Air Force Institute of Technology Research Report 2019

This Research Report presents the FY19 research statistics and contributions of the Graduate School of Engineering and Management (EN) at AFIT. AFIT research interests and faculty expertise cover a broad spectrum of technical areas related to USAF needs, as reflected by the range of topics addressed in the faculty and student publications listed in this report. In most cases, the research work reported herein is directly sponsored by one or more USAF or DOD agencies. AFIT welcomes the opportunity to conduct research on additional topics of interest to the USAF, DOD, and other federal organizations when adequate manpower and financial resources are available and/or provided by a sponsor. In addition, AFIT provides research collaboration and technology transfer benefits to the public through Cooperative Research and Development Agreements (CRADAs). Interested individuals may discuss ideas for new research collaborations, potential CRADAs, or research proposals with individual faculty using the contact information in this document

Efficiency and Effectiveness Impacts of a Computer-Assisted Scheduling and Dispatching System Implementation

Computer-assisted scheduling and dispatch (CASD) systems have been implemented in many paratransit systems in the United States to improve the effectiveness and efficiency of operations. This paper contributes to the limited literature of studies documenting the impact of such systems on paratransit operations based on the implementation of such a system in a small city in Illinois. The analysis provides evidence of small but measurable efficiency and effectiveness gains. This paper also provides evidence that proper CASD evaluation efforts should allow enough time after implementation so that not only familiarity with the system has been established, but also most or all of the necessary organizational changes related to the new technology have been completed

Efficiency and Effectiveness Impacts of a Computer-Assisted Scheduling and Dispatching System Implementation

Computer-assisted scheduling and dispatch (CASD) systems have been implemented in many paratransit systems in the United States to improve the effectiveness and efficiency of operations. This paper contributes to the limited literature of studies documenting the impact of such systems on paratransit operations based on the implementation of such a system in a small city in Illinois. The analysis provides evidence of small but measurable efficiency and effectiveness gains. This paper also provides evidence that proper CASD evaluation efforts should allow enough time after implementation so that not only familiarity with the system has been established, but also most or all of the necessary organizational changes related to the new technology have been completed

Information Technology, Productivity, and Asset Ownership: Evidence from Taxicab Fleets

We develop a simple model that links the adoption of a productivity-enhancing technology to increased vertical integration and a less skilled workforce. We test the model's key prediction using novel microdata on vehicle ownership patterns from the Economic Census during a period when computerized dispatching systems were first adopted by taxicab firms. Controlling for time-invariant firm-specific effects, firms increase the proportion of taxicabs under fleet ownership by 12% when they adopt new computerized dispatching systems. An instrumental variables analysis suggests that the link between dispatching technology and vertical integration is causal. These findings suggest that increasing a firm's productivity can lead to increased vertical integration, even in the absence of asset specificity

Information Technology, Productivity, and Asset Ownership: Evidence from Taxicab Fleets

We develop a simple model that links the adoption of a productivity-enhancing technology to increased vertical integration and a less skilled workforce. We test the model's key prediction using novel microdata on vehicle ownership patterns from the Economic Census during a period when computerized dispatching systems were first adopted by taxicab firms. Controlling for time-invariant firm-specific effects, firms increase the proportion of taxicabs under fleet ownership by 12% when they adopt new computerized dispatching systems. An instrumental variables analysis suggests that the link between dispatching technology and vertical integration is causal. These findings suggest that increasing a firm's productivity can lead to increased vertical integration, even in the absence of asset specificity

Basic zone control performance determination in FTS design

U radu je izložena procedura za procenu vremena blokiranja vozila u kontrolnim zonama, koja predstavlja mali deo postupka za određivanje vrednosti promenljivih performansi sistema i elementarnih podsistema u projektovanju fleksibilnih transportnih sistema (FTS). Procedura je završni korak Integralnog analitičkog modela (IAM) za projektovanje i određivanje performansi FTS-a, čiji je generalni algoritam, takođe, predstavljen. Predložena strategija analitičkog modeliranja znatno poboljšava nivo tačnosti predviđanja performansi sistema i elementarnih podsistema FTS-a.This paper presents procedure for estimation of vehicle control zone blocking times as an only a small part of system and elementary subsystems performance variables calculation in a flexible transport system (FTS) design. Procedure is a final step of an Integral analytical model (IAM) for FTS design and performances determination, whose general algorithm is shown. Some results of sensitively analyses performed by IAM are also presented. Proposed analytical modeling strategy substantially increases the level of accuracy of system and elementary subsystem performance predicting

