{"title":"Optimization design of highway route based on deep learning","authors":"Jiankang Zhang","doi":"10.3389/ffutr.2024.1430509","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1430509","url":null,"abstract":"Introduction: In recent years, the total mileage and line density of China’s highways have increased year by year. It is estimated that by 2026, the total mileage of national highways will exceed 5.74 million kilometers. An efficient highway network is crucial for a country’s move towards traffic modernization, economic development, and improvement of people's livelihoods. The highway route is the basic structure of the highway network, determining whether the highway can maximize its economic and traffic effects. Therefore, research on highway route design holds significant engineering value. Highway planning is a complex issue involving a wide range of factors. Especially with the increasing awareness of environmental protection, it is necessary to consider natural problems in addition to technical and economic costs.Methods: This paper first points out the important position of highway route research in highway rules, summarizes the research status at home and abroad, and lists conventional highway planning measures. It then discusses the optimization design based on vehicle running speed and driver comfort, and introduces related theories of deep learning and their applicability to multi-objective optimization problems. Finally, aiming at the problem of highway route planning influenced by many factors, a deep learning strategy based on a multi-objective genetic algorithm is adopted, and its multi-objective optimization model and optimization objective function are presented.Results: The proposed deep learning strategy based on a multi-objective genetic algorithm is a new attempt to combine genetic algorithms with deep learning in highway route planning to solve its multi-objective comprehensive optimization problem. The results indicate that this strategy can determine the best route scheme by optimizing technology while satisfying external constraints, thereby achieving the optimal solution in terms of technology and economy, and improving the overall efficiency and sustainability of the highway.Discussion: This study provides a reference for the application of deep learning and other nonlinear multi-objective optimization research, aiding the research on highway route optimization design. By combining multi-objective genetic algorithms with deep learning, it effectively solves various multi-objective nonlinear problems, providing new methods and tools for highway route planning.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"10 7","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141804363","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}
{"title":"Size distribution of brake wear particulate matter based on a brake dynamometer investigation","authors":"Chongzhi Zhong, Jiaxing Sun, Zishu Liu, Haomiao Niu, Jing Zhang, Xiaoyu Liang, Jiawei Yin, Lin Wu, Jianfei Peng, Qijun Zhang, Hongjun Mao","doi":"10.3389/ffutr.2024.1407660","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1407660","url":null,"abstract":"A brake dynamometer has been modified to accurately study the concentration and size distribution of wear particles in different testing conditions. The test equipment was a charged low-pressure impactor ELPI+ from Dekati, Finland. 29 test conditions were defined based on speed, acceleration and initial brake temperature. Additionally, five different types of brake pads were selected for testing to provide a more comprehensive understanding of the particle size distribution characteristics of brake wear particles. The results showed that the mass of BWPs was unimodal in the range of 0.01–8.11 μm, with peak sizes at 2–5 μm or >8.11 μm, and particles of 0.5–3.0 μm accounted for an average of 49.09% of the total particulate mass, while particles with sizes of 3.0–8.11 μm accounted for an average of 49.72% of the total particulate mass. The number of particles emitted by abrasion had a bimodal distribution, with one in the nucleation mode and the other in the accumulation mode, with peak sizes of <10 nm and 1 μm, respectively; the nucleation mode particles accounted for an average of 60.11% of the total PN10, and the ultrafine particles accounted for an average of 82.15%.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"20 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-06-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141383715","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}
{"title":"Transport research implementation: current issues and lessons learned from Europe and China","authors":"George A. Giannopoulos, Yidong Li","doi":"10.3389/ffutr.2024.1339893","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1339893","url":null,"abstract":"The implementation of the research results is seen as a crucial step in the development of innovation in the transport sector. Moving to such an implementation is not always easy or straightforward. It requires a suitable organizational framework both inside as well as outside research producing entities and a number of other facilitating factors that are usually found within an innovation ecosystem. The paper examines systematically the conditions and prevailing practices for transport research implementation in Europe (the European Union) and China and draws useful insights as to the factors that influence such implementation, the incentives, and other facilitating provisions that the research funding organizations can take. It also analyses the current practice and lessons learned for research implementation on the road to innovation production in four major areas of transport research namely: Automated Mobility, Intelligent Railways, Shared and Micromobility applications, and Electromobility.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"2 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140654281","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}
