Evaluation of managed-lane operation plan for autonomous vehicles

Author:

Park Nuri1ORCID,Yang Samgyu2ORCID,Park Juneyoung3ORCID,Won Minsu4ORCID

Affiliation:

1. Master's student, Department of Smart City Engineering, Hanyang University, Ansan, South Korea

2. Master's degree, Department of Smart City Engineering, Hanyang University, Ansan, South Korea

3. Assistant Professor, Department of Transportation and Logistics Engineering/Smart City Engineering, Hanyang University, Ansan, South Korea (corresponding author: )

4. Associate Research Fellow, Department of Transport Big Data and A.I., The Korea Transport Institute, Sejong, South Korea

Abstract

Autonomous driving technology, in which cars recognise their surroundings and drive by way of mechanical control, has attracted much attention. However, before the introduction of autonomous driving technology, there will be a mixture of autonomous and non-autonomous vehicles, which will require a traffic operation management strategy to ensure the safety and operational efficiency of the mixed traffic flow. In response, an operation plan is proposed here to design and operate a managed lane to minimise friction between autonomous and non-autonomous vehicles in the commercialisation phase of autonomous vehicles (AVs). To evaluate this AV managed-lane operation strategy, effectiveness measurements relation to safety, operation efficiency and the environment were derived by conducting a simulation analysis using Vissim software. Then, a value function was developed that reflects the three measurements and their importance weighting values. Using this approach, the paper provides a strategy of optimal AV managed-lane operation that can increase operational efficiency and safety in expressway on/off-ramp areas.

Publisher

Thomas Telford Ltd.

Subject

Transportation,Civil and Structural Engineering

Reference38 articles.

1. Atkins WS (2016) Research on the Impacts of Connected and Autonomous Vehicles (CAVs) on Traffic Flow. Stage 2: Traffic Modelling and Analysis Technical Report. Department for Transport, London, UK.

2. Impact of Privately-Owned Level 4 CAV Technologies on Travel Demand and Energy

3. A stochastic framework using Bayesian optimization algorithm to assess the network-level societal impacts of connected and autonomous vehicles

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2. Editorial;Proceedings of the Institution of Civil Engineers - Transport;2023-06

3. Evaluation of managed-lane operation plan for autonomous vehicles;Proceedings of the Institution of Civil Engineers - Transport;2022-11-15

4. Impact of connected and autonomous vehicle dedicated lane on the freeway traffic efficiency;European Transport Research Review;2022-04-04

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