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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Haizheng Zhang; Ravi Seshadri; A. Arun Prakash; Constantinos Antoniou; +2 Authors

    Simulation-based Dynamic Traffic Assignment models have important applications in real-time traffic management and control. The efficacy of these systems rests on the ability to generate accurate estimates and predictions of traffic states, which necessitates online calibration. A widely used solution approach for online calibration is the Extended Kalman Filter (EKF), which -- although appealing in its flexibility to incorporate any class of parameters and measurements -- poses several challenges with regard to calibration accuracy and scalability, especially in congested situations for large-scale networks. This paper addresses these issues in turn so as to improve the accuracy and efficiency of EKF-based online calibration approaches for large and congested networks. First, the concept of state augmentation is revisited to handle violations of the Markovian assumption typically implicit in online applications of the EKF. Second, a method based on graph-coloring is proposed to operationalize the partitioned finite-difference approach that enhances scalability of the gradient computations. Several synthetic experiments and a real world case study demonstrate that application of the proposed approaches yields improvements in terms of both prediction accuracy and computational performance. The work has applications in real-world deployments of simulation-based dynamic traffic assignment systems. Comment: 26 pages, 15 figures

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    DSpace@MIT
    Article . 2021
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    Transportation Research Part C Emerging Technologies
    Article . 2021 . Peer-reviewed
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    Article . 2021
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      DSpace@MIT
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      Transportation Research Part C Emerging Technologies
      Article . 2021 . Peer-reviewed
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    Authors: Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Shenhao Wang; +1 Authors

    Short-term demand forecasting for on-demand ride-hailing services is one of the fundamental issues in intelligent transportation systems. However, previous travel demand forecasting research predominantly focused on improving prediction accuracy, ignoring fairness issues such as systematic underestimations of travel demand in disadvantaged neighborhoods. This study investigates how to measure, evaluate, and enhance prediction fairness between disadvantaged and privileged communities in spatial-temporal demand forecasting of ride-hailing services. A two-pronged approach is taken to reduce the demand prediction bias. First, we develop a novel deep learning model architecture, named socially aware neural network (SA-Net), to integrate the socio-demographics and ridership information for fair demand prediction through an innovative socially-aware convolution operation. Second, we propose a bias-mitigation regularization method to mitigate the mean percentage prediction error gap between different groups. The experimental results, validated on the real-world Chicago Transportation Network Company (TNC) data, show that the de-biasing SA-Net can achieve better predictive performance in both prediction accuracy and fairness. Specifically, the SA-Net improves prediction accuracy for both the disadvantaged and privileged groups compared with the state-of-the-art models. When coupled with the bias mitigation regularization method, the de-biasing SA-Net effectively bridges the mean percentage prediction error gap between the disadvantaged and privileged groups, and also protects the disadvantaged regions against systematic underestimation of TNC demand. Our proposed de-biasing method can be adopted in many existing short-term travel demand estimation models, and can be utilized for various other spatial-temporal prediction tasks such as crime incidents predictions.

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    IEEE Open Journal of Intelligent Transportation Systems
    Article . 2023 . Peer-reviewed
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    Article . 2023
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    Article . 2023
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      IEEE Open Journal of Intelligent Transportation Systems
      Article . 2023 . Peer-reviewed
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    Authors: Andrej Gajduk; Mirko Todorovski; Juergen Kurths; Ljupco Kocarev;

    Plug-in electric vehicles (PEVs) can serve in discharge mode as distributed energy and power resources operating as vehicle-to-grid (V2G) devices and in charge mode as loads or grid-to-vehicle (G2V) devices. It has been documented that PEVs serving as V2G systems can offer possible backup for renewable power sources, can provide reactive power support, active power regulation, load balancing, peak load shaving,% and current harmonic filtering, can provide ancillary services as frequency control and spinning reserves, can improve grid efficiency, stability, reliability, and generation dispatch, can reduce utility operating costs and can generate revenue. Here we show that PEVs can even improve power grid transient stability, that is, stability when the power grid is subjected to large disturbances, including bus faults, generator and branch tripping, and sudden large load changes. A control strategy that regulates the power output of a fleet of PEVs based on the speed of generator turbines is proposed and tested on the New England 10-unit 39-bus power system. By regulating the power output of the PEVs we show that (1) speed and voltage fluctuations resulting from large disturbances can be significantly reduced up to 5 times, and (2) the critical clearing time can be extended by 20-40%. Overall, the PEVs control strategy makes the power grid more robust. Comment: 15 pages, 4 figures, submitted to New Journal of Physics

