考虑交叉口特性的疏散交通路线研究

疏散是应急管理中的重要措施,在应急计划中有必要制定合理的疏散路线以确保疏散车辆尽快到达终点。以往有关最佳疏散交通路线的研究没有考虑交叉口延误和通行能力等因素,若疏散路线经过城市内拥挤路段,忽略交叉口的这些特性会导致结果不尽合理。将交叉口分方向延误和通行能力作为节点权重,建立了点权交通网络,通过在点权网络中求解最小费用流来优化事故地点至安全地点的最佳疏散交通路线及相应的疏散流量,设计了一种最小费用路算法求解该点权网络中的最小费用流。最后以一个数值算例说明了方法的应用,并对考虑和忽略交叉口特性2种情况下得出的路线进行了对比。结果表明该方法能很好地兼顾路网特点和疏散路线优化的要求;若执行忽略交叉口特性的疏散路线方案,极易造成交叉口的拥堵,延长车辆的走行时间。     

行人影响下的信号交叉口通行能力研究

为量化行人交通对信号交叉口通行能力的影响,分析了行人-机动车冲突点处的行人行为特征和人车运行规律,并描述了行人成群到达的现象。在此基础上,利用车队分析法建立冲突点车辆通行能力模型,并且利用实测数据标定模型参数,为计算行人影响下的信号交叉口通行能力提供了分析依据。模型计算的冲突车流通行能力很大程度取决于有效绿灯时间内冲突点处人车冲突的平均次数。模型计算通行能力总体上低于HCM 2000方法,结果随行人流量增加而呈现的下降趋势渐趋平缓。模型建立在冲突点运行规律基础之上,具有较广泛的适应性。研究为混合交通条件下信号交叉口配时设计与交通管理提供了理论基础。     

Fuzzy Modeling Approach for Combined Forecasting of Urban Traffic Flow

Abstract:   This article addresses the problem of the accuracy of short-term traffic flow forecasting in the complex case of urban signalized arterial networks. A new, artificial intelligence (AI)-based approach is suggested for improving the accuracy of traffic predictions through suitably combining the forecasts derived from a set of individual predictors. This approach employs a fuzzy rule-based system (FRBS), which is augmented with an appropriate metaheuristic (direct search) technique to automate the tuning of the system parameters within an online adaptive rolling horizon framework. The proposed hybrid FRBS is used to nonlinearly combine traffic flow forecasts resulting from an online adaptive Kalman filter (KF) and an artificial neural network (ANN) model. The empirical results obtained from the model implementation into a real-world urban signalized arterial demonstrate the ability of the proposed approach to considerably overperform the given individual traffic predictors .     

Impact of Trucks on Signalized Intersection Capacity

Abstract: The most common method used for the analysis of signalized intersections in the United States is contained in the Highway Capacity Manual (HCM). In this method, the base saturation flow rate of the signalized intersection is defined in units of passenger cars per hour green per lane (pc/hg/ln). To account for the presence of large trucks in the traffic stream, the HCM includes a Passenger Car Equivalency (PCE) value. In the current edition of the HCM, a PCE value of 2.0 is applied for all large trucks, with no distinction between different sizes of trucks. The HCM also recommends a single value of 2.0 seconds for startup lost time, regardless of queue composition. Many transportation professionals have questioned the validity of the PCE value and startup lost time recommended by the HCM. They are concerned that the impact of trucks at signalized intersections is being underestimated. If this is the case, then capacity is being overestimated and intersections are not being adequately designed. The objective of this study was to identify appropriate truck PCE values and a relationship for startup lost time as a function of truck percentage in the traffic stream. To accomplish this objective, a custom simulation tool was developed based on the modified Pitt car‐following model, calibrated with field data, and applied to a comprehensive experimental design. The PCE values determined from this study are 1.8, 2.2, and 2.8 for small, medium, and large trucks, respectively. A model for estimating startup lost time based on the same small, medium, and large truck classifications was also developed.     

Simulation model based on Monte Carlo method for traffic assignment in local area road network

For a local area road network, the available traffic data of traveling are the flow volumes in the key intersections, not the complete OD matrix. Considering the circumstance characteristic and the data availability of a local area road network, a new model for traffic assignment based on Monte Carlo simulation of intersection turning movement is provided in this paper. For good stability in temporal sequence, turning ratio is adopted as the important parameter of this model. The formulation for local area road network assignment problems is proposed on the assumption of random turning behavior. The traffic assignment model based on the Monte Carlo method has been used in traffic analysis for an actual urban road network. The results comparing surveying traffic flow data and determining flow data by the previous model verify the applicability and validity of the proposed methodology.     

