信号控制对交通噪声的影响分析

用实验方法测定三种不同车型单辆车在参考距离处的噪声排放量及加减速噪声修正值。然后结合微观交通仿真、车辆噪声排放量和传播衰减模型分别对信号控制下的间断流交通噪声和无控制的连续流交通噪声进行动态模拟。最后对两种不同交通流状况下的等效声级、噪声标准差、交通噪声指数和噪声的频数分布进行对比分析,得到两种不同交通流状况下交通噪声的若干重要差别。     

驾驶员行为对交通噪声的影响

基于微观交通流仿真，结合ASJ-RTN 2008单车噪声排放模型，研究驾驶员行为对交通噪声的影响。通过敏感性分析得知，拥堵状态下的交通噪声对驾驶员跟驰行为和信号反应较为敏感，其中跟驰行为对交通噪声影响高达2.07 dB；而在畅通状态下，驾驶员行为对交通噪声的影响极小。受驾驶员行为变化的影响，区域噪声排放总能量与路旁L Aeq值的变化趋势相似，单位出行里程噪声排放能量与路旁L Aeq值的变化趋势相反。     

以法治站 切实做好机动车检测站计量管理工作

为了保证机动车正常行驶，减少交通事故发生，控制排放有害气体和噪声，公安、交通车辆管理部门逐步完善检测手段，建立机动车安全检测站，购置检测设备如制动试验台、废气分析仪、烟度计等，对保障安全、环保实施有着重要的意义。机动车安全检测站中的检测设备基本上都属于计量器具，用来对机动车各部位的性能进行质量检测和评价。能否正确评价性能好坏关系到车辆行驶安全和人民群众的生命和财产安全，由此机动车检测站的计量管理工作是一项必不可少的重要工作。1．机动车检测站中的检测设备属计量器具，必须向具有《制造计量器具许可证》…     

飞行状态下涡扇发动机风扇音频信号合成

为了能以快速、低成本的方式获得飞机起飞过程中,噪声适航审定飞越噪声测量点处涡扇发动机风扇部件的音频信号,对该音频信号的合成方式进行了研究,并提出了一种基于Heidmann风扇噪声预测模型的音频信号合成方法。该方法首先将环境参数、涡扇发动机风扇部件的尺寸参数和性能参数输入Heidmann预测模型得到源噪声数据,根据ANP数据库计算得到航迹数据,接着根据航迹数据对源噪声数据进行修正,得到噪声适航审定飞越噪声测量点处噪声数据。将上述数据输入Adobe Audition软件,分别用加法合成法和减法合成法合成单音噪声和宽频噪声,再在该软件中对噪声进行组合拼接,最后得到飞行状态下风扇部件的音频信号。对合成的音频信号进行播放并使用声学测量仪器进行测量,验证了该方法的正确性和有效性。     

小波域高斯混合模型方差估计近红外降噪方法

针对抑制近红外光谱噪声与保留光谱信号细节的矛盾,提出一种基于噪声方差估计的小波域降噪方法.该法对光谱信号小波域高频系数建立了两状态高斯混合模型,用EM算法估计模型系数,推证模型对噪声方差准确估计特性,将估计得到的噪声方差建立了阈值降噪模型.实验建立黄酒近红外光谱快速预测酒精度偏最小二乘模型,对比分析Penalty阈值、...     

一种新型的地区机动车排放因子计算方法研究

提出了一种无需环境参数修正的地区机动车排放因子计算模型,改善由修正参数引入的模型不确定度。对模型的原理、结构和排放因子计算流程进行了阐述,证明该模型除需对机动车使用状态参数进行补偿外,无需对环境参数进行补偿。对沈阳市小型轿车和小型客车的日均排放因子进行了计算,并与COPERT-V模型计算结果进行了对比,证明了该模型的优越性,并证明满载状态下小型客车的人均尾气排放因子低于小型轿车。     

虚拟传声器的有源噪声控制

研究虚拟传声器的有源噪声控制问题。该技术适用于控制区域不适合放置误差传声器的场合。将误差传声器置于控制区域之外,得到测量误差。采用前向差分预测算法预测控制区域内的残余误差信号,然后利用自适应LMS算法,得到最优的噪声控制滤波器。为了尽量消除预测中存在的误差,采用自适应变权值预测算法。仿真结果表明该方法能有效地抑制噪声,使控制区域内的噪声信号得到明显衰减。     

