Abstract
Vehicle lane-changing and overtaking are fundamental technology in autonomous driving. This paper proposes an approach that combines guidance navigation and image based visual detection for road following and overtaking maneuver. Two critical issues are considered: Firstly, it is suggested to design a robust constrained road following based line of sight guidance in the presence of unknown time-varying sideslip angle and under unknown dynamic model. Secondly, to trigger the autonomous overtaking manoeuvre. An overtaking procedure is defined as a high-priority task while the road following as a low-priority task. The objective is then to properly switching between the two guidance modes according to the camera vision reading. The adopted control strategy consists of a constrained along and cross-track control law and a nonlinear RISE control law. The closed-loop dynamics of both kinematic errors and the dynamical errors are analyzed in detail using nonlinear interconnected systems theory and the overall system is shown to be input to state stable (ISS). The proposed approach for road following and overtaking are validated in simulations.
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Appendices
Appendix: A
To prove Lemma 1, we will introduce the following tan-type BLF [22], in order to take into account the constraint requirement on the safety distance D(t) that separates the host vehicle from the preceding vehicle:
Taking the time derivative of VG with respect to time, by letting \(s_{\cos \limits }=\frac {s}{\cos \limits ^{2}\left (\frac {\pi s^{2}}{2D^{2}}\right )}\) we obtain
by choosing the control gains (22) and (23), we obtain
Using the following inequalities:
to show that |g|≤ U and the fact that \(ge\tilde {\psi }\leq \frac {U}{2\varepsilon _{1}}\vert e\vert ^{2}+\frac {\varepsilon _{1}U}{2}|\tilde {\psi }|^{2}\), where ε1 is any arbitrary value such that \(1-\frac {1}{2\varepsilon _{1}}>0\), the following holds
where \(C=\min \limits \{k_{2}-2({k_{1}^{2}}-k_{c}), 2\max \limits (U)\}\). From (45), it can be inferred that for all \(\mu =(s,e)^{\top } \in {\mathscr{M}}:=\{\mu \in \mathbb {R}^{2}~|~\frac {1}{2}CV_{G}\geq \gamma (|\psi |)\}\), with γ(.) is \(\mathcal {K}_{\infty }\) function, we have
By the comparison lemma in [23], it follows immediately that for all \(\mu _{0} \in {\mathscr{M}}\), there exists a \(\mathcal {K}{\mathscr{L}}\) function ς such that VG(μ) ≤ ς(VG(μ0), t). Also for all μ such that \(\frac {1}{2}CV_{G}\leq \gamma (|\psi |)\), we have \(V_{g}(\mu )\leq \frac {1}{C}\left (2\gamma (\sup _{\lambda \in [t_{0},t]}|\psi (\lambda )|)\right )\), combining the two inequalities, we arrive at \(V(\mu (t))\leq \max \limits \{\varsigma (V_{G}(\mu _{0}),t),\frac {1}{C}\left (2\gamma (\sup _{\lambda \in [t_{0},t]}|\psi (\lambda )|)\right )\}\), which shows that VG is an ISS-Lyapunov function and thus the closed-loop kinematic tracking error (25) is ISS w.r.t to the entry \(\tilde {\psi }\).
Appendix: B
To prove Lemma 2, first the open-loop tracking error dynamics is developed by taking the time derivative of the filtering error r and using the dynamics (27) and (28) to obtain
where the auxiliary terms \(\tilde {N}(\chi ,\dot {\chi },e,\chi _{r},\dot {\chi }_{r})\in \mathbb {R}^{4}\) and \(N_{d}(\chi _{r},\dot {\chi }_{r},\dot {u})\in \mathbb {R}^{4}\) are defined as
and
The segregated terms (48) and (49) are motivated by the fact that these terms can be upper bounded by state-dependent terms and upper bounded by constants respectively [11] as follows:
where \(\boldsymbol {z}=[\boldsymbol {e}^{\top },\boldsymbol {r}^{\top }]^{\top } \in \mathbb {R}^{8}\) and ρ0, ρ1 are positive upper bound constants. Substituting the reference steering angle δref designed as (29) in the open-loop dynamics (47), yields the following closed-loop dynamics:
To show the stability of the closed-loop dynamics (51), let VD(e, r) be a continuously differentiable, positive-definite function defined as
Taking the time derivative of (52) along the solutions of (51) and using the upper bounds (50), to obtain
If kr satisfies the sufficient gain condition in (31), then the last term in (53) becomes strictly negative, which implies that \(\dot {V}_{D}\) can be upper bounded as
By completing the squares, the upper bound in (54) can be expressed in a more convenient form. To this end, the term \(\frac {{\rho _{0}^{2}}}{4{k_{3}^{2}}}\Vert \boldsymbol {z}\Vert ^{2}\) is added then subtracted to the right-hand side of (54), yields
where the fact that z⊤diag{z} is positive provided that the condition on the gain k3 is satisfied and verifies (31), from the definition of VD in (52) using (55), it follows that \(\dot {V}_{D}\leq -\lambda V_{D}\), hence it can be concluded that \(\Vert \boldsymbol {e}\Vert \leq \Vert \boldsymbol {z}(0)\Vert \exp \left (-\frac {\lambda }{2}t\right ), \forall t\in [0,\infty )\). This implies that Uy converges to Uyd as time goes to infinity. Also \(\dot {\psi }\) converges to \(\dot {\bar {\psi }}\) which consequently implies that ψ converges to ψd as time goes to infinity.
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Osman, K., Ghommam, J. & Saad, M. Guidance Based Lane-Changing Control in High-Speed Vehicle for the Overtaking Maneuver. J Intell Robot Syst 98, 643–665 (2020). https://doi.org/10.1007/s10846-019-01070-6
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DOI: https://doi.org/10.1007/s10846-019-01070-6