公路隧道滞留人员密度和疏散时间预测研究

为研究公路隧道突发火灾事故下滞留人员的密度与疏散时间,结合火灾应急响应时间与处置要求,引入交通波传播理论,考虑交通流状态、人员组成、车辆组成等因素,提出滞留人员密度计算方法,并以人员密度、大巴车疏散时间等为参数,构建人员疏散时间预测模型,分析不同交通流条件下的疏散时间,通过实例计算与数值仿真,验证了模型的有效性。结果表明：基于交通波理论提出的滞留人员密度计算方法,能准确地计算出隧道突发火灾事故后的人员密度分布,符合真实场景中的非均匀分布特征;采用人员疏散时间预测模型,能快速预测公路隧道人员疏散所需时间,预测结果与仿真结果基本一致。     

Detection of critical road roughness sections by trend analysis and investigation of driver speed interaction

Pavement roughness (IRI—International Roughness Index values) influence the stability of traffic movements both on intercity roads and urban roads. This study is to determine the exact locations of critical pavement roughness values that affect traffic motion stability and comfort in city centre highway arteries. Roughness data with 10 m intervals were collected on a 3140 m divided road containing three consecutive signalized intersections in the city centre arterial. These data were analysed using the distance-dependent Mann-Kendall trend analysis method and checkerboard model. The sections where roughness is important were determined at a 95% confidence interval. The results will show where future pavement improvements should be prioritized for municipalities and road maintenance engineers and will form a basis for the urban road management system.     

Location optimization algorithm for emergency signs in public facilities and its application to a single-floor supermarket

Although emergency signs are believed to play an important role in ensuring public safety in facilities during emergencies, in practice, specific and clear standards for placing emergency signs have not yet been established. This paper developed a heuristic algorithm based on the Lagrangian relaxation algorithm for optimizing emergency sign locations with consideration of light-occlusion effects. A cellular automaton (CA) evacuation model was then introduced, and based on this model, the evacuation efficiency of the optimized locations of emergency signs derived from the algorithm was verified, and was compared with the evacuation efficiencies of the same supermarket without and with existing emergency signs. The results showed that the proposed algorithm greatly enlarged the coverage of emergency signs and improved the evacuation efficiency. It was concluded that the proposed algorithm with consideration of light-occlusion effects is valid for application to the problem of location optimization of emergency signs in single-floor facilities.     

Increasing Signalized Intersection Capacity with Unconventional Use of Special Width Approach Lanes

Heavy traffic volume coupled with insufficient capacity due to limited space cause most of traffic congestion at urban signalized intersections. This article presents an innovative design to increase the capacity of heavily congested intersections by using the special width approach lane (SWAL), which consists of two narrow approach lanes that are dynamically utilized by either two passenger cars or a heavy vehicle (e.g., buses or trucks) depending on the composition of traffic. The impact of the SWAL on the saturation flow rate is quantified and validated, followed by an optimization model for best geometric layout and signal timing design with the presence of the SWAL. The optimization model is formulated as a mixed‐integer‐linear‐program for intersection capacity maximization which can be efficiently solved by the standard branch‐and‐bound technique. Results of extensive numerical analyses and case studies show the effectiveness of SWAL to increase intersection capacity, indicating its promising application at intersections with very limited space that prevents the addition of separate lanes.     

Dynamic Optimal Traffic Assignment and Signal Time Optimization Using Genetic Algorithms

Abstract:   In this article a dynamic system-optimal traffic assignment model is formulated for a congested urban road network with a number of signalized intersections. A simulation-based approach is employed for the case of multiple-origin-multiple-destination traffic flows. The artificial intelligence technique of genetic algorithms (GAs) is used to minimize the overall travel cost in the network with fixed signal timings and optimization of signal timings. The proposed method is applied to the example network and results are discussed. It is concluded that GAs allow the relaxation of many of the assumptions that may be needed to solve the problem analytically by traditional methods.     

