The purpose of this study is to develop and implement an analytical framework to calculate deterioration rates for bridges and large culverts based AASHTO-Element inspection data as well as NBI data and demonstrate the application of the approach through currently available inspection data. This analytical approach will be applied to generate deterioration rates for NYS bridges based on, but not limited to climate and/or geographical location, DOT Region, bridge ownership, material types, design types, and bridge types. The outcome of the research will be further implemented in the AASHTO BrM and the Agile Assets Structures Manager and Bridge Analyst.
The research team will first establish a test bed for the development of the advanced WIM (A-WIM) system by collaborating with local transportation agencies for the selection of the test bed site near a static weighing station. Then, it will develop a set of calibration procedures to guarantee that the level of accuracy is reached and preserved over time. These procedures will include, but are not limited to, the effect of temperature, humidity, and pavement type.
This multi-disciplinary project will combine the results of engineering modeling in the area of transportation infrastructure deterioration related to overweight trucks in New Jersey with economic approaches to estimate the contribution of these vehicles to maintenance costs.
This project will investigate technologies to screen overweight trucks including a high-speed weigh-in-motion (HS-WIM) system integrated with a license plate reader and/or security camera, and to evaluate the feasibility of such technologies compared to current screening practices at weighing stations.=.
The main objective of this study is the assessment of the Construction Impact Analysis (CIA) and Work Zone Impact and Strategy Estimator (WISE) tools, and determining the feasibility of their customization with respect to New York City Department of Transportation (NYCDOT) and New York State Department of Transportation (NYSDOT)’s needs and requirements, cost of adoption and modification, and related issues.
This research will focus on false data injection attacks, in which a malicious agent aims to affect the behavior of vehicles in the network by injecting false information about, for example, the traffic condition in the area or the availability of charging stations.
Access to real-time information on flooding can improve resiliency and efficiency by allowing residents to identify navigable transportation routes and make informed decisions to avoid exposure to floodwater contaminants. While there exist commercially available sensors that detect the presence of water inside homes, there is an unmet need for hyperlocal information on the presence and depth of street-level floodwater.
The objective of this study is to develop a model that links the resource requirements for Capital Program delivery functions with the NYSDOT Capital Program.
This study aimed to develop a demand model for an eFFCS service in the City of Seattle, which can increase the feasibility of eFFCS by reducing the cost of relocation by optimally locating the charging stations near the areas of heavy usage and real-time control to minimize manual relocation.
Led by INTERCEP founding director Bill Raisch, this project aims to adapt an information sharing and situational awareness technology platform currently used by INTERCEP’s Metropolitan Resilience Network to support transportation data sharing and stakeholder engagement in New York City and each of the C2SMART consortium member cities. This platform is designed to help users understand their larger operating environment, identify risks in that environment, and make informed decisions during disruptions using the assembled data.