车路协同环境下自适应信号配时优化模型

在车路协同环境下,车辆位置和速度等信息容易获得,为交通信号控制系统提供了新的数据源。针对现有信号控制系统鲁棒性差,不能适应交通流实时变化特征等问题,本文提出了一种车路协同环境下交叉口自适应实时控制优化模型。该模型以交叉口车均延误最小为优化目标,相位绿灯时长为约束条件,采用遗传算法对模型进行求解,实现了对交叉口信号配时方案的实时优化。最后,通过调查数据并设计仿真实验,证明了文中模型比感应控制效果更好,车辆平均延误减少了30%,同时能够保证交叉口各个转向的车均延误均衡。     

基于微观交通仿真的居住小区道路交通噪声研究

采用微观交通仿真对居住小区的道路交通噪声进行动态模拟研究。用微观交通仿真技术进行路网的建模及车辆的动态交通仿真,结合车辆噪声的排放模型以及噪声传播模型,考虑了噪声在建筑物间的反射和衍射,实现了对居住小区在路网用户均衡和非均衡条件下的交通噪声动态模拟,分析了新增道路穿越小区对小区噪声的影响,模拟了不同建筑物布局下居住小区交通噪声的声场分布。通过道路交通噪声的动态模拟不仅得到了小区噪声的等效连续声级,还掌握了其波动起伏特性。最后,进行了实地的交通与噪声监测,实测与模拟结果对比表明该方法精确可行。     

结构损伤识别中噪声的模拟

在有限元仿真的结构振动信号上施加不同水平的噪声,采用随机子空间法,分别从各种噪声水平的信号中提取结构的模态参数。以无噪声信号得到的模态参数为标准值,计算了各信号噪声水平下模态参数的误差,得到了信号噪声水平与模态参数噪声水平的对应关系,给出了模拟模态参数噪声的方式。通过损伤识别算例,考察了识别效果对信号信噪比的要求。     

Corridor-level signalized intersection safety analysis in Shanghai,China using Bayesian hierarchical models

Most traffic crashes in Chinese cities occur at signalized intersections. Research on the intersection safety problem in China is still in its early stage. The recent development of an advanced traffic information system in Shanghai enables in-depth intersection safety analyses using road design, traffic operation, and crash data. In Shanghai, the road network density is relatively high and the distance between signalized intersections is small, averaging about 200 m. Adjacent signalized intersections located along the same corridor share similar traffic flows, and signals are usually coordinated. Therefore, when studying intersection safety in Shanghai, it is essential to account for intersection correlations within corridors. In this study, data for 195 signalized intersections along 22 corridors in the urban areas of Shanghai were collected. Mean speeds and speed variances of corridors were acquired from taxis equipped with Global Positioning Systems (GPS). Bayesian hierarchical models were applied to identify crash risk factors at both the intersection and the corridor levels. Results showed that intersections along corridors with lower mean speeds were associated with fewer crashes than those with higher speeds, and those intersections along two-way roads, under elevated roads, and in close proximity to each other, tended to have higher crash frequencies.     

Differences in passenger car and large truck involved crash frequencies at urban signalized intersections: An exploratory analysis

The influence of intersection features on safety has been examined extensively because intersections experience a relatively large proportion of motor vehicle conflicts and crashes. Although there are distinct differences between passenger cars and large trucks-size, operating characteristics, dimensions, and weight-modeling crash counts across vehicle types is rarely addressed. This paper develops and presents a multivariate regression model of crash frequencies by collision vehicle type using crash data for urban signalized intersections in Tennessee. In addition, the performance of univariate Poisson-lognormal (UVPLN), multivariate Poisson (MVP), and multivariate Poisson-lognormal (MVPLN) regression models in establishing the relationship between crashes, traffic factors, and geometric design of roadway intersections is investigated. Bayesian methods are used to estimate the unknown parameters of these models. The evaluation results suggest that the MVPLN model possesses most of the desirable statistical properties in developing the relationships. Compared to the UVPLN and MVP models, the MVPLN model better identifies significant factors and predicts crash frequencies. The findings suggest that traffic volume, truck percentage, lighting condition, and intersection angle significantly affect intersection safety. Important differences in car, car–truck, and truck crash frequencies with respect to various risk factors were found to exist between models. The paper provides some new or more comprehensive observations that have not been covered in previous studies.     

