A framework for travel time variability analysis using urban traffic incident data

This study aims to develop a framework to estimate travel time variability caused by traffic incidents using integrated traffic, road geometry, incident, and weather data. We develop a series of robust regression models based on the data from a stretch in California's highway system during a two-year period. The models estimate highway clearance time and percent changes in speed for both downstream and upstream sections of the incident bottleneck. The results indicate that highway shoulder and lane width factor adversely impact downstream highway clearance time. Next, travel time variability is estimated based on the proposed speed change models. The results of the split-sample validation show the effectiveness of the proposed models in estimating the travel time variability. Application of the model is examined using a micro-simulation, which demonstrates that equipping travelers with the estimated travel time variability in case of an incident can improve the total travel time by almost 60%. The contribution of this research is to bring several datasets together, which can be advantageous to Traffic Incident Management.     

Urban travel time reliability at different traffic conditions

The decision making of travelers for route choice and departure time choice depends on the expected travel time and its reliability. A common understanding of reliability is that it is related to several statistical properties of the travel time distribution, especially to the standard deviation of the travel time and also to the skewness. For an important corridor in Changsha (P.R. China) the travel time reliability has been evaluated and a linear model is proposed for the relationship between travel time, standard deviation, skewness, and some other traffic characteristics. Statistical analysis is done for both simulation data from a delay distribution model and for real life data from automated number plate recognition (ANPR) cameras. ANPR data give unbiased travel time data, which is more representative than probe vehicles. The relationship between the mean travel time and its standard deviation is verified with an analytical model for travel time distributions as well as with the ANPR travel times. Average travel time and the standard deviation are linearly correlated for single links as well as corridors. Other influence factors are related to skewness and travel time standard deviations, such as vehicle density and degree of saturation. Skewness appears to be less well to explain from traffic characteristics than the standard deviation is.     

A stochastic analysis of highway capacity: Empirical evidence and implications

This paper presents a stochastic characterization of highway capacity and explores its implications on ramp metering control at the corridor level. The stochastic variation of highway capacity is captured through a Space–Time Autoregressive Integrated Moving Average (STARIMA) model. It is identified following a Seasonal STARIMA model (0, 0, 2₃) × (0, 1, 0)₂, which indicates that the capacities of adjacent locations are spatially–temporally correlated. Hourly capacity patterns further verify the stochastic nature of highway capacity. The goal of this paper is to study (1) how to take advantage of the extra information, such as capacity variation, and (2) what benefits can be gained from stochastic capacity modeling. The implication of stochastic capacity is investigated through a ramp metering case study. A mean–standard deviation formulation of capacity is proposed to achieve the trade-off between traffic operation efficiency and robustness. Following that, a modified stochastic capacity-constraint ZONE ramp metering scheme embedded cell transmission model algorithm is introduced. The numerical experiment suggests that considering capacity variation information would alleviate the spillback effect and improve throughput. Monte Carlo simulation further supports this argument. This study helps verify and characterize the stochastic nature of capacity, validates the benefits of using capacity variation information, and thus enhances the necessity of implementing stochastic capacity in traffic operation.     

Signal coordination model for local arterial with heavy bus flows

Conventional Transit Signal Priority (TSP) controls often reach the limitation for arterials accommodating heavy bus flows since the priority function can significantly increase delay at minor streets. Under such conditions, a proper signal progression plan that accounts for the benefits of buses may offer the potential to improve the reliability of bus operations and increase the bus ridership. This study proposes a bus-based progression model to reduce the delay of buses on local arterials. Given the cycle length and green splits at each intersection, the bus-based progression model, grounded on the same notion as conventional signal progression methods, considers the operational characteristics of transit vehicles, such as the impact of bus dwell time and the capacity constraints at bus stops. Also, to deal with the stochastic nature of dwell time, this study introduces additional constraints to maximize the percentage of buses which can stay within the green band after leaving bus stops. Taking an arterial with five intersections and three two-way bus stops as an example, this study applies VISSIM as an unbiased tool for model evaluation. The simulation results demonstrate that the proposed model can significantly reduce bus passenger delays and the average person delays for the entire arterial, compared with the conventional progression models.     

