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arXiv 2024年

作者： Ji, Junyi Richardson, Alex Gloudemans, Derek Zachár, Gergely Nice, Matthew Barbour, William Sprinkle, Jonathan Piccoli, Benedetto Work, Daniel B. Department of Civil and Environmental Engineering Vanderbilt University United States Institute for Software Integrated Systems Vanderbilt University United States Department of Computer Science Vanderbilt University United States Department of Mathematical Sciences Rutgers University Camden United States

Stop-and-go waves are a fundamental phenomenon in freeway traffic flow, contributing to inefficiencies, crashes, and emissions. Recent advancements in high-fidelity sensor technologies have improved the ability to capture detailed traffic dynamics, yet such systems remain scarce and costly. In contrast, conventional traffic sensors are widely deployed but suffer from relatively coarse-grain data resolution, potentially impeding accurate analysis of stop-and-go waves. This article explores whether generative AI models can enhance the resolution of conventional traffic sensor to approximate the quality of high-fidelity observations. We present a novel approach using a conditional diffusion denoising model, designed to reconstruct fine-grained traffic speed field from radar-based conventional sensors via iterative refinement. We introduce a new dataset, WaveX, comprising 132 hours of data from both low and high-fidelity sensor systems, totaling over 2 million vehicle miles traveled. Our approach leverages this dataset to formulate the traffic measurement refinement problem as a spatio-temporal super-resolution task. We demonstrate that our model can effectively reproduce the patterns of stop-and-go waves, achieving high accuracy in capturing these critical traffic dynamics. Our results show promising advancements in traffic data refinement, offering a cost-effective way to leverage existing low spatio-temporal resolution sensor networks for improved traffic analysis and management. We also open-source our dataset, trained model and code to enable further research and applications. Copyright © 2024, The Authors. All rights reserved.

关键词： Highway administration

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A Systematic Review of Automated BIM Modelling for Existing Buildings from 2D Documentation 38

A Systematic Review of Automated BIM Modelling for Existing ...

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38th International Symposium on Automation and Robotics in Construction, ISARC 2021

作者： Zhang, Cheng Zou, Yang Dimyadi, Johannes Department of Civil and Environmental Engineering University of Auckland Auckland New Zealand School of Computer Science University of Auckland Auckland New Zealand Compliance Audit Systems Ltd Auckland New Zealand

ISBN: (纸本)9789526952413

Building Information Model (BIM) with rich geometric and semantic information of facilities has increasingly been used to establish the City Information Model (CIM). Although BIMs for new buildings are becoming more available, BIMs for most existing buildings can only be modelled from 2D drawings and specifications. Manual BIM modelling is an error-prone and time-consuming process, which becomes more challenging for the city scale. Recently, automating the 3D BIM modelling process for existing buildings from their 2D drawings has been an emerging research trend. To understand the state-of-the-art and guide future research, this paper presents a systematic review of automated BIM modelling for existing buildings from 2D drawings. Fifty-five publications, including 34 journal articles and 21 conference papers identified from Scopus from 1998 to 2021, were reviewed and analysed. A chronological distribution shows that most papers (60%) aimed to generate 3D geometric models, and BIM modelling with semantic information appeared in 2015 and increased dramatically. This review classified the existing work into three aspects: geometric modelling, semantic modelling, and model quality checking. The results show fully automated conversion of 2D drawings to semantically enriched BIM has not been eventuated, future work may consider overcoming the following challenges: (1) height information is either set as default or entered manually, and complex components such as staircases are barely studied;(2) most research only focused on floor plans and ignored semantic information contained in other drawings;(3) drawing errors have not been well addressed, and the validation of the generated model is still cumbersome. © 2021 Proceedings of the International Symposium on Automation and Robotics in Construction. All rights reserved.

关键词： Semantics

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Systemic evaluation of spatio-temporal variations in travel time reliability due to a toll road over time

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Urban, Planning and Transport Research 2021年第1期9卷 36-59页

作者： Mathew, Sonu Pulugurtha, Srinivas S. Graduate of Infrastructure & Environmental Systems (INES) Program The University of North Carolina at Charlotte Charlotte NC United States Professor of Civil & Environmental Engineering Department Director of Infrastructure Design Environment & Sustainability (IDEAS) Center The University of North Carolina at Charlotte Charlotte NC United States

