Jung In Kim

Vision-based surveillance system for monitoring traffic conditions

With the rapid advancement of sensing technologies, it has been feasible to collect various types of traffic data such as traffic volume and travel times. Vision-based approach is one of the major scheme actively used for the automated traffic data collection, and continues to gain traction to a broader utilization. It collects video streams from cameras installed near roads, and processes the video streams frame by frame using image processing algorithms. The widely used algorithms include vehicle detection and vehicle tracking which recognize every vehicle in the camera view and track it in the consecutive frames. Vehicle counts and speed can be estimated from the detection and tracking results. Continuous efforts have been made for the performance improvement of the algorithms and for their effective applications. However, little research has been found on the application to the various view settings of highway CCTV cameras as well as the reliability of the speed estimation. This paper proposes a vision-based system that integrates vehicle detection, vehicle tracking, and field of view calibration algorithms to obtain vehicle counting data and to estimate individual vehicle speed. The proposed system is customized for the video streams collected from highway CCTVs which have various settings in terms of focus and view angles. The system detects and tracks every vehicle in the view unless it is occluded by other vehicles. It is also capable of handling occlusions that occurs frequently depending on the view angles. The system has been tested on the several different views including congested scenes. Vehicle counts and speed estimation results are compared to the manual counting and GPS data, respectively. The comparison signifies that the system has a high potential to extract reliable information about highway traffic conditions from highway CCTVs.

Risk analysis model for regional railroad investment

Purpose The purpose of this study is to model risks in financial analysis. These risks associated with uncertainties in the projects should be properly addressed to ensure proper decision regarding the projects. Performance indicators should be developed and assessing risks has high priority. All these activities comprise appraisal, and based on these, a proper course of action should be recommended. Design/methodology/approach To analyze the attractiveness of a project for foreign regional railroad investment or participation, the project should be analyzed in a systematic way. First, the project’s goals and objectives should be evaluated for compatibility. Also, criteria of acceptability for stakeholders should be checked against output from the project. Usually, a project can have many alternatives, and impacts of each alternative should be analyzed in terms of quantitative and qualitative forecasts of impacts. Benefits and costs need to be counted in proper units of measurement per goals and objectives. Findings This paper shows that risk modeling can reflect uncertainty in decision-making and provide robustness of modeling process and improved communication. Also, challenges are presented in using risk analysis. Originality/value To overcome the shortcomings of traditional mathematical optimization model in identifying best sets of projects for private application, the proposed model finds ways to incorporate risk management components for the optimization procedure. Based on simulation results, a brute force solution procedure using enumeration can be used. Another approach is recommended to use the genetic algorithm process to reduce the number of alternatives to search to reach an optimal solution.

Mathematical Analysis for Roundabout Capacity

This paper investigates roundabout capacity analysis using mathematical modelling and microscopic simulation. The capacity in approach section in roundabout is calculated by estimating the number of vehicles that can enter a roundabout for a given approach given a certain circulating volume. Since roundabouts are working with only yield conditions, capacity is dependent on gap acceptance model. Priority rules are used to simulate the gap acceptance model and define the right-of-way for conflicting movements. In the case of roundabouts, priority rules can be utilized to establish right-of-way at each of the conflict points where the approach traffic merges with the circulating traffic of the roundabout. By altering the minimum acceptable gap and related parameters, it is possible to calibrate a simulation model to be that of a real-life roundabout or that of a theoretical roundabout that meets the operating characteristics defined in current capacity models. The proposed roundabout capacity analysis methodology is expected to assist modelling operational conditions for roundabouts. Results are presented that provide evidence to validate the proposed approach.

Efficient customer selection process for various DR objectives

For timely and effective dispatch of demand response (DR) events, utilities require an efficient customer selection process that considers multiple factors, such as customer energy consumption patterns, customer compliance, and DR event time intervals. Moreover, customer targeting strategies may be different depending on the priority of each DR program. Thus, this paper investigates how to efficiently select customers for certain types of incentive-based DR programs (e.g., direct load control and curtailable load control) with various objectives based on hourly energy consumption data. To cope with computation issues arising from big data, we propose a filtering process that reduces the number of eligible customers based on proper criteria and use a novel approximate algorithm to solve the proposed customer selection problems in the format of a stochastic knapsack problem. This paper also suggests how to consider a customer compliance factor in the customer selection process.

Requirements to Enhance the Decision-Making Process for Tunnel Construction by Virtual Design and Construction (VDC)

This paper discusses requirements to enhance the current decision-making process for tunnel construction, which involves significant uncertainties in ground conditions. In current practice, project managers determine resource-loaded construction schedules based on one specific set of ground conditions. In addition, they do not update ground conditions for unexcavated sections with information from excavated sections. This decision-making process often causes cost overruns, schedule delays, and disputes. To mitigate these problems, managers must make timely and robust decisions about construction schedules, during both the preconstruction and construction phases, in a transparent and integrated manner. To this end, we applied a 4D model-based decision-support system, the Development Strategy Simulator (DSS), to a U.S. tunnel project. Our analysis showed that the DSS was able to simultaneously analyze and represent the construction schedule and the resulting resources. However, we argue that it is still necessary to develop a progress-adaptive stochastic earth model, as well as a formal process for the automatic formulation and evaluation of multiple alternative schedules.