastic sheeting, rear door boarding, etc. This research also analyzes long-term impacts for transit operators and challenges to encourage passengers to return to public transit after lockdown requirements ordered by government officials are lifted. A section on the policies that are being explored by government to continue to sustain public transportation is also included

Understanding Electricity-Theft Behavior via Multi-Source Data

Electricity theft, the behavior that involves users conducting illegal operations on electrical meters to avoid individual electricity bills, is a common phenomenon in the developing countries. Considering its harmfulness to both power grids and the public, several mechanized methods have been developed to automatically recognize electricity-theft behaviors. However, these methods, which mainly assess users' electricity usage records, can be insufficient due to the diversity of theft tactics and the irregularity of user behaviors. In this paper, we propose to recognize electricity-theft behavior via multi-source data. In addition to users' electricity usage records, we analyze user behaviors by means of regional factors (non-technical loss) and climatic factors (temperature) in the corresponding transformer area. By conducting analytical experiments, we unearth several interesting patterns: for instance, electricity thieves are likely to consume much more electrical power than normal users, especially under extremely high or low temperatures. Motivated by these empirical observations, we further design a novel hierarchical framework for identifying electricity thieves. Experimental results based on a real-world dataset demonstrate that our proposed model can achieve the best performance in electricity-theft detection (e.g., at least +3.0% in terms of F0.5) compared with several baselines. Last but not least, our work has been applied by the State Grid of China and used to successfully catch electricity thieves in Hangzhou with a precision of 15% (an improvement form 0% attained by several other models the company employed) during monthly on-site investigation.Comment: 11 pages, 8 figures, WWW'20 full pape

Hunts Point Terminal Market: The Demand for Waterborne Transportation as a Part of the Outbound-Distribution System [Brief]

New York City roads and highways leading to the City are congested, in part, due to trucks delivering food products. Some of the deliveries are to the Hunts Point Terminal Market (HPTM) located at the Hunts Point Peninsula. HPTM is the largest fresh food distribution center in the United States. It is the source of 60%1 of food distribution in the New York Metropolitan Area. These trucks increase traffic congestion, pollution, and wear and tear of the roads. In turn, this increases the cost of living in the City, commute time, medical problems and costs, and reduced productivity to name a few negative impacts

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century