Vehicle platooning using connected and automated vehicles (CAVs) has attracted considerable attention. In this paper, we address the problem of optimal coordination of CAV platoons at a highway on-ramp merging scenario. We present a single-level constrained optimal control framework that optimizes the fuel economy and travel time of the platoons while satisfying the state, control, and safety constraints. We also explore the effect of delayed communication among the CAV platoons and propose a robust coordination framework to enforce lateral and rear-end collision avoidance constraints in the presence of bounded delays. We provide a closed-form analytical solution to the optimal control problem with safety guarantees that can be implemented in real time. Finally, we validate the effectiveness of the proposed control framework using a high-fidelity commercial simulation environment.
Citation: A M Ishtiaque Mahbub, Behdad Chalaki, Andreas A. Malikopoulos. A constrained optimal control framework for vehicle platoons with delayed communication[J]. Networks and Heterogeneous Media, 2023, 18(3): 982-1005. doi: 10.3934/nhm.2023043
[1] | Daniel Maxin, Fabio Augusto Milner . The effect of nonreproductive groups on persistent sexually transmitted diseases. Mathematical Biosciences and Engineering, 2007, 4(3): 505-522. doi: 10.3934/mbe.2007.4.505 |
[2] | Yansong Pei, Bing Liu, Haokun Qi . Extinction and stationary distribution of stochastic predator-prey model with group defense behavior. Mathematical Biosciences and Engineering, 2022, 19(12): 13062-13078. doi: 10.3934/mbe.2022610 |
[3] | Asma Alshehri, John Ford, Rachel Leander . The impact of maturation time distributions on the structure and growth of cellular populations. Mathematical Biosciences and Engineering, 2020, 17(2): 1855-1888. doi: 10.3934/mbe.2020098 |
[4] | Katarzyna Pichór, Ryszard Rudnicki . Stochastic models of population growth. Mathematical Biosciences and Engineering, 2025, 22(1): 1-22. doi: 10.3934/mbe.2025001 |
[5] | Brandy Rapatski, James Yorke . Modeling HIV outbreaks: The male to female prevalence ratio in the core population. Mathematical Biosciences and Engineering, 2009, 6(1): 135-143. doi: 10.3934/mbe.2009.6.135 |
[6] | Ping Yan, Gerardo Chowell . Modeling sub-exponential epidemic growth dynamics through unobserved individual heterogeneity: a frailty model approach. Mathematical Biosciences and Engineering, 2024, 21(10): 7278-7296. doi: 10.3934/mbe.2024321 |
[7] | Hao Wang, Yang Kuang . Alternative models for cyclic lemming dynamics. Mathematical Biosciences and Engineering, 2007, 4(1): 85-99. doi: 10.3934/mbe.2007.4.85 |
[8] | Hisashi Inaba . The Malthusian parameter and R0 for heterogeneous populations in periodic environments. Mathematical Biosciences and Engineering, 2012, 9(2): 313-346. doi: 10.3934/mbe.2012.9.313 |
[9] | Jim M. Cushing . The evolutionarydynamics of a population model with a strong Allee effect. Mathematical Biosciences and Engineering, 2015, 12(4): 643-660. doi: 10.3934/mbe.2015.12.643 |
[10] | Jie Bai, Xiunan Wang, Jin Wang . An epidemic-economic model for COVID-19. Mathematical Biosciences and Engineering, 2022, 19(9): 9658-9696. doi: 10.3934/mbe.2022449 |
Vehicle platooning using connected and automated vehicles (CAVs) has attracted considerable attention. In this paper, we address the problem of optimal coordination of CAV platoons at a highway on-ramp merging scenario. We present a single-level constrained optimal control framework that optimizes the fuel economy and travel time of the platoons while satisfying the state, control, and safety constraints. We also explore the effect of delayed communication among the CAV platoons and propose a robust coordination framework to enforce lateral and rear-end collision avoidance constraints in the presence of bounded delays. We provide a closed-form analytical solution to the optimal control problem with safety guarantees that can be implemented in real time. Finally, we validate the effectiveness of the proposed control framework using a high-fidelity commercial simulation environment.
In this paper, we study the coupled chemotaxis-fluid models with the initial-bounary conditions
{nt+u⋅∇n=Δn−∇⋅(n∇c)+γn−μn2,in Q≡(0,T)×Ω,ct+u⋅∇c=Δc−c+n+f,in Q,ut+u⋅∇u=Δu−∇π+n∇φ,in Q,∇⋅u=0,in Q,∂n∂ν=∂c∂ν=0,u=0,on (0,T)×∂Ω,n(x,0)=n0(x),c(x,0)=c0(x),u(x,0)=u0(x),in Ω, | (1.1) |
where
In order to understand the development of system (1.1), let us mention some previous contributions in this direction. Jin [11] dealed with the time periodic problem of (1.1) in spatial dimension
Espejo and Suzuki [6] discussed the chemotaxis-fluid model
nt+u⋅∇n=Δn−∇⋅(n∇c)+n(γ−μn), | (1.2) |
ct+u⋅∇c=Δc−c+n, | (1.3) |
ut=Δu−∇π+n∇φ, | (1.4) |
∇⋅u=0, | (1.5) |
∂n∂ν=∂c∂ν=0,u=0. | (1.6) |
They proved the global existence of weak solution. Tao and Winkler [17] proved the existence of global classical solution and the uniform boundedness. Tao and Winkler [18] also obtained the global classical solution and uniform boundedness under the condition of
The optimal control problems governed by the coupled partial differential equations is important. Colli et al. [4] studied the distributed control problem for a phase-field system of conserved type with a possibly singular potential. Liu and Zhang [14] considered the optimal control of a new mechanochemical model with state constraint. Chen et al. [3] studied the distributed optimal control problem for the coupled Allen-Cahn/Cahn-Hilliard equations. Recently, Guillén-González et al. [9] studied a bilinear optimal control problem for the chemo-repulsion model with the linear production term. The existence, uniqueness and regularity of strong solutions of this model are deduced. They also derived the first-order optimality conditions by using a Lagrange multipliers theorem. Frigeri et al. [8] studied an optimal control problem for two-dimensional nonlocal Cahn-Hilliard-Navier-Stokes systems with degenerate mobility and singular potential. Some other results can be found in [2,5,13,15,19].
In this paper, we discuss the optimal control problem for (1.1). We adjust the external source
In this section, we will construct the existence and some priori estimates of the linearized problem for the chemotaxis-Navier-Stokes system in a bounded domain
In the following lemmas we will state the Gagliardo-Nirenberg interpolation inequality [7].
Lemma 2.1. Let
1p−lN=a(1q−kN)+(1−a)1r. | (2.1) |
Then, for any
‖Dlu‖Lp⩽c1‖Dku‖aLq‖u‖1−aLr+c2‖u‖Lr |
with the following exception: If
The following log-interpolation inequality has been proved by [1].
Lemma 2.2. Let
‖u‖3L3(Ω)≤δ‖u‖2H1(Ω)‖(u+1)log(u+1)‖L1(Ω)+p(δ−1)‖u‖L1(Ω), |
where
We first consider the existence of solutions to the linear problem of system (1.1). Assume functions
{ut−Δu+ˆu⋅∇u=−∇π+ˆn∇φ,in Q,∇⋅u=0,in Q,u=0,on ∂Ω,u(x,0)=u0(x),in Ω. | (2.2) |
By using fixed point method, the existence of solutions can be easily obtained. Therefore, we ignore the process of proof and just give the regularity estimate.
Lemma 2.3. Let
Proof. Multiplying the first equation of (2.2) by
12ddt∫Ωu2dx+∫Ω|∇u|2dx+∫Ωu2dx=∫Ωˆn∇φ⋅udx+∫Ωu2dx≤‖ˆn‖L2‖u‖L2+‖u‖2L2≤C(‖ˆn‖2L2+‖u‖2L2). |
By Gronwall's inequality, we have
‖u‖2L2+∫T0‖u‖2H1dτ≤C(∫T0‖ˆn‖2L2dτ+‖u0‖2L2). |
Operating the Helmholtz projection operator
ut+Au+P(ˆu⋅∇u)=P(ˆn∇φ), |
where
12ddt∫Ω|∇u|2dx+∫Ω|Δu|2dx+∫Ω|∇u|2dx=∫ΩP(ˆu∇u)Δudx−∫ΩP(ˆn∇φ)Δudx+∫Ω|∇u|2dx. |
For the terms on the right, we have
∫ΩP(ˆu∇u)Δudx−∫ΩP(ˆn∇φ)Δudx+∫Ω|∇u|2dx≤‖ˆu‖L4‖∇u‖L4‖Δu‖L2+‖ˆn‖L2‖Δu‖L2+‖∇u‖2L2≤‖ˆu‖L4‖∇u‖1/2L2‖Δu‖3/2L2+‖ˆu‖L4‖∇u‖L2‖Δu‖L2+‖ˆn‖L2‖Δu‖L2+‖∇u‖2L2≤12‖Δu‖2L2+C(‖ˆu‖4L4+‖ˆu‖2L4+1)‖∇u‖2L2+‖ˆn‖2L2. |
Therefore, we get
ddt‖∇u‖2L2+‖∇u‖2H1≤C(‖ˆu‖4L4+‖ˆu‖2L4+1)‖∇u‖2L2+C‖ˆn‖2L2+C. |
By Gronwall's inequality, we derive
‖∇u‖2L2+∫T0‖∇u‖2H1dτ≤C. |
Multiplying the first equation of (2.2) by
∫T0∫Ω|ut|2dxdt≤C. |
Summing up, we complete the proof.
For the above solution
{ct−Δc+u⋅∇c+c=ˆn++f,in Q,∂c∂ν=0,on (0,T)×∂Ω,c(x,0)=c0(x),in Ω. | (2.3) |
Along with fixed point method, the existence of solutions can be easily obtained. Thus we omit the proof and only give the regularity estimate.