This paper evaluates the effectiveness of toll roads in reducing congestion and improving travel time reliability on streets within its vicinity, over time. The data, from the year 2013 to 2017, for the Triangle Expressway in the city of Raleigh, North Carolina was used in the systemic evaluation process. The spatial and temporal variations in the travel time distributions on the toll road, parallel route, and near-vicinity cross-streets (in a 2-mile buffer) were evaluated. The average travel time (ATT), the 95th percentile travel time (or planning time, PT), the buffer time (BT), and the buffer time index (BTI) were computed for each link by the day-of-the-week and the time-of-the-day. Though there was an improvement in travel time after the speed limit change in the year 2014, the travel time reliability got reduced on the Triangle Expressway. Over time, there was a gradual improvement in BT and BTI. The parallel route reliability decreased significantly over time, whereas the travel time reliability of cross-streets showed a consistent trend. The stabilization of travel time distributions and the reliability measures in the year 2017 indicate that further reduction in performance measures may not be expected in the next few years on the near-vicinity links. © 2020 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.

关键词： buffer time buffer time index road spatial temporal Toll travel time

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Detecting Communities and Attributing Purpose to Human Mobility Data

Detecting Communities and Attributing Purpose to Human Mobil...

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2021 Winter Simulation Conference, WSC 2021

作者： John, Esther Cauthen, Katherine Brown, Nathanael Nozick, Linda Complex Systems for National Security Group Sandia National Laboratories AlbuquerqueNM87123 United States Cornell University Department of Civil Environmental Engineering IthacaNY14853 United States

ISBN: (纸本)9781665433112

Many individuals' mobility can be characterized by strong patterns of regular movements and is influenced by social relationships. Social networks are also often organized into overlapping communities which are associated in time or space. We develop a model that can generate the structure of a social network and attribute purpose to individuals' movements, based solely on records of individuals' locations over time. This model distinguishes the attributed purpose of check-ins based on temporal and spatial patterns in check-in data. Because a location-based social network dataset with authoritative ground-truth to test our entire model does not exist, we generate large scale datasets containing social networks and individual check-in data to test our model. We find that our model reliably assigns community purpose to social check-in data, and is robust over a variety of different situations. © 2021 IEEE.

关键词： Statistical tests

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Measuring Consumer Willingness to Enroll in Battery Electric Vehicle Smart Charging Programs

Measuring Consumer Willingness to Enroll in Battery Electric...

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IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Pingfan Hu Brian Tarroja Matthew Dean Kate Forrest Eric Hittinger Alan Jenn John Paul Helveston Department of Engineering Management and Systems Engineering George Washington University Washington DC USA Department of Civil and Environmental Engineering University of California Irvine Irvine CA USA Advanced Power and Energy Program University of California Irvine Irvine CA USA Department of Public Policy Rochester Institute of Technology Rochester NY USA Institute of Transportation Studies University of California Davis Davis CA USA

ISBN: (数字)9798331541606

ISBN: (纸本)9798331541613

As Battery Electric Vehicles (BEVs) gain popularity, managing their charging becomes crucial for grid stability. Smart charging programs can help utilities manage this demand and integrate more renewable energy by controlling when and how BEVs are charged. However, these programs require participation from BEV owners, who may be hesitant to freely provide such control. This study uses a discrete choice experiment (also called conjoint analysis) to measure BEV owners' willingness to participate in smart charging programs under various incentives and features. We examine two types of smart charging: Supplier-Managed Charging (SMC), which controls charging times, and Vehicle-to-Grid (V2G), allowing BEVs to return power to the grid. In an online survey conducted via Facebook and Instagram ads, we collected 858 valid responses, with 815 responses for SMC program choices and 414 for V2G program choices. We used mixed logit (MXL) models to quantify respondents' willingness to participate. The findings indicate a general reluctance to participate in both programs without some form of incentive, with respondents being most sensitive to recurring monetary incentives. For SMC, there is also concern about ensuring sufficient battery levels in the mornings. Simulations were conducted to predict enrollment rates based on different program features. Additional data will be collected to refine the models in the coming months.

关键词： Surveys Vehicle-to-grid Renewable energy sources Analytical models Power system stability Data models Stability analysis Batteries Web sites Smart charging

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A Physics-Guided Deep Learning Approach to Modeling Nonlinear Dynamics: A Case Study of a Bouc-Wen System 13

A Physics-Guided Deep Learning Approach to Modeling Nonlinea...

