• Journal of Auto-vehicle Safety Association
• /
• v.15 no.2
• /
• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.14 no.3
• /
• pp.9-23
• /
• 2015

A lane change maneuver which has a high driver cognitive workload and skills sometimes leads to severe traffic accidents. In this study, the Advanced Lane Change Assist System (ALCAS) was developed to assist with the automatic lane changes in merging sections which is mainly based on an automatic control algorithm for detecting an available gap, determining the Optimal Lane Change Start Point (OLCSP) in various traffic conditions, and positioning the merging vehicle at the OLCSP safely by longitudinal automatic controlling. The analysis of lane change behavior and modeling of fundamental lane change feature were performed for determining the default parameters and the boundary conditions of the algorithm. The algorithm was composed of six steps with closed-loop. In order to confirm the algorithm performance, numerical scenario tests were performed in various surrounding vehicles conditions. Moreover, feasibility of the developed system was verified in microscopic traffic simulation(VISSIM 5.3 version). The results showed that merging vehicles using the system had a tendency to find the OLCSP readily and precisely, so improved merging performance was observed when the system was applied. The system is also effective even during increases in vehicle volume of the mainline.

• Journal of Korean Society of Transportation
• /
• v.35 no.4
• /
• pp.332-347
• /
• 2017

Analysis of the interaction between the automated vehicles and manual vehicles is very important in analyzing the performance of automated cooperative driving environments. In particular, the automated vehicle platooning can affect the driving behavior of adjacent manual vehicles. The purpose of this study is to analyze the lane change behavior of the manual vehicles in automated vehicle platonning environment and to conduct the experiment and questionnaire surveys in three stages. In the first stage, a video questionnaire survey was conducted, and responsive behaviors of manual vehicles were investigated. In second stage, the driving simulator experiments were conducted to investigate the lane change behaviors of in automated vehicle platonning environments. To analyze the lane change behavior of the manual vehicles, lane change durations and acceleration noise, which are indicators of traffic flow stability, were used. The driving behavior of manual vehicles were compared across different market penetration rates (MPR) of automated vehicles and human factors. Lastly, NASA-TLX (NASA Task Load Index) was used to evaluate the workload of the manual vehicle drivers. As a result of the analysis, it was identified that manual vehicle drivers had psychological burdens while driving in automated vehicle platonning environments. Lane change durations were longer when the MPR of the automated vehicles increased, and acceleration noise were increased in the case of 30-40 years old or female drivers. The results from this study can be used as a fundamental for more realistic traffic simulations reflecting the interaction between the automated vehicles and manual vehicles. It is also expected to effectively support the establishment of valuable transportation management strategy in automated vehicle environments.

• Journal of Korean Society of Transportation
• /
• v.27 no.4
• /
• pp.115-126
• /
• 2009

The lane-change behavior usually consists of discretionary lane-change and mandatory lane-change types. For the first type, drivers change lanes selectively to maintain their own driving condition and the second type is the case that the drivers must change the current lane, which can occur in recurrent congestion sections like merging and weaving sections. The mandatory lane-change behavior have a great effect on the operation condition of freeway. In this paper, we first generate data such as traffic volumes, speeds, densities, and the number of lane-change within the merging and weaving sections using the data of individual vehicle collected from time-lapse aerial photography. And then, the data is divided into the stable and congested flow by analyzing the speed variation pattern of individual vehicles. In addition, the number of lane-changing from ramp to mainline within every 30-meter interval is investigated before and after traffic congestion at study sites and the distribution of lane-changing at each 30-meter point is analyzed to identify the variation of lane-changing ratio depending on the stable and congested flows. To recognize the effect of mainline flow influenced by ramp flow, this study also analyzes the characteristics of the lane-changing distributions within the lanes of mainline. The purpose of this paper is to present the basic theory to be used in developing a lane-changing model at the merging and weaving sections on freeways.