Lemma 2.4. Let
Proof. Multiplying the first equation of (2.3) by
12ddt∫Ωc2dx+∫Ω|∇c|2dx+∫Ωc2dx≤‖ˆn‖L2‖c‖L2+‖f‖L2‖c‖L2. |
Therefore, we have
‖c‖2L2+‖c‖2H1≤C(‖c0‖2L2+∫t0(‖ˆn‖2L2+‖f‖2L2)dτ). |
Multiplying the first equation of (2.3) by
12ddt∫Ω|∇c|2dx+∫Ω|Δc|2dx+∫Ω|∇c|2dx=∫Ωu∇cΔcdx−∫ΩΔcˆndx−∫ΩΔcfdx. |
Using the Young inequality and the Hölder inequality, we obtain
∫Ωu∇cΔcdx−∫ΩΔcˆndx−∫ΩΔcfdx≤‖u‖L4‖∇c‖L4‖Δc‖L2+‖ˆn‖L2‖Δc‖L2+‖f‖L2‖Δc‖L2≤C‖u‖H1(‖∇c‖12L2‖Δc‖12L2+‖∇c‖L2)‖Δc‖L2+‖ˆn‖L2‖Δc‖L2+‖f‖L2‖Δc‖L2=C‖u‖H1‖∇c‖12L2‖Δc‖32L2+C‖∇c‖L2‖Δc‖L2+‖ˆn‖L2‖Δc‖L2+‖f‖L2‖Δc‖L2≤12‖Δc‖2L2+C‖u‖4H1‖∇c‖2L2+C(‖ˆn‖2L2+‖f‖2L2). |
Combining this and above inequalities, we conclude
ddt‖∇c‖2L2+‖∇c‖2H1≤C‖u‖4H1‖∇c‖2L2+C(‖ˆn‖2L2+‖f‖2L2). |
We therefore verify that
‖∇c‖2L2+∫t0‖∇c‖2H1≤C(∫t0‖ˆn‖2L2dτ+∫t0‖f‖2L2dτ). |
Applying
12ddt∫Ω|Δc|2dx+∫Ω|∇Δc|2dx+∫Ω|Δc|2dx=∫Ω∇(u∇c)∇Δcdx−∫Ω∇ˆn+∇Δcdx−∫Ω∇f∇Δcdx. |
For the terms on the right, we obtain
∫Ω∇(u∇c)∇Δcdx−∫Ω∇ˆn+∇Δcdx−∫Ω∇f∇Δcdx≤‖∇Δc‖L2(‖u‖L4‖Δc‖L4+‖∇u‖L4‖∇c‖L4)+‖∇ˆn‖L2‖∇Δc‖L2+‖∇f‖L2‖∇Δc‖L2≤‖∇Δc‖L2(‖u‖L4‖Δc‖12L2‖∇Δc‖12L2+‖u‖L4‖Δc‖L2+‖∇u‖12L2‖Δu‖12L2‖∇c‖12L2‖Δc‖12L2+‖∇u‖L2‖∇c‖12L2‖Δc‖12L2+‖∇u‖12L2‖Δu‖12L2‖∇c‖L2+‖∇u‖L2‖∇c‖L2)+‖∇ˆn‖L2‖∇Δc‖L2+‖∇f‖L2‖∇Δc‖L2≤12‖∇Δc‖2L2+C(1+‖Δc‖2L2+‖Δu‖2L2+‖∇ˆn‖2L2+‖∇f‖2L2). |
Straightforward calculations yield
‖Δc‖2L2+∫t0‖Δc‖2H1dτ≤C(1+∫t0‖ˆn‖2H1dτ+∫t0‖f‖2H1dτ). |
Multiplying the first equation of (2.3) by
∫T0∫Ω|ct|2dxdt≤C, |
and thereby precisely arrive at the conclusion.
With above solutions
{nt−Δn+u⋅∇n+n=−∇⋅(n∇c)+(1+γ)ˆn+−μˆn+n,in Q,∂n∂ν|∂Ω=0,n(x,0)=n0(x),in Ω. | (2.4) |
By a similar argument as the above two problems, the existence of solutions can be easily obtained. Therefore, we only give the regularity estimate.
Lemma 2.5. Suppose
Proof. Firstly, we verify the nonnegativity of
ddt∫A(t)ndx−∫∂A(t)∂n∂νds+∫A(t)ndx=(1+γ)∫A(t)ˆn+dx−μ∫A(t)ˆn+ndx. |
Since
∫A(t)ndxdτ+∫t0∫A(t)ndxdτ=0. |
Then, we get
Next, multiplying the first equation of (2.4) by
12ddt∫Ωn2dx+∫Ω(n2+|∇n|2)dx+μ∫Ωˆn+n2dx=∫Ωn∇c∇ndx+(1+γ)∫Ωnˆn+dx≤‖n‖L4‖∇c‖L4‖∇n‖L2+(1+γ)‖ˆn‖L2‖n‖L2≤C(‖n‖12L2‖∇n‖12L2+‖n‖L2)‖c‖H2‖∇n‖L2+(1+γ)‖ˆn‖L2‖n‖L2≤C(‖n‖2L2‖c‖4H2+‖n‖2L2‖c‖2H2+‖ˆn‖L2)+12‖n‖2H1. |
So, we derive that
‖n‖2L2+∫T0‖n‖2H1dt≤C(1+∫T0‖ˆn‖2L2dt). |
Multiplying the first equation of (2.4) by
12ddt∫Ω|∇n|2dx+∫Ω|Δn|2dx+∫Ω|∇n|2dx=∫Ωu∇nΔndx+∫Ω(∇⋅(n∇c)Δn−(1+γ)ˆn+Δn+μˆn+nΔn)dx≤‖u‖L4‖∇n‖L4‖Δn‖L2+‖n‖L4‖Δc‖L4‖Δn‖L2+‖∇n‖L4‖∇c‖L4‖Δn‖L2+(1+γ)‖ˆn‖L2‖Δn‖L2+μ‖n‖L4‖ˆn‖L4‖Δn‖L2≤C‖u‖H1(‖∇n‖12L2‖Δn‖12L2+‖∇n‖L2)‖Δn‖L2+‖n‖L4(‖Δc‖12L2‖∇Δc‖12L2+‖Δc‖L2)‖Δn‖L2+μ‖n‖L4‖ˆn‖L4‖Δn‖L2+(‖∇n‖12L2‖Δn‖12L2+‖∇n‖L2)‖∇c‖H1‖Δn‖L2+(1+γ)‖ˆn‖L2‖Δn‖L2≤12‖Δn‖2L2+C(‖∇n‖2L2+‖n‖4L4+‖Δc‖4L2+‖∇Δc‖2L2+‖ˆn‖2L2+‖ˆn‖4L4)≤12‖Δn‖2L2+C(1+‖∇n‖2L2+‖n‖4L2+‖n‖2L2‖∇n‖2L2+‖∇Δc‖2L2+‖ˆn‖2L2+‖ˆn‖4L4). |
Straightforward calculations yield
‖∇n‖2L2+∫T0∫Ω(|Δn|2+|∇n|2+ˆn+|∇n|2)dxdt≤C. |
Multiplying the first equation of (2.4) by
∫T0∫Ω|nt|2dxdt≤C. |
The proof is complete.
Introduce the spaces
Xu=L4(0,T;L4(Ω)),Xn=L4(0,T;L4(Ω))∩L2(0,T;H1(Ω)),Yu=L∞(0,T;H1(Ω))∩L2(0,T;H2(Ω)),Yn=L∞(0,T;H1(Ω))∩L2(0,T;H2(Ω)). |
Define a map
F:Xu×Xn→Xu×Xn,F(ˆu,ˆn)=(u,n), |
where the
{nt−Δn+u⋅∇n+n=−∇⋅(n∇c)+(1+γ)ˆn+−μˆn+n,in (0,T)×Ω≡Q,ct−Δc+u⋅∇c+c=ˆn++f,in (0,T)×Ω≡Q,ut−Δu+ˆu⋅∇u=−∇π+ˆn∇φ,in (0,T)×Ω≡Q,∇⋅u=0,in (0,T)×Ω≡Q,∂n∂ν=∂c∂ν=0,u=0,on (0,T)×∂Ω,n(x,0)=n0(x),c(x,0)=c0(x),u(x,0)=u0(x),in Ω. |
Next, we use fixed point method to prove the local existence of solutions of the problem (1.1).
Lemma 2.6. The map
Proof. Let
From Lemma 2.6,
{nt−Δn+u⋅∇n+n=−∇⋅(n∇c)+α(1+γ)n−μn2,in Q,ct−Δc+u⋅∇c+c=n+αf,in Q,ut−Δu+u⋅∇u=−∇π+αn∇φ,in Q,∇⋅u=0,in Q,∂n∂ν=∂c∂ν=0,u=0,on (0,T)×∂Ω,n(x,0)=n0(x),c(x,0)=c0(x),u(x,0)=u0(x),in Ω. | (3.1) |
In order to prove the existence of solution, we first give some a priori estimates.
Lemma 3.1. Let
‖n‖L1+∫t0(‖n‖L1+‖n‖L2)dτ≤C, | (3.2) |
‖∇u‖2L2+∫t0‖∇u‖2H1dτ≤C, | (3.3) |
‖∇c‖2L2+∫t0‖∇c‖2H1dτ≤C. | (3.4) |
Proof. With Lemma 2.5 in hand, we get
ddt∫Ωndx+∫Ωndx+μ∫Ωn2dx=α(1+γ)∫Ωndx≤μ2∫Ωn2dx+C. |
Solving this differential inequality, we obtain that
‖n‖L1+∫t0(‖n‖L1+‖n‖L2)dτ≤C. |
Multiplying the third equation of (3.1) by
12ddt∫Ωu2dx+∫Ω|∇u|2dx+∫Ωu2dx=α∫Ωn∇φ⋅udx+∫Ωu2dx≤‖n‖L2‖u‖L2+‖u‖2L2≤C(‖n‖2L2+‖u‖2L2). |
Therefore, we see that
‖u‖2L2+∫t0‖u‖H1dτ≤C. |
By the Gagliardo-Nirenberg interpolation inequality, we deduce that
∫t0‖u‖4L4dτ≤C∫t0(‖u‖2L2‖∇u‖2L2d+‖u‖2L2)τ≤‖u‖2L2∫t0‖∇u‖2L2dτ+∫t0‖u‖2L2dτ≤C. |
Multiplying the third equation of (3.1) by
ddt‖∇u‖2L2+‖∇u‖2H1≤C(‖u‖4L4+‖u‖2L4+1)‖∇u‖2L2+C‖n‖2L2+C. |
Thus, we know
‖∇u‖2L2+∫t0‖∇u‖2H1dτ≤C. |
Multiplying the second equation of (3.1) by
12ddt∫Ωc2dx+∫Ω|∇c|2dx+∫Ωc2dx≤‖n‖L2‖c‖L2+α‖f‖L2‖c‖L2. |
Then, we have
‖c‖L2+∫t0‖c‖H1dτ≤C. |
Multiplying the second equation of (3.1) by
ddt‖∇c‖2L2+‖∇c‖2H1≤C‖u‖4H1‖∇c‖2L2+C(‖n‖2L2+‖f‖2L2). |
Further, we have
‖∇c‖2L2+∫t0‖∇c‖2H1dτ≤C. |
The proof is complete.