A before-and-after study of driver stopping propensity at red light camera intersections

This paper reports a before-and-after study which evaluated the impacts of installing and operating red light cameras at two "T" and one "X" signalized intersections on driver stopping propensity upon the onset of amber. Rather than using video cameras, a special purpose data logger working in conjunction with loop sensors was used to gather traffic parameters, vehicle stopping/crossing movements, and signal phases. Logistic modeling was employed to model the revealed stopping/crossing decisions of non-platoon vehicle drivers in response to the onset of amber with traffic, situational and behavioral variables, including their interactions. The results indicate that the variable Cam_Inst that gathered the impacts of red light camera (RLC) installation on driver decision-making at signalized intersection was significant at 5% level only for the camera approach model of the cross-intersection. The significance of Cam_Inst was undermined for the camera approaches at the T-intersections by the inclusion of a significant two-order variable defining the interaction of Cam_Inst with distance from the stop-line. One may, thus, infer that RLC has a fixed-quantum effect at the cross-intersection, but an accentuated effect with distance at the two T-intersections. Lastly, the effects of a RLC at an intersection on the stopping decision at the non-camera approaches were minimal.     

Exposure to lateral collision in signalized intersections with protected left turn under different traffic control strategies

This paper proposes an original definition of the exposure to lateral collision in signalized intersections and discusses the results of a real world experiment. This exposure is defined as the duration of situations where the stream that is given the right-of-way goes through the conflict zone while road users are waiting in the cross-traffic approach. This measure, obtained from video sensors, makes it possible to compare different operating conditions such as different traffic signal strategies. The data from a real world experiment is used, where the adaptive real-time strategy CRONOS (ContRol Of Networks by Optimization of Switchovers) and a time-plan strategy with vehicle-actuated ranges alternately controlled an isolated intersection near Paris. Hourly samples with similar traffic volumes are compared and the exposure to lateral collision is different in various areas of the intersection and various traffic conditions for the two strategies. The total exposure under peak hour traffic conditions drops by roughly 5 min/h with the CRONOS strategy compared to the time-plan strategy, which occurs mostly on entry streams. The results are analyzed through the decomposition of cycles in phase sequences and recommendations are made for traffic control strategies.     

Micro-simulation of vehicle conflicts involving right-turn vehicles at signalized intersections based on cellular automata

At intersection, vehicles coming from different directions conflict with each other. Improper geometric design and signal settings at signalized intersection will increase occurrence of conflicts between road users and results in a reduction of the safety level. This study established a cellular automata (CA) model to simulate vehicular interactions involving right-turn vehicles (as similar to left-turn vehicles in US). Through various simulation scenarios for four case cross-intersections, the relationships between conflict occurrences involving right-turn vehicles with traffic volume and right-turn movement control strategies are analyzed. Impacts of traffic volume, permissive right-turn compared to red-amber-green (RAG) arrow, shared straight-through and right-turn lane as well as signal setting are estimated from simulation results. The simulation model is found to be able to provide reasonable assessment of conflicts through comparison of existed simulation approach and observed accidents. Through the proposed approach, prediction models for occurrences and severity of vehicle conflicts can be developed for various geometric layouts and traffic control strategies.     

Exposure to lateral collision in signalized intersections with protected left turn under different traffic control strategies

This paper proposes an original definition of the exposure to lateral collision in signalized intersections and discusses the results of a real world experiment. This exposure is defined as the duration of situations where the stream that is given the right-of-way goes through the conflict zone while road users are waiting in the cross-traffic approach. This measure, obtained from video sensors, makes it possible to compare different operating conditions such as different traffic signal strategies. The data from a real world experiment is used, where the adaptive real-time strategy CRONOS (ContRol Of Networks by Optimization of Switchovers) and a time-plan strategy with vehicle-actuated ranges alternately controlled an isolated intersection near Paris. Hourly samples with similar traffic volumes are compared and the exposure to lateral collision is different in various areas of the intersection and various traffic conditions for the two strategies. The total exposure under peak hour traffic conditions drops by roughly 5 min/h with the CRONOS strategy compared to the time-plan strategy, which occurs mostly on entry streams. The results are analyzed through the decomposition of cycles in phase sequences and recommendations are made for traffic control strategies.     

