Hyunjin Park

Development of a Vehicle Electric Power Simulator for Optimizing the Electric Charging System

The vehicle electric power system, which consists of two major components: a generator and a battery, which have to provide numerous electrical and electronic systems with enough electrical energy. A detailed understanding of the characteristics of the electric power system. electrical load demands, and the driving environment such as road, season. and vehicle weight is required when the capacities of the generator and the battery are to be determined for a vehicle. An easy-to-use and inexpensive simulation program may be needed to avoid the over/under design problem of the electric power system. A vehicle electric power simulator is developed in this study. The simulator can be utilized to determine the optimal capacities of generators and batteries. To improve the expandability and easy usage of the simulation program, the program is organized in modular structures, and is run on a PC. Empirical electrical models of various generators and batteries, and the structure of the simulation program are presented. For executing the vehicle electric power simulator, data of engine speed profile and electric loads of a vehicle are required, and these data are obtained from real driving conditions. In order to improve the accuracy of the simulator, numerous driving data of a vehicle are logged and analyzed.

Development of a lane change risk index using vehicle trajectory data

Surrogate safety measures (SSMs) have been widely used to evaluate crash potential, which is fundamental for the development of effective safety countermeasures. Unlike existing SSMs, which are mainly focused on the evaluation of longitudinal vehicle maneuvering leading to rear-end crashes, this study proposes a new method for estimating crash risk while a subject vehicle changes lanes, referred to as the lane change risk index (LCRI). A novel feature of the proposed methodology is its incorporation of the amount of exposure time to potential crash and the expected crash severity level by applying a fault tree analysis (FTA) to the evaluation framework. Vehicle interactions between a subject vehicle and adjacent vehicles in the starting lane and the target lane are evaluated in terms of crash potential during lane change. Vehicle trajectory data obtained from a traffic stream, photographed using a drone flown over a freeway segment, is used to investigate the applicability of the proposed methodology. This study compares the characteristics of compulsory and discretionary lane changes observed in a work zone section and a general section of a freeway using the LCRI. It is expected that the outcome of this study will be valuable in evaluating the effectiveness of various traffic operations and control strategies in terms of lane change safety.

Real-Time Estimation of Lane Change Risks Based on the Analysis of Individual Vehicle Interactions

Lane-changing vehicles continuously interact with adjacent vehicles by adjusting longitudinal and lateral maneuvering. Safe lane changing can be regarded as an outcome of safe vehicle interactions during lane changes. An effective safety assessment of a vehicle changing lanes is essential to developing various countermeasures to prevent crashes. This study developed a methodology for estimating the risks of changing lanes in real time using vehicle trajectory data. Both a real-time risk exposure level (RREL) and a real-time risk severity level (RRSL) were devised to quantify risk levels associated with lane changing based on an analysis of vehicle interactions. Then, fault tree analysis was adopted to integrate the two indicators, RREL and RRSL. This study demonstrated the feasibility of the proposed methodology by conducting VISSIM simulation experiments. The outcome of this study can be used to not only evaluate the effectiveness of traffic management strategies in terms of lane change safety but also support the development of various advanced driving assistance systems.