ABSTRACT

The present research work provides a methodology of calibration of the vehicle-following behavior in VISSIM using vehicle trajectory data obtained under non-lane-based mixed traffic conditions. In this context, two access-controlled mid-block sections, one on the multi-lane urban road with six-lane-divided carriageway and the second one with eight-lane-divided carriageway are identified for extracting high-quality vehicle trajectory data. Later, using trajectory data, lane-wise time-space plots were developed for the vehicles’ movement simultaneously in the same lane as well as from adjacent lanes for studying non-lane-based movement.The investigation is carried out by developing a relationship (hysteresis plots) between relative distance versus relative velocity among the leader–follower vehicle for the vehicles in the same as well as in adjacent lane that is nearby position. Hysteresis phenomenon for vehicles under the following behavior is examined.Data about identified potential vehicular pairs are used for calibration of well-known psychophysical car-following models.

摘要

目前的研究工作提供了一种使用在非基于车道的混合交通条件下获得的车辆轨迹数据来校准 VISSIM 中车辆跟随行为的方法。在此背景下，确定了两个出入控制的中段路段，一个在六车道分行车道的多车道城市道路上，第二个在八车道分行车道上，用于提取高质量的车辆轨迹数据。后来，使用轨迹数据，为车辆在同一车道和相邻车道上的同时运动开发了车道时空图，以研究非基于车道的运动。该调查是通过开发同一车辆以及邻近位置的相邻车道车辆的领导者 - 跟随者车辆之间的相对距离与相对速度之间的关系（滞后图）来进行的。检查车辆在以下行为下的滞后现象。有关已识别潜在车辆对的数据用于校准众所周知的心理物理跟车模型。