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13th International Workshop on Structural Health Monitoring: Enabling Next-Generation SHM for Cyber-Physical systems, IWSHM 2021

作者： Liu, Wei Lai, Zhilu Chatzi, Eleni Structural Mechanics and Monitoring Department of Civil Environmental and Geomatic Engineering ETH-Zürich Zürich8093 Switzerland Future Resilient Systems Singapore-ETH Centre Singapore138602 Singapore

ISBN: (纸本)9781605956879

In this paper, we study the feasibility of applying the recently proposed Physics-guided Deep Markov Model (PgDMM) [1] for the modeling of hysteretic systems. PgDMM forms a hybrid probabilistic physics-guided framework, bridging physics-based state space models with Deep Markov Models, thus delivering a hybrid modeling framework for unsupervised learning and identification of nonlinear dynamical systems. Previously, the framework has been tested on nonlinear elastic systems while in this work, we further test the framework on hysteretic systems described by Bouc-Wen type hysteresis. A physics-based model is used, which partially models the system’s dynamics, which is implemented by a learning-based term parameterized by a neural network. Our results indicate that the physics-based model essentially enforces a more structured and physically interpretable latent space, which is essential for generalization and prediction capabilities. © 2021 Structural Health Monitoring 2021: Enabling Next-Generation SHM for Cyber-Physical systems - Proceedings of the 13th International Workshop on Structural Health Monitoring, IWSHM 2021. All rights reserved.

关键词： Hysteresis

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Microplastic removal and management strategies for wastewater treatment plants

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Chemosphere 2024年 347卷 140648页

作者： Ahmed, Shams Forruque Islam, Nafisa Tasannum, Nuzaba Mehjabin, Aanushka Momtahin, Adiba Chowdhury, Ashfaque Ahmed Almomani, Fares Mofijur, M. Science and Math Program Asian University for Women Chattogram4000 Bangladesh School of Engineering and Technology Central Queensland University RockhamptonQLD4702 Australia Centre for Intelligent Systems Clean Energy Academy Central Queensland University RockhamptonQLD4702 Australia Department of Chemical Engineering Collage of Engineering Qatar University Qatar Centre for Technology in Water and Wastewater School of Civil and Environmental Engineering University of Technology Sydney UltimoNSW2007 Australia School of Biological Sciences Georgia Institute of Technology AtlantaGA30332 United States

Discharging microplastics into the environment with treated wastewater is becoming a major concern around the world. Wastewater treatment plants (WWTPs) release microplastics into terrestrial and aquatic habitats, mostly from textile, laundry, and cosmetic industries. Despite extensive research on microplastics in the environment, their removal, and WWTP management strategies, highlighting their environmental effects, little is known about microplastics' fate and behaviour during various treatment processes. Microplastics interact with treatment technologies differently due to their diverse physical and chemical characteristics, resulting in varying removal efficiency. Microplastics removed from WWTPs may accumulate in soil and harm terrestrial ecosystems. Few studies have examined the cost, energy use, and trade-offs of large-scale implementation of modern treatment methods for the removal of microplastics. To safeguard aquatic and terrestrial habitats from microplastics' contamination, focused and efficient management techniques must bridge these knowledge gaps. This review summarizes microplastic detection, collection, removal and management strategies. A compilation of treatment process studies on microplastics’ removal efficiency and their destiny and transit paths shows recent improvement. Bioremediation, membrane bioreactor (MBR), electrocoagulation, sol-gel technique, flotation, enhanced filtering, and AOPs are evaluated for microplastic removal. The fate and behaviour of microplastics in WWTPs suggest they may be secondary suppliers of microplastics to receiving ecosystems. Innovative microplastic removal strategies and technologies such as nanoparticles, microorganism-based remediation, and tertiary treatment raise issues. These new WWTP technologies are examined for feasibility, limitations, and implementation issues. Pretreatment modifies microplastic size, adsorption potential, and surface morphology to remove microplastics from WWTPs. Membrane bioreact

关键词： Wastewater treatment

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Dynamic Capacity Estimation of Mixed Traffic Flows with Application in Adaptive Traffic Signal Control

SSRN

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SSRN 2022年

作者： Du, Yu Kouvelas, Anastasios ShangGuan, Wei Makridis, Michail A. School of Electronic and Information Engineering Beijing Jiaotong University Beijing China Institute for Transport Planning and Systems Department of Civil Environmental and Geomatic Engineering ETH Zurich ZurichCH-8093 Switzerland

