Although road surface friction is considered the most effective performance measure for maintenance operations, it is not commonly used due to the high cost of collection. As a result, most jurisdictions use subjective visual indicators that qualitatively describe the state of the road surface, even though they create measurement inconsistencies and offer less detailed maintenance tracking. For maintenance personnel to transition into using friction, the collection cost must be reduced. This paper attempts to do so by proposing a low-cost, machine-learning-based method for predicting road surface friction using dash camera imagery and demonstrates its feasibility through a case study. The dataset used for this project was collected in the City of Edmonton, Alberta, during its 2021/2022 winter season. Three models were developed using tree-based algorithms, where all three displayed high performance with an average RMSE of 0.0796 or 79.3% accuracy based on RMSPE.
{"title":"Developing Machine Learning-based Approach for Predicting Road Surface Frictions using Dashcam Images – A City of Edmonton, Canada, Case Study","authors":"Qian Xie, T. Kwon","doi":"10.1139/cjce-2023-0015","DOIUrl":"https://doi.org/10.1139/cjce-2023-0015","url":null,"abstract":"Although road surface friction is considered the most effective performance measure for maintenance operations, it is not commonly used due to the high cost of collection. As a result, most jurisdictions use subjective visual indicators that qualitatively describe the state of the road surface, even though they create measurement inconsistencies and offer less detailed maintenance tracking. For maintenance personnel to transition into using friction, the collection cost must be reduced. This paper attempts to do so by proposing a low-cost, machine-learning-based method for predicting road surface friction using dash camera imagery and demonstrates its feasibility through a case study. The dataset used for this project was collected in the City of Edmonton, Alberta, during its 2021/2022 winter season. Three models were developed using tree-based algorithms, where all three displayed high performance with an average RMSE of 0.0796 or 79.3% accuracy based on RMSPE.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"74 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87813059","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
With the application of machine learning rapidly gaining popularity in computer science and other fields, neural network techniques have successfully simulated the performance of in-service pavements as they are efficient in predicting and solving nonlinear relationships and in dealing with uncertain large-area pavement problems. In this paper, we address the problem of the optimal timing of preventive maintenance of asphalt pavements to accurately predict the condition index (pavement condition index, PCI) of highway asphalt pavements and develop a highly accurate, long-period, multifactor prediction model with the suitability of preventive maintenance at its core. The prediction model is called differential evolution particle swarm optimization back propagation (DEPSO-BP) neural network, and the input dimension of the prediction model is determined by gray correlation analysis (GCA), and DEPSO is used to improve the search efficiency of BP neural network and the asphalt pavement usage performance with parameter continuity prediction model. Finally, the Qinglan Highway (G22) PCI of Gansu Province, China, is selected for example validation, and the prediction results are compared with those of the four models. The results show that the multifactor prediction model based on DEPSO-BP neural network has good generalization ability. This model is important for improving the economic efficiency of road maintenance, and can be used in the long-cycle process to provide model reference and scientific basis for the subsequent road maintenance budget application and decision-making scheme.