{"title":"Nature-based approaches for increasing the use of solar energy in future power systems","authors":"T. Ustun","doi":"10.3389/ffutr.2024.1331782","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1331782","url":null,"abstract":"Problems of energy systems solved by the nature.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"38 8","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140663087","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}
Samuel David Marshall, Karl Snape, David Soper, Mark Sterling, Stefanie Gillmeier
{"title":"The aerodynamic performance of a platoon of lorries in close-proximity during an overtaking manoeuvre","authors":"Samuel David Marshall, Karl Snape, David Soper, Mark Sterling, Stefanie Gillmeier","doi":"10.3389/ffutr.2024.1356539","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1356539","url":null,"abstract":"For the first time, this paper examines the aerodynamic forces that arise in a platoon of Heavy Goods Vehicle lorries travelling in close proximity during an overtaking manoeuvre. Through an in-depth programme of wind tunnel experiments it is demonstrated that there is a complex relationship between the drag and side force coefficients, with a possible hysteresis-like behaviour shown. The influence of the overtaken lorry on the overtaking lorry is shown to be key in terms of the aerodynamic-induced forces experienced by the latter. Furthermore, the overtaking lorry is shown to benefit aerodynamically from the overtaken lorry, and this is attributed to the elliptical nature of the Navier-Stokes equations. In addition to examining the forces that arise during overtaking, the variation of the wind-induced forces with respect to yaw on a single lorry is compared to those on a middle lorry in a 3-lorry platoon. The aerodynamic benefits arising from platooning/vehicles travelling in close proximity are again demonstrated, although it is shown that these benefits may only exist over a limited range of yaw angles, raising questions about the real-world application of this approach. This has important implications for platooning in crosswinds and the drag force reduction that is assumed due to platooning.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"153 8‐9","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140698670","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}
Xiaodan Xu, Hung-Chia Yang, Kyungsoo Jeong, William Bui, Srinath Ravulaparthy, Haitam Laarabi, Zachary Needell, C. Spurlock
{"title":"Teaching freight mode choice models new tricks using interpretable machine learning methods","authors":"Xiaodan Xu, Hung-Chia Yang, Kyungsoo Jeong, William Bui, Srinath Ravulaparthy, Haitam Laarabi, Zachary Needell, C. Spurlock","doi":"10.3389/ffutr.2024.1339273","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1339273","url":null,"abstract":"Understanding and forecasting complex freight mode choice behavior under various industry, policy, and technology contexts is essential for freight planning and policymaking. Numerous models have been developed to provide insights into freight mode selection; most use discrete choice models such as multinomial logit (MNL) models. However, logit models often rely on linear specifications of independent variables despite potential nonlinear relationships in the data. A common challenge for researchers is the absence of a heuristic and efficient method to discern and define these complex relationships in logit model specifications. This often results in models that might be deficient in both predictive power and interpretability. To bridge this gap, we develop an MNL model for freight mode choice using the insights from machine learning (ML) models. ML models can better capture the nonlinear nature of many decision-making processes, and recent advances in “explainable AI” have greatly improved their interpretability. We showcase how interpretable ML methods help enhance the performance of MNL models and deepen our understanding of freight mode choice. Specifically, we apply SHapley Additive exPlanations (SHAP) to identify influential features and complex relationships to improve the MNL model’s performance. We evaluate this approach through a case study for Austin, Texas, where SHAP results reveal multiple important nonlinear relationships. Incorporating those relationships into MNL model specifications improves the interpretability and accuracy of the MNL model. Findings from this study can be used to guide freight planning and inform policymakers about how key factors affect freight decision-making.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"19 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140248247","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}
N. Zacharof, S. Doulgeris, A. Zafeiriadis, A. Dimaratos, René van Gijlswijk, Sonsoles Díaz, Zissis Samaras
{"title":"A simulation model of the real-world fuel and energy consumption of light-duty vehicles","authors":"N. Zacharof, S. Doulgeris, A. Zafeiriadis, A. Dimaratos, René van Gijlswijk, Sonsoles Díaz, Zissis Samaras","doi":"10.3389/ffutr.2024.1334651","DOIUrl":"https://doi.org/10.3389/ffutr.2024.1334651","url":null,"abstract":"The European Union has intensified efforts to reduce CO2 emissions from the transport sector, with the target of reducing tailpipe CO2 emissions from light-duty vehicle new registrations by 55% by 2030 and achieving zero emissions by 2035 according to the “Fit for 55” package. To promote fuel and energy consumption awareness among users under real-world conditions the MILE21—LIFE project provided tools such as a self-reporting tool and a find-a-car tool that included the official and representative on-road fuel/energy consumption values. In order to produce representative values, an in-house vehicle longitudinal dynamics simulation model was developed for use in the background of the on-line platform utilizing only a limited amount of inputs. To achieve this, the applied methodology is based on precalculated efficiency values. These values have been produced using vehicle micro-model simulations covering a wide range of operating conditions. The model was validated using measurements from a dedicated testing campaign and performed well for petrol vehicles with an average divergence of −1.1%. However, the model showed a divergence of 9.7% for diesel vehicles, 10.6% for hybrids and 8.7% for plug-in hybrids. The model was also applied to US vehicles and showed a divergence of 1.2% and 10% for city and highway driving, respectively. The application of the developed model presented in this work showed that it is possible to predict real-world fuel and energy consumption with the desired accuracy using a simplified approach with limited input data.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"6 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139959124","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}
