Experienced travel time prediction for congested freeways

Travel time is an important performance measure for transportation systems, and dissemination of travel time information can help travelers make reliable travel decisions such as route choice or departure time. Since the traffic data collected in real time reflects the past or current conditions on the roadway, a predictive travel time methodology should be used to obtain the information to be disseminated. However, an important part of the literature either uses instantaneous travel time assumption, and sums the travel time of roadway segments at the starting time of the trip, or uses statistical forecasting algorithms to predict the future travel time. This study benefits from the available traffic flow fundamentals (e.g. shockwave analysis and bottleneck identification), and makes use of both historical and real time traffic information to provide travel time prediction. The methodological framework of this approach sequentially includes a bottleneck identification algorithm, clustering of traffic data in traffic regimes with similar characteristics, development of stochastic congestion maps for clustered data and an online congestion search algorithm, which combines historical data analysis and real-time data to predict experienced travel times at the starting time of the trip. The experimental results based on the loop detector data on Californian freeways indicate that the proposed method provides promising travel time predictions under varying traffic conditions.     

Brake light cellular automaton model with advanced randomization for traffic breakdown

Traffic breakdown is one of the most important empirical phenomena in traffic flow theory. Unfortunately, it cannot be simulated by many traffic flow models. In order to clarify its mechanism, the new brake light cellular automaton model has been proposed. Comparing with previous brake light models, three different aspects have been considered: (i) drivers tend to take large decelerations if the time gap is smaller than the safe time gap and the leading vehicle’s brake light is on; (ii) the brake light rule is set according to the reality; (iii) the randomization rule is put forward before the acceleration rule to weaken the impact of brake light on driving behaviors. Analyses show that the new model can explain the mechanism of traffic breakdown and the failures of other brake light models. Simulations confirm that all empirical features of traffic breakdown are successfully reproduced. At last, brake light models are calibrated and validated by the I-80 empirical data provided by NGSIM. Results show that the performance of the new model is the best and models in the three-phase theory are not necessarily better than models in the fundamental diagram approach and vice versa, at least for the brake light models.     

Spectral and time‐frequency analyses of freeway traffic flow

This paper uses spectral and time‐frequency analyses to treat three macroscopic traffic characteristics, namely, time mean speed, volume and occupancy as stochastic processes. Spectral and time‐frequency analyses are performed to characterize power spectral density (PSD), cross‐PSD, autocorrelation and cross‐correlation of these characteristics using TransGuide traffic data collected from four different freeways. It is found that low‐frequency components dominate the PSDs of speed, volume and occupancy at all times. The magnitude of PSDs decreases dramatically as frequency increases and remains almost at a constant level in high‐frequency regimes. A power law is found to exist, which describes the relationship between the frequency and the PSD of traffic characteristics. It is also found that speed can be properly modeled by a narrowband low‐pass stochastic process in a low‐frequency regime and by a nonzero mean white noise in a high‐frequency regime. Strong periodicities and synchronization are both shown in traffic flow. A variety of frequencies can be excited by congestion, and there is no dominant frequency found in stop‐and‐go traffic. Copyright © 2013 John Wiley & Sons, Ltd.     

关于辐流式二沉池设计计算方法的探讨

针对辐流式二沉池设计资料中存在的相关问题,从平面设计要点和竖向设计要点两方面分别对辐流式二沉池中设计流量的选定、沉淀池表面积计算、进出水口、污泥区容积计算,以及有效水深、池边水深和总池高计算等进行了探讨,并对刮(吸)泥设备和配水井的设计要点进行了相关说明.同时结合工程实践,优化平面设计参数和竖向设计参数,合理选择刮(吸)泥设备和配水井等辅助设施,能为相关技术人员提供一定的参考和借鉴意义.     

三叶片节气门进气系统的 CFD 计算和分析

以一款新型三叶片式节气门为主要研究对象，通过发动机台架试验，获得发动机稳态工况下进气歧管三维C FD计算的边界条件，选取不同转速、不同负荷率的12个有代表性的工况点，建立配置传统的单叶片节气门和三叶片节气门的进气歧管网格模型，并进行C FD计算和流场分析。结果表明：发动机处于中、高负荷时，由三叶片节气门产生的进气涡流比单叶片节气门大，且优势随节气门开度的增加而更加明显，但在低转速、小负荷的工况下，配置三叶片节气门的进气歧管内的涡流强度小于单叶片节气门。     

散装水泥运输罐车刹车过程物料流动特性研究

为探索散装水泥运输半挂车在刹车过程罐内物料的流动特性，基于FLUENT计算流体力学软件，采用欧拉-欧拉方法建立双流体模型，通过Syamlal-O＇Brien模型描述气-固曳力，对散装水泥运输半挂车在刹车过程罐内水泥的流动特性进行了数值模拟。结果表明，散装水泥运输半挂车在刹车过程中，罐内水泥向前运动，牵引车载荷高于设计载荷，对此提出通过在罐内顶部增设阻流板，可有效避免散装水泥运输半挂车在刹车过程由于载荷分布不合理而引起的一系列问题的改进措施。     

