Utayba Mohammad

ITS based methodology to reduce energy consumption and emissions

Global warming is currently one established fact threatening the survival of all life forms on planet earth. Although no one industry has been identified to be fully responsible for the greenhouse gases (GHG) emissions, it has become clear that the transportation industry is a key player in this global dilemma and that it has to be addressed. In the U.S, global warming has manifested itself as a financial problem and a potential solution. The U.S dependence on foreign petroleum has been weakening its economy and threatening its national security; which made improving the fuel economy of automobiles and reducing demand on fossil fuel a priority from both the economy and the global warming prospective. As a result, a new wave of environment-aware technology research has been spurred in the U.S targeting different areas of renewable energy and improved energy efficiency machinery. This paper falls into the second category, and it introduces a prototype design application to reduce emissions and to mitigate future global warming by giving appropriate consideration to travel time and expected vehicle performance in all type of plug in hybrid and electric vehicles. Previous studies revealed that aggressive driving is proportionally related to vehicle emissions. Providing vehicles with real time and predictive future traffic information can result in reducing energy consumption and thus GHG emissions. This paper proposes the use of the IntelliDrive and navigation system technologies to integrate energy, emission and travel time constrained algorithm to reduce emissions at traffic intersections (light and sign controlled). The proposed system will provide an advisory audible/visual output to the driver that recommends optimized route, drive and accessory load profiles for improving energy consumption, emission and travel time

Navigating with VFH: a strategy to avoid traps

The IGVC Navigation Challenge course configuration has evolved in complexity to a point where use of a simple reactive local navigation algorithm presents problems in course completion. A commonly used local navigation algorithm, the Vector Field Histogram (VFH), is relatively fast and thus suitable when computational capabilities on a robot are limited. One of the attendant disadvantages of this algorithm is that a robot can get trapped when attempting to get past a concave obstacle structure. The Navigation Challenge course now has several such structures, including some that partially surround waypoints. Elaborate heuristics are needed to make VFH viable in such a situation and their tuning is arduous. An alternate approach that avoids the use of heuristics is to combine a dynamic path planning algorithm with VFH. In this work, the D*Lite path planning algorithm is used to provide VFH with intermediate goals, which the latter then uses as stepping stones to its final destination. Results from simulation studies as well as field deployment are used to illustrate the benefits of using the local navigator in conjunction with a path planner.

Predictive Intelligent Battery Management System to Enhance the Performance of Electric Vehicle

The Electric Vehicle (EV) is emerging as state-of-the-art technology vehicle addressing the continually pressing energy and environment concerns. The benefits of EV emerge from these vehicles’ capability of sustaining their energy demands through electric grid rather than fossil fuel consumption. Wellto-Wheel studies have shown that electric drive (E-drive) offers the highest fuel efficiency and consequently the lowest emission of green house gases. Grid electricity in the United States of America has been shown to be four times cheaper than fuel given gasoline prices at

Scalability in a Dynamic Discovery Service-based Jini for the Next Generation vehicle network

3/gallon. Consequently, it is crucial to further optimize the electric-drive mode for EV. Battery capacity should be designed to allow EV drivers reach their destination while avoiding unnecessary stops to recharge their vehicles. However, this additional battery capacity would impact the vehicle’s space, weight and cost. In view of these limitations, we propose integrating EVs with the vision of Intelligent Transportation Systems (ITS). This chapter starts out by putting the design of EVs into a broader perspective by proposing a Predictive Intelligent Battery Management System (PIBMS), which will enhance the overall performance of EVs including energy consumption and emissions using the ITS infrastructure. At the end of this chapter, the reader should have an understanding of the capabilities and limitations of the PIBMS. It lays out the design foundation for the future implementation of an interconnected EV equipped with PIBMS, which further contributes to the optimization of energy efficiency and reduced emissions.

A new trajectory-based path planning approach for differential drive vehicles

Rapid advances in the areas of computing, sensing, and communications have enabled vehicle manufactures to provide new features for vehicles to enhance safety, pleasure, convenience, and reliability. Moreover future vehicles are expected to become a part of the Internet, either as a network node, or as a hub constructing a vehicular ad hoc network. This vehicular ad hoc network represents large dynamic distributed processing systems. These vehicles communicate with each other and with the Internet, to access services such as traffic conditions, finding nearest hospital, remote monitoring, etc. To accomplish this type of services, new methodology will be needed such as Dynamic Discovery Service. Dynamic Discovery Service is a system in which servers search through lookup services to first discover and then register the service they offer in the lookup service as a proxy.This research proposes Dynamic Discovery Service-based Jini architecture. A Dynamic Discovery Service (DDS)-based Jini system is a distributed environment where services and devices can participate to offer resources to other members of the community. To be efficient DDS-based Jini, system should be evaluated in terms of scalability, latency, bandwidth usage. This paper will examine the scalability of the lookup service mechanisms in terms of lookup latency as well as generated network traffic. Specifically, the experiments examined the lookup response time as a function of increasing number of services registered, and increasing lookup nodes, all in a static environment as well as the lookup response time in a dynamic environment.

Navigating a path delineated by colored flags: an approach for a 2011 IGVC requirement

A new robot local path planning algorithm is proposed that attempts to improve drive path contouring when in autonomous mode, by integrating a vehicle dynamics model into decision making. The technique is formulated in a space made up of path trajectories, where each trajectory corresponds to selected values for four parameters - initial and final forward and turn velocities for the robot. A criterion function that balances speed vs. safety is formulated to pick the best target forward and turn velocities for any given robot state. An advantage of the method is that driving decision commands are directly compatible with typical differential-drive motor controller inputs. The method is implemented on a differential drive robot with torque-limited motors, that is driven in a roadway type environment with occasional partial obstruction. Experimental results are presented.

Performance Evaluation of IEEE 802.15.4/ZigBee Protocol for Automotive Applications

In this work, we address a situation presented as a new requirement for the Autonomous Challenge portion of the 2011 Intelligent Ground Vehicle Competition (IGVC). This new requirement is to navigate between red and green colored flags placed within the normal white painted lane lines. The regular vision algorithms had to be enhanced to reliably identify and localize the colored flags, while the Navigation algorithms had to be modified to satisfy the constraints placed on the robot while transiting through the flag region. The challenge in finding a solution was the size of the flags, the possibility of loosing them against the background, as well as their movement in the wind. The attendant possibility of false positives and negatives also needed to be addressed to increase reliability of detection. Preliminary tests on the robot have produced positive results.