npj Sustainable Mobility and Transport最新文献

{"title":"Scalability challenges of machine learning models for estimating walking and cycling volumes in large networks","authors":"Meead Saberi, Tanapon Lilasathapornkit","doi":"10.1038/s44333-024-00009-1","DOIUrl":"10.1038/s44333-024-00009-1","url":null,"abstract":"This study explores the scalability of machine learning models for estimating walking and cycling volumes across the extensive New South Wales (NSW) Six Cities Region in Australia using mobile phone and crowdsourced data. Previous research has focused on localized applications, missing the complexities of larger networks. The research addresses this gap by identifying unique challenges such as the scarcity and representativeness of observed count data, gaps in the crowdsourced and mobile phone data, and inconsistencies in link-level volume estimates. We propose and demonstrate the application of strategies like enhancing geographical diversity of observed count data and employing an extensive cross-validation approach in model training and testing. By leveraging various auxiliary datasets, the study demonstrates the effectiveness of these strategies in improving model performance. These findings provide valuable insights for transportation modelers, policymakers, and urban planners, offering a robust framework for supporting sustainable transportation infrastructure and policies with advanced data-driven methodologies.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-16"},"PeriodicalIF":0.0,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00009-1.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142360077","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":"Vehicle-to-grid response to a frequency contingency in a national grid","authors":"Bjorn C. P. Sturmberg, Lahiru Hapuarachchi, Laura Jones, Kathryn Lucas-Healey, Justus van Biljon","doi":"10.1038/s44333-024-00010-8","DOIUrl":"10.1038/s44333-024-00010-8","url":null,"abstract":"Vehicle-to-grid technology enables electric vehicles to contribute their large, high-power batteries to power systems reserves. Here we report the first demonstration of a fleet of vehicles discharging to support system security after a frequency contingency in a national grid. Our results highlight the potential of vehicle-to-grid, with vehicles discharging within 6 s of the contingency event, and shortcomings, with vehicles recommencing charging before the power system had fully recovered.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00010-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142329431","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":"Hyper pooling private trips into high occupancy transit like attractive shared rides","authors":"Rafał Kucharski, Oded Cats","doi":"10.1038/s44333-024-00006-4","DOIUrl":"10.1038/s44333-024-00006-4","url":null,"abstract":"The size of the solution space associated with the trip-matching problem has made the search for high-order ride-pooling prohibitive. We introduce hyper-pooled rides along with a method to identify them within urban demand patterns. Travellers of hyper-pooled rides walk to common pick-up points, travel with a shared vehicle along a sequence of stops and are dropped off at stops from which they walk to their destinations. While closely resembling classical mass transit, hyper-pooled rides are purely demand-driven, with itineraries (stop locations, sequences, timings) optimised for all co-travellers. For 2000 trips in Amsterdam the algorithm generated 40 hyper-pooled rides transporting 225 travellers. They would require 52.5 vehicle hours to travel solo, whereas in the hyper-pooled multi-stop rides, it is reduced sixfold to 9 vehicle hours only. This efficiency gain is made possible by achieving an average occupancy of 5.8 (and a maximum of 14) while remaining attractive for all co-travellers.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-14"},"PeriodicalIF":0.0,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00006-4.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142174391","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":"Transport within earth system boundaries","authors":"Joyeeta Gupta, Yang Chen, Crelis Rammelt","doi":"10.1038/s44333-024-00005-5","DOIUrl":"10.1038/s44333-024-00005-5","url":null,"abstract":"Achieving a socially and environmentally sustainable mobility and transport system necessitates a multifaceted approach that considers just Earth System Boundaries. Just Earth System Boundaries are domain-specific (e.g. climate change, water) thresholds beyond which significant harm is done to people and other species. We have crossed these thresholds in 7/8 domains and not yet met the minimum needs of people worldwide. The challenge is to return to the safe and just corridor while prioritising the access of the poorest people to minimum resources as called for by the principle of leaving no one behind. Within this context, the transport sector, a major contributor to climate change and environmental pollution, requires significant and swift transformations. This comment proposes six key principles for building a sustainable transport system: prioritising equitable access, enhancing public transport and limiting private transport, decarbonising fuel and fleets, decoupling freight transport from fossil fuel trade, repurposing infrastructure, and ensuring just financing. These principles may enable just living within just Earth System Boundaries.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2024-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00005-5.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141597205","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":"Optimization of electric charging infrastructure: integrated model for routing and charging coordination with power-aware operations","authors":"Hamid R. Sayarshad","doi":"10.1038/s44333-024-00004-6","DOIUrl":"10.1038/s44333-024-00004-6","url":null,"abstract":"With the increasing adoption of electric vehicles (EVs), optimizing charging operations has become imperative to ensure efficient and sustainable mobility. This study proposes an optimization model for the charging and routing of electric vehicles between Origin-Destination (OD) demands. The objective is to develop an efficient and reliable charging plan that ensures the successful completion of trips while considering the limited range and charging requirements of electric vehicles. This paper presents an integrated model for optimizing electric vehicle (EV) charging operations, considering additional factors of setup time, charging time, bidding price estimation, and power availability from three sources: the electricity grid, solar energy, and wind energy. One crucial aspect addressed by the model is the estimation of bidding prices for both day-ahead and intra-day electricity markets. The model also considers the total power availability from the electricity grid, solar energy, and wind energy. The alignment of charging operations with the capacity of the grid and prevailing bidding prices is essential.This ensures that the charging process is optimized and can effectively adapt to the available grid capacity and market conditions. The utilization of renewable energies led to a 42% decrease in the electricity storage capacity available in batteries at charging stations. Furthermore, this integration leads to a substantial cost reduction of approximately 69% compared to scenarios where renewable energy is not utilized. Hence, the proposed model can design renewable energy systems based on the required electricity capacity at charging stations. These findings highlight the compelling financial advantages associated with the adoption of sustainable power sources.