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Abstract for presentation (Poster or Podium) with a Paper in the Conference Proceedings

CAV Impacts

Impact of Infrastructure-based Automation of Connected and Automated Vehicles on Freeways

Monday, June 17, 2024

1:30 PM - 2:45 PM ET

Room: Galleria

Co-Author(s)

MS

Mandip Sigdel (he/him/his)

Research Assistant
University of Cincinnati
Cincinnati, OH, United States

Primary Author(s)

Mohamed Ahmed, PhD., P.E.

Professor and Director
University of Cincinnati
Cincinnati, OH, United States

Submitter(s)

MA

Mohamed Ahmed, PhD., P.E.

University of Cincinnati
Cincinnati, Ohio, United States

Abstract: Advancements in automation technology present a promising avenue for reducing human errors and enhancing transportation safety. As the capabilities of Connected and Automated Vehicles (CAVs) continue to evolve, it becomes increasingly important to consider the corresponding evolution of roadway infrastructure. The existing infrastructure's limitations in accommodating CAVs raise safety concerns, emphasizing the need for infrastructure adaptation. This study explores the influence of varying automation levels tailored to specific roadway segments, aiming to comprehend the operational and safety benefits in comparison to a uniform automation level across all segments. Using VISSIM's internal modeling parameters, mixed traffic scenarios with diverse automation levels were simulated on various freeway segments. A total of fifteen scenarios were developed, taking into account traffic volumes and segment-specific automation capabilities. Safety evaluations, employing the Surrogate Safety Assessment Model (SSAM) and the Time to Collision (TTC) metric with three distinct thresholds, revealed that implementing mid-level automation on straight segments and high-level automation at junctions and ramps outperformed alternative configurations. These configurations led to a reduction in conflicts by approximately 30% or more when contrasted with a uniform high automation setup. The findings underscore the significant advantages of segment-specific automation in enhancing safety and efficiency within the Connected and Automated Vehicle (CAV) industry.

Learning Objectives:

Attendees can expect to learn the following from this session:

Upon completion, participant will be able to demonstrate the suitability of varying levels of automation based on roadway infrastructure and geometry to improve operational efficiency and safety.
Upon completion, participant will be able to describe the principles of the Surrogate Safety Assessment Model, and the Time to Collision (TTC) metric with different thresholds for evaluating the safety.
Upon completion, participant will be able to develop VISSIM based microsimulation models utilizing internal modeling parameters to analyze various scenarios of mixed traffic, considering different automation levels and roadway segments.