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    New Journal of Physics
    Article . 2014 . Peer-reviewed
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    New Journal of Physics
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      New Journal of Physics
      Article . 2014 . Peer-reviewed
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      New Journal of Physics
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: McCauley, James; Liu, Zhi; Panda, Aurojit; Koponen, Teemu; +3 Authors

    Control planes for global carrier networks should be programmable (so that new functionality can be easily introduced) and scalable (so they can handle the numerical scale and geographic scope of these networks). Neither traditional control planes nor new SDN-based control planes meet both of these goals. In this paper, we propose a framework for recursive routing computations that combines the best of SDN (programmability) and traditional networks (scalability through hierarchy) to achieve these two desired properties. Through simulation on graphs of up to 10,000 nodes, we evaluate our design's ability to support a variety of routing and traffic engineering solutions, while incorporating a fast failure recovery mechanism.

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    ACM SIGCOMM Computer Communication Review
    Article . 2016 . Peer-reviewed
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      ACM SIGCOMM Computer Communication Review
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    Authors: Moore, C.; Mills, M.; Arrigo, K.; Berman-Frank, I.; +19 Authors

    Microbial activity is a fundamental component of oceanic nutrient cycles. Photosynthetic microbes, collectively termed phytoplankton, are responsible for the vast majority of primary production in marine waters. The availability of nutrients in the upper ocean frequently limits the activity and abundance of these organisms. Experimental data have revealed two broad regimes of phytoplankton nutrient limitation in the modern upper ocean. Nitrogen availability tends to limit productivity throughout much of the surface low-latitude ocean, where the supply of nutrients from the subsurface is relatively slow. In contrast, iron often limits productivity where subsurface nutrient supply is enhanced, including within the main oceanic upwelling regions of the Southern Ocean and the eastern equatorial Pacific. Phosphorus, vitamins and micronutrients other than iron may also (co-)limit marine phytoplankton. The spatial patterns and importance of co-limitation, however, remain unclear. Variability in the stoichiometries of nutrient supply and biological demand are key determinants of oceanic nutrient limitation. Deciphering the mechanisms that underpin this variability, and the consequences for marine microbes, will be a challenge. But such knowledge will be crucial for accurately predicting the consequences of ongoing anthropogenic perturbations to oceanic nutrient biogeochemistry. © 2013 Macmillan Publishers Limited. All rights reserved.

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    Oskar Bordeaux
    Article . 2013
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    Nature Geoscience
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    Nature Geoscience
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      Nature Geoscience
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    Authors: Jin, Wen-Long;

    In this study, we present a unified framework for modeling network trip flows with general distributions of trip distances, including negative exponential, constant, and regularly sorting trip distances studied in the literature. In addition to tracking the number of active trips as in Vickrey's model, this model also tracks the evolution of the distribution of active trips' remaining distances. We derive four equivalent differential formulations from the network fundamental diagram and the conservation law of trips for the number of active trips with remaining distances not smaller than any value. Then we define and discuss the properties of stationary and gridlock states, derive the integral form of the bathtub model with the characteristic method, obtain equivalent formulations by replacing the time coordinate with the cumulative travel distance, and present two numerical methods to solve the bathtub model based on the differential and integral forms respectively. We further study equivalent formulations and solutions for two special types of distributions of trip distances: time-independent negative exponential or deterministic. In particular, we present six equivalent conditions for Vickrey's bathtub model to be applicable. Finally we demonstrate that the fundamental diagram and the bathtub model can be extended for multi-commodity trip flows with trips served by mobility service vehicles. Comment: 39 pages, 6 figures

