• 자동차안전학회지
• /
• 제15권2호
• /
• pp.21-27
• /
• 2023

This paper presents a simulation tool for developing and evaluating automated driving systems' lane change algorithm in urban congested traffic. The behavior of surrounding vehicles was modeled based on driver driving data measured in urban congested traffic. Surrounding vehicles are divided into aggressive vehicles and non-aggressive vehicles. The degree of aggressiveness is determined according to the lateral position to initiate interaction with the vehicle in the next lane. In addition, the desired velocity and desired time gap of each vehicle are all randomly assigned. The simulation was conducted by reflecting the cognitive limitations and control performance of the autonomous vehicle. It was possible to confirm the change in the lane change performance according to the variation of the lane change decision algorithm.

• 한국자동차공학회논문집
• /
• 제19권3호
• /
• pp.16-22
• /
• 2011

This paper presents the potential of in-vehicle data recorder system for monitoring aggressive driving patterns and providing feedback to drivers on their on road behaviour. This system can detect 10 risky types of drivers' driving patterns such as aggressive lane change, sudden brakes and turns with acceleration etc. Vehicle dynamics simulation and vehicle road test have been performed in order to develop driving pattern recognition algorithms. Recorder systems are installed to 50 buses in a single company. Drivers' driving behaviour are monitored for 1 month. The drivers' risky driving data collected by the system are analyzed. Aggressive lane change in 50km/h below is a cause in overwhelming majority of risky driving pattern.

• 대한교통학회지
• /
• 제22권6호
• /
• pp.145-157
• /
• 2004

끼어들기 행태는 차로변경 대상 측면차로에 충분한 차간간격이 존재하지 않는 상황에서도 운전자가 강제적으로 차간간격을 만들어내는 적극적인 운행행태이다. 이러한 끼어들기는 주변 주행차량들의 움직임에 종속적으로 대응하지 않는 능동적인 운행행태로 간격수락이론이 주요 기반을 이루는 기존 차로변경보형으로는 설명되지 않는다. 보다 현실적인 교통류 흐름의 모사를 지원하기 위하여 끼어들기 행태를 설명하는 운전자 운행행태 모형 개발이 수반될 필요가 있다. 본 연구에서는 합류부와 분류부를 대상으로 끼어들기 특성 분석 및 분포 추출을 하였으며, 끼어들기 판단지표를 도출하여 모형을 개발하였다. 합류부와 분류부를 대상으로 차로변경행태 분석 결과 차간시간의 경우 차로변경차량과 차로변경 종료차로 선두차량과의 차간시간은 E기뭏(0.343, 3) 분포, 후미차량과의 차간시간은 Weibull(1.12, 1.81) 분포, 상대속도의 경우 차로변경차량과 차로변경 종료차로 선두차량과의 상대속도는 Lognormal (11.8, 4.6) 분포, 후미차량과의 상대속도는 Lognormal (6.01, 4.27) 분포, 차로변경차량의 가속 분포는 Lognormal (1.24, 2.5) 분포, 감속 분포는 Normal(-1.51, 1.27) 분포를 따르는 것으로 분석되었다. 현장관측 자료를 토대로 끼어들기 판단지표 도출 결과 감속하는 차로변경 종료차로 후미차량의 속도 분포가 평균값 6.78m/sec, 분산 9.84m/sec인 Gamma(2.74, 1.74)분포를 따르며, 현장관측 자료의 분포와 모형결과 분포의 동일성 여부를 판단하기 위해 신뢰수준 95%로 $x^2$-test 검정을 실시 한 결과 "모형결과 분포는 현장관측 자료의 분포를 따른다."고 검증되었다.

