Communications in Transportation Research最新文献

{"title":"Estimating freight production/attraction using nighttime satellite imagery","authors":"Tomoya Kawasaki ,&nbsp;Wataru Nakanishi ,&nbsp;Satoshi Hyodo ,&nbsp;Yusaku Namba ,&nbsp;Hirokazu Mori ,&nbsp;Hirotoshi Kishi","doi":"10.1016/j.commtr.2022.100067","DOIUrl":"10.1016/j.commtr.2022.100067","url":null,"abstract":"<div><p>An appropriate understanding and accurate estimation of zonal freight production (FP) and attraction (FA) volume is one of the most important topics and the initial step in developing the origin and destination (OD) matrix. In general, zonal FP and FA are difficult to be obtained as observed data, particularly in developing countries, owing to the lack of large-scale freight surveys. Thus, several proxy indicators are often used for estimating FP and FA, such as the gross regional product (GRP), population, and the number of establishments. However, these indicators do not often estimate the zonal FP and FA accurately and are even not available readily. The nighttime light intensity (NLI) data that is human-induced light emission data and one of the open alternative data, possibly improves the accuracy of FP and FA estimation. However, few studies have examined the relationship between NLI and FP/FA. Therefore, the objectives of this study are to examine whether NLI can be a significant indicator for estimating zonal FP and FA relative to other socio-economic indicators and to examine the types of NLIs that can accurately estimate the FP and FA through a case study in Japan. As a result of the analysis, NLI data are identified as a significant variable for the estimation of FP and FA among various socio-economic variables. Although some of the indicators related to secondary industries provide higher accuracy, NLI exhibits better estimates than the popular indicators such as GRP and population. In addition, we propose three types of total NLI that multiply the unit NLI by the zonal area and this generates higher accuracy of unit NLI, the average light intensity of all pixels in a zone. We have also found that the use of habitable area for the estimation of total NLI provides the highest accuracy among the four types of NLIs including unit NLI. Through the analysis, NLI data is sufficiently applicable for estimating zonal FP and FA, relative to other important socio-economic indicators, although space transferability should be examined in other study areas. These findings could help estimating FP/FA particularly in countries and regions with limited statistical data available.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100067"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000178/pdfft?md5=01cb2bbce48e372be6791ea26fbbbdd3&pid=1-s2.0-S2772424722000178-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74815008","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}

{"title":"Data and Code Disclosure and Sharing Policy of communications in transportation research","authors":"Kun Gao,&nbsp;Hua Wang,&nbsp;Shuaian Wang,&nbsp;Xiaobo Qu","doi":"10.1016/j.commtr.2022.100055","DOIUrl":"10.1016/j.commtr.2022.100055","url":null,"abstract":"","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100055"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000051/pdfft?md5=953c45597ac1ddc83d35b63f65f70cc6&pid=1-s2.0-S2772424722000051-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76730152","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}

{"title":"Public perception of electric vehicles on reddit over the past decade","authors":"Tao Ruan,&nbsp;Qin Lv","doi":"10.1016/j.commtr.2022.100070","DOIUrl":"10.1016/j.commtr.2022.100070","url":null,"abstract":"<div><p>Understanding public perception of electric vehicles (EVs) is imperative for increasing EV adoption, which can significantly reduce greenhouse gas (GHG) emissions, thereby mitigating climate change and global warming. While most existing research characterizes public perception of EV in the context of surveys, questionnaires, or interviews, our study leverages Reddit online social network (OSN) data to capture EV public perception at a much larger scale. We have collected 3,437,917 Reddit posts (including 274,979 submissions and 3,162,938 comments) between January 2011 and December 2020 relevant to EVs and analyzed them along several axes to understand how EVs are perceived by the public on Reddit through the following research questions: (1) What EV-related topics have been discussed by Reddit users? Whether/how Reddit users’ interest in different topics has changed during 2011–2020? (2) What sentiment do Reddit users hold towards EVs? Whether public sentiment on Reddit has shifted over the past 10 years? (3) Whether/how do various Reddit communities (i.e., subreddits) have different perceptions of EVs? Our analysis evinces the potential of utilizing a large-scale OSN dataset for demonstrating a much wider spectrum of topics that the public is interested in than previous studies show, reveals fringe communities including r/conspiracy have many (controversial) discussions on EVs, especially on the environmental impacts of EVs, and one political community (r/The_Donald) has similar patterns with fringe communities in both sentiment and topic aspects. By answering these research questions, we aim to develop a more comprehensive understanding of the public perception of EVs in the past decade.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100070"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000208/pdfft?md5=4917d781c281d51a65a322658f6d0566&pid=1-s2.0-S2772424722000208-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75034124","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}

