Due to the high upfront cost of electric vehicles, many public transit agencies can afford only mixed fleets of internal-combustion and electric vehicles. Optimizing the operation of such mixed fleets is challenging because it requires accurate …
Food insecurity is the lack of consistent and reliable access to nutritious food. In the Houston (Texas) area, over 14% of Harris County households experienced food insecurity before the emergence of COVID-19. It is unclear how the nutritional needs of Houston’s vulnerable populations will be served when the next devastating weather event strikes the region, given that the city is already experiencing multiple disasters, including COVID-19, economic disruptions, and systemic food insecurity. The Houston Food Bank (HFB) collaborates with over 1,500 partners to address the needs of families experiencing food insecurity. The COVID-19 pandemic has stretched funding and personnel significantly while driving substantial increases in demand. HFB has adapted to past natural disasters, such as hurricanes and floods, in an ad hoc manner and seeks to build disaster resilience by incorporating strategies beyond current practices. The urgent needs are to identify food-insecure communities, understand their nutritional needs during disasters, and provide nutritious and culturally appropriate food in a manner that preserves privacy and dignity. Left unaddressed, these issues may create failures in HFB’s ability to distribute food effectively, equitably, and efficiently.
Public transit agencies are focused on making their fixed-line bus systems more energy efficient by introducing electric (EV) and hybrid (HV) vehicles to their fleets. However, because of the high upfront cost of these vehicles, most agencies are …
This Houston-based project establishes a collaborative process with community and commercial technology partners to accelerate the equitable development of accessible fast charging infrastructure and electric vehicle (EV) ownership for low income families by leveraging regional markets of early EV adopters. The novelty of the project lies in a community-driven participatory approach that integrates both social and technical dimensions, bringing transformational change to EV ownership and electrification of smart public transportation. This will be achieved using a data-driven model that integrates real-time data from micro-transit, fixed-route transit, and carpooling services to predict and overcome the uncertainties of traffic conditions, which would result in uncertain travel times and poor reliability. An engaging process establishes collaborative relationships, and identifies adopter indicators and incentives for equitable EV ownership and transit ridership. The project will result in a templet and framework for implementing smart transit hubs, which can be reapplied as best practices at other facilities of the Metropolitan Transit Authority of Harris County (METRO) or other transit systems.
Modern intelligent urban mobility applications are underpinned by large-scale, multivariate, spatiotemporal data streams. Working with this data presents unique challenges of data management, processing and presentation that is often overlooked by …
Electric vehicles (EVs) are critical to the transition to a low-carbon transportation system. The successful adoption of EVs heavily depends on energy consumption models that can accurately and reliably estimate electricity consumption. This article …
Affordable public transit services are crucial for communities since they enable residents to access employment, education, and other services. Unfortunately, transit services that provide wide coverage tend to suffer from relatively low utilization, …
Cyber attacks consisting of several attack actions can present considerable challenge to forensic investigations. Consider the case where a cybersecurity breach is suspected following the discovery of one attack action, for example by observing the …
Moving target defense (MTD) is a proactive defense approach that aims to thwart attacks by continuously changing the attack surface of a system (e.g., changing host or network configurations), thereby increasing the adversary’s uncertainty and attack …
In every public transit system, a trade-off has to be made between concentrating service into very useful routes that serve large numbers of people and spreading service out to ensure that people everywhere have access to at least some service. Improving the efficiency of an existing system while enhancing service in terms of both usefulness and coverage presents considerable challenges. These challenges to operational efficiency are exacerbated by the requirement to provide complementary paratransit services, which are typically characterized by very low efficiency (energy per passenger per mile) and attendant high cost of operation. Our vision is to address these challenges by combining the complementary advantages of fixed- and dynamic-route transit services and seamlessly integrating them. We focus on the following objectives: minimizing energy used per passenger per mile, minimizing passenger wait and trip times, maximizing service coverage, and maximizing the percentage of daily trips serviced by transit. To explore this complex decision space, we will design, implement, and evaluate an artificial intelligence engine, which will enable agencies with mixed-vehicle fleets (EVs, ICEVs, etc.) to operate integrated fixed-dynamic transit services that maximize energy efficiency and make transit more accessible.