Lemma 3.2. Let
‖(n+1)ln(n+1)‖L1+‖∇c‖2L2+‖∇c‖2H1≤C. | (3.5) |
Proof. We rewrite the first equation of (3.1) as
ddt(n+1)+u⋅∇(n+1)−Δ(n+1)=−∇⋅((n+1)⋅∇c)+Δc+α(1+γ)n−μn2. |
Multiplying the above equation by
ddt∫Ω(n+1)ln(n+1)dx+4∫Ω|∇√n+1|2dx≤∫Ω∇(n+1)⋅∇cdx+∫ΩΔcln(n+1)dx+α(1+γ)∫Ωnln(n+1)dx=I1+I2+I3. |
For
I1=−∫ΩnΔcdx≤‖n‖L2‖Δc‖L2≤δ‖Δc‖2L2+C‖n‖2L2. |
For the term
I2=∫ΩΔcln(n+1)dx≤δ‖Δc‖2L2+C‖ln(n+1)‖2L2≤δ‖Δc‖2L2+C∫Ω(n+1)ln(n+1)dx. |
For the rest term
I3=α(1+γ)∫Ωnln(n+1)dx≤(1+γ)∫Ω(n+1)ln(n+1)dx. |
Combining
ddt∫Ω(n+1)ln(n+1)dx+4∫Ω|∇√n+1|2dx≤δ‖Δc‖2L2+C∫Ω(n+1)ln(n+1)dx+C‖n‖2L2. | (3.6) |
Multiplying the second equation of (3.1) by
12ddt∫Ω|∇c|2dx+∫Ω|Δc|2dx+∫Ω|∇c|2dx=∫Ωu∇cΔcdx−∫ΩΔcndx−α∫ΩΔcfdx. |
Straightforward calculations yield
ddt‖∇c‖2L2+‖∇c‖2H1≤C‖∇c‖2L2+C(‖n‖2L2+‖f‖2L2). | (3.7) |
Combing (3.6) and (3.7), it follows that
ddt∫Ω(n+1)ln(n+1)dx+ddt‖∇c‖2L2+(1−δ)‖∇c‖2H1+4∫Ω|∇√n+1|2dx≤C∫Ω(n+1)ln(n+1)dx+C(‖f‖2L2+‖n‖2L2). |
Taking
‖(n+1)ln(n+1)‖L1+‖∇c‖2L2+‖∇c‖2H1≤C. |
The proof is complete.
Lemma 3.3. Assume
‖n‖2L2+‖Δc‖2L2+∫t0‖n‖H1dτ+∫t0‖Δc‖H1dτ≤C. | (3.8) |
Proof. Taking the
12ddt∫Ωn2dx+∫Ω(n2+|∇n|2)dx+μ∫Ωn3dx=∫Ωn∇c∇ndx+α(1+γ)∫Ωn2dx=−12∫Ωn2Δcdx+α(1+γ)∫Ωn2dx. |
Here, we note that
|∫Ωn2Δcdx|≤‖n‖2L3‖Δc‖L3≤C‖n‖2L3(‖∇Δc‖23L2‖∇c‖13L2+‖∇c‖L2)≤C‖n‖2L3(‖∇Δc‖23L2+1). |
From Lemma 2.2 and (3.2), it follows that
−χ2∫Ωn2Δcdx≤C(δ‖n‖2H1‖(n+1)log(n+1)‖L1+p(δ−1)‖n‖L1)23(‖∇Δc‖23L2+1)≤C(δ‖n‖2H1+p(δ−1))23(‖∇Δc‖23L2+1)≤C(δ‖n‖43H1‖∇Δc‖23L2+δ‖n‖43H1+p23(δ−1)‖∇Δc‖23L2+p23(δ−1))≤δ‖∇Δc‖2L2+Cδ12‖n‖2H1+C−1/2δp(δ−1). |
As an immediate consequence
ddt‖n‖2L2+‖n‖2H1≤δ‖∇Δc‖2L2+Cδ12‖n‖2H1+C‖n‖2L2. | (3.9) |
Applying
12ddt∫Ω|Δc|2dx+∫Ω|∇Δc|2dx+∫Ω|Δc|2dx=∫Ω∇(u∇c)∇Δcdx−∫Ω∇n∇Δcdx−∫Ω∇f∇Δcdx=I4+I5. |
For
I4=∫Ω∇(u∇c)∇Δcdx≤‖∇Δc‖L2(‖u‖L4‖Δc‖L4+‖∇u‖L4‖∇c‖L4)≤‖∇Δc‖L2(‖u‖L4‖Δc‖12L2‖∇Δc‖12L2+‖u‖L4‖Δc‖L2+‖∇u‖12L2‖Δu‖12L2‖∇c‖12L2‖Δc‖12L2+‖∇u‖L2‖∇c‖12L2‖Δc‖12L2+‖∇u‖12L2‖Δu‖12L2‖∇c‖L2+‖∇u‖L2‖∇c‖L2)≤14‖∇Δc‖2L2+C(1+‖Δc‖2L2+‖Δu‖2L2). |
For the term
I5=−∫Ω∇n∇Δcdx−∫Ω∇f∇Δcdx≤C(‖∇n‖2L2+‖∇f‖2L2)+14‖∇Δc‖2L2. |
Along with
ddt‖Δc‖2L2+‖∇Δc‖2L2+‖Δc‖2L2≤C(1+‖Δc‖2L2+‖Δu‖2L2+‖∇n‖2L2+‖∇f‖2L2). | (3.10) |
Combining (3.9) and (3.10), it follows that
ddt(‖n‖2L2+‖Δc‖2L2)+‖Δc‖2L2+(1−Cδ12)‖n‖2H1+(1−δ)‖∇Δc‖2L2≤C(1+‖Δc‖2L2+‖Δu‖2L2+‖∇n‖2L2+‖∇f‖2L2). |
By choosing
‖n‖2L2+‖Δc‖2L2+∫t0‖n‖H1dτ+∫t0‖Δc‖H1dτ≤C. |
The proof is complete.
Lemma 3.4. Assume
‖∇n‖2L2+∫t0‖n‖2H2dτ≤C. | (3.11) |
Proof. Taking the
12ddt∫Ω|∇n|2dx+∫Ω|Δn|2dx+∫Ω|∇n|2dx=∫Ωu∇nΔndx+∫Ω∇⋅(n∇c)Δndx+(1+γ)∫Ω|∇n|2dx+μ∫Ωn2Δndx=I6+I7+I8. |
For the term
I6=∫Ωu∇nΔndx=−12∫Ω∇u(∇n)2dx≤‖∇u‖L2‖∇n‖2L4≤‖∇u‖L2(‖∇n‖12L2‖Δn‖12L2+‖∇n‖L2)2≤δ‖Δn‖2L2+C‖∇n‖2L2. |
For the term
I7=∫Ω∇⋅(n∇c)Δndx=∫Ω(∇n∇c+nΔc)Δndx≤‖Δn‖L2(‖∇n‖L3‖∇c‖L6+‖n‖C‖Δc‖L2)≤C‖Δn‖L2(‖∇n‖H13‖∇c‖H1+‖n‖H43‖Δc‖L2)≤C‖n‖H2‖n‖H43‖c‖H2≤C‖n‖53H2‖n‖13L2‖c‖H2≤δ‖n‖2H2+C(δ)‖n‖2L2‖c‖6H2≤δ‖n‖2H2+C. |
For the term
I8=(1+γ)∫Ω|∇n|2dx+μ∫Ωn2Δndx=(1+γ)∫Ω|∇n|2dx−2μ∫Ω|∇n|2ndx≤(1+γ)‖∇n‖2L2. |
Combine the estimates about
ddt‖∇n‖2L2+(1−4δ)‖n‖2H2≤C‖∇n‖2L2+C. |
By taking
‖∇n‖2L2+∫t0‖n‖2H2dτ≤C. |
Therefore, this proof is complete.