The Police Response to Active Shooter Incidents

There have been many active shooter incidents in the United States since Columbine, and police agencies continue to modify their policies and training to reflect the lessons that are learned from each new tragedy. This report summarizes the state of the field as of 2014. The Police Executive Research Forum conducted research on these issues and held a one-day Summit in Washington, D.C., in which an overflow crowd of more than 225 police chiefs and other officials discussed the changes that have occurred, and where they are going from here

Improving Safety Service Patrol Performance

Safety Service Patrols (SSPs) provide motorists with assistance free of charge on most freeways and some key primary roads in Virginia. This research project is focused on developing a tool to help the Virginia Department of Transportation (VDOT) optimize SSP routes and schedules (hereafter called SSP-OPT). The computational tool, SSP-OPT, takes readily available data (e.g., corridor and segment lengths, turnaround points, average annual daily traffic) and outputs potential SSP configurations that meet the desired criteria and produce the best possible performance metrics for a given corridor. At a high level, the main components of the developed tool include capabilities to: a) generate alternative feasible SSP beat configurations for a corridor; b)predict incidents and SSP characteristics (e.g., incident frequency, SSP service time) for a given SSP beat configuration; c) estimate performance measures (e.g., SSP response time, number of incidents responded to); and d) identify and present the best SSP configuration(s) through visual aids that facilitate decision making. To generate the incident data needed for the simulation-based SSP-OPT tool, a hierarchical negative binomial model and a hierarchical Weibull model are developed for incident frequencies and incident durations, respectively, based on the historical incident data. These models have been found to be effective in simulating the spatiotemporal distribution of incidents along highway corridors and for generating their attribute data (e.g., incident type, duration). The simulation program employs a discrete event-based approach and requires a few calibration parameters (e.g., SSP vehicle speed). After calibrating the model, the validation results show good agreement with field observations when applied to a sample SSP corridor from I-95. A user interface is created for the SSP-OPT tool in MS Excel to facilitate data entry and visualization of the output metrics for a given corridor. The output includes the list of alternative feasible beat configurations and aggregated performance measures from multiple runs for each individual beat, as well as for each alternative beat configuration spanning the entire corridor. The proposed SSP optimization model could be applied to corridors with or without existing SSP service. The tool will help identify the best beat configurations to minimize SSP response times and maximize SSP response rates for a given number of SSP vehicles on a corridor. Implementing these optimal solutions in the field will result in travel time savings and improve highway safety since the SSP resources will be more efficiently utilized, thus reducing the impacts of incidents on traffic flow

Knowledge Discovery and Data Mining for Shared Mobility and Connected and Automated Vehicle Applications

The rapid development of shared mobility and connected and automated vehicles (CAVs) has not only brought new intelligent transportation system (ITS) challenges with the new types of mobility, but also brought a huge opportunity to accelerate the connectivity and informatization of transportation systems, particularly when we consider all the new forms of data that is becoming available. The primary challenge is how to take advantage of the enormous amount of data to discover knowledge, build effective models, and develop impactful applications. With the theoretical and experimental progress being made over the last two decades, data mining and machine learning technologies have become key approaches for parsing data, understanding information, and making informed decisions, especially as the rise of deep learning algorithms bringing new levels of performance to the analysis of large datasets. The combination of data mining and ITS can greatly benefit research and advances in shared mobility and CAVs.This dissertation focuses on knowledge discovery and data mining for shared mobility and CAV applications. When considering big data associated with shared mobility operations and CAV research, data mining techniques can be customized with transportation knowledge to initially parse the data. Then machine learning methods can be used to model the parsed data to elicit hidden knowledge. Finally, the discovered knowledge and extracted information can help in the development of effective shared mobility and CAV applications to achieve the goals of a safer, faster, and more eco-friendly transportation systems.In this dissertation, there are four main sections that are addressed. First, new methodologies are introduced for extracting lane-level road features from rough crowdsourced GPS trajectories via data mining, which is subsequently used as the fundamental information for CAV applications. The proposed method results in decimeter level accuracy, which satisfies the positioning needs for many macroscopic and microscopic shared mobility and CAV applications. Second, macroscopic ride-hailing service big data has been analyzed for demand prediction, vehicle operation, and system efficiency monitoring. The proposed deep learning algorithms increase the ride-hailing demand prediction accuracy to 80% and can help the fleet dispatching system reduce 30% of vacant travel distance. Third, microscopic automated vehicle perception data has been analyzed for a real-time computer vision system that can be used for lane change behavior detection. The proposed deep learning design combines the residual neural network image input with time serious control data and reaches 95% of lane change behavior prediction accuracy. Last but not least, new ride sharing and CAV applications have been simulated in a behavior modeling framework to analyze the impact of mobility and energy consumption, which addresses key barriers by quantifying the transportation system-wide mobility, energy and behavior impacts from new mobility technologies using real-world data