铁路高墩大跨度连续刚构桥抗震设计分析

为保证在罕遇地震下桥梁结构满足规范要求,以主跨120m的高墩大跨连续刚构桥——云南万拉木特大桥为例,运用MIDAS Civil建立连续刚构桥空间有限元模型,对其进行动力特性及罕遇地震作用下的非线性时程分析,并优化延性抗震设计。分析结果表明:桥梁振型以梁墩的横向振动为主,第1阶横向侧弯的自振周期为1.697s,全桥最大振幅出现在桥墩墩顶位置。在罕遇地震(50年超越概率为2%)作用下,中跨墩顶、底受力较大,均已进入屈服,但其弯矩均小于钢筋极限弯矩,桥梁满足"大震不倒"抗震性能目标。对塑性铰区进行优化,将墩底以上3m空心与实体分界位置处截面外层部分主筋弯折,形成最不利塑性铰区域;加强墩顶、底塑性铰区域横向约束钢筋布置,提高墩柱延性。     

浅埋大跨小净距桃花峪黄土隧道系统锚杆作用效果研究

为了更好地研究系统锚杆在浅埋大跨小净距黄土隧道中的支护效果,以武西高速公路桃花峪隧道施工为依托,进行有无锚杆现场对比试验,结果表明:从初期支护左右侧拱顶沉降的对比来看,有锚杆段沉降略小于无锚杆段,水平收敛相差不大,锚杆对改善隧道围岩和初期支护受力作用相对较小,有锚杆试验段围岩-初期支护接触压力量值相对较小,相比于无锚杆段的土体压力略微均匀。综上所述,建议取消锚杆,对于薄弱环节可保留先行洞边墙小净距侧的锚杆施作。     

一种基于县域城乡客运公交化改造的公交时刻表编制方法

为进一步协调县域城乡客运公交化改造与公交高效化运营之间的关系,合理确定城乡客运公交化改造后的公交时刻表至关重要。以县域城乡客运公交化改造为研究对象,提出了一种适合城乡客运公交化改造的公交时刻表编制方法。通过人工调查法获取客流信息,建立客流处理模型,获得最大断面客流量等信息。在此基础上,运用客流需求法建立数学模型,求得发车时间间隔并优化。最后,通过比较验证获得最终的公交时刻表。以池河至石泉客运班线公交化改造为例,改造后的公交时刻表极大地方便了沿线居民的出行,从而证明该时刻表具有较好的可行性。     

基于有效绿灯时间利用率的自适应控制策略研究

为了优化单点交叉口信号控制方案,使其适应各个进口道方向交通流动态变化,提高交叉口通行效率,根据交叉口进口道排队车辆数建立有效绿灯利用率模型,提出了一种交叉口自适应控制策略.有效绿灯时间利用率模型以交叉口通行能力最大为控制参数,实时优化确定出最佳相位放行方案以及最优相位切换方案,根据进口道排队车辆最大流向的排队车辆数和车辆到达预测确定相位放行绿灯时间.利用VISSIM交通仿真软件对该自适应控制策略仿真运行,与定时控制以及感应控制对比,评价分析不同车辆到达情况下交叉口通行情况.结果表明:该自适应控制策略能有效降低车均延误,提高交叉口服务水平.     

基于 M/G/1模型的停车场出口排队延误

通过对大型停车场高峰时段出口车辆行驶特性的调查研究,选取了车辆排队的出口车头时距以及出口服务时间两个指标。基于两个指标实测特性和 M/G/1排队模型的分析,计算了停车场出口理论平均排队时间。通过实测车辆平均排队时间,对理论模型计算的平均排队时间进行了修正。实例分析表明：排队时间修正模型能够准确地估计排队时间。提出了基于驾驶员容忍度的排队延误分级标准。     

快速公交发车间隔优化研究

合理的发车间隔对于快速公交车辆发挥其高效、经济和环保的优势具有重要的意义.首先以乘客出行成本和快速公交运营成本最小化为目标,考虑发车时间约束、车辆台数约束,建立了快速公交发车间隔优化模型.然后采用二进制编码,运用单点交叉和基本位变异的遗传算法求解该优化模型.最后以兰州市首条快速公交线路为例进行了实证研究,得到了不同时段下快速公交的发车间隔.实例研究结果表明,该发车间隔优化模型及遗传算法可行,对实现快速公交科学调度具有一定的参考意义.