A theoretical model for evaluating the impact of connected and autonomous vehicles on the operational performance of turbo roundabouts

•A criterion for estimating the capacity under partial and fully automated vehicles environments is presented.•A control area was hypothesized where CAVs start to communicate with a turbo roundabout manager system.•Different traffic scenarios were analysed in the research.•With the increase in marke...

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Veröffentlicht in:International Journal of Transportation Science and Technology 2024-06, Vol.14, p.202-218
1. Verfasser: Guerrieri, Marco
Format: Artikel
Sprache:eng
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Zusammenfassung:•A criterion for estimating the capacity under partial and fully automated vehicles environments is presented.•A control area was hypothesized where CAVs start to communicate with a turbo roundabout manager system.•Different traffic scenarios were analysed in the research.•With the increase in market penetration levels of CAVs, entry capacities increase accordingly. This article presents a methodology to estimate the entry capacity (EC) and total capacity (TC) of basic turbo roundabouts under partial and fully connected and autonomous vehicle (CAV) environments. EC calculations are partially based on capacity models and adjustment factors proposed by the HCM 7th edition, taking into account different proportions of CAVs in traffic streams. The proposed methodology was applied to a case study concerning a basic turbo roundabout with different traffic demands and market penetration levels (MPLs) of CAVs. It was assumed that the traffic stream consisted of 100% passenger cars with MPLs of CAVs ranging from 0% to 100%. The research proves that with the increase in MPLs of CAVs, ECs increase accordingly and delays and queues decrease. To maximize the TC, a control area was also hypothesized, where CAVs start to communicate with a turbo roundabout manager system. The system should be able to distribute and channel CAVs, and therefore the entering flows between entry lanes find the values of the maneuver distribution factors (α, β, γ, δ) between the right lane and the left lane of entries to maximize the TC for each origin–destination matrix of traffic flows.
ISSN:2046-0430
DOI:10.1016/j.ijtst.2023.05.001