Intelligent Transportation Systems

Since Hurricane Katrina, there has been an increasing focus on disaster relief efforts in the United States. In this paper, the authors examine the progression of transportation management under emergency conditions and opportunities for addressing disasters by leveraging the sharing economy. The sharing economy mobilizes the unused capacity and resources of individuals through mobile and Internet platforms. Notable examples include mobility and the housing sectors. The authors argue here that there is an opportunity to improve disaster preparedness, response, and recovery by...

In 1996, California Partners in Advanced Transit and Highways (PATH) commissioned a project team led by the Institute of Transportation Studies, University of California at Davis with the Claremont Graduate School to undertake a review of the environmental impacts of Intelligent Transportation Systems (ITS). The objectives of this project were to: 1) review previous qualitative and quantitative environmental assessments of ITS, from both field operational tests and modeling studies; 2) review the regulatory and policy contexts which encompass ITS; 3) develop a modeling framework suitable...

With a projected rise in the number of elderly, most of whom have also relied primarily on the private automobile for their mobility, it is likely that future adaptations in vehicle design will be linked in some part to the physical infirmities often faced by the elderly. This paper offers a bridge between medical research on the physical impairments of the elderly and automobile design and driving safety. We describe recent findings on the driving-related physical and cognitive impairments faced by the elderly. We then propose two major types of vehicle design and infrastructure...

This article demonstrates a novel, compact-sized hardware-in-the-loop (HIL) system, and its verification using machine learning (ML) and artificial intelligence (AI) features in battery controls. Conventionally, a battery management system (BMS) involves algorithm development for battery modeling, estimation, and control. These tasks are typically validated by running the battery tester open-loop, i.e., the tester equipment executes the predefined experimental protocols line by line. Additional equipment is required to make the testing closed-loop, but the integration is typically not...