Cross-cutting Issues

The automotive market is ripe for in-car computing systems that deliver better safety, entertainment and information. Microsoft has spent the last five years working closely with automakers, automotive electronics manufacturers and consumers to develop its Windows CE for Automotive operating system, based upon our vision to empower the automotive industry with great software to provide information, entertainment, communication, and services in vehicles.

We have recently shipped, the third version of Windows CE for Automotive, firmly establishing our ability to deliver timely and innovative client platforms for the embedded automotive market. This latest release showcases Microsoft’s ability to lead with an operating system that is flexible, reliable, and able to integrate information, entertainment and wireless access to the outside world.

2000 Microsoft Corporation

Presented at the 11th ITS Annual Conference and Exposition, June 4-7, 2001 Miami Beach, Florida

In this paper, we present adaptations of the A* algorithm for computing shortest paths between an origin node and a destination node in dynamic networks for one or multiple departure times. We give some properties of dynamic networks on which the dynamic adaptations of the A* algorithm are based. We develop efficient lower bounds on minimum travel times that exploit these properties. These lower bounds are then exploited to design efficient adaptations of the A* algorithm to solve instances of the one-to-one dynamic shortest path problem. The adapted algorithms are implemented and their computational performance is experimentally evaluated and tested. Using randomly generated networks, we show that the computer implementations of these adaptations can lead to a saving ratio of 11, in terms of number of nodes selected, and a saving ratio of 5 in terms of computation times for a network with 3000 nodes 10000 links and 100 time intervals. It is also shown that the savings increase with the network size.

Massachusetts Institute of Technology

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA

Efficient storage, processing and communication of dynamic data are at the heart of Intelligent Transportation Systems (ITS) applications. The speed of communication and processing as well as the storage space required by such data depend on the method used for its representation. ITS applications typically involve dynamic data that is discrete and require fast computation and communication to support real-time operations. In this paper, we present an efficient representation method, which we call the bit-stream representation, for discrete-time dynamic data. We illustrate its positive impacts by developing efficient representations for storage and communication of travel times in dynamic transportation networks. We show theoretically that this representation method typically leads to an L/2-fold gain in both storage space and in communication speed as compared to methods that represent discrete-time dynamic data using L-bits to store an integer. The bit-stream representation method also opens new horizons in the research and development of algorithms that operate on dynamic data and holds the potential to discover a new generation of fast algorithms.

Massachusetts Institute of Technology

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA

This paper describes the situations of Intelligent Transport Systems (ITS hereinafter) in developing countries, especially Asian countries and a study of recommended approaches to introduce ITS in a provisional country. So far, ITS has been regarded as a system for the developed countries. However, looking at traffic problems such as accidents and congestion, we recognize that developing countries have the same or worse situations compared to the developed countries.

ITS America

Kobe University - Graduate School of Science and Technology

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA

A significant investment in intelligent vehicle R&D in the U.S. is being conducted by the US Department of Defense (DOD) through the Demo III autonomous scout vehicle program. Robotics has been identified by numerous DOD studies as a key enabling technology for future military operational concepts. The Demo III program is a multiyear effort encompassing technology development and demonstration on testbed platforms, together with modeling, simulation, and experimentation directed toward optimization of operational concepts to employ this technology. The primary program focus is the advancement of capabilities for autonomous mobility through unstructured environments, concentrating on both perception and intelligent control technology. The scout mission will provide the military operational context for demonstration of this technology, although a significant emphasis is being placed upon both hardware and software modularity to permit rapid extension to other military missions, including on-road freight movement. The program has developed the Experimental Unmanned vehicle (XUV), a small technology testbed vehicle. The XUV design couples multisensor perception with intelligent control to permit autonomous cross-country navigation at speeds of up to 32 kph during daylight and 16 kph during hours of darkness. The system design also encompasses on-road operations at up to 64 kph, including the capability to respond intelligently to other traffic and obstacles. When it concludes in 2002, Demo III will provide the military with both the technology and the initial experience required to develop and field the first generation of semi-autonomous tactical ground vehicles for combat, combat support, and logistics applications. The program has a high potential for technology spinoffs to civilian transportation, particularly in the area of obstacle detection and intelligent machine perception. This paper includes a description of the program rationale and requirements; the XUV status and capabilities; details on sensor selection, performance, and software architecture; and potential spinoff areas to ITS.

General Dynamics Robotic Systems

Richard Bishop Consulting

Presented at the 10th ITS Annual Conference and Exposition, May 1-4, 2000 Boston, MA