Fundamental diagram and stability of mixed traffic flow considering platoon size and intensity of connected automated vehicles

Yao, Zhihong; Gu, Qiufan; Jiang, Yangsheng; Ran, Bin

doi:10.1016/j.physa.2022.127857

Cited by 40 publications

(9 citation statements)

References 53 publications

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“…From Table (3), it can be seen that the mean free-flow speed of composition lies between 95% confidence interval, i.e. [34,28] km/hr. It can also be seen that ρ jam for C2 is higher than C1 as the T W and BLT proportion is higher for C2.…”

Section: Resultsmentioning

confidence: 91%

“…Researchers have been exploring composite fundamental diagrams of human-driven vehicles (HVs) with different penetrations of connected autonomous vehicles (CAVs). Few studies follow average stable headway to estimate the composite fundamental diagrams where the combinations of CAVs and HVs were modeled probabilistically [34], [35]. Also, microsimulation-based IDM car-following models [36] were used to model the CAVs and HVs stream with different perceptions and reaction times for analyzing the properties of FDs in different composition levels [37].…”

Section: Introductionmentioning

confidence: 99%

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Empirical Investigation of Fundamental Diagrams in Mixed Traffic

Maiti

Chilukuri

2023

IEEE Access

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A thorough understanding of the fundamental relation of traffic flow variables is critical for the efficient operation of traffic systems. However, their relationships in mixed traffic are challenging to model due to the continuously changing vehicle composition. This paper proposes a composition-based approach for estimating the fundamental relationships between traffic flow variables using empirical data. The methodology seeks to eliminate the difficulties in class-specific ss identification by introducing a continuous wavelet transformation with oblique cumulative arrival and oblique occupancy time plots. We used machine learning (ML) algorithms to delineate regimes and showed the fundamental diagrams for a given location that has a composition-invariant free-flow branch but has distinct composition-specific branches in congestion. Also, it was observed that the congested regime (CR) has a wide scatter indicating possible stochastic inter-class interactions for varying vehicular composition. We proposed a distance optimization method to re-cluster the CR data and found that the proposed method improves the fit with the empirical observations. The inter-class interactions result illustrates that the heavy vehicles will dominate the high-speed vehicles with the increase of AO. It is found that beyond a critical level of AO in congestion, all vehicle class travel at the same speed. Finally, it is found that validation with different datasets shows that the proposed methodology is robust in estimating fundamental diagrams under mixed traffic conditions.

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Section: Resultsmentioning

confidence: 91%

Section: Introductionmentioning

confidence: 99%

Empirical Investigation of Fundamental Diagrams in Mixed Traffic

Maiti

Chilukuri

2023

IEEE Access

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“…Subsequent studies can consider how to determine the optimal merging positions and driving strategy for the CAV platoon [38,39]. (3) When the CAV merges, there is no obstacle in the acceleration lane.…”

Section: Data Availabilitymentioning

confidence: 99%

Combined Safety and Coordination of Connected Automated Vehicles in Merging Area with Featuring Optimal Merging Positions

Liu

Cen

Yao

et al. 2022

Journal of Advanced Transportation

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Freeway on-ramp merging area is deemed to be typical bottlenecks section, which leads to low traffic efficiency, congestions, and frequent accidents. Most existing studies on merging for the connected and automated vehicles focus on merging at a single fixed merging point. However, the problem of coordination between merging vehicle and arterial traffic flow in the acceleration lane is ignored in the existing studies. is study proposes a merging model, which combined safety and coordination of CAVs with featuring optimal merging positions. e proposed model has two stages: one is analysis of merging velocity of the insertable gap and the other one is determining constraint condition of cooperative merging. e outputs of first stage are interval of merging speed and the mergeable range. e outputs of second stage are optional insertable gap and the corresponding driving scheme.en, a traffic simulation experiment is designed to evaluate the proposed model. e simulation results show that the proposed model can effectively guarantee driving safety and make the merging process smoother with 28.7% reduction in travel time for the CAV merging. Furthermore, the proposed model does not sacrifice the interests of surrounding traffic to assist in CAV merging.e results indicate the promising potential of using the proposed methods can approximately get a fair use of road resources for each CAV.

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“…All vehicles are supposed to maintain the same driving behavior in most car-following traffic models, yet the actual situations are difficult to represent. In actual traffic scenarios, the car-following behaviors exhibit heterogeneity due to varying conditions of drivers or vehicles [ [28] , [29] , [30] , [31] , [32] , [33] , [34] , [35] , [36] , [37] , [38] ]. One of the most typical examples is that vehicles vary in size.…”

Section: Introductionmentioning

confidence: 99%