重庆四公里立交至江南立交拥堵改造分析

文章主要探讨重庆四公里立交至江南立交拥堵改造设计,分析立交范围内交通运行特征及交通拥堵分布,深入剖析立交拥堵成因,结合分析结论将两座立交及相关设施视为统一整体进行交通组织设计,针对性地提出多项立交改造措施,同时依靠VISSIM交通仿真软件对现状和改造方案进行模拟及评价,为四公里立交至江南立交改造提供技术支持,也为城市立交拥堵改造提供参考。     

高速公路高密集互通群立交路段分离式断面标准论证

文章结合南京至马鞍山高速公路江苏段扩建工程,对高密集互通群立交路段分离式断面标准进行论证,从分析老路现状的拓宽改造条件入手,综合考虑高密互通群路段的断面方案,高密集互通群立交改造方案,高密集互通群立交交通适应性等方面因素,得出了功能清晰、服务水平高、交通运行均衡性良好、工程经济合理的扩建方案。     

基于VISSIM的城市非互通式立体交叉口交通拥堵改善研究

文章分析了城市非互通式立体交叉口存在的问题及其成因,并以甘肃省兰州市北滨河路和城关黄河大桥立交为实例,提出了四种改善方案,同时运用VIS-SIM仿真软件对所提出的改善方案进行模拟和对比,得出最优的改善方案,为非互通式立交交通改善提供理论依据。     

基于VB的高速公路动态限速仿真软件平台

文章利用VB语言及VISSIM交通仿真软件自主开发了高速公路动态限速仿真软件平台,对高速公路网进行微观仿真,并结合宏观交通流模型及成本函数制定高速公路动态限速方案。通过广西柳州(鹿寨)至南宁高速公路改扩建项目动态限速仿真软件平台的应用实践表明,该平台可以有效帮助高速公路交通规划管理部门制定科学合理的动态限速方案,并产生容量可观的数据库,有利于相关研究人员进行进一步的分析与评价。     

考虑多因素下互通式立交方案选择的优化算法

依据城市道路网络规划,从总体上分析道路的交通流量特征是建立城市互通式立交的有效方法,其设计应综合诸多影响因素以及其交通功能。文章提出了互通式立交选型的评价指标体系并对指标进行了量化,介绍了层次分析法、均值方差法和综合评价法三种指标权重值计算方法,以及信息不确定的PROMETHEE方法、灰色关联理想解法构建混合方程以及扩张矩阵算法FCV三种决策模型方法,对诸多立交方案进行优选分析,并依据Borda函数对所有方案的分数进行排名。所提出的算法和模型,可在众多方案中选择出最佳的互通式立交方案,不仅能优化道路网络,还能减少交通堵塞。     

高速公路立交和开放式单侧服务区合建方案研究

在高速公路服务区+旅游融合发展的背景下,文章提出立交、开放式单侧服务区合建的设计方案,分析了立交、服务区合建时的交通流特性,研究了对应的交通组织及诱导方案,并将提出的立交、开放式单侧服务区合建方案与传统的合建方案、独立设置方案进行对比,得出立交、开放式单侧服务区合建方案可节约用地规模和工程造价,且能更有效地与地方旅游融合发展,为打造服务区+旅游的建设方案提供了一种新的思路。     

TransCAD软件在城市单向交通组织方案中的验证应用

单向交通组织可以改善城市交通拥堵和提高路网利用率,因此,在交通组织管理方案实施前就应对其进行评价与完善,综合分析道路单向运行后的各交通参数,优化单向交通方案,是单向交通组织成功的必要前提。采用美国Caliper公司开发的交通软件TransCAD,对单向交通组织方案进行仿真,通过对比评价组织方案实施后的综合交通效益,确定单向交通组织方案的优劣。     

基于VISSIM仿真的交叉口信号配时优化分析

随着我国城市化发展和车辆保有量的增加,城市交通负荷也随之急剧增长,现有交通信号配时方案与交通需求不能很好地匹配。为了缓解交通延误、提高道路通行效率,文章以石河子市北五路—东二路交叉口为例,利用交通仿真软件VISSIM对该交叉口建立微观道路交通流模型并进行仿真优化分析。结果表明,优化后交叉口排队长度、车辆延误等指标明显降低,能够有效缓解交通拥堵、提高安全性。     

基于交通仿真的广汇立交桥交通拥堵改善方案研究

乌鲁木齐市广汇立交桥是苜蓿叶形完全互通式立交桥,是该区域交通的典型拥堵点。文章通过交通数据调查,分析了该立交桥交通拥堵的成因,从交织区域交通流的优化和提高匝道通行能力角度提出了交通组织优化方案,并利用交通微观仿真软件Vissim对该立交桥现状交通情况和优化组织方案进行了仿真比较。仿真结果显示优化后的立交桥区域交通拥堵情况得到了明显改善,研究成果可为该类型立交桥的交通组织提供参考。     