Lemma 3.5. The operator
Proof. Let
F(ˆnm,ˆum)→(ˆn,ˆu) weakly in Yu×Yn and strongly in Xu×Xn. |
Let
Theorem 3.1. Let
‖n‖L∞(0,T;H1(Ω))+‖n‖L2(0,T;H2(Ω))+‖nt‖L2(0,T;L2(Ω))+‖c‖L∞(0,T;H2(Ω))+‖c‖L2(0,T;H3(Ω))+‖ct‖L2(0,T;L2(Ω))+‖u‖L∞(0,T;H1(Ω))+‖u‖L2(0,T;H2(Ω))+‖ut‖L2(0,T;L2(Ω))≤C. | (3.12) |
Proof. From Lemmas 3.1, 3.3 and 3.4, it is easy to verify the existence of solution and (3.11). Therefore, we will prove the uniqueness of the solution in the following part. For convenience, we set
nt−Δn+u1⋅∇n+u∇n2=−∇⋅(n1∇c)−∇(n∇c2)+γn−μn(n1+n2),in (0,T)×Ω≡Q, | (3.13) |
ct−Δc+u1⋅∇c+u∇c2+c=n,in (0,T)×Ω≡Q, | (3.14) |
ut−Δu+u1⋅∇u+u⋅∇u2=n∇φ,in (0,T)×Ω≡Q, | (3.15) |
∇⋅u=0,in (0,T)×Ω≡Q, | (3.16) |
∂n∂ν=∂c∂ν=0,u=0,on (0,T)×∂Ω, | (3.17) |
n0(x)=c0(x)=u0(x)=0,in Ω. | (3.18) |
Taking the
12ddt∫Ωn2dx+∫Ω|∇n|2dx+∫Ωn2dx≤−∫Ωu∇n2ndx+∫Ωn1∇c∇ndx+∫Ωn∇c2∇ndx+(1+γ)∫Ωn2dx=I9+I10+I11+I12. |
For the term
I9=−∫Ωu∇n2ndx≤‖∇n2‖L2‖u‖L4‖n‖L4≤C‖∇n2‖L2‖u‖H1(‖n‖12L2‖∇n‖12L2+‖n‖L2)≤δ3‖∇n‖2L2+C‖n‖2L2. |
For the term
I10=∫Ωn1∇c∇ndx≤‖∇n‖L2‖n1‖L4‖∇c‖L4≤C‖∇n‖L2‖n1‖H1‖∇c‖H1≤δ3‖∇n‖2L2+C. |
For the term
I11=∫Ωn∇c2∇ndx≤‖∇n‖L2‖∇c2‖L4‖n‖L4≤‖∇n‖L2‖∇c2‖H1‖n‖H1≤δ3‖∇n‖2L2+C. |
With the use of estimates
ddt‖n‖2L2+‖n‖H1≤δ‖∇n‖2L2+C‖n‖2L2+C. | (3.19) |
Taking the
12ddt∫Ωc2dx+∫Ω|∇c|2dx+∫Ωc2dx=−∫Ωu1∇ccdx−∫Ωu∇c2cdx+∫Ωncdx≤‖c‖2L4‖∇u1‖L2+‖u‖L2‖∇c2‖L4‖c‖L4+‖n‖L2‖c‖L2≤C(‖c‖12L2‖∇c‖12L2+‖c‖L2)2‖∇u1‖L2+(‖c‖12L2‖∇c‖12L2+‖c‖L2)‖u‖L2‖∇c2‖H1+‖n‖L2‖c‖L2≤δ‖∇c‖2L2+C‖c‖2L2. |
Then, we get
ddt‖c‖2L2+‖c‖H1≤δ‖∇c‖2L2+C‖c‖2L2. | (3.20) |
Taking the
12∫Ωu2dx+∫Ω|∇u|2dx=∫Ωn∇φudx. |
Straightforward calculations yield
ddt‖u‖2L2+‖u‖H1≤C(‖u‖2L2+‖n‖2L2). | (3.21) |
Then, a combination of (3.19), (3.20) and (3.21) yields
ddt(‖n‖2L2+‖c‖2L2+‖u‖2L2)+(‖n‖H1+‖c‖H1+‖u‖H1)≤δ(‖∇n‖2L2+‖∇c‖2L2+‖∇u‖2L2)+(‖n‖2L2+‖c‖2L2+‖u‖2L2)+C. |
By choosing
ddt(‖n‖2L2+‖c‖2L2+‖u‖2L2)≤C(‖n‖2L2+‖c‖2L2+‖u‖2L2)+C. |
Applying Gronwall's lemma to the resulting differential inequality, we finally obtain the uniqueness of the solution.
In this section, we will prove the existence of the optimal solution of control problem. The method we use for treating this problem was inspired by some ideas of Guillén-González et al [9]. Assume
Minimize the cost functional
J(n,c,u,f)=β12‖n−nd‖2L2(Qd)+β22‖c−cd‖2L2(Qd)+β32‖u−ud‖2L2(Qd)+β42‖n(T)−nΩ‖2L2(Ωd)+β52‖c(T)−cΩ‖2L2(Ωd)+β62‖u(T)−uΩ‖2L2(Ωd)+β72‖f(x,t)‖2L2(Qc), | (4.1) |
subject to the system (1.1). Moreover, the nonnegative constants
nd∈L2(Qd),cd∈L2(Qd),ud∈L2(Qd),nΩ∈L2(Ωc),cΩ∈L2(Ωc),uΩ∈L2(Ωc),f∈U. |
The set of admissible solutions of optimal control problem (4.1) is defined by
Sad={s=(n,c,u,f)∈H:s is a strong solution of (1.1)}. |
The function space
H=Yn×Yc×Yu×U, |
where
Now, we prove the existence of a global optimal control for problem (1.1).
Theorem 4.1. Suppose
Proof. Along with Theorem 3.1, we conduct that
limm→+∞J(nm,cm,um,fm)=inf(n,c,u,f)∈SadJ(n,c,u,f). | (4.2) |
According to the definition of
{nmt+um⋅∇nm=Δnm−∇⋅(nm⋅∇cm)+γnm−μn2m,in Q,cmt+um⋅∇cm=Δcm−cm+nm+fm,in Q,umt+um⋅∇um=Δum−∇π+nm∇φ,in Q,∇⋅um=0,in Q,∂nm∂ν|∂Ω=∂cm∂ν|∂Ω=0,um|∂Ω=0,nm(0)=n0,cm(0)=c0,um(0)=u0,in Ω. | (4.3) |
Observing that
nm→ˉn, weakly in L2(0,T;H2(Ω)) and weakly* in L∞(0,T;H1(Ω)),cm→ˉc, weakly in L2(0,T;H3(Ω)) and weakly* in L∞(0,T;H2(Ω)),um→ˉu, weakly in L2(0,T;H2(Ω)) and weakly* in L∞(0,T;H1(Ω)),fm→ˉf, weakly in L2(0,T;H1(Ωc)), and ˜f∈U. |
According to the Aubin-Lions lemma [16] and the compact embedding theorems, we obtain
nm→ˉn, strongly in C([0,T];L2(Ω))∩L2(0,T;H1(Ω)),cm→ˉc, strongly in C([0,T];H1(Ω))∩L2(0,T;H2(Ω)),um→ˉu, strongly in C([0,T];L2(Ω))∩L2(0,T;H1(Ω)). |
Since
∇⋅(nm∇cm)→χ, weakly in L2(0,T;L2(Ω)). |
Recalling that
nm∇cm→ˉn∇ˉc, weakly in L∞(0,T;L2(Ω)). |
Therefore, we get that
limm→+∞J(nm,cm,um,fm)=inf(u,c,u,f)∈SadJ(u,c,u,f)≤J(ˉn,ˉc,ˉu,ˉf). |
On the other hand, we deduce from the weak lower semicontinuity of the cost functional
J(ˉn,ˉc,ˉu,ˉf)≤lim infm→+∞J(nm,cm,um,fm). |
Therefore, this implies that
In order to derive the first-order necessary optimality conditions for a local optimal solution of problem (4.1). To this end, we will use a result on existence of Lagrange multipliers in Banach spaces ([20]). First, we discuss the following problem
minJ(s) subject to s∈S={s∈H:G(s)∈N}, | (5.1) |
where
A+={ρ∈X′:⟨ρ,a⟩X′≥0,∀a∈A}. |
We consider the following Banach spaces
X=Vn×Vc×Vu×L2(0,T;H1(Ωc)),Y=L2(Q)×L2(0,T;H1(Ω))×L2(Q)×H1(Ω)×H2(Ω)×H1(Ω), |
where
Vn={n∈Yn:∂n∂ν on (0,T)×∂Ω},Vc={n∈Yc:∂c∂ν on (0,T)×∂Ω},Vu={n∈Yu:u=0 on (0,T)×∂Ω and ∇⋅u=0 in (0,T)×Ω} |
and the operator
G1:X→L2(Q),G2:X→L2(0,T;H1(Ω)),G3:X→L2(Q),G4:X→H1(Ω),G5:X→H2(Ω),G6:X→H1(Ω), |
which are defined at each point
{G1=nt+u⋅∇n−Δn+∇⋅(n⋅∇c)−γn+μn2,G2=ct+u⋅∇c−Δc+c−n−f,G3=ut+u⋅∇u−Δu+∇π−n∇φ,G4=n(0)−n0,G5=c(0)−c0,G6=u(0)−u0. | (5.2) |
The function spaces are given as follows
H=Vn×Vc×Vu×U. |
We see that
minJ(s) subject to s∈Sad={s∈H:G(s)=0}. | (5.3) |
Taking the differentiability of
Lemma 5.1. The functional
J′(ˉs)[r]=β1∫T0∫Ωd(ˉn−nd)˜ndxdt+β2∫T0∫Ωd(ˉc−cd)˜cdxdt+β3∫T0∫Ωd(ˉu−ud)˜u(T)dxdt+β4∫Ωd(ˉn(T)−nΩ)˜n(T)dx+β5∫Ωd(ˉc(T)−cΩ)˜cdx+β6∫Ωd(ˉu(T)−uΩ)˜u(T)dx+β7∫T0∫Ωdˉf˜fdxdt. | (5.4) |
Lemma 5.2. The operator
G′(ˉs)[r]=(G′1(ˉs)[r],G′2(ˉs)[r],G′3(ˉs)[r],G′4(ˉs)[r],G′5(ˉs)[r],G′6(ˉs)[r]) |
defined by
{G′1(ˉs)[r]=˜nt−Δ˜n+ˉu⋅∇˜n+˜u∇ˉn+∇⋅(ˉn∇˜c)+∇(˜n∇ˉc)−γ˜n+2μ˜nˉn,inQ,G′2(ˉs)[r]=˜ct−Δ˜c+ˉu⋅∇˜c+˜u⋅∇ˉc+˜c−˜n−˜f,inQ,G′3(ˉs)[r]=˜ut−Δ˜u+ˉu⋅∇˜u+˜u⋅∇ˉu−˜n∇φ,inQ,∇⋅˜u=0,inQ,∂˜n∂ν=∂˜c∂ν=0,˜u=0,on(0,T)×∂Ω,˜n(0)=˜n0,˜c(0)=˜c0,˜u(0)=˜u0,inΩ. |
Lemma 5.3. Let
Proof. For any fixed
{˜nt−Δ˜n+ˉu⋅∇˜n+˜u∇ˉn+∇⋅(ˉn∇˜c)+∇(˜n∇ˉc)−γ˜n+2μ˜nˉn=gn,in Q,˜ct−Δ˜c+ˉu⋅∇˜c+˜u⋅∇ˉc+˜c−˜n=gc,in Q,˜ut−Δ˜u+ˉu⋅∇˜u+˜u⋅∇ˉu−˜n∇φ=gu,in Q,∇⋅˜u=0,in Q,∂˜n∂ν=∂˜c∂ν=0,˜u=0,on (0,T)×∂Ω,˜n(0)=˜n0,˜c(0)=˜c0,˜u(0)=˜u0,in Ω. | (5.5) |
Next, we use Leray-Schauder's fixed point method to prove the existence of solutions of the problem (5.5), the operator
{˜nt−Δ˜n+ˉu⋅∇˜n+˜u∇ˉn+∇⋅(ˉn∇˜c)+∇(˜n∇ˉc)−γ˜n+2μ˙nˉn=gn,in Q,˜ct−Δ˜c+ˉu⋅∇˜c+˜u⋅∇ˉc+˜c−˙n=gc,in Q,˜ut−Δ˜u+ˉu⋅∇˜u+˙u⋅∇ˉu−˙n∇φ=gu,in Q. | (5.6) |
The system (5.6) is complemented by the corresponding Neumann boundary and initial conditions. Similar to the proof of Lemmas 2.3, 2.4, 2.5 and 2.6, we conduct that operator
Similar to the proof of Theorem 3.1,
{˜nt−Δ˜n+˜n=−ˉu⋅∇˜n−˜u⋅∇ˉn−∇⋅(ˉn∇˜c)−∇(˜n∇ˉc)+α(γ+1)˜n−2μ˜nˉn+αgn,in Q,˜ct−Δ˜c+˜c=−ˉu⋅∇˜c−˜u⋅∇ˉc+α˜n+αgc,in Q,˜ut−Δ˜u=−ˉu⋅∇˜u−˜u⋅∇ˉu+α˜n∇φ+αgu,in Q, | (5.7) |
complemented by the corresponding Neumann boundary and initial conditions.