• 한국자동차공학회논문집
• /
• 제12권5호
• /
• pp.125-135
• /
• 2004

The validity of simulation has been well-established for decades in areas such as computer and communication system. Recently, the technique has become entrenched in specific areas such as transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and their driver's characteristics, even though it is known that they are important factors for any traffic flow analysis, have never been considered sufficiently. In this paper, the traffic simulation using a multi-agent approach with considering vehicle dynamics is proposed. The multi-agent system is constructed with the traffic environment and the agents of vehicle and driver. The traffic environment consists of multi-lane roads, nodes, virtual lanes, and signals. To ensure the fast calculation, the agents are performed on the based of the rules to regulate their behaviors. The communication frameworks are proposed for the agents to share the information of vehicles' velocity and position. The model of a driver agent which controls a vehicle agent is described in the companion paper. The vehicle model contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation has proceeded for an interrupted and uninterrupted flow model. The result has shown that the driver agent performs human-like behavior ranging from slow and careful to fast and aggressive driving behavior, and that the change of the traffic state is closely related with the distance and the signal delay between intersections. The system developed shows the effectiveness and the practical usefulness of the traffic simulation.

• International Journal of Automotive Technology
• /
• 제7권2호
• /
• pp.145-154
• /
• 2006

In the companion paper, the composition and structure of the MATDYMO (Multi-Agent for Traffic Simulation with Vehicle Dynamic Model) were proposed. MATDYMO consists of the road management system, the vehicle motion control system, the driver management system, and the integration control system. Among these systems, the road management system and the integration control system were discussed In the companion paper. In this paper, the vehicle motion control system and the driver management system are discussed. The driver management system constructs the driver agent capable of having different driving styles ranging from slow and careful driving to fast and aggressive driving through the yielding index and passing index. According to these indices, the agents pass or yield their lane for other vehicles; the driver management system constructs the vehicle agents capable of representing the physical vehicle itself. A vehicle agent shows its behavior according to its dynamic characteristics. The vehicle agent contains the nonlinear subcomponents of engine, torque converter, automatic transmission, and wheels. The simulation is conducted for an interrupted flow model and its results are verified by comparison with the results from a commercial software, TRANSYT-7F. The interrupted flow model simulation is implemented for three cases. The first case analyzes the agents' behaviors in the interrupted flow model and it confirms that the agent's behavior could characterize the diversity of human behavior and vehicle well through every rule and communication frameworks. The second case analyzes the traffic signals changed at different intervals and as the acceleration rate changed. The third case analyzes the effects of the traffic signals and traffic volume. The results of these analyses showed that the change of the traffic state was closely related with the vehicle acceleration rate, traffic volume, and the traffic signal interval between intersections. These simulations confirmed that MATDYMO can represent the real traffic condition of the interrupted flow model. At the current stage of development, MATDYMO shows great promise and has significant implications on future traffic state forecasting research.

• International Journal of Automotive Technology
• /
• 제7권1호
• /
• pp.25-34
• /
• 2006

For decades, simulation technique has been well validated in areas such as computer and communication systems. Recently, the technique has been much used in the area of transportation and traffic forecasting. Several methods have been proposed for investigating complex traffic flows. However, the dynamics of vehicles and diversities of driver characteristics have never been considered sufficiently in these methods, although they are considered important factors in traffic flow analysis. In this paper, we propose a traffic simulation tool called Multi-Agent for Traffic Simulation with Vehicle Dynamics Model (MATDYMO). Road transport consultants, traffic engineers and urban traffic control center managers are expected to use MATDYMO to efficiently simulate traffic flow. MATDYMO has four sub systems: the road management system, the vehicle motion control system, the driver management system, and the integration control system. The road management system simulates traffic flow for various traffic environments (e.g., multi-lane roads, nodes, virtual lanes, and signals); the vehicle motion control system constructs the vehicle agent by using various vehicle dynamic models; the driver management system constructs the driver agent capable of having different driving styles; and lastly, the integrated control system regulates the MATDYMO as a whole and observes the agents running in the system. The vehicle motion control system and driver management system are described in the companion paper. An interrupted and uninterrupted flow model were simulated, and the simulation results were verified by comparing them with the results from a commercial software, TRANSYT-7F. The simulation result of the uninterrupted flow model showed that the driver agent displayed human-like behavior ranging from slow and careful driving to fast and aggressive driving. The simulation of the interrupted flow model was implemented as two cases. The first case analyzed traffic flow as the traffic signals changed at different intervals and as the turning traffic volume changed. Second case analyzed the traffic flow as the traffic signals changed at different intervals and as the road length changed. The simulation results of the interrupted flow model showed that the close relationship between traffic state change and traffic signal interval.