Intersection control plays a vital role in influencing transportation efficiency inside urban areas. Connected and Automated Vehicle (CAV) technology enables frequent traffic information sharing through vehicular networks, which emerges as a promising way to reduce vehicle travelling time and improve intersection capacity. Meanwhile, with the gradual deployment of CAVs, the traditional traffic flow consisting of human driven vehicles will evolve into a mixed traffic flow composed of traffic participants with differing intelligence capabilities. Considering the evolution towards the mixed traffic environment, we propose a dynamic capacity-aware traffic signal control method: max-pressure for mixed traffic flow (MPMF) traffic signal controller. Firstly, the lane capacity is modeled and approximated based on the saturation flow rate in mixed traffic flow considering the penetration rate of CAVs. Then the dynamic capacity is involved in calculating pressure in the max-pressure method to indicate the importance of a path in mixed traffic flow. A modification strategy for the max-pressure input value is also proposed. An isolated intersection scenario was simulated first to assess the proposed method locally. A multi-intersection network experiment was also conducted to verify the network-level performance of the proposed MPMF method. Comparative results between the proposed MPMF method, the classic max-pressure control, and the existing fixed time control method demonstrate that the MPMF can effectively improve the performance of intersections and be suitable for the multi-intersection road network. © 2022, The Authors. All rights reserved.

关键词： Controllers

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BMG-Q: Localized Bipartite Match Graph Attention Q-Learning for Ride-Pooling Order Dispatch

arXiv

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arXiv 2025年

作者： Hu, Yulong Feng, Siyuan Li, Sen The Department of Civil and Environmental Engineering The Hong Kong University of Science and Technology Hong Kong Intelligent Transportation Thrust Systems Hub The Hong Kong University of Science and Technology Guangzhou China The Department of Logistics and Maritime Studies The Hong Kong Polytechnic University Hong Kong

This paper introduces Localized Bipartite Match Graph Attention Q-Learning (BMG-Q), a novel Multi-Agent Reinforcement Learning (MARL) algorithm framework tailored for ride-pooling order dispatch. BMG-Q advances ride-pooling decision-making process with the localized bipartite match graph underlying the Markov Decision Process, enabling the development of novel Graph Attention Double Deep Q Network (GATDDQN) as the MARL backbone to capture the dynamic interactions among ride-pooling vehicles in fleet. Our approach enriches the state information for each agent with GATDDQN by leveraging a localized bipartite interdependence graph and enables a centralized global coordinator to optimize order matching and agent behavior using Integer Linear Programming (ILP). Enhanced by gradient clipping and localized graph sampling, our GATDDQN improves scalability and robustness. Furthermore, the inclusion of a posterior score function in the ILP captures the online exploration-exploitation trade-off and reduces the potential overestimation bias of agents, thereby elevating the quality of the derived solutions. Through extensive experiments and validation, BMG-Q has demonstrated superior performance in both training and operations for thousands of vehicle agents, outperforming benchmark reinforcement learning frameworks by around 10% in accumulative rewards and showing a significant reduction in overestimation bias by over 50%. Additionally, it maintains robustness amidst task variations and fleet size changes, establishing BMG-Q as an effective, scalable, and robust framework for advancing ride-pooling order dispatch operations. Copyright © 2025, The Authors. All rights reserved.

关键词： Markov processes

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Cyanobacterial Trends in Major California Reservoirs Using Multispectral Satellite Remote Sensing

Cyanobacterial Trends in Major California Reservoirs Using M...

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IEEE International Symposium on Geoscience and Remote Sensing (IGARSS)

作者： Brittany N. Lopez Barreto Erin L. Hestir Christine M. Lee Natasha Stavros Department of Civil & Environmental Engineering Environmental Systems Graduate Group University of California Merced California United States Center for Information Technology Research in the Interest of Society & the Banatao Institute University of California Merced NASA Jet Propulsion Laboratory California Institute of Technology Pasadena CA United States Ball Aerospace & Technologies Corp Civil Space Boulder CO United States

ISBN: (数字)9798350360325

ISBN: (纸本)9798350360332

Climate change is projected to reduce raw water quality, posing risks to drinking water even with conventional treatment. This work closely aligns with the United Nation’s 2030 sustainable development goals pertaining to clean water and life below water. We selected six California reservoirs to measure cyanobacteria, which may be harmful if ingested, using CI cyano data provided from the Cyanobacteria Assessment Network. Primary land class, post-fire soil loss erosion, and wildfire frequency were considered to determine if they influence cyanobacterial trends. We found a slight increasing CI cyano trend for all water pixels in the lake and a greater increase when only considering CI cyano pixels and the percentage of the lake covered with CI cyano pixels. Higher soil loss and wildfire frequency did not lead to higher a CI cyano , but land class may have a greater influence. Future work incorporating temperature and drought may help better understand cyanobacteria dynamics.

关键词： Temperature sensors Wildfires Satellites Cyanobacteria Water quality Lakes Soil

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