{"title":"The Eco Ladder for energy management: a literature review of economic driving and energy management","authors":"Tor-Olav Nævestad, Ingeborg Storesund Hesjevoll","doi":"10.3389/ffutr.2023.1044795","DOIUrl":"https://doi.org/10.3389/ffutr.2023.1044795","url":null,"abstract":"Transport accounts for nearly 25% of man-made emissions of greenhouse gases, and goods transport by road accounts for 45% of the total energy consumption in transport. Measures within goods transport will therefore be a good starting point for reducing greenhouse gas emissions. Existing research shows that trucking companies’ measures to facilitate an economic driving style can achieve between 5% and 10% reduction in fuel consumption. They can probably reduce their energy consumption even more, by focusing on factors additional to driving style. However, existing recipes for such measures (e.g., ISO: 50001) seem to be relatively complicated, resource-intensive, and to a small extent adapted to transport. Previous research shows low implementation of such management systems in trucking companies, because most of them are small (&lt;5 employees), and probably have few resources when it comes to economy, time and expertise. The aim of the study, is therefore to develop a research-based model of how trucking companies can work with economic driving and energy management at the organizational level. The model is based on a systematic review of measures for economic driving and energy management in trucking companies. The model is referred to as the Eco Ladder for energy management, and describes an approach with gradual introduction of specific measures. Companies must start with the measures that are assumed to have the greatest effect, and which are easiest to implement, before moving on to the next level. Based on existing research, we discuss expected effects for economy, emissions, traffic safety and working environment.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135885190","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}
{"title":"A movement and interaction model for cyclists and other non-lane-based road users","authors":"Heather Kaths","doi":"10.3389/ffutr.2023.1183270","DOIUrl":"https://doi.org/10.3389/ffutr.2023.1183270","url":null,"abstract":"Cyclists and other types of road users who do not adhere to lane discipline pose a challenge in microscopic traffic simulation. In most software, the models are adapted to increase the lateral flexibility of road users, either through introducing sub-lanes ( SUMO ) or introducing a continuous lateral axis ( PTV Vissim ). These solutions enable the simulation of some behaviors, such as passing within the same driving lane. However, other behaviors exhibited by these flexible road users, including switching between cycling infrastructure, the roadways, and the sidewalk, riding against the given direction of travel, and selecting unexpected pathways to cross at intersections, remain difficult to simulate. This paper presents a modeling approach for cyclists, users of micro-mobility modes, and other non-lane-based road users. This method uses the concept of guidelines, or desire lines, that represent the intended path of non-lane-based road users. Guidelines are the same in form as the center line of road (sub-)lanes. Instead of following these lines precisely, the guideline is used to determine the desired direction for the road user in the next time step, which is used as input into an adapted social force type model. The movement and interaction model is formulated based on the NOMAD model for pedestrian dynamics. The single acceleration vector is divided into a speed component and a direction component that are calibrated and validated using trajectory data from cyclists at four signalized intersections in Munich, Germany. Maximum Likelihood Estimation (MLE) is used to estimate the model parameters and k-fold cross-validation is used to evaluate the modeling approach. The results are discussed and an outlook for future research is presented.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136014201","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}
{"title":"Sensehacking passenger wellbeing while in the air","authors":"Charles Spence","doi":"10.3389/ffutr.2023.1261045","DOIUrl":"https://doi.org/10.3389/ffutr.2023.1261045","url":null,"abstract":"Air travel has undoubtedly become a more stressful activity for many passengers in recent years, in part as a result of the global Covid pandemic. Consequently, there has been a growing focus on how to optimize the psychological wellbeing of passengers while in the air. This narrative historical review considers how the passenger experience can potentially be hacked through the more intelligent stimulation of the travellers’ senses. In particular, the focus is on promoting passenger comfort, enhancing the provision of healthy food and beverage options/experiences, facilitating relaxation and sleep and, when appropriate, boosting passengers’ arousal/alertness as well (e.g., prior to arrival). A number of concrete suggestions concerning how to sensehack passenger wellbeing at the various stages while in the air are made.","PeriodicalId":491609,"journal":{"name":"Frontiers in future transportation","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135738510","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}