A framework for short-term traffic flow forecasting using the combination of wavelet transformation and artificial neural networks

The main objective of this paper is to develop a framework for short-term traffic flow forecasting models with high accuracy. Due to flow oscillations, the real-time information presented to the drivers through variable message signs, etc., may not be valid by the time the driver reaches the location. On the other hand, not all compartments of the flow signal are of same importance in determining its future state. A model is developed to predict the value of traffic flow in near future (next 5–35?minutes) based on the combination of wavelet transformation and artificial neural networks. This model is called the hybrid WT-ANN. Wavelet transformation is set to denoise the flow signal, i.e., filtering the unimportant fluctuations of the flow signal. Unimportant fluctuations are those that have little or no effect on the future condition of the signal. The neural network is set and trained to use previous data for predicting future flow. To implement the system, traffic data of US-101 were used from Next Generation Simulation (NGSIM). Results show that removing the noises has improved the accuracy of the prediction to a great extent. The model was used to predict the flow in three different locations on the same highway and a different highway in a different country. The model rendered highly reliable predictions. The proposed model predicts the flow of next 5?min on the same location with 2.5% Mean Absolute Percentage Error (MAPE) and of next 35?min with less than 12% MAPE. It predicts the flow on downstream locations for next 5?min with less than 8% MAPE and for the different highway with 2.3% MAPE.     

岩溶隧道超前地质预报几种主要物探方法的选择与实践

超前地质预报的物探方法有多种，由于岩溶发育空间分布的复杂性和岩溶含水介质充填物的多样性，单一的超前地质预报方法都具有局限性，如何针对岩溶的地球物理特征，选择适用的地质预报物探方法，以提高预报成果的准确度非常必要。通过对TSP法、地质雷达法、瞬变电磁法等超前地质预报主要物探方法工作原理、有效探测距离和地球物理特征等进行分析，论述岩溶隧道超前地质预报方法的理论依据和方法选择。以九景衢铁路何家隧道为例，详细论述施工过程中采用的几种主要超前地质预报方法以及组合方法，通过对比分析，验证和总结几种主要物探方法预报成果的适用性和准确度。实践成果表明： 1）单一的超前地质预报方法都具有局限性，难以应对岩溶隧道的复杂地质条件和施工高风险，需采取“三结合”措施，选取不同的超前预报方法作为组合方法，相互验证。2）TSP法未能对是岩溶还是断层破碎带进行区分，必须结合其他方法，进行对比验证才能区分； TSP法+地质雷达法长短结合探测方法，是一般简单岩溶隧道通用的组合。3）瞬变电磁法在岩溶隧道探测中效果明显，判译解释准确度高，适合大型岩溶强发育地段； 超前水平钻+瞬变电磁法+地质雷达法+水文监测地质预报组合，是复杂岩溶隧道超前地质预报可采用的有效组合。叠加超前水平钻与瞬变电磁剖面图进行分析，能详细分析出岩溶的空间分布和形态特征。     

High-resolution numerical relaxation approximations to second-order macroscopic traffic flow models

A novel numerical approach for the approximation of several, widely applied, macroscopic traffic flow models is presented. A relaxation-type approximation of second-order non-equilibrium models, written in conservation or balance law form, is considered. Using the relaxation approximation, the nonlinear equations are transformed to a semi-linear diagonilizable problem with linear characteristic variables and stiff source terms. To discretize the resulting relaxation system, low- and high-resolution reconstructions in space and implicit–explicit Runge–Kutta time integration schemes are considered. The family of spatial discretizations includes a second-order MUSCL scheme and a fifth-order WENO scheme, and a detailed formulation of the scheme is presented. Emphasis is given on the WENO scheme and its performance for solving the different traffic models. To demonstrate the effectiveness of the proposed approach, extensive numerical tests are performed for the different models. The computations reported here demonstrate the simplicity and versatility of relaxation schemes as solvers for macroscopic traffic flow models.     

复合地层泥水盾构环流关键参数选择探析

为研究复合地层泥水盾构泥水环流参数选择的问题,结合狮子洋隧道盾构工程,采用泥浆临界沉淀流速计算方法计算软弱地层和软硬不均地层所需的泥浆送、排量,并运用费祥俊模型试验公式进行验算。由于复合地层地质条件的复杂性,泥水盾构环流参数的影响因素较多,结合以上计算结果分析不同地层特性对泥浆送、排量的影响。研究结果表明： 1）2种方法的泥浆送、排量计算结果相差不大,证明泥浆临界沉淀流速计算方法具有准确性和合理性; 2）在软硬不均地层进行泥水盾构施工时,应加大泥浆送、排量,以减少输送颗粒在排浆管内滑移、平动,同时减少舱内积碴和泥浆管的磨损。研究结果可为复合地层下的泥水盾构施工提供参考。