Transferability of calibrated microsimulation model parameters for safety assessment using simulated conflicts

Several studies have investigated the relationship between field-measured conflicts and the conflicts obtained from micro-simulation models using the Surrogate Safety Assessment Model (SSAM). Results from recent studies have shown that while reasonable correlation between simulated and real traffic conflicts can be obtained especially after proper calibration, more work is still needed to confirm that simulated conflicts provide safety measures beyond what can be expected from exposure. As well, the results have emphasized that using micro-simulation model to evaluate safety without proper model calibration should be avoided. The calibration process adjusts relevant simulation parameters to maximize the correlation between field-measured and simulated conflicts.The main objective of this study is to investigate the transferability of calibrated parameters of the traffic simulation model (VISSIM) for safety analysis between different sites. The main purpose is to examine whether the calibrated parameters, when applied to other sites, give reasonable results in terms of the correlation between the field-measured and the simulated conflicts. Eighty-three hours of video data from two signalized intersections in Surrey, BC were used in this study. Automated video-based computer vision techniques were used to extract vehicle trajectories and identify field-measured rear-end conflicts. Calibrated VISSIM parameters obtained from the first intersection which maximized the correlation between simulated and field-observed conflicts were used to estimate traffic conflicts at the second intersection and to compare the results to parameters optimized specifically for the second intersection. The results show that the VISSIM parameters are generally transferable between the two locations as the transferred parameters provided better correlation between simulated and field-measured conflicts than using the default VISSIM parameters. Of the six VISSIM parameters identified as important for the safety analysis, two parameters were directly transferable, three parameters were transferable to some degree, and one parameter was not transferable.     

Validating a driving simulator using surrogate safety measures

Traffic crash statistics and previous research have shown an increased risk of traffic crashes at signalized intersections. How to diagnose safety problems and develop effective countermeasures to reduce crash rate at intersections is a key task for traffic engineers and researchers. This study aims at investigating whether the driving simulator can be used as a valid tool to assess traffic safety at signalized intersections. In support of the research objective, this simulator validity study was conducted from two perspectives, a traffic parameter (speed) and a safety parameter (crash history). A signalized intersection with as many important features (including roadway geometries, traffic control devices, intersection surroundings, and buildings) was replicated into a high-fidelity driving simulator. A driving simulator experiment with eight scenarios at the intersection were conducted to determine if the subjects' speed behavior and traffic risk patterns in the driving simulator were similar to what were found at the real intersection. The experiment results showed that speed data observed from the field and in the simulator experiment both follow normal distributions and have equal means for each intersection approach, which validated the driving simulator in absolute terms. Furthermore, this study used an innovative approach of using surrogate safety measures from the simulator to contrast with the crash analysis for the field data. The simulator experiment results indicated that compared to the right-turn lane with the low rear-end crash history record (2 crashes), subjects showed a series of more risky behaviors at the right-turn lane with the high rear-end crash history record (16 crashes), including higher deceleration rate (1.80+/-1.20 m/s(2) versus 0.80+/-0.65 m/s(2)), higher non-stop right-turn rate on red (81.67% versus 57.63%), higher right-turn speed as stop line (18.38+/-8.90 km/h versus 14.68+/-6.04 km/h), shorter following distance (30.19+/-13.43 m versus 35.58+/-13.41 m), and higher rear-end probability (9/59=0.153 versus 2/60=0.033). Therefore, the relative validity of driving simulator was well established for the traffic safety studies at signalized intersections.     

Pedestrian risk decrease with pedestrian flow. A case study based on data from signalized intersections in Hamilton,Ontario

A unique database provided information on pedestrian accidents, intersection geometry and estimates of pedestrian and vehicle flows for the years 1983-1986 for approximately 300 signalized intersections in Hamilton, Ont., Canada. Pedestrian safety at semi-protected schemes, where left-turning vehicles face no opposing traffic but have potential conflicts with pedestrians, were compared with pedestrian safety at normal non-channelized signalized approaches, where right-turning vehicles have potential conflicts with pedestrians. Four different ways of estimating hourly flows for left- and right-turning vehicles were explored. Hourly flows were estimated for periods of 15 min, hours, two periods a day (a.m. and p.m.) and the 'daily' period (7 h). Parameter estimates were somewhat affected by the time period used for flow estimation. However, parameter estimates seem to be affected far more by the traffic pattern (left- or right-turning traffic), even though approaches were selected such that the situation for left- and right-turning turning traffic was similar (no opposing traffic, no advanced green or other separate phases and no channelization). Left-turning vehicles caused higher risks for pedestrians than right-turning vehicles. At low vehicular flows right turns and semi-protected left turns seemed to be equally safe for pedestrians. When risks for pedestrians were calculated as the expected number of reported pedestrian accidents per pedestrian, risk decreased with increasing pedestrian flows and increased with increasing vehicle flow. As risk decreases with increasing pedestrian flows, promoting walking will have a positive effect on pedestrian risk at signalized intersections.