Pub Date : 2025-05-16DOI: 10.1016/j.treng.2025.100349
Hadi Taghavifar
A new arrangement of the engine is introduced where the cylinder revolves around the hinged structure to let the normal force be exerted on the connecting rod. It is proven that in this case, up to 26.3 % extra force can be obtained compared to a conventional design. In this design, constant maintenance such as lubrication, cooling due to intensive friction, and piston-cylinder sealing is reduced. When the cylinder is hinged, it runs more smoothly, and under the same 1 bar input pressure, the engine speed is 60 rpm more than that of an engine in the conventional configuration. This demonstrates the efficiency of the hinged-cylinder configuration. The consolidated connecting rod/piston assembly in a freely revolving cylindrical duct has a DOF = 2, showing the design's full practical potential. To prove the validity of the proposed power system, the multibody dynamic simulation of assembly is implemented in ADAMS, which again confirms higher force applied to the shaft (Fhinged ≈ 7.5 kN > Ffixed ≈ 1.28 kN).
{"title":"Design and fabrication of a power system with a swinging cylinder: a hinged cylinder-piston layout of pendulum motion","authors":"Hadi Taghavifar","doi":"10.1016/j.treng.2025.100349","DOIUrl":"10.1016/j.treng.2025.100349","url":null,"abstract":"<div><div>A new arrangement of the engine is introduced where the cylinder revolves around the hinged structure to let the normal force be exerted on the connecting rod. It is proven that in this case, up to 26.3 % extra force can be obtained compared to a conventional design. In this design, constant maintenance such as lubrication, cooling due to intensive friction, and piston-cylinder sealing is reduced. When the cylinder is hinged, it runs more smoothly, and under the same 1 bar input pressure, the engine speed is 60 rpm more than that of an engine in the conventional configuration. This demonstrates the efficiency of the hinged-cylinder configuration. The consolidated connecting rod/piston assembly in a freely revolving cylindrical duct has a DOF = 2, showing the design's full practical potential. To prove the validity of the proposed power system, the multibody dynamic simulation of assembly is implemented in ADAMS, which again confirms higher force applied to the shaft (F<sub>hinged</sub> ≈ 7.5 kN > F<sub>fixed</sub> ≈ 1.28 kN).</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100349"},"PeriodicalIF":0.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-16DOI: 10.1016/j.treng.2025.100347
Francesco Piras , Gianfranco Fancello , Antonio Comi
In recent years, e-shopping has gained increasing popularity, with more people gradually shifting from traditional shopping channels to online platforms causing significant impacts on city sustainability due to small, frequent, sprawled, and failed deliveries. In fact, due to the necessity of using sometimes-inefficient delivery trips to deliver products to consumers (such as at their residences), this can have a substantial influence on freight traffic in metropolitan regions. Using data from interviews with 509 respondents carried out in Sardinia (Italy) in 2022, the current study investigates how end consumers’ choices between online and physical (in-store) shopping are related. In doing this, two different econometrics models for simulating online and in-store shopping were constructed: a multivariate ordered probit model to understand which covariates influence the propensity to purchase different kinds of products online and in-store; a binary probit model to identify who is more likely to reduce the number of trips due to e-shopping. From the descriptive statistical analysis, it emerged that a majority of individuals in the sample (62.3 %) reduced their number of physical shopping trips due to e-shopping (substitution effect). The multivariate ordered probit model shows that socio-demographic characteristics, land-use attributes, and psychological variables significantly influence shopping behavior. Specifically, the perception of online shopping accessibility and quality positively correlates with the likelihood of purchasing certain product categories online. Conversely, the perceived importance of touching products and in-store safety positively affects in-store shopping preferences. Additionally, positive correlation terms among online and in-store shopping tendencies for the same product categories suggest that consumers inclined to buy certain items online are also more likely to purchase them in-store. The binary probit model highlights substantial heterogeneity in the likelihood of reducing physical shopping trips. Individuals with more experience shopping online, higher perceptions of online quality, and lower importance placed on touching products are more likely to reduce in-store visits. From a policy perspective, this study emphasizes the need for urban planners and policymakers to integrate consumer shopping behavior into strategies aimed at managing urban mobility, logistics, and last-mile delivery systems.
