• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.111-120
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• 2007

More accurate vehicle trajectory data are now readily available through Differential Global Positioning Systems (DGPS). A variety of research opportunities emerge with utilization of such high resolution traffic data. A novel approach of this study is to explore drivers' responsive behavior to variable message signs (VMS) by using individual vehicle trajectories extracted from in-vehicle DGPS data. Responsive characteristics of drivers traveling on urban freeways, which can be represented by speeds and acceleration rates, under the provision of real-time traffic information through VMS are statistically investigated. In addition to conducting an ANOVA test, probability density functions of acceleration rates were estimated. The findings of this study can be used to understand the impact of drivers' workload when providing VMS messages on traffic flow patterns. Furthermore, results can be important fundamentals to assist in conducting more realistic traffic simulations.

• International Journal of Automotive Technology
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• v.8 no.3
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• pp.375-382
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• 2007

The multi-driver off-road vehicle drive-line consists of many components, with close connections among them. In order to design and analyze the drive-line efficiently, a modular methodology should be taken. The aim of a modular approach to the modeling of complex systems is to support behavior analysis and simulation in an iterative and thus complex engineering process, by using encapsulated submodels of components and of their interfaces. Multi-driver off-road vehicles are comparatively complicated. The driving-line is an important core part to the vehicle, it has a significant contribution to the performance. Multi-driver off-road vehicles have complex driving-lines, so performance is heavily dependent on the driving-line. A typical off-road vehicle's driving-line system consists of a torque converter, transmission, transfer case and driving-axles, which transfers the power generated by the engine and distributes it effectively to the driving wheels according to the road condition. According to its main function, this paper proposes a modularized approach for design and evaluation of the vehicle's driving-line. It can be used to effectively estimate the performance of the driving-line during the concept design stage. Through an appropriate analysis and assessment method, an optimal design can be reached. This method has been applied to practical vehicle design, it can improve the design efficiency and is convenient to assess and validate the performance of a vehicle, especially of multi-driver off-road vehicles.

• Journal of the Korea Safety Management & Science
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• v.16 no.4
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• pp.91-99
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• 2014

This study highlights the theme of human error of train drivers, conducting empirical analysis on the relationship between organizational culture, safety climates, safety behavior, and accident. The empirical test results based on questionnaires received from 223 train drivers working at A subway firm indicated that relationship conflict and psychological reward as the elements of organizational culture variables showed a significant positive effect on CEO philosophy, communication, and boss's leadership. And only boss's leadership showed a positive influence on safety behavior, which in turn showed a significant negative relationship with accidents.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.2747-2752
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• 2003

This paper has develops a new framework to understand the human’s driving maneuver based on the expression as HDS focusing on the driver’s stopping maneuver. The driving data has been collected by using the three-dimensional driving simulator based on CAVE, which provides three-dimensional visual information. In our modeling, the relationship between the measured information such as distance to the stop line, its first and second derivatives and the braking amount has been expressed by the PWPS model, which is a class of HDS. The key idea to solve the identification problem was to formulate the problem as the MILP with replacing the switching conditions by binary variables. From the obtained results, it is found that the driver appropriately switches the ‘control law’ according to the following scenario: At the beginning of the stopping behavior (just after finding the stopping point), the driver decelerate the vehicle based on the acceleration information, and then switch to the control law based on the distance to the stop line.

• International Journal of Automotive Technology
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• v.7 no.5
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• pp.619-624
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• 2006

This paper presents design of a vehicle stop-and-go cruise control strategy based on analyzed results of the manual driving data. Human drivers driving characteristics have been investigated using vehicle driving data obtained from 100 participants on low speed urban traffic ways. The control algorithm has been designed to incorporate the driving characteristics of the human drivers and to achieve natural vehicle behavior of the controlled vehicle that would feel comfortable to the human driver under low speed stop-and-go driving conditions. Vehicle following characteristics of the cruise controlled vehicle have been investigated using a validated vehicle simulator and real driving radar sensor data.

• Transactions of the Korean Society of Automotive Engineers
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• v.20 no.2
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• pp.103-109
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• 2012

Adaptive cruise control Stop&Go system has been developed to reduce the driver's workload on highway or public road. This system is characterized by a moderate control of engine and brake actuator. A control system capable of modeling driver's driving characteristics has been constructed to provide natural vehicle behavior in full speed driving. But, ACC Stop&Go system has some limitations. One of the limitations is a detection limitation on near cut-in situation. This paper presents development of the near cut-in test procedure, finding of the limitation value on near cut-in scenario and performance comparisons on ACC Stop&Go system.

• International Journal of Automotive Technology
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• v.7 no.1
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• pp.25-34
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• 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.

• Journal of Korean Society of Transportation
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• v.31 no.6
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• pp.34-42
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• 2013

The reasons of traffic accidents can be classified into the vehicle, road environment and human factors. In development of vehicle and road technologies, the human factor is the most important. The emotion research recently carried out showed that emotions play an important role in human judgment and decision making. They are also expected to partly determine driving behavior. The purpose of this study was to investigate the effects of drivers' emotions on their driving behavior. The results of this study showed that positive emotions do not affect driving behavior. As for negative emotions, however, safe driving(SD) and comfort driving(CD) factors have a negative correlation, and violence driving(VD) and regulation violation(RO) factors have a positive correlation. This study is significant as a basic study for establishing and determining a policy for reducing traffic accidents and for educating drivers.

• Journal of Korean Society of Transportation
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• v.35 no.6
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• pp.545-556
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• 2017

Various assessment indexes have been developed and utilized to evaluate the driver workload. However, existing workload assessment indexes do not fully reflect driving habits and driving patterns of individual drivers. In addition, there exists significant differences in the amount of workload experienced by a driver and the ability to overcome the driver's workload. To overcome these limitations associated with existing indexes, this study has developed a novel workload assessment index to reflect an individual driver's driving pattern. An average of the absolute values of the steering velocity for each driver are set as a threshold value in order to reflect the driving patterns of individual drivers. Further, the sum of the areas of the steering velocities exceeding the threshold value, which is defined as erratic steering area (ESA) in this study, was quantified. The developed ESA index is applied in evaluating the driver workload of manually driven vehicles in automated vehicle platooning environments. Driving simulation experiments are conducted to collect drivers' responsive behavior data which are used for exploring the relationship between the NASA-TLX score and the ESA by the correlation analysis. As a result, ESA is found to have the greatest correlation with the NASA-TLX score among the various driver workload evaluation indexes in the lane change scenario, confirming the usefulness of ESA.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.32 no.4D
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• pp.313-322
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• 2012

This study analyzes taxi driver's risk-taking propensity with respect to risk-taking behaviour and traffic locus of control. In order to explore the traffic risk-taking, we present a predictive model by structural analysis of driver's risk-taking propensity. By applying this model to survey data from taxi drivers, we can observe that driver's risk-taking propensity has a significant impact on the traffic violation intention, and the higher perception of law and the lower lack of law-abiding drivers have, the more they tend to violate. Second, we test using multivariate analysis if the level of risk-taking propensity differs by the locus of control( external or internal). Drivers of external control shows higher risk-taking level compared to those of internal control so that the risk-taking propensity shows difference according to the locus of control for the responsibility of traffic accidents. The structural equation model of our study yielded ${\chi}^2$ = 279.7, ${\chi}^2$/df = 1.55, RMSEA = 0.44, GFI = 0.911, TLI = 0.916, CFI = 0.929.