This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a...This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.展开更多
In the past,development of road weather information system(RWIS)mainly reflected in gradual expansion of a network of environmental sensing stations(ESS)along the main roads in Latvia.Since a concept of common platfor...In the past,development of road weather information system(RWIS)mainly reflected in gradual expansion of a network of environmental sensing stations(ESS)along the main roads in Latvia.Since a concept of common platform of Intelligent Transportation System(ITS)became mature and has a Pan European framework,RWIS as its integral part,got opportunities for more effective usage,but at the same time,new challenges of data accessibility and interoperability occurred.The presentation deals with ongoing projects and future vision about:how existing ESS stations should be built up to a multifunctional road,traffic and environment control points;how RWIS of different authorities and other data sources should be integrated;how to cover road network(including secondary routes)with low-cost sensors and provide proper decision-making tool for antiicing strategy and overall road management;how RWIS data can be used wider and processed for new marketplaces in Latvia.展开更多
This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers mult...This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.展开更多
The road weather information system （RWIS）, which collects and monitors weather and pavement surface conditions, has been proven effective to support winter road maintenance by improving safety, mobility, and effi- ...The road weather information system （RWIS）, which collects and monitors weather and pavement surface conditions, has been proven effective to support winter road maintenance by improving safety, mobility, and effi- ciency. Although the geographic information systems are being widely applied for facility siting, traditional practices of sitting RWIS stations still heavily rely on the experi- ences of maintenance and operation personnel, which is time-consuming and subjective. This study develops a linear model to determine the optimal RWlS locations subject to three selection criteria： weather, traffic condition, and distance to existing RWIS sites, while considering practical constraints to satisfy specific requirements of various agencies （e.g., different weights of weather/traffic factors, various available budgets, etc.）.展开更多
气象因素是影响高速公路行车安全的因素之一。以往研究较少采用实时气象数据,且大多只针对某类气象因素进行研究。现利用TJRD平台上的高速公路车辆轨迹数据和道路实时气象信息系统(Road Weather Information System, RWIS)数据,综合考...气象因素是影响高速公路行车安全的因素之一。以往研究较少采用实时气象数据,且大多只针对某类气象因素进行研究。现利用TJRD平台上的高速公路车辆轨迹数据和道路实时气象信息系统(Road Weather Information System, RWIS)数据,综合考虑了交通流因素和气象因素对交通冲突的影响,采用负二项分布模型,构建了高速公路交通冲突致因分析模型。分析表明,纵向风速和纵向速度标准差是影响高速公路行车安全的主要因素,能见度和路面湿滑系数为次要因素。研究结果可以为高速公路安全管控策略制定提供理论依据。展开更多
基于卫星遥感的水体提取算法对面积较大的水体效果较好,应用于细小水体时受混合像元、异物同谱等因素影响,容易出现误判。Sentinel-2卫星多光谱遥感数据空间分辨率为10 m、20 m、60 m,双星时间分辨率5 d,时间和空间分辨率较高,因此本文...基于卫星遥感的水体提取算法对面积较大的水体效果较好,应用于细小水体时受混合像元、异物同谱等因素影响,容易出现误判。Sentinel-2卫星多光谱遥感数据空间分辨率为10 m、20 m、60 m,双星时间分辨率5 d,时间和空间分辨率较高,因此本文采用了Sentinel-2绿光波段(560 nm)、红边波段(705 nm)、近红外波段(842 nm、865 nm)和短波红外波段(2190 nm)的遥感反射率,提出了一种植被红边水体指数算法RWI(Vegetation Red Edge based Water Index)。对比分析了植被、阴影、建筑物、混合像元、裸土、水体6种地物的归一化遥感反射率,从机理上解释了为什么RWI比其他水体指数具有更好的提取细小水体的效果。本文对比了常用的几种水体提取算法,包括改进的归一化差异水体指数MNDWI(Modified Normalized Difference Water Index)、多波段水体指数MBWI(Multi-Band Water Index)、自动水提取指数AWEI(Automated Water Extraction Index),以人工目视解译的水体结果为准,对比以上几种算法得到的水体提取结果,得出RWI、MNDWI、MBWI、AWEIsh、AWEInsh的面积提取差异分别为3.6%,4.2%,12.2%,8.8%,19.8%。从结果可以看出RWI算法精度最高。从影像提取结果来看,本文提出的RWI算法提取的水体边界效果更佳,而且能够一定程度上消除山体和建筑物阴影、云阴影以及混合像元的影响。同时,在2016-01—2018-12时间范围内筛选选取了共43景无云的Sentinel-2影像,利用本文提出的算法对雄安新区、神东矿区、永城矿区3个区域的细小水体分布开展了多时相分析。观察后发现每个时相的结果均十分良好,细小水体的边界区分度较高,基本没有错提、漏提,算法具有良好的适用性和稳定性。展开更多
We analyzed the characteristics of subway station environment and the change of thermal comfort for passengers when they are in and out of the station. The dynamic thermal comfort evaluation model RWI(relative warmth ...We analyzed the characteristics of subway station environment and the change of thermal comfort for passengers when they are in and out of the station. The dynamic thermal comfort evaluation model RWI(relative warmth index) and HDR(heat deficit rate) were built on the distinguishing features of public area in subway station. Taking one representative subway station in Nanjing as the research object, the thermal comfort conditions in different seasons and different parts were studied by field tests, questionnaires and model-evaluating. The calculated RWI shows that although the thermal comfort in Nanjing metro is relatively acceptable, ideal thermal comfort has not been achieved. And it is found that associated with predicted mean vote(PMV), using RWI can evaluate the thermal comfort more precisely.展开更多