{"title":"Towards a sustainable urban mobility: comparing online and in-store shopping choices","authors":"Francesco Piras , Gianfranco Fancello , Antonio Comi","doi":"10.1016/j.treng.2025.100347","DOIUrl":"10.1016/j.treng.2025.100347","url":null,"abstract":"<div><div>In recent years, e-shopping has gained increasing popularity, with more people gradually shifting from traditional shopping channels to online platforms causing significant impacts on city sustainability due to small, frequent, sprawled, and failed deliveries. In fact, due to the necessity of using sometimes-inefficient delivery trips to deliver products to consumers (such as at their residences), this can have a substantial influence on freight traffic in metropolitan regions. Using data from interviews with 509 respondents carried out in Sardinia (Italy) in 2022, the current study investigates how end consumers’ choices between online and physical (in-store) shopping are related. In doing this, two different econometrics models for simulating online and in-store shopping were constructed: a multivariate ordered probit model to understand which covariates influence the propensity to purchase different kinds of products online and in-store; a binary probit model to identify who is more likely to reduce the number of trips due to e-shopping. From the descriptive statistical analysis, it emerged that a majority of individuals in the sample (62.3 %) reduced their number of physical shopping trips due to e-shopping (substitution effect). The multivariate ordered probit model shows that socio-demographic characteristics, land-use attributes, and psychological variables significantly influence shopping behavior. Specifically, the perception of online shopping accessibility and quality positively correlates with the likelihood of purchasing certain product categories online. Conversely, the perceived importance of touching products and in-store safety positively affects in-store shopping preferences. Additionally, positive correlation terms among online and in-store shopping tendencies for the same product categories suggest that consumers inclined to buy certain items online are also more likely to purchase them in-store. The binary probit model highlights substantial heterogeneity in the likelihood of reducing physical shopping trips. Individuals with more experience shopping online, higher perceptions of online quality, and lower importance placed on touching products are more likely to reduce in-store visits. From a policy perspective, this study emphasizes the need for urban planners and policymakers to integrate consumer shopping behavior into strategies aimed at managing urban mobility, logistics, and last-mile delivery systems.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100347"},"PeriodicalIF":0.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144123245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-16DOI: 10.1016/j.treng.2025.100350
Toni Simolin , Pertti Järventausta , Mario Paolone
Electric vehicles (EVs) fast-charging is a crucial enabler for the smooth electrification of the private mobility. In the available literature, studies related to fast-charging have been mainly focusing on the optimal sizing/placement and/or operation of the related infrastructure. However, little effort is made to develop methods to model the fast-charging process of EVs with heterogeneous characteristics and where no other information, like ambient temperature and EV specifications, are available. This paper aims to fill this gap by proposing a fast-charging profile model based on the analysis of real-world level 3 charging measurements available open source. The proposed model is compared to existing ones proposed in the literature. The proposed model yields an RMSE of 15.5 kW for charging power and 9.2 min for charging duration modelling, which are both more than 25 % lower than those of existing methods. Consequently, the proposed model can be used by planners and operators requiring the knowledge of accurate EV fast-charging profiles.