A Hybrid Bilevel Model for the Optimal Shelter Assignment in Emergency Evacuations

Abstract: The rise in natural and man‐made disasters in recent years has led to an increased interest in emergency evacuation planning. Athough the vast majority of the existing evacuation planning models assumes system optimal (cooperative) behavior, recent research has shown that during large evacuations people tend to exhibit selfish (noncooperative) behavior. This article presents a hybrid bilevel model that balances both behavioral assumptions (in the upper level, shelter assignment occurs in a system optimal fashion, whereas evacuees are free to choose how to reach their assigned shelters in the lower level), hence providing a model that is more in line with the current state‐of‐the‐knowledge of human behavior during disasters. The proposed model is solved using a simulated annealing algorithm. A hypothetical evacuation scenario in Sioux Falls, South Dakota, illustrates the proposed model. We demonstrate that the resulting evacuation strategies can be significantly different from conventional system optimal evacuation plans.     

Wireless charging utility maximization and intersection control delay minimization framework for electric vehicles

This study presents the Wireless Charging Utility Maximization (WCUM) framework, which aims to maximize the utility of Wireless Charging Units (WCUs) for electric vehicle (EV) charging through the optimal WCU deployment at signalized intersections. Furthermore, the framework aims to minimize the control delay at all signalized intersections of the network. The framework consists of a two‐step optimization formulation, a dynamic traffic assignment model to calculate the user equilibrium, a traffic microsimulator to formulate the objective functions, and a global Mixed Integer Non‐Linear Programming (MINLP) optimization solver. An optimization problem is formulated for each intersection, and another for the entire network. The performance of the WCUM framework is tested using the Sioux Falls network. We perform a comparative study of 12 global MINLP solvers with a case study. Based on solution quality and computation time, we choose the Couenne solver for this framework.     

信号控制交叉口进口道公共汽车停靠影响分析

本文在分析信号控制交叉口进口道公共汽车 (以下简称公交) 停靠时间特性的基础上,对国内典型的进口道公交停靠现象进行了分类与总结,并主要针对公交占用机动车外侧混合车道停靠的情况进行了定量分析,得出了公交停靠损失时间、站台位置及单位小时公交停靠车辆数等参数与交叉口交通延误、通行能力等交通效益指标变化情况的相互关系,从而为合理设置公交线路及站台位置,评价公交影响及运行效益提供了理论基础与分析工具。     

Increasing the Capacity of the Intersection Downstream of the Freeway Off‐Ramp Using Presignals

High volume from urban freeway off‐ramps coupled with extensive traffic weaving and limited capacity at downstream intersections create major bottlenecks in urban road networks. This article presents an integrated design model to eliminate traffic weaving and to maximize the section's overall capacity by using the presignal and sorting area concept. The selection of movements controlled by the presignal, the layout of the section, and the signal timing are optimized in a uniform framework by a mixed‐integer nonlinear program model. The mathematical model was linearized and solved using the standard branch‐and‐bound technique. Extensive numerical analysis and a case study validate the effectiveness of the proposed integrated model in improving capacity with the comparison of conventional design under various geometric configuration and traffic demand pattern scenarios. The proposed model has promising application at locations where the queuing space is long enough and the number of exit lanes is enough to receive the traffic stream from the sorting area.     

Modeling evacuation route choices under influence of variable message signs

This work develops a novel methodology for investigating dynamic evacuation route switching behavior and its influence on evacuation traffic assignment considering evacuees’ intuitionistic fuzzy perception and cognition of multitype multiattribute real‐time variable message sign (VMS) information. The methodology has three distinctive features. First, a link‐based VMS information utility model is developed. Second, two link‐specific dynamic escape speed models (DESMs), characterized by VMS information, evacuee attributes, and hazard‐related information, are proposed. Third, VMS information characteristics and the intuitionistic fuzzy method are integrated into route choice behavior models. The link‐specific DESMs are used to adjust the reactive DYNASTOCH algorithm to simulate emergency traffic evacuation. Results demonstrate that the proposed models are effective in characterizing not only dynamic evacuation route switching behavior (microscopic) but also network‐wide evacuation traffic performances (macro) under behavioral and information uncertainties.     