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-24"},"PeriodicalIF":0.0,"publicationDate":"2024-06-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00004-6.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141489071","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":"Planning to fail? How science can respond to reduced climate mitigation ambition","authors":"Greg Marsden, Tim Schwanen","doi":"10.1038/s44333-024-00002-8","DOIUrl":"10.1038/s44333-024-00002-8","url":null,"abstract":"The prospect of remaining within 1.5C of planetary warming relies on developed economies tracking increasingly steep and challenging emission reduction pathways. This paper explores how the UK is now proactively planning to miss its targets, using the surface transport sector as a critical case. It discusses how the research–policy interface might both challenge downgraded ambition and provide more actionable routes forward.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00002-8.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141079012","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":"Reduced travel emissions through a carbon calculator with accessible environmental data: a case study in Madison, Wisconsin","authors":"Erin E. Bulson, Wissam Kontar, Soyoung Ahn, Andrea Hicks","doi":"10.1038/s44333-024-00003-7","DOIUrl":"10.1038/s44333-024-00003-7","url":null,"abstract":"The echoing environmental toll of the transportation system calls for a drastic need to move beyond carbon-intensive modes of transportation into more sustainable ones. With the rise of emerging modes of transportation, this transition is more promising than ever. In this work, we take a travel-centric approach to promoting and accelerating the transition away from carbon-intensive modes of transportation by informing travelers about their emissions. A carbon calculator—as a function of trip distance and Well-to-Wheel (WTW) Life Cycle Assessment (LCA)—was developed and embedded on a website platform. Users would input their trip distance, and the calculator outputs the carbon footprint (CO2e) of the trip if it was to be done through seven different modes: car (gasoline), car (hybrid), car (electric), bus, electric bike, bike, and walking. In addition, the calculator outputs the equivalent of CO2e as cheeseburgers for a more intuitive display. The overall goal of this work is to understand how travelers respond to being exposed to carbon footprint information. This serves as a step forward in realizing a sustainable transportation system. We make available the calculator online through this link . Study results indicated that trip distance, environmental awareness, age, income, and mode of transportation used were the most influential features in predicting modal shifts. Importantly, the majority of modal shifts resulted in reduced CO2e emissions.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-9"},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00003-7.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141079014","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":"Calibrated confidence learning for large-scale real-time crash and severity prediction","authors":"Md Rakibul Islam, Dongdong Wang, Mohamed Abdel-Aty","doi":"10.1038/s44333-024-00001-9","DOIUrl":"10.1038/s44333-024-00001-9","url":null,"abstract":"Real-time crash and severity prediction is a complex task, and there is no existing framework to predict crash likelihood and severity together. Creating such a framework poses numerous challenges, particularly not independent and identically distributed (non-IID) data, large model sizes with high computational costs, missing data, sensitivity vs. false alarm rate (FAR) trade-offs, and real-world deployment strategies. This study introduces a novel modeling technique to address these challenges and develops a deployable real-world framework. We used extensive real-time traffic and weather data to develop a crash likelihood prediction modeling prototype, leveraging our preliminary work of spatial ensemble modeling. Next, we equipped this spatial ensemble model with local model regularization to calibrate model confidence training. The investigated regularizations include weight decay, label smoothing and knowledge distillation. Furthermore, post-calibration on model outputs was conducted to improve severity rating identification. We tested the framework to predict crashes and severity in real-time, categorizing crashes into four levels. Results were compared with benchmark models, real-world deployment mechanisms were explained, traffic safety improvement potential and sustainability aspects of the study were discussed. Modeling results demonstrated excellent performance, and fatal, severe, minor and PDO crash severities were predicted with 91.7%, 83.3%, 85.6%, and 87.7% sensitivity, respectively, and with very low FAR. Similarly, the viability of our model to predict different severity levels for specific crash types, i.e., all-crash types, rear-end crashes, and sideswipe/angle crashes, were examined, and it showed excellent performance. Our modeling technique showed great potential for reducing model size, lowering computational costs, improving sensitivity, and, most importantly, reducing FAR. Finally, the deployment strategy for the proposed crash and severity prediction technique is discussed, and its potential to predict crashes with severity levels in real-time will make a substantial contribution to tailoring specific strategies to prevent crashes.","PeriodicalId":501714,"journal":{"name":"npj Sustainable Mobility and Transport","volume":" ","pages":"1-15"},"PeriodicalIF":0.0,"publicationDate":"2024-05-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.nature.com/articles/s44333-024-00001-9.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141079010","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}