轨道交通ATS仿真运行框架的设计与实现

在分析轨道交通ATS系统特性的基础上,选用面向对象的仿真建模框架和逻辑控制框架,结合城市轨道交通的运行特点,对ATS仿真系统的时间控制和对象控制进行明确定义,克服传统仿真控制逻辑发散于描述模型过程代码中的缺点,介绍了一种面向对象的ATS仿真系统运行框架的设计和实现方法,为ATS仿真系统提供新的思路和方案。     

高速公路改扩建中车行天桥的拆除施工及安全管控研究

为最大限度降低高速公路改扩建工程非封闭路段原有上跨车行天桥拆除施工对车流通行的影响,并确保施工与交通安全,本文以成乐高速公路扩建试验段的5座旧桥拆除工程为例,针对现有施工技术对拆除作业及交通运行可能带来的风险因素,研究提出了分批次统一破碎拆除的施工方法和安全管控方案,通过合理的施工组织方案和施工工艺、全面的安全管控措施解决了破碎拆除法中可能出现的安全及环保问题。     

Evaluating the impacts of urban corridor traffic signal optimization on vehicle emissions and fuel consumption

This study investigates the impacts of traffic signal timing optimization on vehicular fuel consumption and emissions at an urban corridor. The traffic signal optimization approach proposed integrates a TRANSIMS microscopic traffic simulator, the VT-Micro model (a microscopic emission and fuel consumption estimation model), and a genetic algorithm (GA)-based optimizer. An urban corridor consisting of four signalized intersections in Charlottesville, VA, USA, is used for a case study. The result of the case study is then compared with the best traffic signal timing plan generated by Synchro using the TRANSIMS microscopic traffic simulator. The proposed approach achieves much better performance than that of the best Synchro solution in terms of air quality, energy and mobility measures: 20% less network-wide fuel consumption, 8–20% less vehicle emissions, and nearly 27% less vehicle-hours-traveled (VHT).     

Estimating link travel time functions for heterogeneous traffic flows on freeways

Oversized vehicles, such as trucks, significantly contribute to traffic delays on freeways. Heterogeneous traffic populations, that is, those consisting of multiple vehicles types, can exhibit more complicated travel behaviors in the operating speed and performance, depending on the traffic volume as well as the proportions of vehicle types. In order to estimate the component travel time functions for heterogeneous traffic flows on a freeway, this study develops a microscopic traffic‐simulation based four‐step method. A piecewise continuous function is proposed for each vehicle type and its parameters are estimated using the traffic data generated by a microscopic traffic simulation model. The illustrated experiments based on VISSIM model indicate that (i) in addition to traffic volume, traffic composition has significant influence on the travel time of vehicles and (ii) the respective estimations for travel time of heterogeneous flows could greatly improve their estimation accuracy. Copyright © 2016 John Wiley & Sons, Ltd.     

Decision-making on Large Infrastructure Projects: The Role of the Dutch Parliament

Abstract

Validating microscopic traffic simulation models incorporates several challenges because of the inadequacy and rareness of validation data, and the complexity of the car following and lane-changing processes. In addition, validation data were usually measured in aggregate form at the link level and not at the level of the individual vehicle. The majority of model validation attempts in the literature use average link measurements of traffic characteristics. However, validation techniques based on averages of traffic variables have several limitations including possible inconsistency between the field observed and simulation-estimated variables, and as such the resulting spatial–temporal traffic stream patterns.

Due to these inconsistencies, this paper introduces a novel approach to the validation of microscopic traffic simulation models. A three-stage procedure for validating microscopic simulation models is presented. The paper describes the field measurements, experimental setup, and the simulation-based analysis of the three stages. The purpose of the first stage is to validate a benchmark simulator (NETSIM) using limited field data. The second stage examines the spatial–temporal traffic patterns extracted from the benchmark simulator versus those extracted from the simulation model to be validated (I-SIM-S). Different traffic patterns were examined accounting for various factors, such as traffic flow, link speeds, and signal timing. The third stage compares the aggregate traffic measures extracted from the subject simulator against those extracted from the benchmark simulator.     