Taking the
12∫Ω˜u2dx+∫Ω|∇˜u|2dx=α∫Ω˜n∇φ˜udx+α∫Ω˜ugudx. |
By the Poincaré inequality and Young's inequality, we have
ddt‖˜u‖2L2+‖˜u‖2H1≤C(‖˜n‖2L2+‖gu‖2L2)+C‖˜u‖2L2. | (5.8) |
Taking the
12∫Ω˜c2dx+∫Ω|∇˜c|2dx+∫Ω˜c2dx=∫Ω˜u∇ˉc˜cdx+α∫Ω˜n˜cdx+α∫Ωgc˜cdx. |
With the Poincaré inequality and Young's inequality in hand, we see that
ddt‖˜c‖2L2+‖˜c‖2H1≤C(‖˜n‖2L2+‖gc‖2L2)+C‖˜c‖2L2. | (5.9) |
Taking the
12∫Ω|∇˜c|2dx+∫Ω|Δ˜c|2dx+∫Ω|∇˜c|2dx=∫Ω˜u∇ˉcΔ˜cdx+∫Ωˉu∇˜cΔ˜cdx−α∫Ω˜nΔ˜cdx−α∫ΩgcΔ˜cdx=J1+J2+J3. |
For the term
J1=∫Ω˜u∇ˉcΔ˜cdx≤‖Δ˜c‖L2‖∇ˉc‖L4‖˜u‖L4≤16‖Δ˜c‖2L2+C‖∇ˉc‖2H1‖˜u‖2H1. |
For the term
J2=∫Ωˉu∇˜cΔ˜cdx=−12∫Ω∇ˉu|∇˜c|2dx≤‖∇ˉu‖L2‖∇˜c‖2L4≤‖∇ˉu‖L2(‖∇˜c‖12L2‖Δ˜c‖12L2+‖∇˜c‖L2)≤16‖Δ˜c‖2L2+C‖∇˜c‖2L2. |
For the term
J3=−α∫Ω˜nΔ˜cdx−α∫ΩgcΔ˜cdx≤16‖Δ˜c‖2L2+C(‖˜n‖2L2+‖gc‖2L2). |
Therefore, combining
ddt‖∇˜c‖2L2+‖∇˜c‖2H1≤C‖∇˜c‖2L2+C(‖˜n‖2L2+‖gc‖2L2). | (5.10) |
Taking the
ddt∫Ω˜n2dx+∫Ω|∇˜n|2dx+∫Ω˜n2dx=−∫Ω˜u∇ˉn˜ndx+∫Ω∇˜nˉn∇˜cdx+∫Ω∇˜n˜n∇ˉcdx+α(γ+1)∫Ω˜n2dx+2μ∫Ωˉn˜n2dx+α∫Ω˜ngndx=J4+J5+J6+J7. |
For the term
J4=−∫Ω˜u∇ˉn˜ndx≤‖˜u‖L4‖∇ˉn‖L2‖˜n‖L4≤C(‖∇˜u‖12L2‖˜u‖12L2+‖˜u‖L2)‖∇ˉn‖L2‖˜n‖H1≤δ‖˜n‖2H1+C‖∇˜u‖L2‖˜u‖L2+C‖˜u‖2L2≤δ‖˜n‖2H1+δ‖∇˜u‖2L2+C‖˜u‖2L2. |
For the term
J5=∫Ω∇˜nˉn∇˜cdx≤‖∇˜n‖L2‖ˉn‖L4‖∇˜c‖L4≤‖∇˜n‖L2‖ˉn‖H1(‖∇˜c‖12L2‖Δ˜c‖12L2+‖∇˜c‖L2)≤δ‖∇˜n‖2L2+‖∇˜c‖L2‖Δ˜c‖L2+C‖∇˜c‖2L2≤δ‖∇˜n‖2L2+δ‖Δ˜c‖L2+C‖∇˜c‖2L2. |
For the term
J6=∫Ω∇˜n˜n∇ˉcdx≤‖˜n‖2L4‖Δˉc‖L2≤(‖˜n‖12L2‖∇˜n‖12L2+‖˜n‖L2)‖Δˉc‖L2≤δ‖∇˜n‖2L2+C‖˜n‖2L2+C. |
For the term
J7=α(γ+1)∫Ω˜n2dx+2μ∫Ωˉn˜n2dx+α∫Ω˜ngndx≤(γ+1)‖˜n‖2L2+‖gn‖L2‖˜n‖L2+‖ˉn‖L2‖˜n‖2L4≤(γ+1)‖˜n‖2L2+‖gn‖L2‖˜n‖L2+‖ˉn‖L2(‖˜n‖12L2‖∇˜n‖12L2+‖˜n‖L2)≤δ‖∇˜n‖L2+C‖˜n‖2L2+C‖gn‖2L2. |
Therefore, by choosing
ddt‖˜n‖2L2+‖˜n‖2H1≤C(‖˜n‖2L2+‖∇˜c‖2L2+‖˜u‖2L2)+δ‖Δ˜c‖L2+δ‖∇˜u‖2L2+C‖gn‖2L2. | (5.11) |
By choosing
ddt(‖˜n‖2L2+‖˜c‖2H1+‖˜u‖2L2)+‖˜n‖2H1+‖˜c‖2H2+‖˜u‖2H1≤C(‖gn‖2L2+‖gc‖2L2+‖gu‖2L2)+C(‖˜n‖2L2+‖˜c‖2H1+‖˜u‖2L2). |
Applying Gronwall's lemma to the resulting differential inequality, we obatin
‖˜n‖2L2+‖˜c‖2H1+‖˜u‖2L2+∫t0‖˜n‖2H1dτ+∫t0‖˜c‖2H2dτ+∫t0‖˜u‖2H1dτ≤C. | (5.12) |
Taking the
12ddt∫Ω|∇˜u|2dx+∫Ω|Δ˜u|2dx=∫Ωˉu⋅∇˜uΔ˜udx+∫Ω˜u⋅∇ˉuΔ˜udx−α∫Ω˜n∇φΔ˜udx−α∫ΩguΔ˜udx=J8+J9+J10. |
With the use of the Gagliardo-Nirenberg interpolation inequality, we derive
J8=∫Ωˉu⋅∇˜uΔ˜udx≤‖ˉu‖L4‖∇˜u‖L4‖Δ˜u‖L2≤‖ˉu‖H1(‖∇˜u‖12L2‖Δ˜u‖12L2+‖∇˜u‖L2)‖Δ˜u‖L2≤δ‖Δ˜u‖2L2+C‖∇˜u‖2L2 |
and
J9=∫Ω˜u⋅∇ˉuΔ˜udx≤‖Δ˜u‖L2‖∇ˉu‖L4‖˜u‖L4≤C‖Δ˜u‖L2‖∇ˉu‖H1(‖∇˜u‖12L2‖˜u‖12L2+‖˜u‖L2)≤δ‖Δ˜u‖2L2+C‖∇˜u‖2L2. |
For the term
J10=α∫Ω˜n∇φΔ˜udx−α∫ΩguΔ˜udx≤δ‖Δ˜u‖2L2+C(‖˜n‖2L2+‖gu‖2L2). |
By choosing
ddt‖∇˜u‖2L2+‖Δ˜u‖2L2≤C‖∇˜u‖2L2+C‖gu‖2L2. | (5.13) |
Applying
12ddt∫Ω|Δc|2dx+∫Ω|∇Δc|2dx+∫Ω|Δc|2dx=−∫Ω∇(ˉu∇˜c)∇Δ˜cdx−∫Ω∇(˜u∇ˉc)∇Δ˜cdx+α∫Ω∇˜n∇Δ˜cdx+α∫Ω∇gc∇Δ˜cdx=J11+J12+J13. |
For the first term
J11=−∫Ω∇(ˉu∇˜c)∇Δ˜cdx=−∫Ω∇ˉu∇˜c∇Δ˜cdx−∫ΩˉuΔ˜c∇Δ˜cdx≤‖∇Δ˜c‖L2‖∇ˉu‖L4‖∇˜c‖L4+‖∇Δ˜c‖L2‖ˉu‖L4‖Δ˜c‖L4≤‖∇Δ˜c‖L2(‖∇ˉu‖12L2‖Δˉu‖12L2+‖∇ˉu‖L2)(‖∇ˉc‖12L2‖Δˉc‖12L2+‖∇ˉc‖L2)+‖∇Δ˜c‖L2‖ˉu‖H1(‖∇Δ˜c‖12L2‖Δ˜c‖12L2+‖Δ˜c‖L2)≤δ‖∇Δ˜c‖2L2+C‖Δˉu‖2L2+C‖Δ˜c‖2L2. |
Similarly, for the term
J12=−∫Ω∇(˜u∇ˉc)∇Δ˜cdx=−∫Ω∇˜u∇ˉc∇Δ˜cdx−∫Ω˜uΔˉc∇Δ˜cdx≤‖∇Δ˜c‖L2‖∇˜u‖L4‖∇ˉc‖L4+‖˜u‖L4‖Δˉc‖L4‖∇Δ˜c‖L2≤C‖∇Δ˜c‖L2(‖∇˜u‖12L2‖Δ˜u‖12L2+‖∇˜u‖L2)‖∇ˉc‖H1+(‖˜u‖12L2‖∇˜u‖12L2+‖˜u‖L2)(‖Δˉc‖12L2‖∇Δˉc‖12L2+‖Δˉc‖L2)‖∇Δ˜c‖L2≤δ‖∇Δ˜c‖2L2+δ‖Δ˜u‖2L2+C‖∇Δˉc‖2L2+C‖∇˜u‖2L2. |
For the rest term
J13=α∫Ω∇˜n∇Δ˜cdx+α∫Ω∇gc∇Δ˜cdx≤δ‖∇Δ˜c‖2L2+C(‖∇˜n‖2L2+‖∇gc‖2L2). |
By choosing
ddt‖Δ˜c‖2L2+‖Δ˜c‖2H1≤C(‖∇˜n‖2L2+‖Δ˜c‖2L2+‖∇˜u‖2L2)+C‖Δˉu‖2L2+δ‖Δ˜u‖2L2+C‖∇Δˉc‖2L2+C‖∇gc‖2L2. | (5.14) |
From (5.13) and (5.14), along with
ddt(‖∇˜u‖2L2+‖Δ˜c‖2L2)+‖Δ˜u‖2L2+‖Δ˜c‖2H1≤C(‖∇˜u‖2L2+‖Δ˜c‖2L2)+(‖∇˜n‖2L2+‖Δˉu‖2L2+‖∇Δˉc‖2L2+‖∇gc‖2L2)+C‖gu‖2L2. |
Applying Gronwall's lemma to the resulting differential inequality, we know
‖∇˜u‖2L2+‖Δ˜c‖2L2+∫t0‖Δ˜u‖2L2dτ+∫t0‖Δ˜c‖2H1dτ≤C. |
Taking the
12ddt∫Ω|∇˜n|2dx+∫Ω|Δ˜n|2dx+∫Ω|∇˜n|2dx=−∫Ωˉu⋅∇˜nΔ˜ndx−∫Ω˜u⋅∇ˉnΔ˜ndx−∫Ω∇(˜n∇ˉc)Δ˜ndx−∫Ω∇(ˉn∇˜c)Δ˜ndx−α(1+γ)∫Ω˜nΔ˜ndx+2μ∫Ω˜nˉnΔ˜ndx−α∫ΩgnΔ˜ndx=J14+J15+J16+J17+J18. |
With the Gagliardo-Nirenberg interpolation inequality in hand, we can estimate
Similar to above estimates, we see
Similarly, we derive
and
For the rest terms, we know
Therefore, Taking
Applying Gronwall's lemma to the resulting differential inequality, we know
Therefore, from Leray-Schauder theorem, we derive the existence of solution for (5.5). Along with the regularity of
Theorem 5.1. Assume that
(5.15) |
where
Proof. With the Lemma 5.3 in hand, we get that
for all
Corollary 5.1. Assume that
(5.16) |
(5.17) |
(5.18) |
which corresponds to the linear system
(5.19) |
subject to the following boundary and final conditions
and the following identities hold
(5.20) |
Proof. By taking
By choosing
Theorem 5.2. Under the assumptions of Theorem 5.1, system (5.19) has a unique weak solution such that
Proof. For convenience, we set
(5.21) |
subject to the following boundary and final conditions
Following an analogous reasoning as in the proof of Lemma 5.3, we omit the process and just give a number of a priori estimates as follows.
Taking the
Then, we have
(5.22) |
Taking the
Thus, we get
(5.23) |
Taking the
As an immediate consequence, we obtain
(5.24) |
Taking the
Therefore, we see that
(5.25) |
Combining (5.22)-(5.25) and taking
Applying Gronwall's lemma to the resulting differential inequality, we know
The proof is complete.
The authors would like to express their deep thanks to the referee's valuable suggestions for the revision and improvement of the manuscript.
[1] | A. Al Alam, A. Gattami, K. H. Johansson, An experimental study on the fuel reduction potential of heavy duty vehicle platooning, 13th international IEEE conference on intelligent transportation systems, IEEE, Funchal, Portugal, (2010), 306–311. https://doi.org/10.1109/ITSC.2010.5625054 |
[2] |
J. Alam A. Martensson, K. H. Johansson, Experimental evaluation of decentralized cooperative cruise control for heavy-duty vehicle platooning, Control Eng. Pract., 38 (2015), 11–25. https://doi.org/10.1016/j.conengprac.2014.12.009 doi: 10.1016/j.conengprac.2014.12.009
![]() |
[3] |
J. Alonso, V. Milanés, J. Pérez, E. Onieva, C. González, T. de Pedro, Autonomous vehicle control systems for safe crossroads, Transp. Res. Part C Emerg. Technol., 19 (2011), 1095–1110. https://doi.org/10.1016/j.trc.2011.06.002 doi: 10.1016/j.trc.2011.06.002
![]() |
[4] | T. Ard, F. Ashtiani, A. Vahidi, H. Borhan, Optimizing gap tracking subject to dynamic losses via connected and anticipative mpc in truck platooning, American Control Conference (ACC), IEEE, Denver, CO, USA, (2020), 2300–2305. https://doi.org/10.23919/ACC45564.2020.9147849 |
[5] |
M. Athans, A unified approach to the vehicle-merging problem, Transp. Res., 3 (1969), 123–133. https://doi.org/10.1016/0041-1647(69)90109-9 doi: 10.1016/0041-1647(69)90109-9
![]() |
[6] | T. C. Au, P. Stone, Motion planning algorithms for autonomous intersection management, Bridging the gap between task and motion planning, AAAI press, (2010), 2–9. https://dl.acm.org/doi/abs/10.5555/2908515.2908516 |
[7] |
