Connected Cities for Smart Mobility toward Accessible and Resilient Transportation
project posts that is managed in CIP
Although lots of research have been conducted on multi-vehicle cooperative perception, few studies have considered combining information from vehicle onboard sensors and roadside sensors. This project argues that it would be highly beneficial to utilize roadside sensors for cooperative driving perception.
Overview Transportation agencies have been enforcing illegal overweight trucks at the weighing stations and by the Police enforcement units. It was found that only 8.6% of the actual overweight trucks
This project will increase the safety profile and ease-of-use of the VISION (Visually Impaired Smart Service System for Spatial Intelligence and Onboard Navigation) platform toward ‘connected’ dynamic navigation in complex urban environments, providing a new level of security to the end user and permitting one to break down significant barriers to employment and social interaction.
Autonomous vehicles (AV) and connected vehicles (CV) technology has been much of the focus of transportation industry lately, and they will likely make a vast impact on the future of transportation systems. This project will combine AV and CV technologies for connected and autonomous vehicles (CAVs) to reduce congestion and improve network performance and safety by developing new tools and methods using reinforcement learning and nonlinear and optimal control techniques.
Game theory is a powerful tool for security risk analysis that has been extensively used in various engineering systems, and game-theoretic approaches have been applied to studying the security of routing in transportation and communications. This project will be the basis for a synthesis of game theory and queuing theory, essential for capturing the interaction between the queuing dynamics and players decisions, in order to protect the ITS system from spoofing and attacks.
Dr. Zhou and Dr. Ozbay found that, if the traffic flow parameters are time-varying and/or the knowledge of these parameters are biased, the performances of a traffic state estimator that has assumed them to be known and fixed-valued can be significantly downgraded. Moreover, only augmenting these parameters into the state vector and then resorting to nonlinear recursive estimation techniques such as extended Kalman filter (EKF) cannot solve the issue. This is because, under a CTM-based traffic estimator, the critical density is unobservable under free-flow conditions, and hence biased initial knowledge of the critical density can cause false switching of the working model of the estimator and distort the estimation afterward.
This perception of transit can be captured through the sentiment of posts made by users on social media. Performance metrics based on user perception can provide the service provider a customer-facing view of their service and help enhance their service and address the user concerns, especially from a public health standpoint in a post-COVID lockdown world, appropriately.
This project focuses on the feasibility of the proposed EMEH to power sensors that are used to regularly monitor the structural integrity of materials and components of highway bridges such as acceleration and temperature sensors.
The primary objective of this research project is to define quantifiable metrics that make it possible to adequately represent accessibility of EV charging infrastructure and to internalize these metrics in decision-support procedures and tools that are used by utilities and authorities to determine electricity rates (tariffs) and additional incentives to promote investments in EV charging infrastructure.
Traffic simulation is an important tool that can assist researchers, analysts, and policymakers to test vehicle/traffic control algorithms, gain insights of micro/macro traffic dynamics, and design traffic management strategies. However, different implementations require different simulation scales and there is no multiscale simulation platform that satisfies all requirements. In this research, we propose to establish a multiscale vehicle-traffic-demand (VTD) simulation platform for connected and automated transportation systems (CATS).