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    Transportation Research Part B Methodological
    Article . 2020 . Peer-reviewed
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      Transportation Research Part B Methodological
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    Authors: Ríos Insua, David; Caballero, William N.; Naveiro, Roi;

    Current technologies are unable to produce massively deployable, fully autonomous vehicles that do not require human intervention. Such technological limitations are projected to persist for decades. Therefore, roadway scenarios requiring a driver to regain control of a vehicle, and vice versa, will remain critical to the safe operation of semi-autonomous vehicles for the foreseeable future. Herein, we adopt a comprehensive perspective on this problem taking into account the operational design domain, driver and environment monitoring, trajectory planning, and driver intervention performance assessment. Leveraging decision analysis and Bayesian forecasting, both the support of driving mode management decisions and the issuing of early warnings to the driver are addressed. A statistical modeling framework is created and a suite of algorithms are developed to manage driving modes and issue relevant warnings in accordance with the management by exception principle. The efficacy of these developed methods are then illustrated and examined via a simulated case study.

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    https://doi.org/10.48550/arxiv...
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    Authors: Adham Kalila; Zeyad Awwad; Riccardo Di Clemente; Marta C. González;

    Falling oil revenues and rapid urbanization are putting a strain on the budgets of oil producing nations which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. While fuel consumption models have started to incorporate data sources from ubiquitous sensing devices, the opportunity is to develop comprehensive models at urban scale leveraging sources such as Global Positioning System (GPS) data and Call Detail Records. We combine these big data sets in a novel method to model fuel consumption within a city and estimate how it may change due to different scenarios. To do so we calibrate a fuel consumption model for use on any car fleet fuel economy distribution and apply it in Riyadh, Saudi Arabia. The model proposed, based on speed profiles, is then used to test the effects on fuel consumption of reducing flow, both randomly and by targeting the most fuel inefficient trips in the city. The estimates considerably improve baseline methods based on average speeds, showing the benefits of the information added by the GPS data fusion. The presented method can be adapted to also measure emissions. The results constitute a clear application of data analysis tools to help decision makers compare policies aimed at achieving economic and environmental goals. Comment: 11 pages, 6 figures, TRB conference

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    Transportation Research Record Journal of the Transportation Research Board
    Article . 2018 . Peer-reviewed
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      Transportation Research Record Journal of the Transportation Research Board
      Article . 2018 . Peer-reviewed
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    Authors: Baichuan Mo; Zhejing Cao; Hongmou Zhang; Yu Shen; +1 Authors

    Abstract Emerging autonomous vehicles (AV) can either supplement the public transportation (PT) system or compete with it. This study examines the competitive perspective where both AV and PT operators are profit-oriented with dynamic adjustable supply strategies under five regulatory structures regarding whether the AV operator is allowed to change the fleet size and whether the PT operator is allowed to adjust headway. Four out of the five scenarios are constrained competition while the other one focuses on unconstrained competition to find the Nash Equilibrium. We evaluate the competition process as well as the system performance from the standpoints of four stakeholders—the AV operator, the PT operator, passengers, and the transport authority. We also examine the impact of PT subsidies on the competition results including both demand-based and supply-based subsidies. A heuristic algorithm is proposed to update supply strategies for AV and PT based on the operators’ historical actions and profits. An agent-based simulation model is implemented in the first-mile scenario in Tampines, Singapore. We find that the competition can result in higher profits and higher system efficiency for both operators compared to the status quo. After the supply updates, the PT services are spatially concentrated to shorter routes feeding directly to the subway station and temporally concentrated to peak hours. On average, the competition reduces the travel time of passengers but increases their travel costs. Nonetheless, the generalized travel cost is reduced when incorporating the value of time. With respect to the system efficiency, the bus supply adjustment increases the average vehicle load and reduces the total vehicle kilometers traveled measured by the passenger car equivalent (PCE), while the AV supply adjustment does the opposite. The results suggest that PT should be allowed to optimize its supply strategies under specific operation goals and constraints, and AV operations should be regulated to reduce their system impacts, including potentially limiting the number of licenses, operation time, and service areas, which makes AV operate in a manner more complementary to the PT system. Providing subsidies to PT results in higher PT supply, profit, and market share, lower AV supply, profit, and market share, and increased passenger’s generalized cost and total system PCE.