{"title":"Analysis and modelling of DC fast-charging profiles of heterogeneous EVs","authors":"Toni Simolin , Pertti Järventausta , Mario Paolone","doi":"10.1016/j.treng.2025.100350","DOIUrl":"10.1016/j.treng.2025.100350","url":null,"abstract":"<div><div>Electric vehicles (EVs) fast-charging is a crucial enabler for the smooth electrification of the private mobility. In the available literature, studies related to fast-charging have been mainly focusing on the optimal sizing/placement and/or operation of the related infrastructure. However, little effort is made to develop methods to model the fast-charging process of EVs with heterogeneous characteristics and where no other information, like ambient temperature and EV specifications, are available. This paper aims to fill this gap by proposing a fast-charging profile model based on the analysis of real-world level 3 charging measurements available open source. The proposed model is compared to existing ones proposed in the literature. The proposed model yields an RMSE of 15.5 kW for charging power and 9.2 min for charging duration modelling, which are both more than 25 % lower than those of existing methods. Consequently, the proposed model can be used by planners and operators requiring the knowledge of accurate EV fast-charging profiles.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100350"},"PeriodicalIF":0.0,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144105280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-14DOI: 10.1016/j.treng.2025.100339
Grégory Andreoli , Amine Ihamouten , Franziska Schmidt , Mai Lan Nguyen , David Souriou , Xavier Dérobert
Time resolution is one of the limiting factors when using Ground Penetrating Radar (GPR) techniques to characterize thin layers in the subsurface, such as the tack coat in pavements. To evaluate this residual bituminous emulsion at the interface between the wearing course and the binder course, we have developed an inverse method based on a hybrid data processing approach that combines machine learning (ML) algorithms with Full-Waveform Inversion (FWI). Adding the dielectric permittivity of the wearing course (extracted via FWI) as a structural a priori input into the SVM/SVR models has demonstrated the strong potential of this methodology on synthetic time domain signals. This research, proposes extending such a methodology through experimental campaigns. To carry out this study, three distinct campaigns have been planned, namely on: Hot-Mix Asphalt (HMA)-controlled slabs manufactured in the laboratory; a controlled full-scale structure using the Gustave Eiffel University fatigue carousel (Nantes, France); and a new, yet-to-be-used, road in France. These experiments serve to validate the performance improvements of various classification and regression SVM/SVR algorithms when adding the dielectric permittivity of the wearing course. Herein will be compared the results of the global approach, without preprocessing raw time domain signals, with the developed hybrid model.
{"title":"Hybrid ML/FWI method using GPR data to evaluate the tack coat characteristics in pavements: Experimental validation","authors":"Grégory Andreoli , Amine Ihamouten , Franziska Schmidt , Mai Lan Nguyen , David Souriou , Xavier Dérobert","doi":"10.1016/j.treng.2025.100339","DOIUrl":"10.1016/j.treng.2025.100339","url":null,"abstract":"<div><div>Time resolution is one of the limiting factors when using Ground Penetrating Radar (GPR) techniques to characterize thin layers in the subsurface, such as the tack coat in pavements. To evaluate this residual bituminous emulsion at the interface between the wearing course and the binder course, we have developed an inverse method based on a hybrid data processing approach that combines machine learning (ML) algorithms with Full-Waveform Inversion (FWI). Adding the dielectric permittivity of the wearing course (extracted via FWI) as a structural <em>a priori</em> input into the SVM/SVR models has demonstrated the strong potential of this methodology on synthetic time domain signals. This research, proposes extending such a methodology through experimental campaigns. To carry out this study, three distinct campaigns have been planned, namely on: Hot-Mix Asphalt (HMA)-controlled slabs manufactured in the laboratory; a controlled full-scale structure using the Gustave Eiffel University fatigue carousel (Nantes, France); and a new, yet-to-be-used, road in France. These experiments serve to validate the performance improvements of various classification and regression SVM/SVR algorithms when adding the dielectric permittivity of the wearing course. Herein will be compared the results of the global approach, without preprocessing raw time domain signals, with the developed hybrid model.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100339"},"PeriodicalIF":0.0,"publicationDate":"2025-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144070049","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hydroplaning is a critical hazard for motorcyclists, often resulting in severe injuries or fatalities, particularly on wet road surfaces and at elevated speeds. This study presents advanced methodologies to evaluate hydroplaning force, aiming to mitigate these risks and optimize motorcycle tire tread patterns. A state-of-the-art hydroplaning testing apparatus was developed to precisely measure tire behavior on wet surfaces under controlled conditions. Comprehensive analyses of various tire tread patterns were conducted to identify key parameters influencing tire-to-ground contact. Leveraging these insights, a refined mathematical model was formulated to predict the tire contact area, achieving a minimal error margin of 5.72 %. This model was integrated into a hydroplaning force equation that accounts for velocity, tire inflation pressure, supporting load, and groove area, demonstrating strong predictive accuracy with a coefficient of determination (R²) of 0.91288 when validated against empirical data. The proposed model provides a robust framework for designing motorcycle tires with enhanced performance and safety on wet road conditions.
