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SCIENCE CHINA Information Sciences, Volume 64 , Issue 11 : 212202(2021) https://doi.org/10.1007/s11432-020-3107-7

Distributed multilane merging for connected autonomous vehicle platooning

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  • ReceivedMay 4, 2020
  • AcceptedOct 1, 2020
  • PublishedOct 20, 2021

Abstract


Acknowledgment

This work was supported in part by National Key Research and Development Program of China (Grant No. 2017YFB0102503) and National Natural Science Foundation of China (Grant No. 52072243).


References

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  • Figure 1

    Illustration of the scenario. The following CAVs $1,2,\ldots,n$ initially located in multiple lanes are expected to achieve a single-lane platoon formation with a desired distance ${\boldsymbol~r}_i$ relative to the leader and maintain the same velocity ${\boldsymbol~v}_l$ as the leader.

  • Figure 2

    (Color online) (a) The tracking models. The gray vehicle represents the reference. (b) The block diagram of the proposed PaTFS framework for the merging and platoon formation task.

  • Figure 3

    (a) The relationship between acceleration and velocity. The vectors $a_{\rm~ref}$ and $v_{\rm~ref}$ generated by the point model are used to deduce the sideslip angle $\beta$ and turning radius $R$. (b) The geometric relationships of the sideslip angles: $\beta_f,~\beta_r,~\beta$ and the feedforward steering angle $\delta_{\rm~ff}$ that needs to be derived.

  • Figure 4

    Illustration of the forces exerted on a CAV $i$ when a velocity consensus is reached, with the assumption of a repulsive force.

  • Figure 5

    (Color online) (a) illustrates the composition of the HiL experiment platform and the signal flow. Hardware connections and the data transferred within the network are given. (b) shows the actual implemented testbed.

  • Figure 6

    (Color online) (a), (c) and (e) illustrate the trajectories of CAV 1, CAV 2 and CAV 3 during the merging and platooning operations using PT, PaT, and PaTFS respectively. In each subfigure, each of the colored lines denotes the trajectory of a particular CAV with one of the aforementioned three controllers while the gray dotted lines represent the results of other CAVs. The position error state evolutions of CAV 1, CAV 2 and CAV 3 are illustrated in (b), (d) and (f). The differences in CAV positions using PT and PaTFS are given. These values compare the actual (A) and planned (P) positions of the PaTFS with those of the PT. Deviations from PT in the merging phase were ultimately alleviated.

  • Figure 7

    (Color online) The spacing evolution of PT, PaT, and PaTFS applied to each CAV is given in the left column. (a), (c) and (e) show the spacing between CAV 1, CAV 2 and CAV 3 and their predecessors. The reference spacing is given to demonstrate convergence. The velocities of PT, PaT and PaTFS applied to each CAV are given in the right column. (b), (d) and (f) show the velocities of CAV 1, CAV 2 and CAV 3. The reference velocity is given to demonstrate convergence.

  • Figure 8

    (Color online) The lateral deviations of CAV 1 (a), CAV 2 (b), and CAV 3 (c) from the desired lane respectively. The results of the cases where PT, PaT and PaTFS are applied to each CAV are all plotted. The desired lateral position is also plotted for each CAV as the reference.

  • Figure 9

    (Color online) The absolute tracking errors at each step for all CAVs in the (a) close and (b) distant cases, respectively. Absolute values are chosen for comparison. Note that ACLT only provides trajectories for the merging CAVs 3 and 4; the comparison of the tracking errors is thus based on these two CAVs. CAVs 3 and 4 exhibit larger deviations from the trajectories for ACLT. On the other hand, a much smaller magnitude of errors is observed when PaTFS is applied.

  • Table 11  

    Table 1Table 1

    Parameter settings

  • Table 22  

    Table 2Table 2

    Vehicle parameters

  • Table 33  

    Table 3Table 3

    RMS and final values of the tracking errors for 3 states of the following CAVs using the PaTFS framework

  • Table 4  

    Table 4Lateral deviations of the CAVs from the desired positions under the PT, PaT and PaTFS models, respectively

    Scheme CAV 1 CAV 2 CAV 3
    RMS (m)PT $0.1237$0.8667 0.8115
    PaT 0.8898 0.9556 1.1209
    PaTFS 0.039210.79940.8714
    shortstackFinalerror (m)PT $-7.0732\times~10^{-3}$ $-5.5593\times~10^{-3}$ $-2.7976\times~10{-3}$
    PaT $-0.6969$ $-0.5046$ $-0.1012$
    PaTFS $4.9173\times~10^{-4}$ $3.7834\times~10^{-4}$ $1.9921\times~10^{-4}$
  • Table 54  

    Table 5Table 4

    Parameter settings for scenario 2

  • Table 65  

    Table 6Table 5

    Peak longitudinal and lateral acceleration of the CAVs

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