基金funded by the Aurora Programfunded by National Sciences and Engineering Research Council of Canada (NSERC)Ontario Ministry of Transportation (MTO)
文摘This article presents a comprehensive framework for determining the location of road weather information system （RWIS） stations over a regional road network. In the proposed methodology, the region is divided into a grid of equal-sized zones which are considered as the minimum spatial unit for allocating a candidate set of RWIS stations. These zones are ranked according to a set of pre-specified criteria that reflect the needs for, and potential benefits from, real-time RWIS, including road surface temperature variability, precipitation, network traffic, and collision patterns. A case study based on the existing RWIS network in the province of Ontario was conducted to illustrate the major features of the proposed method and evaluate the implications of alternative loca- tion selection criteria. The findings of the study suggest that it is feasible to develop a systematic process for locating RWIS stations using an integrated location criterion to capture multiple factors being considered in prac- tice. The study has also revealed the need to establish quantitative models for estimating the benefit of real-time information from RWIS stations, which is the foundation of a cost-benefit-based RWIS location optimization model.
文摘In the past,development of road weather information system(RWIS)mainly reflected in gradual expansion of a network of environmental sensing stations(ESS)along the main roads in Latvia.Since a concept of common platform of Intelligent Transportation System(ITS)became mature and has a Pan European framework,RWIS as its integral part,got opportunities for more effective usage,but at the same time,new challenges of data accessibility and interoperability occurred.The presentation deals with ongoing projects and future vision about:how existing ESS stations should be built up to a multifunctional road,traffic and environment control points;how RWIS of different authorities and other data sources should be integrated;how to cover road network(including secondary routes)with low-cost sensors and provide proper decision-making tool for antiicing strategy and overall road management;how RWIS data can be used wider and processed for new marketplaces in Latvia.
基金supported by a grant from the MaineDOT and Vanasse Hangen Brustlin(VHB).Grant number:VHB 52874.03 WIN 026140.00,Name of the author who received the funding:Tae J.Kwon.
文摘This paper extends the previously developed method of optimizing Road Weather Information Systems(RWIS)station placement by unveiling a sophisticated multi-variable semivariogram model that concurrently considers multiple vital road weather variables.Previous research primarily centered on single-variable analysis focusing on road surface temperature(RST).The study bridges this oversight by introducing a framework that integrates multiple critical weather variables into the RWIS location allocation framework.This novel approach ensures balanced and equitable RWIS distribution across zones and aligns the network with areas both prone to traffic accidents and areas of high uncertainty.To demonstrate the effectiveness of this refinement,the authors applied the framework to Maine’s existing RWIS network,conducted a gap analysis through varying planning scenarios and generated optimal solutions using a heuristic optimization algorithm.The analysis identified areas that would benefit most from additional RWIS stations and guided optimal resource utilization across different road types and priority locations.A sensitivity analysis was also performed to evaluate the effect of different weightings for weather and traffic factors on the selection of optimal locations.The location solutions generated have been adopted by MaineDOT for future implementations,attesting to the model’s practicality and signifying an important advancement for more effective management of road weather conditions.