{"title":"Erratum to “Investigating the impacts of urban speed limit reduction through microscopic traffic simulation” [Commun. Trans. Res. 1C 100018]","authors":"Mánuel Gressai,&nbsp;Balázs Varga,&nbsp;Tamás Tettamanti,&nbsp;István Varga","doi":"10.1016/j.commtr.2022.100062","DOIUrl":"https://doi.org/10.1016/j.commtr.2022.100062","url":null,"abstract":"","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100062"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000129/pdfft?md5=2a5452d8b0859163abad7ed63f8473f4&pid=1-s2.0-S2772424722000129-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"136849719","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}

{"title":"Incident indicators for freeway traffic flow models","authors":"Azita Dabiri ,&nbsp;Balázs Kulcsár","doi":"10.1016/j.commtr.2022.100060","DOIUrl":"10.1016/j.commtr.2022.100060","url":null,"abstract":"<div><p>Developed in this paper is a traffic flow model parametrised to describe abnormal traffic behaviour. In large traffic networks, the immediate detection and categorisation of traffic incidents/accidents is of capital importance to avoid breakdowns, further accidents. First, this claims for traffic flow models capable to capture abnormal traffic condition like accidents. Second, by means of proper real-time estimation technique, observing accident related parameters, one may even categorize the severity of accidents. Hence, in this paper, we suggest to modify the nominal Aw-Rascle (AR) traffic model by a proper incident related parametrisation. The proposed Incident Traffic Flow (ITF) model is defined by introducing the incident parameters modifying the anticipation and the dynamic speed relaxation terms in the speed equation of the AR model. These modifications are proven to have physical meaning. Furthermore, the characteristic properties of the ITF model is discussed in the paper. A multi stage numerical scheme is suggested to discretise in space and time the resulting non-homogeneous system of PDEs. The resulting systems of ODE is then combined with receding horizon estimation methods to reconstruct the incident parameters. Finally, the viability of the suggested incident parametrisation is validated in a simulation environment.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100060"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000105/pdfft?md5=a02dee56af9a1996d3283c7448702a4f&pid=1-s2.0-S2772424722000105-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77683545","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}

{"title":"Validation and correction of auto-logged position measurements","authors":"Angelos Ikonomakis ,&nbsp;Ulrik Dam Nielsen ,&nbsp;Klaus Kähler Holst ,&nbsp;Jesper Dietz ,&nbsp;Roberto Galeazzi","doi":"10.1016/j.commtr.2022.100051","DOIUrl":"10.1016/j.commtr.2022.100051","url":null,"abstract":"<div><p>Accurate position measurements are extremely valuable in the shipping industry for various reasons such as safety (collision avoidance), security (situational awareness), fuel-saving (weather identification), punctuality (route prediction), etc. Although GNSS (Global Navigation Satellite System) receivers installed on-board the ships are proven to be highly accurate, the data logging process may occasionally be problematic, mainly due to the complexity of the measurements and the decimal precision that is required. Data were collected from 3 years of operations of 228 Maersk Line container vessels and an analysis reveals that there is a substantial amount <span><math><mrow><mo>(</mo><mrow><mo>≈</mo><mn>20</mn><mi>%</mi></mrow><mo>)</mo></mrow></math></span> of historical position measurements sent to shore that does not reflect reality. In the study, the sources of the faulty logged position measurements are categorized and an interpolation methodology is proposed to validate and correct them by using AIS (Automatic Identification System) data.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100051"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000014/pdfft?md5=6d3aa3988bc717887eba0146ccd1c97a&pid=1-s2.0-S2772424722000014-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88898820","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}

{"title":"Corrigendum to “Understanding travel behavior adjustment under COVID-19” [Commun. Transport. Res. 2C (2022) 100068]","authors":"Wenbin Yao ,&nbsp;Jinqiang Yu ,&nbsp;Ying Yang ,&nbsp;Nuo Chen ,&nbsp;Sheng Jin ,&nbsp;Youwei Hu ,&nbsp;Congcong Bai","doi":"10.1016/j.commtr.2022.100082","DOIUrl":"10.1016/j.commtr.2022.100082","url":null,"abstract":"","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100082"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000324/pdfft?md5=b0841fc22aa64e28181f97374b731308&pid=1-s2.0-S2772424722000324-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80629529","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}