Online calibration for microscopic traffic simulation and dynamic multi-step prediction of traffic speed

Simulating driving behavior in high accuracy allows short-term prediction of traffic parameters, such as speeds and travel times, which are basic components of Advanced Traveler Information Systems (ATIS). Models with static parameters are often unable to respond to varying traffic conditions and simulate effectively the corresponding driving behavior. It has therefore been widely accepted that the model parameters vary in multiple dimensions, including across individual drivers, but also spatially across the network and temporally. While typically on-line, predictive models are macroscopic or mesoscopic, due to computational and data considerations, nowadays microscopic models are becoming increasingly practical for dynamic applications. In this research, we develop a methodology for online calibration of microscopic traffic simulation models for dynamic multi-step prediction of traffic measures, and apply it to car-following models, one of the key models in microscopic traffic simulation models. The methodology is illustrated using real trajectory data available from an experiment conducted in Naples, using a well-established car-following model. The performance of the application with the dynamic model parameters consistently outperforms the corresponding static calibrated model in all cases, and leads to less than 10% error in speed prediction even for ten steps into the future, in all considered data-sets.     

Estimating fuel consumption and emissions based on reconstructed vehicle trajectories

Microscopic emission models are widely used in emission estimation and environment evaluation. Traditionally, microscopic traffic simulation models and probe vehicles are two sources of inputs to a microscopic emission model. However, they are not effective in reflecting all vehicles' real‐world operating conditions. Using each vehicle's spot speed data recorded by detectors, this paper provides a new method to estimate all vehicles' real‐world activities data. These data can then be used as inputs to a microscopic emission model to estimate vehicle fuel consumption and emissions. The main task is to reconstruct trajectory of each vehicle and calculate second‐by‐second speed and acceleration from the activities data. The Next Generation Simulation dataset and the Comprehensive Modal Emissions Model are used in this study to calculate and analyze the emission results for both lane‐level and link‐level. The results showed that using the proposed method for estimating vehicle fuel consumption and emissions is promising. Copyright © 2012 John Wiley & Sons, Ltd.     

The development of taiwan arterial traffic‐adaptive signal control system and its field test: A taiwan experience

This Taiwan traffic‐adaptive arterial signal control model borrowed its traffic flow framework mainly from a British traffic‐adaptive control model with a cyclic traffic progression function, i.e. SCOOT (Split Cycle Office Optimisation Technique). The new arterial control model can take into account delays of both major and minor streets and make real‐time signal timing decisions with optimal two‐way signal offsets, so as to create the best arterial signal operation performance. It has been developed to be an online real‐time software for both simulation testing and field validation. Through simulation, it was found that the performance when operating this newly developed real‐time arterial traffic‐adaptive model was significantly better than when using the optimal fixed‐time arterial timing plan. On the aspect of field testing, three signalized intersections located in East District, Tainan City, Taiwan were selected to be the test sites. Fairly good traffic control performance has been demonstrated in that it can effectively reduce travel delays of the control arterial as a whole. Additional discussions about how to combine travel delay and the total number of vehicle stops into a new control performance index have also been included to make the new traffic‐adaptive model more flexible and reasonable to meet the expectations of different driver groups in the arterial system.     

A microscopic analysis of speed deviation impacts on lane-changing behavior

Driving behavior models that capture drivers’ tactical maneuvering decisions in different traffic conditions are essential to microscopic traffic simulation systems. This paper focuses on a parameter that has a great impact on road users’ aggressive overtaking maneuvers and directly affects lane-changing models (an integral part of microscopic traffic simulation models), namely, speed deviation. The objective of this research is to investigate the impacts of speed deviation in terms of performance measures (delay time, network mean speed, and travel time duration) and the number of lane-change maneuvers using the Aimsun traffic simulator. Following calibration of the model for a section of urban highway in Tehran, this paper explores the sensitivity of lane-changing maneuvers during different speed deviations by conducting two types of test. Simulation results show that, by decreasing speed deviation, the number of lane changes reduces remarkably and so network safety increases, thus reducing travel time due to an increase in network mean speed.     

VISSIM/MOVES integration to investigate the effect of major key parameters on CO2 emissions

This paper looks at CO₂ emissions on limited access highways in a microscopic and stochastic environment using an optimal design approach. Estimating vehicle emissions based on second-by-second vehicle operation allows the integration of a microscopic traffic simulation model with the latest US Environmental Protection Agency’s mobile source emissions model to improve accuracy. A factorial experiment on a test bed prototype of the I-4 urban limited access highway corridor located in Orlando, Florida was conducted to identify the optimal settings for CO₂ emissions reduction and to develop a microscopic transportation emission prediction model. An exponentially decaying function towards a limiting value expressed in the freeway capacity is found to correlate with CO₂ emission rates. Moreover, speeds between 55 and 60 mph show emission rate reduction effect while maintaining up to 90% of the freeway’s capacity. The results show that speed has a significant impact on CO₂ emissions when detailed and microscopic analysis of vehicle operations of acceleration and deceleration are considered.