文摘The road weather information system （RWIS）, which collects and monitors weather and pavement surface conditions, has been proven effective to support winter road maintenance by improving safety, mobility, and effi- ciency. Although the geographic information systems are being widely applied for facility siting, traditional practices of sitting RWIS stations still heavily rely on the experi- ences of maintenance and operation personnel, which is time-consuming and subjective. This study develops a linear model to determine the optimal RWlS locations subject to three selection criteria： weather, traffic condition, and distance to existing RWIS sites, while considering practical constraints to satisfy specific requirements of various agencies （e.g., different weights of weather/traffic factors, various available budgets, etc.）.
基金山西交科院项目二期:车路协同试点应用风险评估与预警防控技术the Shanxi Transportation Research Institute Group Co.,Ltd.(20-JKKJ-1)。
文摘气象因素是影响高速公路行车安全的因素之一。以往研究较少采用实时气象数据,且大多只针对某类气象因素进行研究。现利用TJRD平台上的高速公路车辆轨迹数据和道路实时气象信息系统(Road Weather Information System, RWIS)数据,综合考虑了交通流因素和气象因素对交通冲突的影响,采用负二项分布模型,构建了高速公路交通冲突致因分析模型。分析表明,纵向风速和纵向速度标准差是影响高速公路行车安全的主要因素,能见度和路面湿滑系数为次要因素。研究结果可以为高速公路安全管控策略制定提供理论依据。
文摘基于卫星遥感的水体提取算法对面积较大的水体效果较好,应用于细小水体时受混合像元、异物同谱等因素影响,容易出现误判。Sentinel-2卫星多光谱遥感数据空间分辨率为10 m、20 m、60 m,双星时间分辨率5 d,时间和空间分辨率较高,因此本文采用了Sentinel-2绿光波段(560 nm)、红边波段(705 nm)、近红外波段(842 nm、865 nm)和短波红外波段(2190 nm)的遥感反射率,提出了一种植被红边水体指数算法RWI(Vegetation Red Edge based Water Index)。对比分析了植被、阴影、建筑物、混合像元、裸土、水体6种地物的归一化遥感反射率,从机理上解释了为什么RWI比其他水体指数具有更好的提取细小水体的效果。本文对比了常用的几种水体提取算法,包括改进的归一化差异水体指数MNDWI(Modified Normalized Difference Water Index)、多波段水体指数MBWI(Multi-Band Water Index)、自动水提取指数AWEI(Automated Water Extraction Index),以人工目视解译的水体结果为准,对比以上几种算法得到的水体提取结果,得出RWI、MNDWI、MBWI、AWEIsh、AWEInsh的面积提取差异分别为3.6%,4.2%,12.2%,8.8%,19.8%。从结果可以看出RWI算法精度最高。从影像提取结果来看,本文提出的RWI算法提取的水体边界效果更佳,而且能够一定程度上消除山体和建筑物阴影、云阴影以及混合像元的影响。同时,在2016-01—2018-12时间范围内筛选选取了共43景无云的Sentinel-2影像,利用本文提出的算法对雄安新区、神东矿区、永城矿区3个区域的细小水体分布开展了多时相分析。观察后发现每个时相的结果均十分良好,细小水体的边界区分度较高,基本没有错提、漏提,算法具有良好的适用性和稳定性。
文摘We analyzed the characteristics of subway station environment and the change of thermal comfort for passengers when they are in and out of the station. The dynamic thermal comfort evaluation model RWI(relative warmth index) and HDR(heat deficit rate) were built on the distinguishing features of public area in subway station. Taking one representative subway station in Nanjing as the research object, the thermal comfort conditions in different seasons and different parts were studied by field tests, questionnaires and model-evaluating. The calculated RWI shows that although the thermal comfort in Nanjing metro is relatively acceptable, ideal thermal comfort has not been achieved. And it is found that associated with predicted mean vote(PMV), using RWI can evaluate the thermal comfort more precisely.
