Lane Change Duration Research Articles

Adaptive fuzzy pattern classification for the online detection of driver lane change intention

In this paper we introduce a new fuzzy system using adaptive fuzzy pattern classification (AFPC) for data-based online evolvement. The fuzzy pattern concept represents an efficient tool for handling uncertainty in multi-dimensional data streams and combines powerful performance, flexibility and meaningful interpretability within one consistent framework. We outline AFPC for non-linear, multi-dimensional transition processes, namely, for the identification of lane change intention in car driving. While lane changes are rare, they are highly safety-relevant transition processes, showing high fuzziness and large individual and inter-individual variations (e.g., in lane change duration). The method employs a combined knowledge- and data-based approach, and the underlying fuzzy potential membership function concept models expert knowledge, closely mirroring human cognition. The design of AFPC comprises (I) an initial training phase (off-line and supervised), which generates a meaningful start-classifier, (II) an online application phase, and finally (III) an evolvement phase (online and unsupervised). Here we consider parametric and structural adaptations and discuss prospects and future challenges. Furthermore, we present specific modeling results for such online data from a real driving study. Next-generation advanced driver assistance systems, as well as autonomously driven vehicles need to evolve, in terms of parameters and structure, based on online real-time data. AFPC presents an efficient tool for application in this area and others (e.g., medicine).

Exploratory Analysis of Lane Changing on Freeways Based on Driver Behavior

Lane changing has received much attention as it is a significant component of microscopic traffic simulation. Many studies have focused on the details of the lane changing maneuver from external observation-based data which do not consider the type of driver performing the maneuver. The research reported in this paper relates the physical details of freeway lane changing to the type of driver performing the maneuver. Forty-six research participants drove an instrumented vehicle and performed a combined total of 726 freeway lane changes. Each research participant was categorized into one of four groups ranging from conservative to aggressive based on cluster analysis. The data were analyzed to identify any trends between the different driver types and their lane changing characteristics, specifically lane changing duration and gap acceptance characteristics. In general, more conservative drivers have greater lane changing durations than aggressive drivers. The gap acceptance comparison among driver types did not yield any conclusive trend. In addition, distributions were fitted to lane changing duration and gap acceptance histograms. The results suggest that driver type impacts freeway lane changing behavior, and therefore should be taken into account when developing or refining simulation-based lane changing models.

드라이빙 시뮬레이터를 이용한 차내 보행자 충돌 경고정보시스템 효과평가 방법론 개발 및 적용

본 연구의 목적은 차내 보행자 경고정보 제공유무에 따른 운전자의 반응특성을 분석하고 충돌속도를 이용해 보행자 상해심각도를 산출하여 시스템의 교통안전효과를 평가하는 방법론을 개발하는 것이다. 운전자 반응특성 분석을 위해 드라이빙 시뮬레이터를 이용하여 피험자별 주행특성 자료를 수집하였으며, 시나리오는 보행자-차량 사고유형에 따라 2개의 시나리오로 구성하였다. 분석결과, Mid-block내의 보행자 무단횡단, 길가장자리구역의 보행자 통행 상황에서 경고정보 제공 전 후로 충돌속도는 위험운전자 그룹이 54%, 25% 감소하였고, 일반운전자 그룹은 26%, 33%감소하였다. 경고정보 제공 전 후의 충돌속도를 이용하여 산출한 보행자 사망확률은 보행자 무단횡단과 길가장자리 구역의 보행자 통행 상황에서 경고정보 제공 전 후로 위험운전자 그룹이 95%, 30% 감소하였고, 일반운전자 그룹은 80%, 89% 감소하는 것으로 나타났다. 본 연구에서 선정한 운전자 반응특성 평가지표 및 충돌속도에 따른 보행자 상해심각도를 산출하여 시스템의 효과를 평가하는 방법론은 향후 보행자-차량 간의 사고예방을 위한 기술 또는 시스템의 교통안전효과를 평가하는데 활용될 수 있을 것으로 기대된다. The objective of this study is to develop a methodology for evaluating the effectiveness of in-vehicle pedestrian warning systems. Driving Simulator-based experiments were conducted to collect data to represent driver's responsive behavior. The braking frequency, lane change duration, and collision speed were used as measure of effectiveness (MOE) to evaluate the effectiveness. Collision speed data obtained from the simulation experiments were further used to predict pedestrian injury severity. Results demonstrated the effectiveness of warning information systems by reducing the pedestrian injury severity. It is expected that the proposed evaluation methodology and outcomes will be useful in developing various vehicular technologies and relevant policies to enhance pedestrian safety.