{"title":"Prediction of asphalt pavement performance based on DEPSO-BP neural network","authors":"Rui Tao, Pengfei Ding, Rui Peng, Jiangang Qiao","doi":"10.1139/cjce-2022-0198","DOIUrl":"https://doi.org/10.1139/cjce-2022-0198","url":null,"abstract":"With the application of machine learning rapidly gaining popularity in computer science and other fields, neural network techniques have successfully simulated the performance of in-service pavements as they are efficient in predicting and solving nonlinear relationships and in dealing with uncertain large-area pavement problems. In this paper, we address the problem of the optimal timing of preventive maintenance of asphalt pavements to accurately predict the condition index (pavement condition index, PCI) of highway asphalt pavements and develop a highly accurate, long-period, multifactor prediction model with the suitability of preventive maintenance at its core. The prediction model is called differential evolution particle swarm optimization back propagation (DEPSO-BP) neural network, and the input dimension of the prediction model is determined by gray correlation analysis (GCA), and DEPSO is used to improve the search efficiency of BP neural network and the asphalt pavement usage performance with parameter continuity prediction model. Finally, the Qinglan Highway (G22) PCI of Gansu Province, China, is selected for example validation, and the prediction results are compared with those of the four models. The results show that the multifactor prediction model based on DEPSO-BP neural network has good generalization ability. This model is important for improving the economic efficiency of road maintenance, and can be used in the long-cycle process to provide model reference and scientific basis for the subsequent road maintenance budget application and decision-making scheme.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-05-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81458649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In Qualifications-Based Selection (QBS), consultants are selected according to their competencies rather than price. However, clients are often apprehensive about the subjectivity associated with implementing QBS because non-price criteria are hard to measure. In addition, there is no complete set of all relevant consultant evaluation criteria established. There is also a lack of an automated decision support system for objectively assisting owners in selecting qualified consultants with improved consistency and transparency. In this paper, a comprehensive set of consultant evaluation criteria is identified. Evaluation rules are also established for measuring qualitative criteria, where those rules determine the linguistic performance ratings for the fuzzy TOPSIS model instead of decision-makers, which minimizes subjectivity and increases transparency. The decision support system presented in this paper is flexible, allowing the decision-maker to adjust criteria weights based on the project characteristics and to exclude any non-applicable evaluation rules that may not fit in some projects.
{"title":"Decision support system for selecting engineering consultants using Qualifications-Based Selection (QBS) and fuzzy TOPSIS","authors":"Maram Nomir, A. Hammad","doi":"10.1139/cjce-2022-0076","DOIUrl":"https://doi.org/10.1139/cjce-2022-0076","url":null,"abstract":"In Qualifications-Based Selection (QBS), consultants are selected according to their competencies rather than price. However, clients are often apprehensive about the subjectivity associated with implementing QBS because non-price criteria are hard to measure. In addition, there is no complete set of all relevant consultant evaluation criteria established. There is also a lack of an automated decision support system for objectively assisting owners in selecting qualified consultants with improved consistency and transparency. In this paper, a comprehensive set of consultant evaluation criteria is identified. Evaluation rules are also established for measuring qualitative criteria, where those rules determine the linguistic performance ratings for the fuzzy TOPSIS model instead of decision-makers, which minimizes subjectivity and increases transparency. The decision support system presented in this paper is flexible, allowing the decision-maker to adjust criteria weights based on the project characteristics and to exclude any non-applicable evaluation rules that may not fit in some projects.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"38 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-05-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78056506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In construction, the accurate measurements are important in ensuring the quality of work delivered. Different measuring tools have been developed to help workers conduct accurate measuring. However, they may be subject to manipulation difficulties, such as the need for tap/gesture interaction. This paper proposes a novel eye gaze-aided virtual tape measure framework which provides a hands-free manner for conducting the measurements in construction. This framework consists of three components: data collection for point-of-interest, sensor calibration, and distance calculation. Its effectiveness is tested by measuring the dimensions of 15 common objects in laboratory and onsite environments and achieves the average absolute and relative errors of 2.4 cm and 4.8%. The absolute errors range from 0.3 cm to 7.3 cm. A comparison study is conducted to demonstrate its superior performance over iPhone’s Measure application. The results illustrate the feasibility and potential of using the framework to enable measures for smart construction.
