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The Minnesota Guidestar program promotes research, development, operational testing, deployment, and operations of Intelligent Transportation Systems (ITS) in Minnesota. In the Twin Cities metropolitan area, the program focuses on the Minnesota Department of Transportation's (Mn/DOT's) Regional Transportation Management Center located in Roseville. This center manages traffic flow, incidents, and traveler information in the Twin Cities. In greater Minnesota, Transportation Operation and Communications Centers provide traveler information on road and weather conditions as well as dispatching State Patrol troopers and Mn/DOT maintenance vehicles.

This seminar will discuss three Guidestar projects. The Mayday project is a joint effort between Mn/DOT and On-Star to improve emergency response to motorists involved in a crash. The Truck Priority project investigated the advantages of providing preferred traffic signal timing for trucks. The CARS/511 program provides traveler information to motorists via the telephone and the Web.

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Recent natural or man-made disasters around the world have provided compelling evidence that transportation system plays a crucial role in the emergency evacuation and have stressed the need for effective evacuation traffic management to maximize the utilization of the transportation system and to minimize fatalities and losses. This talk presents a model reference adaptive control (MRAC) framework for real time traffic management under emergency evacuation. Distinct from the well-studied evacuation planning, real time traffic management for evacuation aims to dynamically guide (control) traffic flow under evacuation in such a way that certain system objective (e.g. minimization of fatalities or property losses) could be achieved. The proposed framework is based on both dynamic network modeling techniques and adaptive control theory, by considering the traffic network under evacuation as a dynamic system. Simulation studies show that the proposed framework based on MRAC can significantly improve the performance of real time evacuation traffic management.

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Employing multiple-system models is a way to rapidly adapt estimation or control routines to the current operating mode of the system. In terms of estimation, having multiple plant models can ensure having one model that represents the current system behavior and produces accurate state estimates over all time. The key concern is finding algorithms that are computationally acceptable. Optimal routines can explode exponentially in the number of models. In this seminar, Dr. Caveney will present a probabilistic technique that is roughly linear in the number of models and that can handle sensor issues commonly encountered in a target tracking problem.

This problem was motivated by Dr. Caveney's doctoral work with BMW Research and Technology involving Adaptive Cruise Control systems. He will first discuss the prototype multiple model, multiple-target tracking routine implemented on BMW's test vehicles in Munich, Germany. He will also describe the interconnection of such a multiple model estimator with multiple model-based controllers.

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This presentation will walk through the steps taken to design and develop and infrastructure-based decision support system to help drivers cross rural stop-controlled intersections. The human factors process includes the identification of driver tasks and related errors while navigating rural stop-controlled intersections, identification of high-risk populations and identification of potential information to be used on the system. A summary of results obtained from the simulator study will also be discussed.

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Over the last decade, approximately 6,000 teenagers have died on our nation's roads every year. One possible approach to reduce the number of teenage driver crashes and fatalities is through the use of in-vehicle technology. Such a system should address the primary contributing factors associated with the majority of teen fatal crashes: speed, aggressive driving, low seat belt use, and alcohol impairment. This could be accomplished through a combination of forcing, feedback, and reporting functions. Forcing functions could take the form of ignition interlocks to enforce seat belt compliance and sober driving. A feedback function could provide real time tutoring and warnings about illegal or unsafe speeds. A reporting function could record vehicle information for parents to review and enforce teen driver performance. If implemented, a Teen Driver Support System (TDSS) such as described here could significantly decrease the number of teenagers killed in traffic crashes.

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Ridership is a key element in the transit industry. Most travel analysis identifies two types of users: captive and choice riders. Captive riders are typically those who lack an alternative an alternative to transit, and so use it as their main mode of travel to reach their destination. Choice riders are those who typically can choose to use transit or a different mode (car or walking) to reach their destination.

The ridership of both populations is affected by service reliability and availability. However, substantial increases in ridership are usually assumed to be derived only from choice riders.

This research analyzes results from two surveys conducted in the Twin Cities metropolitan region: one of existing riders and the other of non-riders. The aim is to understand the characteristics of both captive and choice riders, with an eye toward the factors that can increase ridership of the latter population. In particular, the research focus lies in understanding different classifications of existing and proposed riders (based on preferences from the surveys) and commenting on how advanced forms of technology could be used to increase various populations.

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This presentation will describe efforts to develop a global dynamic testing method and equipment for evaluating rapid in-place testing techniques that assess the structural health of timber bridges. Minnesota has more than 4,000 timber bridges in service, and traditional testing is both time-intensive and challenging.

Deterioration of wood superstructures caused by decay, insects, overloading, or other factors reduces the strength and stiffness of wood components and affects the dynamic behavior of the system. An analytical model based on simple beam theory was proposed to represent the relationship between the first bending mode frequency and bridge stiffness (characterized as EI product). Results indicated that the forced vibration method has potential for quickly assessing the superstructure stiffness of timber bridges with longitudinal stringers, but improvements must be made in measurement systems to correctly identify the first bending mode frequency in bridges in the field.

This presentation will demonstrate the advanced vibration equipment being used to assess wooden bridges in Minnesota, as well as the potential implications of this technology for single-span steel and concrete bridges.