Developing an evacuation evaluation model for offshore oil and gas platforms using BIM and agent-based model

Accidents on offshore oil and gas platforms (OOGPs) usually cause serious fatalities and financial losses considering the demanding environment where such platforms are located and the complicated topsides structure that the platforms have. Conducting evacuation planning on OOGPs is challenging. Computational tools are considered as a good way to plan evacuation by emergency simulation. However, the complex structure of OOGPs and various evacuation behaviors can weaken the advantages of computational simulation. Therefore, this study develops a simulation model for OOGPs to evaluate different evacuation plans to improve evacuation performance by integrating building information modeling (BIM) technology and agent-based model (ABM). The developed model consists of four parts: evacuation model input, simulation environment modeling, agent definition, and simulation and comparison. Necessary platform information is extracted from BIM and then used to model the simulation environment by integrating matrix model and network model. In addition to essential attributes, environment sensing and dynamic escape path planning functions are developed and assigned to agents in order to improve simulation performance. Total evacuation time for all agents on an offshore platform is used to evaluate the evacuation performance of each simulation. An example OOGP BIM topsides with different emergency scenarios is used to illustrate the developed evacuation evaluation model. The results show that the developed model can accurately simulate evacuation and improve evacuation performance on OOGPs. The developed model is also applicable to other industries such as the architecture, engineering, and construction industry, where there is an increasing demand for evacuation planning and simulation.     

Simulation of high-rise building evacuation considering fatigue factor based on cellular automata: A case study in China

Stair evacuation plays a crucial role in building evacuation since stairs are generally the only means to evacuate high-rises on fire. To ensure safety stair design, the Life Safety Code suggests using a performance-based design approach, which requires evacuation simulations. Most of existing simulations, however, do not consider the structure of stairs and fatigue of evacuees, and these simulations are not validated by real emergency events or experiments. This paper is on improving the simulation of pedestrian flow in the stairs of high-rises by addressing these issues. A new Cellular Automata simulation model is developed where the simulation map is divided into zones based on the stair structure, and the rule of evacuees’ movement for each zone is appropriately defined to simulate turning behavior. To validate the simulation, a fire drill was held in two high-rise buildings. In this drill, evacuees felt tired after a walk. The simulation results demonstrate that, compared with the simulation without fatigue factor, our simulation can predict the evacuation time more accurately. Building designers can make evacuation plans and strategies based on the new simulation.     

Fuzzy Cellular Automata Model for Signalized Intersections

At signalized intersections, the decision‐making process of each individual driver is a very complex process that involves many factors. In this article, a fuzzy cellular automata (FCA) model, which incorporates traditional cellular automata (CA) and fuzzy logic (FL), is developed to simulate the decision‐making process and estimate the effect of driving behavior on traffic performance. Different from existing models and applications, the proposed FCA model utilizes fuzzy interface systems (FISs) and membership functions to simulate the cognition system of individual drivers. Four FISs are defined for each decision‐making process: car‐following, lane‐changing, amber‐running, and right‐turn filtering. A field observation study is conducted to calibrate membership functions of input factors, model parameters, and to validate the proposed FCA model. Simulation experiments of a two‐lane system show that the proposed FCA model is able to replicate decision‐making processes and estimate the effect on overall traffic performance.     

Bilevel optimization of a housing allocation and traffic emission problem in a predictive dynamic continuum transportation system

In recent decades, the effects of vehicle emissions on urban environments have raised increasing concerns, and it has been recognized that vehicle emissions affect peoples’ choice of housing location. Additionally, housing allocation patterns determine people's travel behavior and thus affect vehicle emissions. This study considers the housing allocation problem by incorporating vehicle emissions in a city with a single central business district (CBD) into a bilevel optimization model. In the lower level subprogram, under a fixed housing allocation, a predictive dynamic continuum user-optimal (PDUO-C) model with a combined departure time and route choice is used to study the city's traffic flow. In the upper level subprogram, the health cost is defined and minimized to identify the optimal allocation of additional housing units to update the housing allocation. A simulated annealing algorithm is used to solve the housing allocation problem. The results show that the distribution of additional housing locations is dependent on the distance and direction from the CBD. Sensitivity analyses demonstrate the influences of various factors (e.g., budget and cost of housing supply) on the optimized health cost and travel demand pattern.     

公路隧道交通拥堵疏散决策技术研究

针对公路隧道发生事故后交通拥堵疏散问题,结合隧道事故等级、事故处理时间、车辆行驶速度,引入交通流、交通波模型,依托重庆某特长公路隧道实际交通量数据,建立公路隧道交通拥堵疏散决策模型,分析公路隧道交通拥堵状态下的疏散控制,通过实例计算和模型仿真,验证了模型的准确性和适用性。结果表明:公路隧道交通拥堵疏散决策模型可非常准确地预判隧道发生各级事故后交通拥堵时间、排队长度等交通特征,依托模型预测结果,可快速制定高效交通诱导方案,实现交通管控和疏散,让公路隧道及所属路段快速恢复高效运行,为公路隧道的安全、高效运营管理提供决策支持。