In this project we report a comprehensive assessment of the power that is available for harvesting in the vehicle suspension system and the tradeoff among energy harvesting, ride comfort, and road handing with analysis, simulations, and experiments. The excitation from road irregularity is modeled as a stationary random process with road roughness suggested in the ISO standard.

An efficient electromagnetic energy harvester featured with mechanical motion rectifier (MMR) is designed to recover energy from the vibration-like railroad track deflections induced by passing trains. Comparing to typical existing vibration energy harvester technologies can only harvest sub-watts or milliwatts power applications, the proposed harvester is designed to power major track-side accessories and possibly make railroad independent from national grid.

Abstract: An effi cient electromagnetic energy harvester featured with mechanical motion rectifi er (MMR) is designed to recover energy from the vibration-like railroad track defl ections induced by passing trains. Trackside electrical infrastructures for safety and monitoring typically require a power supply of 10-100 Watts, such as warning signals, switches, and health monitoring systems, while typical existing vibration energy harvester technologies can only harvest sub-watts or milliwatts power.

This project develops a method for predicting coastal flooding considering climate change and sea level rise, and its impact on population and transportation network. In particular, a modeling framework has been proposed to predict flooding and estimate affected population and traffic systems needed for evacuation plans, and the following tasks have been conducted:

This research aims to explore performance measures quantified based on different transportation data sources. It examined the major performance measures that can help describe both traffic operations and safety conditions. The available data sources that can be used to derive the performance measures were investigated. Particularly, performance measures related to travel time reliability, incident duration, and secondary crashes have been emphasized. Data-driven methodologies for performance quantification have been proposed for each category.

In the past, transportation data was collected through the limited deployment of infrastructure-based sensors and manual spot counts and surveys. Massive on-line data being collected on a nearly 24/7 basis enable researchers and transportation managers alike to quantify a number of realistic “performance measures” that allow transportation agencies to make timely and proactive decisions.

While population increases, so do the demand for products and the freight traffic to deliver them. The increase in truck traffic creates many negative effects including increased traffic congestion, illegal parking and resting, incessant idling, and greenhouse gas and local pollutants emissions. Recently, many initiatives have been promoted to address this problem. The event presented cross-disciplinary perspectives on urban logistics using electric vehicles (EV) and other vehicles as a sustainable mobility transportation solution.