{"title":"An Eye Gaze-Aided Virtual Tape Measure for Smart Construction","authors":"Xin Wang, Wei Han, E. Du, Fei Dai, Zhenhua Zhu","doi":"10.1139/cjce-2023-0056","DOIUrl":"https://doi.org/10.1139/cjce-2023-0056","url":null,"abstract":"In construction, the accurate measurements are important in ensuring the quality of work delivered. Different measuring tools have been developed to help workers conduct accurate measuring. However, they may be subject to manipulation difficulties, such as the need for tap/gesture interaction. This paper proposes a novel eye gaze-aided virtual tape measure framework which provides a hands-free manner for conducting the measurements in construction. This framework consists of three components: data collection for point-of-interest, sensor calibration, and distance calculation. Its effectiveness is tested by measuring the dimensions of 15 common objects in laboratory and onsite environments and achieves the average absolute and relative errors of 2.4 cm and 4.8%. The absolute errors range from 0.3 cm to 7.3 cm. A comparison study is conducted to demonstrate its superior performance over iPhone’s Measure application. The results illustrate the feasibility and potential of using the framework to enable measures for smart construction.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"11 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74326079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The present paper discusses a numerical model study for the simulation of flow characteristics and critical submergence for a laterally placed horizontal circular bottom intake under uniform flow. The proposed model simulates the free surface using the Volume of Fluid (VOF) model to check the vortex formation at critical submergence. A new combined approach using phase volume fraction and swirl-strength-based vortex identification mechanism is used to compute the critical submergence. The swirl strength-based vortex identification mechanism can show the vortex tube in approach flow with swirl generated at the free surface due to the axial flow withdrawal through side bottom intake at critical submergence. The CFD model results were validated using experimental data, which showed a maximum error of less than ±10% in the prediction of the critical submergence. The effect of significant parameters like intake and approach flow Froude number and sill height of intake on the critical submergence is discussed.
{"title":"Numerical Study for the Computation of Critical Submergence for Side Circular Intake under Uniform Flow","authors":"Muhammed Hashid, A. Hussain, Z. Ahmad","doi":"10.1139/cjce-2021-0554","DOIUrl":"https://doi.org/10.1139/cjce-2021-0554","url":null,"abstract":"The present paper discusses a numerical model study for the simulation of flow characteristics and critical submergence for a laterally placed horizontal circular bottom intake under uniform flow. The proposed model simulates the free surface using the Volume of Fluid (VOF) model to check the vortex formation at critical submergence. A new combined approach using phase volume fraction and swirl-strength-based vortex identification mechanism is used to compute the critical submergence. The swirl strength-based vortex identification mechanism can show the vortex tube in approach flow with swirl generated at the free surface due to the axial flow withdrawal through side bottom intake at critical submergence. The CFD model results were validated using experimental data, which showed a maximum error of less than ±10% in the prediction of the critical submergence. The effect of significant parameters like intake and approach flow Froude number and sill height of intake on the critical submergence is discussed.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"43 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87572633","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abdul Basith Siddiqui, Jeff Allen, Sanjana Hossein, A. Weiss
The postsecondary students in the Greater Toronto and Hamilton Area (GTHA) maintain a constant source of demand and ridership for the region's transit infrastructure. With the province investing billions of dollars to meet the transit needs of the residents of the GTHA, a comprehensive analysis establishing the correlation between transit and automobile trips and the factors that influence the trip generation for these modes is warranted. Using data from 2015 and 2019, a cross-sectional study to gain behavioral insights into travel by postsecondary students is performed. Using a bivariate ordered-probit approach, the effect of land-use attributes and socio-demographics on the propensities of making transit and automobile trips is determined, followed by a marginal effects analysis. The results indicate that propensity of making transit and automobile trips decreases if the commute distance to campus is below 5 km, and improvement in transit accessibility can considerably increase the transit trip-making propensity.
