Transportation Research Procedia最新文献_第5页

Workshop synthesis: Latest improvements and testing of GPS and app-based surveys 研讨会综合：GPS和基于应用程序的测量的最新改进和测试

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-06-05 DOI: 10.1016/j.trpro.2026.04.154

Mathijs de Haas , Zachary Patterson

引用次数: 0

Assessing residential location and commuting preferences 评估居住地点和通勤偏好

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-06-05 DOI: 10.1016/j.trpro.2026.04.171

Viktoriya Kolarova Dr. , Ilka Dubernet Dr. , Simon Hein , Johannes Nießen , Tobias Kuhnimhof (Prof. Dr.)

{"title":"Assessing residential location and commuting preferences","authors":"Viktoriya Kolarova Dr. , Ilka Dubernet Dr. , Simon Hein , Johannes Nießen , Tobias Kuhnimhof (Prof. Dr.)","doi":"10.1016/j.trpro.2026.04.171","DOIUrl":"10.1016/j.trpro.2026.04.171","url":null,"abstract":"<div><div>Understanding the interplay between residential location choices and commuting behavior is crucial for addressing urban mobility and housing policies. This paper introduces a comprehensive survey conducted in Germany, integrating three discrete choice experiments to simultaneously measure preferences for residential locations, commuting distances, and transportation modes. The sample comprises 1,169 employed respondents, recruited through a professional service provider with quotas based on age, gender, and residential location. Experiment 1 focused on residential location preferences without considering commuting characteristics, utilizing a Multiple Discrete-Continuous Extreme Value (MDCEV) model to assess budget allocations for various dwelling attributes. Results indicate that the quality of the residential area holds greater significance than the specific place of residence. Experiments 2 and 3 explored the trade-offs between dwelling characteristics and commuting time, alongside mode choice preferences. These experiments revealed that while dwelling attributes are prioritized over commuting duration, commuting time remains a significant factor in residential decisions. Notably, teleworking scenarios were associated with a reduction in the Value of Travel Time Savings (VTTS) for commuting, highlighting the diminishing burden of travel time for remote workers. The three experiments build progressively from housing preferences to commuting trade-offs and mode choices. Together, they reveal how residential and mobility decisions interact. The findings contribute valuable insights for integrating residential location and travel demand models, emphasizing the impact of teleworking on future commuting patterns. Future work will focus on joint model estimations and further integration into predictive models to inform integrated land-use and transport planning policies.</div></div>","PeriodicalId":101261,"journal":{"name":"Transportation Research Procedia","volume":"97 ","pages":"Pages 338-349"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148154080","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}

引用次数: 0

Data-Driven Machine Learning Models for Predicting CO2 Emission Rates Combustion from Grey Hydrogen and Classification of Traffic Congestion Level for Enhanced Smart Mobility 基于灰氢燃烧预测CO2排放率的数据驱动机器学习模型和增强智能交通的交通拥堵等级分类

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-06-05 DOI: 10.1016/j.trpro.2026.03.016

Zeina Alabido

{"title":"Data-Driven Machine Learning Models for Predicting CO2 Emission Rates Combustion from Grey Hydrogen and Classification of Traffic Congestion Level for Enhanced Smart Mobility","authors":"Zeina Alabido","doi":"10.1016/j.trpro.2026.03.016","DOIUrl":"10.1016/j.trpro.2026.03.016","url":null,"abstract":"<div><div>Smart mobility is a term that refers to how adopting cleaner, safer, and efficient behaviour towards shifting to clean transportation matters to enhance smart mobility. The term refers to using different modes of transportation, or instead of owning a gas-fuelled vehicle, such as ride sharing, public transportation, car-sharing, biking, or even walking. Finding a reasonable solution to monitor the traffic congestion and the emission of carbon resulted from the grey hydrogen, which is nature gas, is the future of eco-friendly technology towards saving the environment. Following this approach, we will get closer to zero emissions, zero accidents, and zero pollution. There are key principles to achieve smart mobility, flexibility of transportation options, efficiency of the travel with minimum disruption, safety, and clean technology. However, many cities are facing problems in roads and streets, which leads to complex traffic congestion, has a negative impact on the environment. Also, high congestion leads to other problems, such as the disruption of road infrastructure, a high rate of potential accidents, and leads to high CO<sub>2</sub> emission resulting from the combustion of grey hydrogen. To mitigate and support this environmental problem, an artificial optimized machine learning approach will be built to predict the levels of CO<sub>2</sub> emissions, and predicting traffic conditions, thereby enabling data-driven strategies for cleaner, smarter, and more efficient mobility systems. In this research, regression models will be employed to detect the CO<sub>2</sub> emission rate. In addition, classification techniques to predict the traffic conditions Geotab (2024).</div></div>","PeriodicalId":101261,"journal":{"name":"Transportation Research Procedia","volume":"96 ","pages":"Pages 119-125"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148154126","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}

引用次数: 0

Improving the Management of Loading Docks using Booking Systems with Digital Twins 利用数码孪生订舱系统改善装货码头的管理

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-07-15 DOI: 10.1016/j.trpro.2026.04.113

Russell G. Thompson, Seyed Sina Mohri, Lele Zhang

引用次数: 0

Innovations in modelling city logistics 城市物流建模创新

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-07-15 DOI: 10.1016/j.trpro.2026.04.098

Eiichi Taniguchi, Russell G. Thompson, Ali G. Qureshi

引用次数: 0

Urban Freight Impact of Restricted Access: A Case Study of Leuven 限制通行对城市货运的影响——以鲁汶为例

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-07-15 DOI: 10.1016/j.trpro.2026.04.127

