Search

Bus rapid transit (BRT) has been proved to be an effective tool to improve mass transit services. However, BRT's adaptive operations like management and scheduling under different scenarios are too complicated to implement using traditional methods. The ACP approach, which is based on holism and complex system theory and consists of artificial systems (A), computational experiments (C) and parallel execution (P), offers an efficient new method to cope with these complex systems, including BRT. In this paper, the parallel transportation management and control system for BRT (PTMS-BRT) is presented, which is designed and implemented using the ACP approach. PTMS-BRT integrates such functions as BRT's monitoring, warning, forecasting, incident management, and real-time scheduling, to provide its operations smoother, safer, more efficient, and reliable. It has been piloted successfully in Guangzhou BRT to demonstrate it as another successful example of parallel transportation systems.

Open source microcontroller (MCU) boards have made significant inroads towards classroom teaching over the last decade. Many programs have already switched from the traditional educational boards to, for example Arduino products, due to their low costs, easy to use, flexibility, and wide adoption in both consumer and industrial applications. However, comparing with their commercial counterparts, open source boards still lack rigorous and well-designed teaching, especially lab materials to have a seamless integration with existing curricular. Engine systems and controls is a core course in automotive engineering (AET) program that teaches students the theory and application of on-board diagnostics and monitoring system. The course has an intense lab component. Despite the consensus that AET curriculum needs more mechatronics material to reflect the critical roles that electrical, electronics, computing, communications, controls and software technologies play in today's vehicles, we find that nationwide, the lab facility of automotive programs are still heavily mechanical. We believe open source MCU boards are the ideal tool to develop new educational equipment and materials to transform automotive labs and to bridge the gap between classroom and industry knowledge base. In this work-in-progress paper we first introduce the Arduino shields for engine sensing and communication that we have designed at the request of, and in collaboration with AET faculty. We then present the assessment plan to evaluate the boards' effectiveness in helping students understand fundamental mechatronics concepts and practices, and their impact on students' learning experience for engineering design in a multi-disciplinary team.

This paper investigates the productivity and collaborations patterns in the publications of IEEE Transactions on Intelligent Transportation Systems (T-ITS) between 2010 and 2013. Our findings show that industry is playing a more important role in research cooperation. Such a trend is particularly beneficial for expediting the commercialization of scientific and technological advances. In addition, growing international collaborations have become a norm as researchers in the U.S., China, and Europe are increasingly involved in joint research endeavors.

Cardiovascular diseases are the leading cause of death in the United States. Advances in wireless technology have made possible the remote monitoring of a patient's heart sensors as part of a body area network. Some of these networks use a Bluetooth Low Energy (BLE) component to transmit the signal between the bio sensors and a smart phone. This study investigates the impact that stray wireless transmissions from residential microwave ovens have on the BLE component of the body area network. The results of this study may lead to improvements and widespread use of body area network medical systems, which may lead to better monitoring, more data, and fewer fatalities due to misdiagnosed heart conditions.

The application of supervised learning to train an intelligent vehicle with a neuro-fuzzy controller to mimic the driving behavior of a human driver is discussed. An initial fuzzy control system for vehicle driving was set up on the basis of general human driving experiences, and its control rules were modified to fit the driving behavior of an individual driver. This provides an effective mechanism to construct driving control systems with personality for automated intelligent vehicles.