{"title":"On the simulation of shared autonomous micro-mobility","authors":"Naroa Coretti Sanchez ,&nbsp;Iñigo Martinez ,&nbsp;Luis Alonso Pastor ,&nbsp;Kent Larson","doi":"10.1016/j.commtr.2022.100065","DOIUrl":"10.1016/j.commtr.2022.100065","url":null,"abstract":"<div><p>Fast urbanization and climate change require innovative systems for an efficient movement of people and goods in cities. As trends towards vehicle-sharing, autonomous vehicles, and the use of micro-mobility systems gain strength, the intersection of these fields appears as an area of great opportunity. Autonomy could potentially bring the convenience of on-demand mobility into already prevalent shared micro-mobility systems (SMMS), increasing their efficiency and incentivizing more people to use active mobility modes. The novelty of introducing autonomous driving technology into SMMS and their inherent complexity requires tools to assess and quantify the potential impact of autonomy on fleet performance and user experience. This paper presents an ad-hoc agent-based simulator for the assessment of the fleet behavior of autonomous SMMS in realistic scenarios, including a rebalancing system based on demand prediction. It also allows comparing its performance to station-based and dockless schemes. The proposed simulation framework is highly configurable and flexible and works with high resolution and precision geospatial data. The results of studies carried out with this simulation tool could provide valuable insights for many stakeholders, including vehicle design engineers, fleet operators, city planners, and governments.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100065"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000154/pdfft?md5=f3e963218e6bbdbc7207565bf6c50b60&pid=1-s2.0-S2772424722000154-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86297401","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}

{"title":"Replacing urban trucks via ground–air cooperation","authors":"Xiaobo Qu ,&nbsp;Ziling Zeng ,&nbsp;Kai Wang ,&nbsp;Shuaian Wang","doi":"10.1016/j.commtr.2022.100080","DOIUrl":"10.1016/j.commtr.2022.100080","url":null,"abstract":"<div><p>The advent of drones is leading to a paradigm shift in courier services, while their large-scale deployment is confined by a limited range. Here, we design a low-cost product that allows drones to drop parcels onto and pick them up from the roofs of moving passenger vehicles. With this, we propose a ground-air cooperation (GAC) based business model for parcel delivery in an urban environment. As per our case study using real-world data in Beijing, the new business model will not only shorten the parcel delivery time by 86.5% with a comparable cost, but also reduce road traffic by 8.6%, leading to an annual social benefit of 6.67 billion USD for Beijing. The proposed model utilizes the currently “wasted or unused” rooftops of passenger vehicles and has the potential to replace most parcel trucks and trailers, thus fundamentally addressing the congestion, noise, pollution, and road wear and tear problems caused by trucks, and bringing in immense social benefit.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100080"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000300/pdfft?md5=11ec5792155a60b1aacf7fb0cb730c2b&pid=1-s2.0-S2772424722000300-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76034606","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}

{"title":"Data fusion and machine learning for ship fuel efficiency modeling: Part I – Voyage report data and meteorological data","authors":"Xiaohe Li ,&nbsp;Yuquan Du ,&nbsp;Yanyu Chen ,&nbsp;Son Nguyen ,&nbsp;Wei Zhang ,&nbsp;Alessandro Schönborn ,&nbsp;Zhuo Sun","doi":"10.1016/j.commtr.2022.100074","DOIUrl":"10.1016/j.commtr.2022.100074","url":null,"abstract":"<div><p>The International Maritime Organization has been promoting energy-efficient operational measures to reduce ships' bunker fuel consumption and the accompanying emissions, including speed optimization, trim optimization, weather routing, and the virtual arrival policy. The theoretical foundation of these measures is a model that can accurately forecast a ship's bunker fuel consumption rate according to its sailing speed, displacement/draft, trim, weather conditions, and sea conditions. Voyage report is an important data source for ship fuel efficiency modeling but its information quality on weather and sea conditions is limited by a snapshotting practice with eye inspection. To overcome this issue, this study develops a solution to fuse voyage report data and publicly accessible meteorological data and constructs nine datasets based on this data fusion solution. Eleven widely-adopted machine learning models were tested over these datasets for eight 8100-TEU to 14,000-TEU containerships from a global shipping company. The best datasets found reveal the benefits of fusing voyage report data and meteorological data, as well as the practically acceptable quality of voyage report data. Extremely randomized trees (ET), AdaBoost (AB), Gradient Tree Boosting (GB) and XGBoost (XG) present the best fit and generalization performances. Their <em>R</em>^<em>2</em> values over the best datasets are all above 0.96 and even reach 0.99 to 1.00 for the training set, and 0.74 to 0.90 for the test set. Their fit errors on daily bunker fuel consumption are usually between 0.5 and 4.0 ton/day. These models have good interpretability in explaining the relative importance of different determinants to a ship's fuel consumption rate.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100074"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000245/pdfft?md5=c42bcfd3fd5eb14aced65e04ac7813c9&pid=1-s2.0-S2772424722000245-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88729940","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}