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Archival Research01:40

Archival Research

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Some researchers gain access to large amounts of data without interacting with a single research participant. Instead, they use existing records to answer various research questions. This type of research approach is known as archival research. Archival research relies on looking at past records or data sets to look for interesting patterns or relationships. For example, a researcher might access the academic records of all individuals who enrolled in college within the past ten years and...
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Unlocking Mutual Gains-An Experimental Study on Collaborative Autonomous Driving in Urban Environment.

Sumbal Malik1,2, Manzoor Ahmed Khan1,2, Hesham El-Sayed1,2

  • 1College of Information Technology, United Arab Emirates University, Abu Dhabi 15551, United Arab Emirates.

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Summary
This summary is machine-generated.

Convoy driving, or collaborative autonomous driving, improves traffic flow and reduces emissions. This study models incentives like insurance discounts to encourage individual vehicle participation, balancing societal and personal benefits.

Keywords:
coalitional gamecollaborative drivingconvoyincentivizationpollutant emissiontraffic flowurban environment

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Area of Science:

  • Transportation Engineering
  • Autonomous Systems
  • Game Theory

Background:

  • Convoy driving offers societal benefits like reduced congestion and emissions.
  • Individual vehicle participation in convoys is crucial but often overlooked.
  • Existing research prioritizes collective benefits over individual incentives.

Purpose of the Study:

  • To model societal benefits of convoy driving (traffic flow, emissions).
  • To design and model individual-level incentives for convoy participation.
  • To bridge the gap between societal goals and individual vehicle owner motivations.

Main Methods:

  • Modeling mixed traffic flow using a fundamental diagram.
  • Incorporating Connected Autonomous Vehicles (CAVs) penetration rates, coalition intensity, and size.
  • Applying coalitional game theory to model collaborative convoy driving.
  • Developing a novel utility function with incentives (insurance, fines, tolls).

Main Results:

  • Mixed traffic flow dynamics analyzed based on CAV penetration, coalition intensity, and size.
  • Identified the necessity of balancing CAV penetration, coalition factors, and speed for optimal benefits.
  • Demonstrated the effectiveness of proposed incentives in encouraging convoy formation.

Conclusions:

  • Convoy driving requires aligning road authority sustainability goals with individual vehicle owner benefits.
  • A balanced approach to CAV integration and incentive design is key.
  • This research promotes a mutually beneficial future for convoy driving.