• Journal of Auto-vehicle Safety Association
• /
• v.14 no.3
• /
• pp.65-70
• /
• 2022

Lane change in urban environments is a challenge for both human-driving and automated driving due to their complexity and non-linearity. With the recent development of deep-learning, the use of the RNN network, which uses time series data, has become the mainstream in this field. Many researches using RNN show high accuracy in highway environments, but still do not for urban environments where the surrounding situation is complex and rapidly changing. Therefore, this paper proposes a lane change possibility decision network by adopting Attention layer, which is an SOTA in the field of seq2seq. By weighting each time step within a given time horizon, the context of the road situation is more human-like. A total 7D vectors of x, y distances and longitudinal relative speed of side front and rear vehicles, and longitudinal speed of ego vehicle were used as input. A total 5,614 expert data of 4,098 yield cases and 1,516 non-yield cases were used for training, and the performance of this network was tested through 1,817 data. Our network achieves 99.641% of test accuracy, which is about 4% higher than a network using only LSTM in an urban environment. Furthermore, it shows robust behavior to false-positive or true-negative objects.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.19 no.3
• /
• 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.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.16 no.6
• /
• pp.79-89
• /
• 2017

Current intersection with collectors allow entry and exit in the relevant sections just as defined by the pertinent design criteria without considering driving behavior of the vehicles coming in and out of the intersection. This study analyzed the roads in the weaving sections to review driving behavior. As a result, vehicles entering a main line are found to try to change a driving lane at a section 50~55m away from a nose part, while those entering a ramp from a main line try to change it at 35~40m from a nose part. Accordingly vehicles exiting to a connecting road from a main line were found to take prior action to change a lane earlier than those entering a main line. Conflict took place intensively at 35~40m section from the nose part entering a main line. Consequently, such conflict at an weaving section may be controlled by adjusting the length of driving lane making use of a double line (solid and dotted line) that can control changing a lane. Outcome of this study may be used as a basic data for operating and maintaining an weaving section of a intersection of a road and improving traffic safety.

• Journal of Korean Society of Transportation
• /
• v.22 no.6
• /
• pp.145-157
• /
• 2004

Microscopic freeway simulation models project the uncertain values of performance measures for subject traffic conditions by explaining drivers' driving behavior with lane changing and car-following models. However, the existing lane changing models are limited to gap acceptance oriented passive behavior of drivers and not able to capture more-or-less aggressive driving behavior(e.g. cut-in lane changing) ordinarily obseved in field. This paper suggests the definition of cut-inlane changing and presents its characteristics based on the findings from two different freeway on- and off-ramp sections. In addition, this paper proposes a new lane changing model capable of handling both passive and active drivers' driving behavior for better performance of simulations. The proposed lane changing model was tested with Hanyang Simulatin (HYTSIM), a microscopic freeway simulation program developed for this study. The HYTSIM simulation results reflecting the performance of the proposed lane changing model were compared against the field data. The test results showed that the distribution of gaps collected when vehicles change lanes were statistically identical to the field data at 95% confidence level.

• Transactions of the Korean Society of Automotive Engineers
• /
• v.5 no.3
• /
• pp.209-219
• /
• 1997

A fuzzy driver model based on a preview-predictor and yaw rate is developed. The model is used to investigate the handling performance of two wheel steering system(2WS) and four wheel steering system(4WS) vehicles. The two degree-of- freedom model which has yaw and lateral motion predicts the path of the vehicles. Based upon the yaw rate and lateral deviations, the fuzzy engine describes the human driver's complicated control behavior which is adjusted for the driving environment. Both typical single lane change maneuver and double lane change maneuver are adopted to demonstrate the feasibility of fuzzy driver model.

• Journal of Power System Engineering
• /
• v.17 no.4
• /
• pp.23-30
• /
• 2013

In this paper, the payload condition is considered and computer simulation is carried out to analyze the dynamic behavior of the middle-sized truck under the condition with different weight and location. The computer model for the truck is established and ADAMS/Car is employed to simulate the truck vehicle. A single lane change and bump-pass simulation are performed to evaluate the performance according to the weight and the position of it. Effects of the location and weight of commercial vehicle are analyzed. According to the simulation results, the front deck is preferred as the load location.