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    Transportation Research Part C Emerging Technologies
    Article . 2021 . Peer-reviewed
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      Transportation Research Part C Emerging Technologies
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    Authors: Soria, Jason; Stathopoulos, Amanda;

    Transformative mobility services present both considerable opportunities and challenges for urban mobility systems. Increasing attention is being paid to ridehailing platforms and connections between demand and continuous innovation in service features; one of these features is dynamic ride-pooling. To disentangle how ridehailing impacts existing transportation networks and its ability to support economic vitality and community livability it is essential to consider the distribution of demand across diverse communities. In this paper we expand the literature on ridehailing demand by exploring community variation and spatial dependence in ridehailing use. Specifically, we investigate the diffusion and role of solo requests versus ride-pooling to shed light on how different mobility services, with different environmental and accessibility implications, are used by diverse communities. This paper employs a Social Disadvantage Index, Transit Access Analysis, and a Spatial Durbin Model to investigate the influence of both local and spatial spillover effects on the demand for shared and solo ridehailing. The analysis of 127 million ridehailing rides, of which 15% are pooled, confirms the presence of spatial effects. Results indicate that density and vibrancy variables have analogue effects, both direct and indirect, on demand for solo vs pooled rides. Instead, our analysis reveals significant contrasting effects for socio-economic disadvantage, which is positively correlated with ride-pooling and negatively with solo rides. Additionally, we find that higher rail transit access is associated with higher demand for both solo and pooled ridehailing along with substantial spatial spillovers. We discuss implications for policy, operations and research related to the novel insight on how pooled ridesourcing relate to geography, living conditions, and transit interactions. Submitted to journal of Transport Geography

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    Journal of Transport Geography
    Article . 2021 . Peer-reviewed
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      Journal of Transport Geography
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    Authors: Haizheng Zhang; Ravi Seshadri; A. Arun Prakash; Constantinos Antoniou; +2 Authors

    Simulation-based Dynamic Traffic Assignment models have important applications in real-time traffic management and control. The efficacy of these systems rests on the ability to generate accurate estimates and predictions of traffic states, which necessitates online calibration. A widely used solution approach for online calibration is the Extended Kalman Filter (EKF), which -- although appealing in its flexibility to incorporate any class of parameters and measurements -- poses several challenges with regard to calibration accuracy and scalability, especially in congested situations for large-scale networks. This paper addresses these issues in turn so as to improve the accuracy and efficiency of EKF-based online calibration approaches for large and congested networks. First, the concept of state augmentation is revisited to handle violations of the Markovian assumption typically implicit in online applications of the EKF. Second, a method based on graph-coloring is proposed to operationalize the partitioned finite-difference approach that enhances scalability of the gradient computations. Several synthetic experiments and a real world case study demonstrate that application of the proposed approaches yields improvements in terms of both prediction accuracy and computational performance. The work has applications in real-world deployments of simulation-based dynamic traffic assignment systems. Comment: 26 pages, 15 figures

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    Transportation Research Part C Emerging Technologies
    Article . 2021 . Peer-reviewed
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      Transportation Research Part C Emerging Technologies
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    Authors: Yunhan Zheng; Qingyi Wang; Dingyi Zhuang; Shenhao Wang; +1 Authors