H. Bang, B. Chalaki, A. A. Malikopoulos, Combined optimal routing and coordination of connected and automated vehicles, IEEE Control Syst. Lett., 6 (2022), 2749–2754. https://doi.org/10.1109/LCSYS.2022.3176594 doi: 10.1109/LCSYS.2022.3176594
![]() |
[8] |
L. E. Beaver, B. Chalaki, A. M. Mahbub, L. Zhao, R. Zayas, A. A. Malikopoulos, Demonstration of a time-efficient mobility system using a scaled smart city, Veh. Syst. Dyn., 58 (2020), 787–804. https://doi.org/10.1080/00423114.2020.1730412 doi: 10.1080/00423114.2020.1730412
![]() |
[9] |
L. E. Beaver, A. A. Malikopoulos, Constraint-driven optimal control of multi-agent systems: A highway platooning case study, IEEE Control Syst. Lett., 6 (2022), 1754–1759. https://doi.org/10.1109/LCSYS.2021.3133801 doi: 10.1109/LCSYS.2021.3133801
![]() |
[10] | C. Bergenhem, S. Shladover, E. Coelingh, C. Englund, S. Tsugawa, Overview of platooning systems, Proceedings of the 19th ITS World Congress, Vienna, Austria, 2012. |
[11] |
B. Besselink, K. H. Johansson, String stability and a delay-based spacing policy for vehicle platoons subject to disturbances, IEEE Trans. Autom. Control, 62 (2017), 4376–4391. https://doi.org/10.1109/TAC.2017.2682421 doi: 10.1109/TAC.2017.2682421
![]() |
[12] |
A. K. Bhoopalam, N. Agatz, R. Zuidwijk, Planning of truck platoons: A literature review and directions for future research, Transp. Res. Part B Methodol., 107 (2018), 212–228. https://doi.org/10.1016/j.trb.2017.10.016 doi: 10.1016/j.trb.2017.10.016
![]() |
[13] | A. E. Bryson, Y. C. Ho, Applied optimal control: optimization, estimation and control, CRC Press, 1975. |
[14] |
B. Chalaki, L. E. Beaver, A. M. I. Mahbub, H. Bang, A. A. Malikopoulos, A research and educational robotic testbed for real-time control of emerging mobility systems: From theory to scaled experiments, IEEE Control Syst. Mag., 42 (2022), 20–34. https://doi.org/10.1109/MCS.2022.3209056 doi: 10.1109/MCS.2022.3209056
![]() |
[15] | B. Chalaki, L. E. Beaver, A. A. Malikopoulos, Experimental validation of a real-time optimal controller for coordination of cavs in a multi-lane roundabout, 2020 IEEE Intelligent Vehicles Symposium (IV), IEEE, Las Vegas, NV, USA, (2020), 775–780. https://doi.org/10.1109/IV47402.2020.9304531 |
[16] |
B. Chalaki, A. A. Malikopoulos, Time-optimal coordination for connected and automated vehicles at adjacent intersections, IEEE Trans. Intell. Transp. Syst., 23 (2022), 13330–13345. https://doi.org/10.1109/TITS.2021.3123479 doi: 10.1109/TITS.2021.3123479
![]() |
[17] |
B. Chalaki, A. A. Malikopoulos, Optimal control of connected and automated vehicles at multiple adjacent intersections, IEEE Trans. Control Syst. Technol., 30 (2022), 972–984. https://doi.org/10.1109/TCST.2021.3082306 doi: 10.1109/TCST.2021.3082306
![]() |
[18] |
B. Chalaki, A. A. Malikopoulos, A priority-aware replanning and resequencing framework for coordination of connected and automated vehicles, IEEE Control Syst. Lett., 6 (2022), 1772–1777. https://doi.org/10.1109/LCSYS.2021.3133416 doi: 10.1109/LCSYS.2021.3133416
![]() |
[19] | B. Chalaki, A. A. Malikopoulos, Robust learning-based trajectory planning for emerging mobility systems, 2022 American Control Conference (ACC), IEEE, Atlanta, GA, USA, (2022), 2154–2159. https://doi.org/10.23919/ACC53348.2022.9867265 |
[20] |
X. Chang, H. Li, J. Rong, X. Zhao, A. Li, Analysis on traffic stability and capacity for mixed traffic flow with platoons of intelligent connected vehicles, Physica A, 557 (2020), 124829. https://doi.org/10.1016/j.physa.2020.124829 doi: 10.1016/j.physa.2020.124829
![]() |
[21] | A. de La Fortelle, Analysis of reservation algorithms for cooperative planning at intersections, 13th International IEEE Conference on Intelligent Transportation Systems, IEEE, Funchal, Portugal, (2010), 445–449. https://doi.org/10.1109/ITSC.2010.5624978 |
[22] | K. Dresner, P. Stone, Multiagent traffic management: A reservation-based intersection control mechanism, in Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagents Systems, IEEE Computer Society, (2004), 530–537. https://dl.acm.org/doi/10.5555/1018410.1018799 |
[23] |
K. Dresner, P. Stone, A multiagent approach to autonomous intersection management, J. Artif. Intell. Res., 31 (2008), 591–656. https://doi.org/10.1613/jair.2502 doi: 10.1613/jair.2502
![]() |
[24] |
D. J. Fagnant, K. M. Kockelman, The travel and environmental implications of shared autonomous vehicles, using agent-based model scenarios, Transp. Res. Part C Emerg. Technol., 40 (2014), 1–13. https://doi.org/10.1016/j.trc.2013.12.001 doi: 10.1016/j.trc.2013.12.001
![]() |
[25] | M. Fellendorf, P. Vortisch, Microscopic traffic flow simulator vissim, Fundamentals of Traffic Simulation, International Series in Operations Research and Management Science, Springer, New York, NY, 145 (2010), 63–93. |
[26] |
S. Feng, Y. Zhang, S. E. Li, Z. Cao, H. X. Liu, L. Li, String stability for vehicular platoon control: Definitions and analysis methods, Annu. Rev. Control, 47 (2019), 81–97. https://doi.org/10.1016/j.arcontrol.2019.03.001 doi: 10.1016/j.arcontrol.2019.03.001
![]() |
[27] | A. Ferrara, S. Sacone, S. Siri, Freeway Traffic Modeling and Control, Springer, Berlin, 2018. https://doi.org/10.1007/978-3-319-75961-6 |
[28] |
J. Guanetti, Y. Kim, F. Borrelli, Control of connected and automated vehicles: State of the art and future challenges, Annu. Rev. Control, 45 (2018), 18–40. https://doi.org/10.1016/j.arcontrol.2018.04.011 doi: 10.1016/j.arcontrol.2018.04.011
![]() |
[29] |
S. V. D. Hoef, J. Mårtensson, D. V. Dimarogonas, K. H. Johansson, A predictive framework for dynamic heavy-duty vehicle platoon coordination, ACM Trans. Cyber-Phys. Syst., 4 (2019), 1–25. https://doi.org/10.1145/3299110 doi: 10.1145/3299110
![]() |
[30] |
S. Huang, A. Sadek, Y. Zhao, Assessing the mobility and environmental benefits of reservation-based intelligent intersections using an integrated simulator, IEEE Trans. Intell. Transp. Syst., 13 (2012), 1201–1214. https://doi.org/10.1109/TITS.2012.2186442 doi: 10.1109/TITS.2012.2186442
![]() |
[31] | A. Johansson, E. Nekouei, K. H. Johansson, J. Mårtensson, Multi-fleet platoon matching: A game-theoretic approach, 2018 21st International Conference on Intelligent Transportation Systems (ITSC), IEEE, Maui, HI, USA, 2018, 2980–2985. https://doi.org/10.1109/ITSC.2018.8569379 |
[32] |
M. Kamal, M. Mukai, J. Murata, T. Kawabe, Model predictive control of vehicles on urban roads for improved fuel economy, IEEE Trans. Control Syst. Technol., 21 (2013), 831–841. https://doi.org/10.1109/TCST.2012.2198478 doi: 10.1109/TCST.2012.2198478
![]() |
[33] |
S. Karbalaieali, O. A. Osman, S. Ishak, A dynamic adaptive algorithm for merging into platoons in connected automated environments, IEEE Trans. Intell. Transp. Syst., 21 (2019), 4111–4122. https://doi.org/10.1109/TITS.2019.2938728 doi: 10.1109/TITS.2019.2938728
![]() |