{"title":"Optimizing motorcycle tire tread patterns to mitigate hydroplaning: Development and validation of a predictive mathematical model","authors":"Weerachai Chaiworapuek , Ravivat Rugsaj , Chakrit Suvanjumrat","doi":"10.1016/j.treng.2025.100344","DOIUrl":"10.1016/j.treng.2025.100344","url":null,"abstract":"<div><div>Hydroplaning is a critical hazard for motorcyclists, often resulting in severe injuries or fatalities, particularly on wet road surfaces and at elevated speeds. This study presents advanced methodologies to evaluate hydroplaning force, aiming to mitigate these risks and optimize motorcycle tire tread patterns. A state-of-the-art hydroplaning testing apparatus was developed to precisely measure tire behavior on wet surfaces under controlled conditions. Comprehensive analyses of various tire tread patterns were conducted to identify key parameters influencing tire-to-ground contact. Leveraging these insights, a refined mathematical model was formulated to predict the tire contact area, achieving a minimal error margin of 5.72 %. This model was integrated into a hydroplaning force equation that accounts for velocity, tire inflation pressure, supporting load, and groove area, demonstrating strong predictive accuracy with a coefficient of determination (R²) of 0.91288 when validated against empirical data. The proposed model provides a robust framework for designing motorcycle tires with enhanced performance and safety on wet road conditions.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100344"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143950387","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-10DOI: 10.1016/j.treng.2025.100337
Mondira Chakraborty, Sajeeb Saha, Selina Sharmin
Driver scheduling is an integral component of the Intelligent Transportation System (ITS). It improves travel efficiency by reducing traffic bottlenecks, irregularities, and accidents and enhancing passenger safety, and driver quality in public transport systems. The scheduling and maintenance of effective timetables are the biggest challenges in developing nations. Furthermore, competent and skilled drivers are not compensated extra for their work. To solve this problem, we proposed a bus transportation system that included a journey schedule and driver scheduling algorithm. Drivers are ranked based on their skill sets and standards. The schedule incorporates peak-hour passenger volume and schedules a set number of trips and lines. The drivers are selected based on their skills and attributes, encouraging them to improve and follow traffic laws, making the trip safe and secure. Our Quality-Aware Optimal Solution (QAOS) allocates the best drivers to complete journeys following labor rules. An alternative Quality-Aware Greedy Solution (QAGS) can complete the same number of trips in less time with more drivers due to the problem’s NP-hardness. Experimental results from a real-world case study reveal that our approach eliminates bus driver laborers, regulates labor limitations, maintains rest hours, and assigns qualified drivers to trips.
{"title":"Quality-aware bus-driver scheduling for intelligent transportation system","authors":"Mondira Chakraborty, Sajeeb Saha, Selina Sharmin","doi":"10.1016/j.treng.2025.100337","DOIUrl":"10.1016/j.treng.2025.100337","url":null,"abstract":"<div><div>Driver scheduling is an integral component of the Intelligent Transportation System (ITS). It improves travel efficiency by reducing traffic bottlenecks, irregularities, and accidents and enhancing passenger safety, and driver quality in public transport systems. The scheduling and maintenance of effective timetables are the biggest challenges in developing nations. Furthermore, competent and skilled drivers are not compensated extra for their work. To solve this problem, we proposed a bus transportation system that included a journey schedule and driver scheduling algorithm. Drivers are ranked based on their skill sets and standards. The schedule incorporates peak-hour passenger volume and schedules a set number of trips and lines. The drivers are selected based on their skills and attributes, encouraging them to improve and follow traffic laws, making the trip safe and secure. Our Quality-Aware Optimal Solution (QAOS) allocates the best drivers to complete journeys following labor rules. An alternative Quality-Aware Greedy Solution (QAGS) can complete the same number of trips in less time with more drivers due to the problem’s NP-hardness. Experimental results from a real-world case study reveal that our approach eliminates bus driver laborers, regulates labor limitations, maintains rest hours, and assigns qualified drivers to trips.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100337"},"PeriodicalIF":0.0,"publicationDate":"2025-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-09DOI: 10.1016/j.treng.2025.100340
Khalid A. Ghuzlan , Ghazi G. Al-Khateeb , Waleed Zeiada , Alaa Sukkari , Mohammed W. Alani , Helal Ezzat
Asphalt pavements are the backbone of the highways. Research has been conducted to enhance the performance of asphalt binders and mixes. Part of the enhancement is utilizing waste bio-oil and warm mix additives. Sasobit, an organic wax, is used as the WMA additive, and date seed oil (DSO) was added to assess the high- and low-temperature performance. Mechanical tests were conducted to investigate the physical properties, while rheological tests were done to assess the viscoelastic performance. Two percent Sasobit was added to the asphalt binder and mixed with 0.5, 1.5, 2.5, 3.5, 4.5, and 5.5 % DSO. The results show an increased high-temperature performance at 2 % Sasobit + 0.5 % DSO, with a reduced performance with increased DSO content. Contrary to the performance, the viscosity decreases with the increase in DSO. An increase in DSO is favored at low temperatures to decrease thermal cracking.