    Short-term demand forecasting for on-demand ride-hailing services is one of the fundamental issues in intelligent transportation systems. However, previous travel demand forecasting research predominantly focused on improving prediction accuracy, ignoring fairness issues such as systematic underestimations of travel demand in disadvantaged neighborhoods. This study investigates how to measure, evaluate, and enhance prediction fairness between disadvantaged and privileged communities in spatial-temporal demand forecasting of ride-hailing services. A two-pronged approach is taken to reduce the demand prediction bias. First, we develop a novel deep learning model architecture, named socially aware neural network (SA-Net), to integrate the socio-demographics and ridership information for fair demand prediction through an innovative socially-aware convolution operation. Second, we propose a bias-mitigation regularization method to mitigate the mean percentage prediction error gap between different groups. The experimental results, validated on the real-world Chicago Transportation Network Company (TNC) data, show that the de-biasing SA-Net can achieve better predictive performance in both prediction accuracy and fairness. Specifically, the SA-Net improves prediction accuracy for both the disadvantaged and privileged groups compared with the state-of-the-art models. When coupled with the bias mitigation regularization method, the de-biasing SA-Net effectively bridges the mean percentage prediction error gap between the disadvantaged and privileged groups, and also protects the disadvantaged regions against systematic underestimation of TNC demand. Our proposed de-biasing method can be adopted in many existing short-term travel demand estimation models, and can be utilized for various other spatial-temporal prediction tasks such as crime incidents predictions.

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    IEEE Open Journal of Intelligent Transportation Systems
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    Authors: Andrej Gajduk; Mirko Todorovski; Juergen Kurths; Ljupco Kocarev;

    Plug-in electric vehicles (PEVs) can serve in discharge mode as distributed energy and power resources operating as vehicle-to-grid (V2G) devices and in charge mode as loads or grid-to-vehicle (G2V) devices. It has been documented that PEVs serving as V2G systems can offer possible backup for renewable power sources, can provide reactive power support, active power regulation, load balancing, peak load shaving,% and current harmonic filtering, can provide ancillary services as frequency control and spinning reserves, can improve grid efficiency, stability, reliability, and generation dispatch, can reduce utility operating costs and can generate revenue. Here we show that PEVs can even improve power grid transient stability, that is, stability when the power grid is subjected to large disturbances, including bus faults, generator and branch tripping, and sudden large load changes. A control strategy that regulates the power output of a fleet of PEVs based on the speed of generator turbines is proposed and tested on the New England 10-unit 39-bus power system. By regulating the power output of the PEVs we show that (1) speed and voltage fluctuations resulting from large disturbances can be significantly reduced up to 5 times, and (2) the critical clearing time can be extended by 20-40%. Overall, the PEVs control strategy makes the power grid more robust. Comment: 15 pages, 4 figures, submitted to New Journal of Physics

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    New Journal of Physics
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    Authors: McCauley, James; Liu, Zhi; Panda, Aurojit; Koponen, Teemu; +3 Authors

    Control planes for global carrier networks should be programmable (so that new functionality can be easily introduced) and scalable (so they can handle the numerical scale and geographic scope of these networks). Neither traditional control planes nor new SDN-based control planes meet both of these goals. In this paper, we propose a framework for recursive routing computations that combines the best of SDN (programmability) and traditional networks (scalability through hierarchy) to achieve these two desired properties. Through simulation on graphs of up to 10,000 nodes, we evaluate our design's ability to support a variety of routing and traffic engineering solutions, while incorporating a fast failure recovery mechanism.

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    Authors: Moore, C.; Mills, M.; Arrigo, K.; Berman-Frank, I.; +19 Authors

    Microbial activity is a fundamental component of oceanic nutrient cycles. Photosynthetic microbes, collectively termed phytoplankton, are responsible for the vast majority of primary production in marine waters. The availability of nutrients in the upper ocean frequently limits the activity and abundance of these organisms. Experimental data have revealed two broad regimes of phytoplankton nutrient limitation in the modern upper ocean. Nitrogen availability tends to limit productivity throughout much of the surface low-latitude ocean, where the supply of nutrients from the subsurface is relatively slow. In contrast, iron often limits productivity where subsurface nutrient supply is enhanced, including within the main oceanic upwelling regions of the Southern Ocean and the eastern equatorial Pacific. Phosphorus, vitamins and micronutrients other than iron may also (co-)limit marine phytoplankton. The spatial patterns and importance of co-limitation, however, remain unclear. Variability in the stoichiometries of nutrient supply and biological demand are key determinants of oceanic nutrient limitation. Deciphering the mechanisms that underpin this variability, and the consequences for marine microbes, will be a challenge. But such knowledge will be crucial for accurately predicting the consequences of ongoing anthropogenic perturbations to oceanic nutrient biogeochemistry. © 2013 Macmillan Publishers Limited. All rights reserved.

