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Short-distance transport refers to transport that occurs over a distance of just 2-3 cells, crossing the plasma membrane in the process. Small uncharged molecules, such as oxygen, carbon dioxide, and water, can diffuse across the plasma membrane on their own. In contrast, ions and larger molecules require the assistance of transport proteins due to their charge or size. Transport across membranes also occurs within individual cells, playing a variety of essential roles for the plant as a whole.
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Distributed loads are a common type of load that engineers and scientists encounter in various practical situations. Distributed loads often refer to a type of load spread over a surface or a structure and can be modeled as continuous force per unit area.
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Evaluating the Effect of Roadside Parking on a Dual-Direction Urban Street
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Routing and Rebalancing Intermodal Autonomous Mobility-on-Demand Systems in Mixed Traffic.

Salomón Wollenstein-Betech1, Mauro Salazar2, Arian Houshmand1

  • 1The authors are with the Division of Systems Engineering and the Center for Information and Systems Engineering, Boston University, Boston, MA 02215 USA.

IEEE Transactions on Intelligent Transportation Systems : a Publication of the IEEE Intelligent Transportation Systems Council
|May 1, 2023
PubMed
Summary
This summary is machine-generated.

Autonomous Mobility-on-Demand (AMoD) systems can cause congestion. Integrating AMoD with public transit, walking, and micromobility improves system performance and reduces traffic impacts.

Keywords:
Mixed AutonomyMobility-on-DemandRebalancingSystem-Optimal Routing

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Area of Science:

  • Transportation Engineering
  • Operations Research
  • Urban Planning

Background:

  • Autonomous Mobility-on-Demand (AMoD) systems are emerging as a transformative mobility solution.
  • Understanding the impact of AMoD on traffic congestion is crucial for sustainable urban transportation.
  • Existing models often overlook the endogenous effects of AMoD on travel times and exogenous impacts from private vehicles.

Purpose of the Study:

  • To develop and evaluate congestion-aware route-planning policies for intermodal AMoD systems.
  • To optimize AMoD routing and rebalancing strategies considering mixed traffic conditions.
  • To assess the benefits of integrating AMoD with public transit and other mobility options.

Main Methods:

  • Devised a network flow model for joint optimization of AMoD routing and rebalancing.
  • Incorporated congestion effects from both AMoD and private vehicles using a sequential approach.
  • Developed algorithms to derive explicit user routes from link flow results.
  • Validated the framework using case studies in Eastern Massachusetts and New York City.

Main Results:

  • Pure AMoD systems can be detrimental at high demand due to rebalancing traffic.
  • Blending AMoD with public transit, walking, and micromobility significantly enhances system performance.
  • High-throughput public transit combined with flexible micro-mobility options offers a synergistic advantage.
  • Congestion-aware policies are essential for efficient AMoD integration.

Conclusions:

  • Intermodal AMoD systems, when strategically integrated, offer a sustainable path for urban mobility.
  • Policy interventions focusing on mode integration are vital to mitigate congestion.
  • The proposed framework provides a robust tool for planning and managing future mobility systems.