{"title":"Impact of Sasobit/Bio-oil Combination on The Performance of Asphalt Binders","authors":"Khalid A. Ghuzlan , Ghazi G. Al-Khateeb , Waleed Zeiada , Alaa Sukkari , Mohammed W. Alani , Helal Ezzat","doi":"10.1016/j.treng.2025.100340","DOIUrl":"10.1016/j.treng.2025.100340","url":null,"abstract":"<div><div>Asphalt pavements are the backbone of the highways. Research has been conducted to enhance the performance of asphalt binders and mixes. Part of the enhancement is utilizing waste bio-oil and warm mix additives. Sasobit, an organic wax, is used as the WMA additive, and date seed oil (DSO) was added to assess the high- and low-temperature performance. Mechanical tests were conducted to investigate the physical properties, while rheological tests were done to assess the viscoelastic performance. Two percent Sasobit was added to the asphalt binder and mixed with 0.5, 1.5, 2.5, 3.5, 4.5, and 5.5 % DSO. The results show an increased high-temperature performance at 2 % Sasobit + 0.5 % DSO, with a reduced performance with increased DSO content. Contrary to the performance, the viscosity decreases with the increase in DSO. An increase in DSO is favored at low temperatures to decrease thermal cracking.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100340"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936020","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-09DOI: 10.1016/j.treng.2025.100342
Mahdi Rahimi Nahoujy
Since 2018, the German Federal Highway Research Institute (BASt) has been using a traffic speed deflectometer (TSD) for measurements on network level to assess the structural condition of asphalt pavements. TSD collects a variety of data, such as deflections, temperature and slope values at each measuring point. But for the evaluation of this data, there is no established methodological framework yet. The common methodological approach for falling weight deflectometer (FWD) data uses threshold values for different categories in order to assess the condition of the pavement. But as the load setup and properties of the TSD are different from FWD, the existing FWD- based thresholds are not directly applicable to TSD-based data.
The objective of this study is to develop a new, data-driven approach for the analysis of TSD data in order to find categories for the structural status assessment of flexible pavements. A database with >113,000 data points of TSD measured data is used for K-means clustering slope values and SCI300 values in order to divide the data into different categories relevant for the assessment of the structural condition of pavements.
The resulting threshold values of the categories found showed obvious correlations to the results of mechanistic models. The K-means model is thus a good supplement to mechanistic models and may even support their validation. The results support the practical applicability of the TSD as new measuring device for the pavement management system.