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    Oskar Bordeaux
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    Nature Geoscience
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      Nature Geoscience
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    Authors: Jin, Wen-Long;

    In this study, we present a unified framework for modeling network trip flows with general distributions of trip distances, including negative exponential, constant, and regularly sorting trip distances studied in the literature. In addition to tracking the number of active trips as in Vickrey's model, this model also tracks the evolution of the distribution of active trips' remaining distances. We derive four equivalent differential formulations from the network fundamental diagram and the conservation law of trips for the number of active trips with remaining distances not smaller than any value. Then we define and discuss the properties of stationary and gridlock states, derive the integral form of the bathtub model with the characteristic method, obtain equivalent formulations by replacing the time coordinate with the cumulative travel distance, and present two numerical methods to solve the bathtub model based on the differential and integral forms respectively. We further study equivalent formulations and solutions for two special types of distributions of trip distances: time-independent negative exponential or deterministic. In particular, we present six equivalent conditions for Vickrey's bathtub model to be applicable. Finally we demonstrate that the fundamental diagram and the bathtub model can be extended for multi-commodity trip flows with trips served by mobility service vehicles. Comment: 39 pages, 6 figures

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    Transportation Research Part B Methodological
    Article . 2020 . Peer-reviewed
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      Transportation Research Part B Methodological
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    Authors: Ríos Insua, David; Caballero, William N.; Naveiro, Roi;

    Current technologies are unable to produce massively deployable, fully autonomous vehicles that do not require human intervention. Such technological limitations are projected to persist for decades. Therefore, roadway scenarios requiring a driver to regain control of a vehicle, and vice versa, will remain critical to the safe operation of semi-autonomous vehicles for the foreseeable future. Herein, we adopt a comprehensive perspective on this problem taking into account the operational design domain, driver and environment monitoring, trajectory planning, and driver intervention performance assessment. Leveraging decision analysis and Bayesian forecasting, both the support of driving mode management decisions and the issuing of early warnings to the driver are addressed. A statistical modeling framework is created and a suite of algorithms are developed to manage driving modes and issue relevant warnings in accordance with the management by exception principle. The efficacy of these developed methods are then illustrated and examined via a simulated case study.

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    https://doi.org/10.48550/arxiv...
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    Authors: Adham Kalila; Zeyad Awwad; Riccardo Di Clemente; Marta C. González;

    Falling oil revenues and rapid urbanization are putting a strain on the budgets of oil producing nations which often subsidize domestic fuel consumption. A direct way to decrease the impact of subsidies is to reduce fuel consumption by reducing congestion and car trips. While fuel consumption models have started to incorporate data sources from ubiquitous sensing devices, the opportunity is to develop comprehensive models at urban scale leveraging sources such as Global Positioning System (GPS) data and Call Detail Records. We combine these big data sets in a novel method to model fuel consumption within a city and estimate how it may change due to different scenarios. To do so we calibrate a fuel consumption model for use on any car fleet fuel economy distribution and apply it in Riyadh, Saudi Arabia. The model proposed, based on speed profiles, is then used to test the effects on fuel consumption of reducing flow, both randomly and by targeting the most fuel inefficient trips in the city. The estimates considerably improve baseline methods based on average speeds, showing the benefits of the information added by the GPS data fusion. The presented method can be adapted to also measure emissions. The results constitute a clear application of data analysis tools to help decision makers compare policies aimed at achieving economic and environmental goals. Comment: 11 pages, 6 figures, TRB conference

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    Transportation Research Record Journal of the Transportation Research Board
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      Transportation Research Record Journal of the Transportation Research Board
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    Authors: Baichuan Mo; Zhejing Cao; Hongmou Zhang; Yu Shen; +1 Authors

