"公交集簇"的机理解析及其管理控制策略研究

In addition to being more susceptible to external disturbances, as the headways between buses change from the designed value these disturbances are magnified over time until buses can travel in pairs instead of evenly spaced. This effect is referred to as bunching. The actual level of service users experience depends on the reliability of the system to operate as designed. Each component carries with it some level of reliability, and when taken as a whole they determine how well the system behaves. As we all know, bus bunching is the most significant manifestation of the low reliability. China's bus system has overall large flow and high departure frequency, which makes the bus bunching phenomenon frequently. Bus system abroad has smaller flow and lower departure frequency, and oversea research thought the main cause for bunching comes from the fact that the time a bus spends at a bus stop increases with the number of users that need to board and alight the bus. Compared the bus system characteristics in China and abroad, we can makes the point that the cause and the control policy of bus bunching is not always applicable in China. The goal of this research is to reveal the main cause in our country which makes bus bunching frequently, and to seek targeted management control strategy to reduce this phenomenon. This research proposes a new approach to solving the problem that uses the GPS data and in-car-video data in typical city in our country to observe this phenomenon. Correlation analysis, confirmatory factor analysis and structural equation modeling is mainly used in the data processing procedure to verify the cause of the bunching. Simulation tool and analytic method are presented as tools to systematically analyze the coupling of bus departure frequency with the signal cycle. Bus signal priority is used to realize decoupling control. Network optimization model and real-time decision support model are used in decoupling control to determine the assemble of bus signal priority control point on urban trunk road and the effective priority threshold area of signal cycle. The resulting bus controlling system is not only improving the management theory direct at China's bus system current situation, but also supporting the intelligent bus priority management system.

公交集簇，俗称公交串车，是公交运营可靠度低最为常见的表现，也是乘客最为诟病的现象。我国城市公交系统总体流量大、发车频率高的特点使得公交运行中集簇现象频发，且难以采用国外针对乘客量较少、发车间隔长为特征所提出的运行动态控制策略加以解决。本课题的研究目标是揭示造成我国城市公交运行中集簇现象频繁的主要原因，并寻求有针对性的管理控制策略以减轻这一现象。课题将充分利用车载GPS、车内视频所采集的国内典型城市公交实测数据，采用结构方程模型实证信号延误为我国城市中诱发公交集簇的主要因素,进而以实测数据仿真建模手段解析高发车频率和长信号周期之间的耦合效用。考虑采用信号优先作为解耦手段，构建规划管理层的点位寻优模型，以确定城市干道上最佳信号优先点位组合；构建控制管理层的决策模型，以确定交叉口信号周期中有效优先阈值区域。课题成果不仅是针对我国公交运营现状的管理控制理论完善，还是智能公交优先管理系统的技术支撑。

公交优先是各地推广公交出行的重要举措，但实践中公交运行稳定性仍然不足，公交集簇现象时有发生。公交集簇是指连续两辆公交车同时到达或在很短时间间隔内到达车站。这一现象使乘客等待时间的期望值和变异性增大，影响了公交出行可靠度和舒适性，降低了公交的整体服务水平。.本课题基于海量公交运行数据，研究公交集簇现象的发生规律，并解析公交集簇现象的产生原因，重点关注信号配时及发车频率与公交集簇现象之间的相关性；在充分认识公交集簇现象发生机理的基础上，设计缓解公交集簇现象的策略，重点考虑信号优先措施和信息发布策略对公交集簇的缓解作用，并通过数值仿真和工程实践验证策略的效果。.首先对公交运行状态进行了研究，提出通过站点的连续车头时距密度图反映不同类别的运行状态，发现公交运行随着运行长度增加呈现出以下几种状态：规则运行状态、集簇过渡状态、集簇运行状态与组队运行状态。建立了标准路网公交运行数值仿真模型，根据实际数据提取公交运行数值仿真所需的运行特征参数或分布。通过仿真发现，当发车间隔固定时，短路段长度和长信号周期发生了耦合，并且随着线路长度的增加，由于路段长度和信号周期的耦合造成公交集簇现象加剧。当路段长度固定时，长信号周期和短发车间隔发生耦合，当发车间隔与信号周期接近时，由于信号周期的影响产生大量的组队运行状态。.考虑通过公交信号优先和信息发布缓解公交集簇现象。基于分析模型确定公交优先触发概率确定公交优先候选交叉口，并建立DEA模型实施公交优先策略。通过SP-OF-RP调查获得乘客出行选择数据，据此建立非集计模型分析乘客选择行为发现，在信息发布情况下，车内时间、车外时间和拥挤度变化均会对乘客选择行为产生影响。通过仿真分析发现，信号优先和信息发布可以显著提高车头时距稳定性、减少公交集簇现象的发生。.以上策略通过示范工程得以应用，取得了良好效果，高峰和平峰时段均显著缓解了公交集簇的产生，相关研究成果有望得到进一步推广应用。