[34] | P. Kavathekar, Y. Chen, Vehicle platooning: A brief survey and categorization, International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, Washington, DC, USA, (2011), 829–845. https://doi.org/10.1115/DETC2011-47861 |
[35] | V. L. Knoop, H. J. Van Zuylen, S. P. Hoogendoorn, Microscopic traffic behaviour near accidents, Transportation and Traffic Theory 2009: Golden Jubilee, Springer, Boston, MA, 2009. |
[36] | S. Kumaravel, A. A. Malikopoulos, R. Ayyagari, Decentralized cooperative merging of platoons of connected and automated vehicles at highway on-ramps, in 2021 American Control Conference (ACC), IEEE, New Orleans, LA, USA, (2021), 2055–2060. https://doi.org/10.23919/ACC50511.2021.9483390 |
[37] |
S. Kumaravel, A. A. Malikopoulos, R. Ayyagari, Optimal coordination of platoons of connected and automated vehicles at signal-free intersections, IEEE Trans. Intell. Veh., 7 (2022), 186–197. https://doi.org/10.1109/TIV.2021.3096993 doi: 10.1109/TIV.2021.3096993
![]() |
[38] |
J. Larson, K. Y. Liang, K. H. Johansson, A distributed framework for coordinated heavy-duty vehicle platooning, IEEE Trans. Intell. Transp. Syst., 16 (2015), 419–429. https://doi.org/10.1109/TITS.2014.2320133 doi: 10.1109/TITS.2014.2320133
![]() |
[39] |
W. Levine, M. Athans, On the optimal error regulation of a string of moving vehicles, IEEE Trans. Autom. Control, 11 (1966), 355–361. https://doi.org/10.1109/TAC.1966.1098376 doi: 10.1109/TAC.1966.1098376
![]() |
[40] |
J. Lioris, R. Pedarsani, F. Y. Tascikaraoglu, P. Varaiya, Platoons of connected vehicles can double throughput in urban roads, Transp. Res. Part C Emerging Technol., 77 (2017), 292–305. https://doi.org/10.1016/j.trc.2017.01.023 doi: 10.1016/j.trc.2017.01.023
![]() |
[41] | A. M. I. Mahbub, V. Karri, D. Parikh, S. Jade, A. A. Malikopoulos, A decentralized time- and energy-optimal control framework for connected automated vehicles: From simulation to field test, arXiv preprint, 2020. https://doi.org/10.48550/arXiv.1911.01380 |
[42] | A. M. I. Mahbub, V. A. Le, A. A. Malikopoulos, A safety-prioritized receding horizon control framework for platoon formation in a mixed traffic environment, arXiv preprint. https://doi.org/10.48550/arXiv.2205.10673 |
[43] |
A. M. I. Mahbub, V. A. Le, A. A. Malikopoulos, Safety-aware and data-driven predictive control for connected automated vehicles at a mixed traffic signalized intersection, IFAC-PapersOnLine, 24 (2022), 51–56. https://doi.org/10.1016/j.ifacol.2022.10.261 doi: 10.1016/j.ifacol.2022.10.261
![]() |
[44] | A. M. I. Mahbub, A. A. Malikopoulos, Concurrent optimization of vehicle dynamics and powertrain operation using connectivity and automation, arXiv preprint, 2019. https://doi.org/10.48550/arXiv.1911.03475 |
[45] | A. M. I. Mahbub, A. A. Malikopoulos, Conditions for state and control constraint activation in coordination of connected and automated vehicles, 2020 American Control Conference (ACC), IEEE, Denver, CO, USA, (2020), 436–441. https://doi.org/10.23919/ACC45564.2020.9147842 |
[46] |
A. M. I. Mahbub, A. A. Malikopoulos, A platoon formation framework in a mixed traffic environment, IEEE Control Syst. Lett., 6 (2021), 1370–1375. https://doi.org/10.1109/LCSYS.2021.3092188 doi: 10.1109/LCSYS.2021.3092188
![]() |
[47] |
A. M. I. Mahbub, A. A. Malikopoulos, Conditions to provable system-wide optimal coordination of connected and automated vehicles, Automatica, 131 (2021), 109751. https://doi.org/10.1016/j.automatica.2021.109751 doi: 10.1016/j.automatica.2021.109751
![]() |
[48] | A. M. I. Mahbub, A. A. Malikopoulos, Platoon formation in a mixed traffic environment: A model-agnostic optimal control approach, 2022 American Control Conference (ACC), IEEE, Atlanta, GA, USA, (2022), 4746–4751. https://doi.org/10.23919/ACC53348.2022.9867168 |
[49] | A. M. I. Mahbub, L. Zhao, D. Assanis, A. A. Malikopoulos, Energy-optimal coordination of connected and automated vehicles at multiple intersections, 2019 American Control Conference (ACC), IEEE, Philadelphia, PA, USA, (2019), 2664–2669. https://doi.org/10.23919/ACC.2019.8814877 |
[50] |
A. I. Mahbub, A. A. Malikopoulos, L. Zhao, Decentralized optimal coordination of connected and automated vehicles for multiple traffic scenarios, Automatica, 117 (2020), 108958. https://doi.org/10.1016/j.automatica.2020.108958 doi: 10.1016/j.automatica.2020.108958
![]() |
[51] |
A. A. Malikopoulos, A duality framework for stochastic optimal control of complex systems, IEEE Trans. Autom. Control, 18 (2016), 780–789. https://doi.org/10.1109/TAC.2015.2504518 doi: 10.1109/TAC.2015.2504518
![]() |
[52] |
A. A. Malikopoulos, L. E. Beaver, I. V. Chremos, Optimal time trajectory and coordination for connected and automated vehicles, Automatica, 125 (2021), 109469. https://doi.org/10.1016/j.automatica.2020.109469 doi: 10.1016/j.automatica.2020.109469
![]() |
[53] |
A. A. Malikopoulos, C. G. Cassandras, Y. J. Zhang, A decentralized energy-optimal control framework for connected automated vehicles at signal-free intersections, Automatica, 93 (2018), 244–256. https://doi.org/10.1016/j.automatica.2018.03.056 doi: 10.1016/j.automatica.2018.03.056
![]() |
[54] | A. A. Malikopoulos, L. Zhao, A closed-form analytical solution for optimal coordination of connected and automated vehicles, 2019 American Control Conference (ACC), IEEE, Philadelphia, PA, USA, (2019), 3599–3604. https://doi.org/10.23919/ACC.2019.8814759 |
[55] | A. A. Malikopoulos, L. Zhao, Optimal path planning for connected and automated vehicles at urban intersections, 2019 IEEE 58th Conference on Decision and Control (CDC), IEEE, Nice, France, (2019), 1261–1266. https://doi.org/10.1109/CDC40024.2019.9030093 |
[56] | R. Margiotta, D. Snyder, An agency guide on how to establish localized congestion mitigation programs, Technical report, U.S. Department of Transportation, Federal Highway Administration, 2011. |
[57] | F. Morbidi, P. Colaneri, T. Stanger, Decentralized optimal control of a car platoon with guaranteed string stability, 2013 European Control Conference (ECC), IEEE, Zurich, Switzerland, (2013), 3494–3499. https://doi.org/10.23919/ECC.2013.6669336 |
[58] |
G. J. Naus, R. P. Vugts, J. Ploeg, M. J. van De Molengraft, M. Steinbuch, String-stable cacc design and experimental validation: A frequency-domain approach, IEEE Trans. Veh. Technol., 59 (2010), 4268–4279. https://doi.org/10.1109/TVT.2010.2076320 doi: 10.1109/TVT.2010.2076320
![]() |
[59] |
I. A. Ntousakis, I. K. Nikolos, M. Papageorgiou, Optimal vehicle trajectory planning in the context of cooperative merging on highways, Transp. Res. Part C Emerging Technol., 71 (2016), 464–488. https://doi.org/10.1016/j.trc.2016.08.007 doi: 10.1016/j.trc.2016.08.007
![]() |
[60] |
M. Papageorgiou, A. Kotsialos, Freeway ramp metering: An overview, IEEE Trans. Intell. Transp. Syst., 3 (2002), 271–281. https://doi.org/10.1109/TITS.2002.806803 doi: 10.1109/TITS.2002.806803
![]() |
[61] |