    Abstract Emerging autonomous vehicles (AV) can either supplement the public transportation (PT) system or compete with it. This study examines the competitive perspective where both AV and PT operators are profit-oriented with dynamic adjustable supply strategies under five regulatory structures regarding whether the AV operator is allowed to change the fleet size and whether the PT operator is allowed to adjust headway. Four out of the five scenarios are constrained competition while the other one focuses on unconstrained competition to find the Nash Equilibrium. We evaluate the competition process as well as the system performance from the standpoints of four stakeholders—the AV operator, the PT operator, passengers, and the transport authority. We also examine the impact of PT subsidies on the competition results including both demand-based and supply-based subsidies. A heuristic algorithm is proposed to update supply strategies for AV and PT based on the operators’ historical actions and profits. An agent-based simulation model is implemented in the first-mile scenario in Tampines, Singapore. We find that the competition can result in higher profits and higher system efficiency for both operators compared to the status quo. After the supply updates, the PT services are spatially concentrated to shorter routes feeding directly to the subway station and temporally concentrated to peak hours. On average, the competition reduces the travel time of passengers but increases their travel costs. Nonetheless, the generalized travel cost is reduced when incorporating the value of time. With respect to the system efficiency, the bus supply adjustment increases the average vehicle load and reduces the total vehicle kilometers traveled measured by the passenger car equivalent (PCE), while the AV supply adjustment does the opposite. The results suggest that PT should be allowed to optimize its supply strategies under specific operation goals and constraints, and AV operations should be regulated to reduce their system impacts, including potentially limiting the number of licenses, operation time, and service areas, which makes AV operate in a manner more complementary to the PT system. Providing subsidies to PT results in higher PT supply, profit, and market share, lower AV supply, profit, and market share, and increased passenger’s generalized cost and total system PCE.

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    Transportation Research Part C Emerging Technologies
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      Transportation Research Part C Emerging Technologies
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    Authors: Soria, Jason; Stathopoulos, Amanda;

    Transformative mobility services present both considerable opportunities and challenges for urban mobility systems. Increasing attention is being paid to ridehailing platforms and connections between demand and continuous innovation in service features; one of these features is dynamic ride-pooling. To disentangle how ridehailing impacts existing transportation networks and its ability to support economic vitality and community livability it is essential to consider the distribution of demand across diverse communities. In this paper we expand the literature on ridehailing demand by exploring community variation and spatial dependence in ridehailing use. Specifically, we investigate the diffusion and role of solo requests versus ride-pooling to shed light on how different mobility services, with different environmental and accessibility implications, are used by diverse communities. This paper employs a Social Disadvantage Index, Transit Access Analysis, and a Spatial Durbin Model to investigate the influence of both local and spatial spillover effects on the demand for shared and solo ridehailing. The analysis of 127 million ridehailing rides, of which 15% are pooled, confirms the presence of spatial effects. Results indicate that density and vibrancy variables have analogue effects, both direct and indirect, on demand for solo vs pooled rides. Instead, our analysis reveals significant contrasting effects for socio-economic disadvantage, which is positively correlated with ride-pooling and negatively with solo rides. Additionally, we find that higher rail transit access is associated with higher demand for both solo and pooled ridehailing along with substantial spatial spillovers. We discuss implications for policy, operations and research related to the novel insight on how pooled ridesourcing relate to geography, living conditions, and transit interactions. Submitted to journal of Transport Geography

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of Transport...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Journal of Transport Geography
    Article . 2021 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
    https://doi.org/10.48550/arxiv...
    Article . 2021
    License: CC BY NC ND
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Journal of Transport...arrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Journal of Transport Geography
      Article . 2021 . Peer-reviewed
      License: Elsevier TDM
      Data sources: Crossref
      https://doi.org/10.48550/arxiv...
      Article . 2021
      License: CC BY NC ND
      Data sources: Datacite
      addClaim

      This Research product is the result of merged Research products in OpenAIRE.

      You have already added works in your ORCID record related to the merged Research product.