Ted Morris

Development of internet-based traffic simulation framework for transportation education and training

Many traffic simulation software packages are available to help traffic engineers and researchers study and evaluate the potential impact of proposed traffic management strategies and policies. However, the existing tools require a significant investment in time to learn how to create models, perform calibrations, and, finally, analyze the results. This substantial learning curve severely restricts their application and makes it difficult for engineering students, the general public, and policy makers to take advantage of these tools. An Internet-based traffic simulation framework was developed to enhance the learning experience for transportation students and engineers. Pregenerated traffic scenarios were first implemented as part of an undergraduate civil engineering class. An interactive simulation tool was developed to allow users to make changes to the model and examine the impacts on traffic. This now allows students, for example, to minimize the queue length at the traffic signal by changing the cycle length or splits. This interactive traffic simulation tool was deployed and tested in an undergraduate class of 73 students. Feedback was collected from the instructors and the students and will lead to additional enhancements of the laboratory module. This web-based traffic simulation framework can also incorporate larger road networks that allow one to consider a multiplicity of traffic management strategies, thus providing a valuable tool for educating and training transportation professionals.

Using a maximum error statistic to evaluate measurement errors in 3d position and orientation tracking systems

One approach to tracking anatomical and robot joint motion consists of tracking the XYZ locations of multiple point targets that are attached to each of the moving segments and then computing the three translations and three orientation angles between adjoining segments. The complexity of such systems requires that we introduce a new conservative maximum error statistic to be used for evaluating the accuracy of 3D motion tracking systems. This paper addresses the various phenomena that contribute to measurement error when computing six degrees of freedom associated with the relative motion between the adjacent segments. The characteristics of these errors, common to many 3D motion tracking systems, were first determined by experimentation using one such system (MnSCAN). These and additional artifacts were then modeled in order to quantitatively evaluate their effects using the maximum error statistic. Based on these computer experiments, several relationships were identified that predict how each of these phenomena influences the predicted measurement of relative motion between bodies. These suggest where design emphasis should be placed in order to minimize the error in tracking the six degrees of freedom. The methodology and the conclusions based on these results can be applied to designing most six degree of freedom position and motion measurement systems.

Deployment of Wireless Mobile Detection and Surveillance for Data-Intensive Applications

Real-time information about traffic conditions is vital in construction, advanced traffic management systems, advanced traffic information systems, and other operational or design activities. Traditionally, at most permanent installations, such information is captured by in-pavement sensors and transmitted through land-based communications. However, temporary detection and surveillance are often needed as alternatives to the permanent sensor and camera systems at construction sites, during special events, or during communication or sensor failures. In such cases, temporary detection and surveillance must be reliable and low cost. Recent advances in wireless technologies have enabled development of portable detection and surveillance systems that can detect traffic, collect measurements, capture live video, and transmit this information wire-lessly back to the supervising station to facilitate rapid, inexpensive, and efficient deployment. However, to make widespread use practical, further improvements are needed in robustness, ease of use, functionality, and cost reduction. A low-cost, easily deployable detection and surveillance system is presented. The system integrates machine vision sensors for data collection, compressed digital video for surveillance, and wireless communications for information retrieval and remote control. It can be placed on existing or mobile structures and assembled with off-the-shelf components to serve department of transportation needs for both temporary traffic monitoring and planning and research data collection. Four of these advanced detection systems were deployed at a 1.7-mi site for wireless, continuous coverage, allowing detailed real-time data collection and surveillance. This data- and video-intensive deployment serves as a live laboratory for applications ranging from evaluation of new technologies (such as sensors, video, wireless communications) to testing of advanced traffic-simulation models or refinement of accident-prevention studies.

An automated system for persistent real-time truck parking detection and information dissemination

Tractor-trailer freight hauling has increased markedly within the United States over the past several years, resulting in higher truck volumes. commercial heavy vehicle drivers are required under federal Hours Of Services rules to rest and take breaks to mitigate driving while fatigued. Although there are many rest area facilities available to truck drivers, there is a lack of persistent timely information on truck parking availability. An automated real-time sensing system to directly detect and disseminate parking space occupancy from truck parking facilities is described in detail. The methodology and system architecture are presented in which robust, persistent, parking occupancy detection is achieved by extending Structure from Motion (SfM) techniques using a multiplicity of commercial, off-the-shelf cameras. The system architecture allows the approach to be scaled to a region-wide comprehensive truck parking information system for commercial heavy vehicle drivers and operators. Per parking space detection accuracy of 99% is achieved over continuous operation. Classification accuracy under diverse scene and parking behavior scenarios is discussed.