H. Pei, S. Feng, Y. Zhang, D. Yao, A cooperative driving strategy for merging at on-ramps based on dynamic programming, IEEE Trans. Veh. Technol., 68 (2019), 11646–11656. https://doi.org/10.1109/TVT.2019.2947192 doi: 10.1109/TVT.2019.2947192
![]() |
[62] | N. Pourmohammad Zia, F. Schulte, R. R. Negenborn, Platform-based platooning to connect two autonomous vehicle areas, 2020 IEEE 23rd International Conference on Intelligent Transportation Systems (ITSC), IEEE, Rhodes, Greece, (2020), 1–6. https://doi.org/10.1109/ITSC45102.2020.9294689 |
[63] |
R. Rajamani, H. S. Tan, B. K. Law, W. B. Zhang, Demonstration of integrated longitudinal and lateral control for the operation of automated vehicles in platoons, IEEE Trans. Control Syst. Technol., 8 (2000), 695–708. https://doi.org/10.1109/87.852914 doi: 10.1109/87.852914
![]() |
[64] |
J. Rios-Torres, A. A. Malikopoulos, A survey on coordination of connected and automated vehicles at intersections and merging at highway on-ramps, IEEE Trans. Intell. Transp. Syst., 18 (2017), 1066–1077. https://doi.org/10.1109/TITS.2016.2600504 doi: 10.1109/TITS.2016.2600504
![]() |
[65] |
J. Rios-Torres, A. A. Malikopoulos, Automated and cooperative vehicle merging at highway on-ramps, IEEE Trans. Intell. Transp. Syst., 18 (2017), 780–789. https://doi.org/10.1109/TITS.2016.2587582 doi: 10.1109/TITS.2016.2587582
![]() |
[66] | B. Schrank, B. Eisele, T. Lomax, 2019 Urban Mobility Scorecard, Technical report, Texas A and M Transportation Institute, 2019. |
[67] | M. Shida, T. Doi, Y. Nemoto, K. Tadakuma, A short-distance vehicle platooning system: 2nd report, evaluation of fuel savings by the developed cooperative control, in Proceedings of the 10th International Symposium on Advanced Vehicle Control (AVEC), KTH Royal Institute of Technology Loughborough, United Kingdom, (2010), 719–723. |
[68] |
S. E. Shladover, C. A. Desoer, J. K. Hedrick, M. Tomizuka, J. Walrand, W. B. Zhang, et al., Automated vehicle control developments in the PATH program, IEEE Trans. Veh. Technol., 40 (1991), 114–130. https://doi.org/10.1109/25.69979 doi: 10.1109/25.69979
![]() |
[69] | S. Singh, Critical reasons for crashes investigated in the National Motor Vehicle Crash Causation Survey. (Traffic Safety Facts Crash Stats.), Technical Report, 2018. |
[70] | K. Spieser, K. Treleaven, R. Zhang, E. Frazzoli, D. Morton, M. Pavone, Toward a systematic approach to the design and evaluation of automated mobility-on-demand systems: A case study in singapore, Road vehicle automation, Springer, Cham, (2014), 229–245. |
[71] | S. S. Stanković, M. J. Stanojević, D. D. Šiljak, Decentralized suboptimal lqg control of platoon of vehicles, Proc. 8th IFAC/IFIP/IFORS Symp. Transp. Syst., 1 (1997) 83–88. |
[72] | C. Tang, Y. Li, Consensus-based platoon control for non-lane-discipline connected autonomous vehicles considering time delays, 2018 37th Chinese Control Conference (CCC), IEEE, Wuhan, (2018), 7713–7718. https://doi.org/10.23919/ChiCC.2018.8484016 |
[73] |
S. Tsugawa, An overview on an automated truck platoon within the energy its project, IFAC Proc. Volumes, 46 (2013), 41–46. https://doi.org/10.3182/20130904-4-JP-2042.00110 doi: 10.3182/20130904-4-JP-2042.00110
![]() |
[74] |
A. Tuchner, J. Haddad, Vehicle platoon formation using interpolating control, IFAC-PapersOnLine, 48 (2015), 414–419. https://doi.org/10.1016/j.ifacol.2015.09.492 doi: 10.1016/j.ifacol.2015.09.492
![]() |
[75] | A. Valencia, A. M. I. Mahbub, A. A. Malikopoulos, Performance analysis of optimally coordinated connected automated vehicles in a mixed traffic environment, 2022 30th Mediterranean Conference on Control and Automation (MED), IEEE, Vouliagmeni, Greece, (2022), 1053–1058. https://doi.org/10.1109/MED54222.2022.9837281 |
[76] |
S. Van De Hoef, K. H. Johansson, D. V. Dimarogonas, Fuel-efficient en route formation of truck platoons, IEEE Trans. Intell. Transp. Syst., 19 (2017), 102–112. https://doi.org/10.1109/TITS.2017.2700021 doi: 10.1109/TITS.2017.2700021
![]() |
[77] |
P. Varaiya, Smart cars on smart roads: Problems of control, IEEE Trans. Autom. Control, 38 (1993), 195–207. https://doi.org/10.1109/9.250509 doi: 10.1109/9.250509
![]() |
[78] |
Z. Wadud, D. MacKenzie, P. Leiby, Help or hindrance? the travel, energy and carbon impacts of highly automated vehicles, Transp. Res. Part A Policy Pract., 86 (2016), 1–18. https://doi.org/10.1016/j.tra.2015.12.001 doi: 10.1016/j.tra.2015.12.001
![]() |
[79] | Z. Wang, G. Wu, P. Hao, K. Boriboonsomsin, M. Barth, Developing a platoon-wide eco-cooperative adaptive cruise control (cacc) system, 2017 ieee intelligent vehicles symposium (iv), IEEE, Los Angeles, CA, USA, (2017), 1256–1261. https://doi.org/10.1109/IVS.2017.7995884 |
[80] | R. Wiedemann, Simulation des Strassenverkehrsflusses, PhD thesis, Universität Karlsruhe, Karlsruhe, 1974. |
[81] |
W. Xiao, C. G. Cassandras, Decentralized optimal merging control for connected and automated vehicles with safety constraint guarantees, Automatica, 123 (2021), 109333. https://doi.org/10.1016/j.automatica.2020.109333 doi: 10.1016/j.automatica.2020.109333
![]() |
[82] | X. Xiong, E. Xiao, L. Jin, Analysis of a stochastic model for coordinated platooning of heavy-duty vehicles, 2019 IEEE 58th Conference on Decision and Control (CDC), IEEE, Nice, France, (2019), 3170–3175. https://doi.org/10.1109/CDC40024.2019.9029179 |
[83] | F. Xu, T. Shen, Decentralized optimal merging control with optimization of energy consumption for connected hybrid electric vehicles, IEEE Trans. Intell. Transp. Syst.. https://doi.org/10.1109/TITS.2021.3054903 |
[84] |
L. Xu, W. Zhuang, G. Yin, C. Bian, H. Wu, Modeling and robust control of heterogeneous vehicle platoons on curved roads subject to disturbances and delays, IEEE Trans. Veh. Technol., 68 (2019), 11551–11564. https://doi.org/10.1109/TVT.2019.2941396 doi: 10.1109/TVT.2019.2941396
![]() |
[85] | S. Yao, B. Friedrich, Managing connected and automated vehicles in mixed traffic by human-leading platooning strategy: A simulation study, in 2019 IEEE Intelligent Transportation Systems Conference (ITSC), IEEE, Auckland, New Zealand, (2019), 3224–3229. https://doi.org/10.1109/ITSC.2019.8917007 |
[86] |
L. Zhang, F. Chen, X. Ma, X. Pan, Fuel economy in truck platooning: A literature overview and directions for future research, J. Adv. Transp., 2020 (2020). https://doi.org/10.1155/2020/2604012 doi: 10.1155/2020/2604012
![]() |
[87] |
Y. Zhang, C. G. Cassandras, Decentralized optimal control of connected automated vehicles at signal-free intersections including comfort-constrained turns and safety guarantees, Automatica, 109 (2019), 108563. https://doi.org/10.1016/j.automatica.2019.108563 doi: 10.1016/j.automatica.2019.108563
![]() |
1. | Shenxing Li, Wenhe Li, Dynamical Behaviors of a Stochastic Susceptible-Infected-Treated-Recovered-Susceptible Cholera Model with Ornstein-Uhlenbeck Process, 2024, 12, 2227-7390, 2163, 10.3390/math12142163 |