{"title":"Applying a K-means model to TSD data to find categories for the structural assessment of flexible pavements","authors":"Mahdi Rahimi Nahoujy","doi":"10.1016/j.treng.2025.100342","DOIUrl":"10.1016/j.treng.2025.100342","url":null,"abstract":"<div><div>Since 2018, the German Federal Highway Research Institute (BASt) has been using a traffic speed deflectometer (TSD) for measurements on network level to assess the structural condition of asphalt pavements. TSD collects a variety of data, such as deflections, temperature and slope values at each measuring point. But for the evaluation of this data, there is no established methodological framework yet. The common methodological approach for falling weight deflectometer (FWD) data uses threshold values for different categories in order to assess the condition of the pavement. But as the load setup and properties of the TSD are different from FWD, the existing FWD- based thresholds are not directly applicable to TSD-based data.</div><div>The objective of this study is to develop a new, data-driven approach for the analysis of TSD data in order to find categories for the structural status assessment of flexible pavements. A database with >113,000 data points of TSD measured data is used for K-means clustering slope values and SCI300 values in order to divide the data into different categories relevant for the assessment of the structural condition of pavements.</div><div>The resulting threshold values of the categories found showed obvious correlations to the results of mechanistic models. The K-means model is thus a good supplement to mechanistic models and may even support their validation. The results support the practical applicability of the TSD as new measuring device for the pavement management system.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100342"},"PeriodicalIF":0.0,"publicationDate":"2025-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144072622","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-08DOI: 10.1016/j.treng.2025.100343
Angeliki Armeni , Andreas Loizos
Τhe knowledge of the bearing capacity of airfield pavements consists a valuable information for airport authorities in terms of airport asset management. This information can be also used for reporting the load-bearing capacity of airfield pavements according to globally recognized systems, which provide a useful communication code between the involved parties. However, since a detailed technical evaluation for accurately assessing the bearing capacity of an airfield pavement may be not always feasible in practice, reporting through the newly introduced index denoted as (Pavement Classification Rating) PCR becomes a challenging task. On this basis historical data of the existing (Pavement Classification Number) PCN index already available to airport authorities may be also useful. Therefore, the present study aims to investigate the existence of any potential correlation between PCN and PCR that could provide an overview of the modified reported strength expressed through PCR, in order to optimize decision-making procedures. For this reason, the PCN and PCR indices for various flexible and rigid airfield pavement cross-sections are determined according to Federal Aviation Administration (FAA) procedures. The study demonstrates the benefits of developing a model, which can provide a useful tool for airport authorities in order to support decision-making planning optimization in terms of airport asset management.
{"title":"Challenges in estimating airfield pavement strength","authors":"Angeliki Armeni , Andreas Loizos","doi":"10.1016/j.treng.2025.100343","DOIUrl":"10.1016/j.treng.2025.100343","url":null,"abstract":"<div><div>Τhe knowledge of the bearing capacity of airfield pavements consists a valuable information for airport authorities in terms of airport asset management. This information can be also used for reporting the load-bearing capacity of airfield pavements according to globally recognized systems, which provide a useful communication code between the involved parties. However, since a detailed technical evaluation for accurately assessing the bearing capacity of an airfield pavement may be not always feasible in practice, reporting through the newly introduced index denoted as (Pavement Classification Rating) PCR becomes a challenging task. On this basis historical data of the existing (Pavement Classification Number) PCN index already available to airport authorities may be also useful. Therefore, the present study aims to investigate the existence of any potential correlation between PCN and PCR that could provide an overview of the modified reported strength expressed through PCR, in order to optimize decision-making procedures. For this reason, the PCN and PCR indices for various flexible and rigid airfield pavement cross-sections are determined according to Federal Aviation Administration (FAA) procedures. The study demonstrates the benefits of developing a model, which can provide a useful tool for airport authorities in order to support decision-making planning optimization in terms of airport asset management.</div></div>","PeriodicalId":34480,"journal":{"name":"Transportation Engineering","volume":"20 ","pages":"Article 100343"},"PeriodicalIF":0.0,"publicationDate":"2025-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143936021","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-05-03DOI: 10.1016/j.treng.2025.100329
Ngoc An Nguyen, Joerg Schweizer, Federico Rupi
Large-scale, activity-based microscopic transport models provide a powerful framework for analyzing dynamic travel demand and assessing the impact of transportation policies on daily travel behavior. At the core of these models is the generation of travel demand, which necessitates the creation of detailed synthetic populations and daily travel plans associated with personalized activities. These time-dependent travel plans are then integrated into dynamic traffic assignment models to simulate agent-based systems. This paper presents a comprehensive review of existing demand generation models within activity-based frameworks, focusing on various methodologies including constraint-based, utility-based, rule-based, learning-based, and hybrid approaches. A comparative analysis is offered, highlighting their theoretical foundations, data requirements, key outputs, and particularly their applications in large-scale microsimulations. In addition, the paper discusses the possibility of collecting input data for these models, as well as explores innovative approaches capable of modeling daily mobility patterns as sequences of activities linked by trips, offering greater flexibility in capturing dynamic travel behavior. Furthermore,potential research directions are also discussed, including the development of travel models for large-scale scenarios using big data sources and the optimization of their integration with dynamic traffic assignment. These methods hold significant promise for integration into large-scale, microscopic dynamic traffic assignment platforms. This study provides critical insights for researchers and practitioners focused on advancing large-scale microscopic traffic modeling to improve decision-making processes.
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