{"title":"Incident indicators for freeway traffic flow models","authors":"Azita Dabiri , 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}
Angelos Ikonomakis , Ulrik Dam Nielsen , Klaus Kähler Holst , Jesper Dietz , Roberto Galeazzi
{"title":"Validation and correction of auto-logged position measurements","authors":"Angelos Ikonomakis , Ulrik Dam Nielsen , Klaus Kähler Holst , Jesper Dietz , 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}
Wenbin Yao , Jinqiang Yu , Ying Yang , Nuo Chen , Sheng Jin , Youwei Hu , Congcong Bai
{"title":"Corrigendum to “Understanding travel behavior adjustment under COVID-19” [Commun. Transport. Res. 2C (2022) 100068]","authors":"Wenbin Yao , Jinqiang Yu , Ying Yang , Nuo Chen , Sheng Jin , Youwei Hu , 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}
Naroa Coretti Sanchez , Iñigo Martinez , Luis Alonso Pastor , Kent Larson
{"title":"On the simulation of shared autonomous micro-mobility","authors":"Naroa Coretti Sanchez , Iñigo Martinez , Luis Alonso Pastor , 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 , Ziling Zeng , Kai Wang , 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}
Xiaohe Li , Yuquan Du , Yanyu Chen , Son Nguyen , Wei Zhang , Alessandro Schönborn , Zhuo Sun
{"title":"Data fusion and machine learning for ship fuel efficiency modeling: Part I – Voyage report data and meteorological data","authors":"Xiaohe Li , Yuquan Du , Yanyu Chen , Son Nguyen , Wei Zhang , Alessandro Schönborn , 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><sup><em>2</em></sup> 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}
Wenbin Yao , Jinqiang Yu , Ying Yang , Nuo Chen , Sheng Jin , Youwei Hu , Congcong Bai
{"title":"Understanding travel behavior adjustment under COVID-19","authors":"Wenbin Yao , Jinqiang Yu , Ying Yang , Nuo Chen , Sheng Jin , Youwei Hu , Congcong Bai","doi":"10.1016/j.commtr.2022.100068","DOIUrl":"10.1016/j.commtr.2022.100068","url":null,"abstract":"<div><p>The outbreak and spreading of the COVID-19 pandemic have had a significant impact on transportation system. By analyzing the impact of the pandemic on the transportation system, the impact of the pandemic on the social economy can be reflected to a certain extent, and the effect of anti-pandemic policy implementation can also be evaluated. In addition, the analysis results are expected to provide support for policy optimization. Currently, most of the relevant studies analyze the impact of the pandemic on the overall transportation system from the macro perspective, while few studies quantitatively analyze the impact of the pandemic on individual spatiotemporal travel behavior. Based on the license plate recognition (LPR) data, this paper analyzes the spatiotemporal travel patterns of travelers in each stage of the pandemic progress, quantifies the change of travelers' spatiotemporal behaviors, and analyzes the adjustment of travelers' behaviors under the influence of the pandemic. There are three different behavior adjustment strategies under the influence of the pandemic, and the behavior adjustment is related to the individual's past travel habits. The paper quantitatively assesses the impact of the COVID-19 pandemic on individual travel behavior. And the method proposed in this paper can be used to quantitatively assess the impact of any long-term emergency on individual micro travel behavior.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100068"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S277242472200018X/pdfft?md5=0417fa2e8dd309b1aa3e9a56e92316f1&pid=1-s2.0-S277242472200018X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84614502","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":"Importance of the reputation of data manager in the acceptance of connected vehicles","authors":"Sailesh Acharya, Michelle Mekker","doi":"10.1016/j.commtr.2022.100053","DOIUrl":"10.1016/j.commtr.2022.100053","url":null,"abstract":"<div><p>With the known evidence that potential connected vehicle (CV) users are worried about sharing data because of the associated data privacy and security issues, this study investigates the importance of the reputation of the data manager (who collects, stores, and owns the data) of CV technology (CVT). Based on a questionnaire survey of 2400 US adults, this study asserts that the data manager's reputation has a significant impact on the public perception of data privacy and security issues in CVT along with overall CV acceptance. The results show that data privacy issues have a more negative impact on CV acceptance than data security issues. In addition, the reputation of a data manager has a bigger role in the eyes of the public in shaping their perception of data privacy in comparison to data security. Based on the results, the public considers data privacy as the responsibility of the data manager to protect their data from unauthorized/illegal third-party access, whereas data security is the technological strength of CVT to protect the data from hacking. Finally, it is recommended that CV stakeholders take actions to improve potential CV users' confidence in the privacy of data shared by disclosing the data management process, data privacy protection efforts, building public trust in the data manager, and introducing/enforcing laws regarding data privacy protection.</p></div>","PeriodicalId":100292,"journal":{"name":"Communications in Transportation Research","volume":"2 ","pages":"Article 100053"},"PeriodicalIF":0.0,"publicationDate":"2022-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2772424722000038/pdfft?md5=be5d54c69489c16f872c7bd19053043c&pid=1-s2.0-S2772424722000038-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76492140","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}