Uncertainty modeling of connected and automated vehicle penetration rate under mixed traffic environment

Jiali Peng, Wei Shangguan, Cong Peng and Linguo Chai

Physica A: Statistical Mechanics and its Applications, 2024, vol. 639, issue C

Abstract: Accurate knowledge of the penetration rate of connected and automated vehicles (CAVs) is crucial for effective control applications during the transition from mixed traffic to full CAV deployment. Previous studies have focused on characterizing or controlling mixed traffic with a fixed CAV penetration rate. However, in reality, the on-road penetration rate of CAVs varies, even if their market share remains constant. This study presents a mathematical model that estimates the CAV penetration rate while considering this variability. We propose an uncertainty-based penetration rate estimation model to assess the variability of CAV numbers on the road. This model utilizes a probabilistic modified random walk approach to estimate the distribution. To enhance the realism of mixed traffic flow, we incorporate realistic vehicle braking and starting behaviors using an improved cellular automata-based mixed traffic flow model. Simulation results demonstrate that our uncertainty-based penetration rate estimation model accurately describes CAV numbers and estimates the variability in mixed traffic flow, specifically within opened circular boundaries and on-ramps. Moreover, we demonstrate the practical applicability of the uncertainty models in real-world situations, showcasing their potential to enhance system optimizations.

Keywords: Connected and automated vehicle penetration rate; Stochastic modeling; Cellular automata; Uncertainty estimation (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0378437124001481
Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:639:y:2024:i:c:s0378437124001481

DOI: 10.1016/j.physa.2024.129640

Access Statistics for this article

Physica A: Statistical Mechanics and its Applications is currently edited by K. A. Dawson, J. O. Indekeu, H.E. Stanley and C. Tsallis

More articles in Physica A: Statistical Mechanics and its Applications from Elsevier
Bibliographic data for series maintained by Catherine Liu ().