{"title":"Modeling Transit and Automobile Trip-Generation Propensities of Postsecondary students in the Greater Toronto and Hamilton Area: A Cross-Sectional Study","authors":"Abdul Basith Siddiqui, Jeff Allen, Sanjana Hossein, A. Weiss","doi":"10.1139/cjce-2022-0445","DOIUrl":"https://doi.org/10.1139/cjce-2022-0445","url":null,"abstract":"The postsecondary students in the Greater Toronto and Hamilton Area (GTHA) maintain a constant source of demand and ridership for the region's transit infrastructure. With the province investing billions of dollars to meet the transit needs of the residents of the GTHA, a comprehensive analysis establishing the correlation between transit and automobile trips and the factors that influence the trip generation for these modes is warranted. Using data from 2015 and 2019, a cross-sectional study to gain behavioral insights into travel by postsecondary students is performed. Using a bivariate ordered-probit approach, the effect of land-use attributes and socio-demographics on the propensities of making transit and automobile trips is determined, followed by a marginal effects analysis. The results indicate that propensity of making transit and automobile trips decreases if the commute distance to campus is below 5 km, and improvement in transit accessibility can considerably increase the transit trip-making propensity.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"17 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85256660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To improve the climate resiliency of existing and new pavements, it is important to carry out pavement designs using continuous climate records at high temporal frequencies. Over the years, significant research efforts have been dedicated to obtain high-quality climatic data for pavement design including the latest adoption of the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The purpose of this study is to assess how MERRA-2 performs when compared to the Canadian Weather Energy and Engineering Datasets (CWEEDS), which provides hourly meteorological data for many parts of the country from various periods. In a first part, climate parameters at nine locations were directly compared to determine the correlation between two datasets. In a second part, long-term performances were simulated for typical flexible pavement to assess the relative impact of each climate scenario. As detailed in this paper, observed differences between MERRA-2 and CWEEDS indicate the need for further improvement of climate data quality and availability for designing resilient pavements in Canada.
{"title":"Comparison between MERRA-2 and CWEEDS for Use in Pavement Mechanistic-Empirical Design in Canada","authors":"M. Shafiee, O. Maadani, Juan Hiedra Cobo","doi":"10.1139/cjce-2022-0384","DOIUrl":"https://doi.org/10.1139/cjce-2022-0384","url":null,"abstract":"To improve the climate resiliency of existing and new pavements, it is important to carry out pavement designs using continuous climate records at high temporal frequencies. Over the years, significant research efforts have been dedicated to obtain high-quality climatic data for pavement design including the latest adoption of the Modern-Era Retrospective analysis for Research and Applications, version 2 (MERRA-2). The purpose of this study is to assess how MERRA-2 performs when compared to the Canadian Weather Energy and Engineering Datasets (CWEEDS), which provides hourly meteorological data for many parts of the country from various periods. In a first part, climate parameters at nine locations were directly compared to determine the correlation between two datasets. In a second part, long-term performances were simulated for typical flexible pavement to assess the relative impact of each climate scenario. As detailed in this paper, observed differences between MERRA-2 and CWEEDS indicate the need for further improvement of climate data quality and availability for designing resilient pavements in Canada.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"62 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80662758","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Forecasting the time development of scour depth at bridge pier foundations is of great significance to mitigate or avoid the potential failure of bridges. Presently, several models have been developed to predict the scour depth at the base of bridge piers in the case of flood events. This study summarizes existing models for the temporal evolution of bridge pier scour and divides these studies into semiempirical models and empirical models, as well as artificial intelligence models. Several experimental data sets collected from previous studies, 665 points in total, are used to develop a new multigene genetic programming (MGGP) model for temporal scour depth at a circular bridge pier. In addition, independent data, 899 points in total, from previous studies and new physical modeling tests are applied to evaluate the behaviours of existing models, as well as the newly developed MGGP model. It is shown that the MGGP model has good prediction capability when compared with existing empirical and mathematical models.