Observations and Analysis of Multistep-Approach Lane Changes at Expressway Merge Bottlenecks in Shanghai, China

One major cause of accidents at signalized intersections is vehicles running the red light. To discourage red light running, many authorities have installed red light cameras. From numerous field observations at two expressway merge bottlenecks, this paper identifies and studies a peculiar type of lane change, referred to as the multistep-approach lane change (MALC). The characteristics and detailed maneuvers of the MALC are first described and compared with three traditional types of lane changes (normal, cooperative, and forced). Next, descriptive parameters, such as the lane-changing duration and velocity and the number of affected vehicles, are investigated and analyzed during the transline ride (TLR) period. The parameters are taken from 132 sets of vehicle trajectory data collected at two merge bottlenecks in Shanghai, China. Significant differences are found between the MALC and traditional lane changes: the MALC takes longer to complete (10 s on average), involves lower lane-changing velocity (15 km/h on average during the TLR period), and affects more vehicles (six vehicles on average). As such, the MALC poses more disruptive influences on the traffic flow and could explain the occurrences of rapid drops in capacity at expressway merge bottlenecks.

EMPIRICAL STUDY OF ACCEPTED GAP AND LANE CHANGE DURATION WITHIN ARTERIAL TRAFFIC UNDER RECURRENT AND NON-RECURRENT CONGESTION

This paper investigated variations in accepted gaps and lane change duration on arterials under recurrent and non-recurrent congestion. Descriptive statistics and best- fit distributions were obtained for the two parameters for both traffic conditions. Hypothesis testing using Mann-Whitney U-Test showed that the means of accepted gaps and lane change durations were statistically different between the two types of traffic’ conditions. The study found that during non-recurrent congestion, drivers on an average accepted smaller gaps but took longer lane change durations. Based on the fact that the data were collected for the same flow-rate (70-90 vehicles/minute) in both traffic conditions and based on the literature, the reason for the above findings could be that drivers get more frustrated during non-recurring congestion so that they accept smaller gaps. Drivers visiting the study location for game day (non-recurrent) exhibit different driver behavioral characteristics when compared to regular commuters (recurrent) which could have also contributed to the statistical differences in the lane changing characteristics of two types of congestion. These findings have direct implications on the lane changing parameters used in microscopic traffic simulation and also help transportation planners and managers to understand driver behavior during recurrent and non-recurrent congestion and better manage the facilities.

Modeling Speed Disturbance Absorption Following Current State-Control Action-Expected State Chains: Integrated Car-Following and Lane-Changing Scenarios

This paper explores driver behavior in a paired car-following mode in response to a speed disturbance from a front vehicle. A current state-control action-expected state (SAS) chain is developed to provide a framework for modeling of the hierarchy of expected actions incurred during the need for speed disturbance absorption. Three car-following scenarios and one lane-changing scenario are identified with defined perceptual informative variables to describe the process of speed disturbance absorption. Those variables include dynamic spacing versus the follower's speed, disturbance-effecting and ending spacing, headway, acceleration-deceleration, speed recovery period, speed advantage, and lane-changing duration. A significant improvement in car-following modeling introduced in the paper is the integration of car-following and lane-changing behaviors in the SAS chain. Moreover, critical values of perceptual informative variables are statistically developed as a function of the follower's speed by using obse...

Modeling Speed Disturbance Absorption following Current State–Control Action–Expected State Chains

This paper explores driver behavior in a paired car-following mode in response to a speed disturbance from a front vehicle. A current state– control action–expected state (SAS) chain is developed to provide a framework for modeling of the hierarchy of expected actions incurred during the need for speed disturbance absorption. Three car-following scenarios and one lane-changing scenario are identified with defined perceptual informative variables to describe the process of speed disturbance absorption. Those variables include dynamic spacing versus the follower's speed, disturbance-effecting and -ending spacing, headway, acceleration– deceleration, speed recovery period, speed advantage, and lane-changing duration. A significant improvement in car-following modeling introduced in the paper is the integration of car-following and lane-changing behaviors in the SAS chain. Moreover, critical values of perceptual informative variables are statistically developed as a function of the follower's speed by using observed vehicle trajectory data. Furthermore, models that determine the probability of a lane change in response to a speed disturbance and models for acceptable lane-changing decision-making conditions at the adjacent lanes are developed on the basis of the analysis of observed vehicle trajectory data. The work presented in this paper provides an analysis of speed disturbance and speed absorption phenomena and car-following and lane-changing behaviors at the microscopic level. This work establishes the foundation for further research on multiple speed disturbance absorption and its impact on traffic stabilities at the macroscopic analysis level.