Zhenhan (Xander) Peng, Johan W. Joubert

引用次数: 0

Delivering by eco-friendly vehicles: an overview 环保车辆运输：概述

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-07-15 DOI: 10.1016/j.trpro.2026.04.106

Antonio Comi, Ippolita Idone

引用次数: 0

From linear elastic to advanced analysis approaches: A critical review of backcalculation methods in pavement engineering 从线弹性到先进的分析方法：路面工程中反计算方法的重要回顾

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1016/j.trpro.2026.07.108

Yazmin Martinez, Yongsung Koh, Erol Tutumluer, Youngdae Kim, Issam I.A. Qamhia, Jeb S. Tingle, Timothy Parson, Rami Chkaiban, Jesse Fritz, Michael J. Harrell

{"title":"From linear elastic to advanced analysis approaches: A critical review of backcalculation methods in pavement engineering","authors":"Yazmin Martinez, Yongsung Koh, Erol Tutumluer, Youngdae Kim, Issam I.A. Qamhia, Jeb S. Tingle, Timothy Parson, Rami Chkaiban, Jesse Fritz, Michael J. Harrell","doi":"10.1016/j.trpro.2026.07.108","DOIUrl":"10.1016/j.trpro.2026.07.108","url":null,"abstract":"<div><div>Backcalculation is a widely used technique in pavement engineering for assessing pavement structural integrity by estimating layer moduli from nondestructive deflection measurements, most commonly gathered with falling weight deflectometers (FWD). Within the Advancing Power Projection through Lines-of-Communication (APPLoC) project, the Joint Evaluation and Design Integrated (JEDI) framework was developed to integrate a state-of-the-art backcalculation algorithm that supports informed pavement evaluation and design decisions. Backcalculation may use linear elastic or more advanced analytical approaches. Linear backcalculation typically includes three components: a forward analysis engine that computes surface deflections for assumed moduli, a convergence mechanism that minimizes discrepancies between measured and predicted deflections, and a search algorithm that identifies the optimal moduli. Reviewed forward analysis methods include finite element modeling, artificial neural networks, layered elastic theory, and deflection basin fitting. Convergence criteria such as root mean square error, absolute error, and hybrid tolerance-based equations were evaluated. Search algorithms such as the downhill simplex method and genetic algorithms were also examined. Although computationally efficient, linear approaches rely on simplifying assumptions, motivating the review of advanced techniques incorporating dynamic loading, viscoelasticity, and nonlinear material behavior.</div></div>","PeriodicalId":101261,"journal":{"name":"Transportation Research Procedia","volume":"99 ","pages":"Pages 707-714"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148806630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Rubber-modified ballasted track systems for noise and vibration mitigation 减小噪声和振动用橡胶改进型有碴轨道系统

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1016/j.trpro.2026.07.123

Stanislav Lenart, Siva Ram Karumanchi, David Garcia Sanchez

引用次数: 0

Laboratory characterisation of biochar-modified bitumen: A combined rheological and spectroscopic approach 生物炭改性沥青的实验室表征：流变学和光谱相结合的方法

Transportation Research Procedia Pub Date : 2026-01-01 Epub Date: 2026-08-25 DOI: 10.1016/j.trpro.2026.07.056

Stavros Kalampokis, Alexis D. Kouvelas, Johannes Mirwald, Georgios Pipintakos, Wim Van den bergh, Ioannis N. Lykakis, Bernhard Hofko, Evangelos Manthos

{"title":"Laboratory characterisation of biochar-modified bitumen: A combined rheological and spectroscopic approach","authors":"Stavros Kalampokis, Alexis D. Kouvelas, Johannes Mirwald, Georgios Pipintakos, Wim Van den bergh, Ioannis N. Lykakis, Bernhard Hofko, Evangelos Manthos","doi":"10.1016/j.trpro.2026.07.056","DOIUrl":"10.1016/j.trpro.2026.07.056","url":null,"abstract":"<div><div>The present study explores the investigation of olive-waste derived biochar as an alternative, bio-based modifier for conventional bitumen. Three bio-modified binders were produced with different biochar contents (5%, 10% and 15% by weight of bitumen) using a 70/100 penetration grade bitumen as the base binder. At the first stage, all four binders underwent a series of evaluations to assess their conventional properties. In addition, the rheological behavior was examined via a Dynamic Shear Rheometer (DSR). The structural impact and the physicochemical properties were analyzed using two spectroscopic methods, Fourier Transform Infrared (FTIR) and Proton Nuclear Magnetic Resonance (<span><span><sup>1</sup></span></span>H-NMR), determining how biochar alters the structure of bitumen at a molecular level. The tests were conducted before and after applying Rolling Thin Film Oven Test (RTFOT) ageing. To further evaluate the effect of biochar on the ageing susceptibility of bitumen, ten different ageing indexes were calculated, two rheological and eight physicochemical. Based on the above studies, three key findings were identified: (a) biochar enhanced the high-temperature performance of bitumen by improving the rutting resistance attributed to biochar’s stiffening effect, (b) biochar contents above 5% led to a decline of fatigue behavior and storage stability and (c) the evaluation of the ageing susceptibility was not decisive across the different ageing metrics, revealing the selectivity in distinguishing between physicochemical and rheological evaluation factors. Consequently, the applicability of the standardized evaluation methods for bio-modified binders requires further investigation.</div></div>","PeriodicalId":101261,"journal":{"name":"Transportation Research Procedia","volume":"99 ","pages":"Pages 282-289"},"PeriodicalIF":0.0,"publicationDate":"2026-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"148806739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0