{"title":"A new model developed by multigene genetic programming for the temporal evolution of bridge pier scour","authors":"W. Zhang, C. Rennie, I. Nistor","doi":"10.1139/cjce-2022-0430","DOIUrl":"https://doi.org/10.1139/cjce-2022-0430","url":null,"abstract":"Forecasting the time development of scour depth at bridge pier foundations is of great significance to mitigate or avoid the potential failure of bridges. Presently, several models have been developed to predict the scour depth at the base of bridge piers in the case of flood events. This study summarizes existing models for the temporal evolution of bridge pier scour and divides these studies into semiempirical models and empirical models, as well as artificial intelligence models. Several experimental data sets collected from previous studies, 665 points in total, are used to develop a new multigene genetic programming (MGGP) model for temporal scour depth at a circular bridge pier. In addition, independent data, 899 points in total, from previous studies and new physical modeling tests are applied to evaluate the behaviours of existing models, as well as the newly developed MGGP model. It is shown that the MGGP model has good prediction capability when compared with existing empirical and mathematical models.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"38 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75938862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
By facilitating public buses' movement through traffic signal-controlled intersections, a Transit Signal Priority (TSP) strategy can contribute to the reduction of queuing time at intersections. However, the traditional TSP has a negative impact on non-prioritized movements and other transport modes. This research proposes new TSP strategies that also seek to optimize other performance measure such as the person-delay at an isolated intersection and along a corridor. This research focused on major arterials as well as on minor arterial roads, whereas the majority of the existing studies addressed only the major arterial approach. As part of this research, the bus schedule was also taken into consideration. The proposed method is described in detail and is implemented on an arterial corridor in VISSIM. The study area simulation results indicated that the proposed TSP methods performed better than the conventional TSP.
{"title":"New Signal Priority Strategies to Improve Public Transit Operations in an Urban Corridor","authors":"A. Mazaheri, C. Alecsandru","doi":"10.1139/cjce-2023-0002","DOIUrl":"https://doi.org/10.1139/cjce-2023-0002","url":null,"abstract":"By facilitating public buses' movement through traffic signal-controlled intersections, a Transit Signal Priority (TSP) strategy can contribute to the reduction of queuing time at intersections. However, the traditional TSP has a negative impact on non-prioritized movements and other transport modes. This research proposes new TSP strategies that also seek to optimize other performance measure such as the person-delay at an isolated intersection and along a corridor. This research focused on major arterials as well as on minor arterial roads, whereas the majority of the existing studies addressed only the major arterial approach. As part of this research, the bus schedule was also taken into consideration. The proposed method is described in detail and is implemented on an arterial corridor in VISSIM. The study area simulation results indicated that the proposed TSP methods performed better than the conventional TSP.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"1 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87810206","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Optimizing the inspection route for a bridge network is a paramount factor in reducing inspection duration and cost, particularly for bridges located in a large geographical area. Accordingly, this study presents a Bridge Network Inspection Planning (BNIP) model, which aims to minimize the total inspection cost by reducing traveling distance, accommodation cost, wasted time, and inspection team cost. In this model, a Discrete Event Simulation model was built to estimate the inspection duration for each bridge in the network, whereas Genetic Algorithm (GA) approach was used to optimize the inspection route. Web scraping technique was utilized to develop a geospatial information algorithm dedicated to extracting the actual driving distance between any two points in the inspection route. The model was tested against a real bridge network in the Illinois State, USA. The model provides strong guidance for consultants and authorities in charge of bridges in planning the upcoming inspection activities.
{"title":"Optimizing the Inspection Schedule for Bridge Networks","authors":"S. Abdelkhalek, T. Zayed","doi":"10.1139/cjce-2022-0348","DOIUrl":"https://doi.org/10.1139/cjce-2022-0348","url":null,"abstract":"Optimizing the inspection route for a bridge network is a paramount factor in reducing inspection duration and cost, particularly for bridges located in a large geographical area. Accordingly, this study presents a Bridge Network Inspection Planning (BNIP) model, which aims to minimize the total inspection cost by reducing traveling distance, accommodation cost, wasted time, and inspection team cost. In this model, a Discrete Event Simulation model was built to estimate the inspection duration for each bridge in the network, whereas Genetic Algorithm (GA) approach was used to optimize the inspection route. Web scraping technique was utilized to develop a geospatial information algorithm dedicated to extracting the actual driving distance between any two points in the inspection route. The model was tested against a real bridge network in the Illinois State, USA. The model provides strong guidance for consultants and authorities in charge of bridges in planning the upcoming inspection activities.","PeriodicalId":9414,"journal":{"name":"Canadian Journal of Civil Engineering","volume":"78 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2023-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88587418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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