Abstract
We model the operation of a dockless bicycle-sharing system by two groups of interacting components, bicycles on a sidewalk and users of the system. The model illustrates the bicycle-sharing system by a nonlinear evolutionary equation about the density of bikes on the sidewalk. Users’ behaviours, which are some straightforward and necessary actions, determine coefficients of the nonlinear evolutionary equation. Some nontrivial solutions to the equation show that even if every user has no malice, and the environment is stable, it is still possible that heaps of shared-bicycles appear somewhere along the road. Based on the data of heaps, parameters of users’ psychological models can be obtained. A numerical simulation shows how to calculate features of users and change the supply of bicycles into the system.
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29 March 2022
A Correction to this paper has been published: https://doi.org/10.1007/s12652-022-03831-y
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Acknowledgements
We would like to extend sincere gratitude to two anonymous reviewers for their careful comments and inspired suggestions that have helped improve this paper substantially. This work is supported by national natural science foundation of China (Grants no. 11991023 and no. 11771352), Research achievement Cultivation Fund of Northwest University, and fundamental research funds for the central universities.
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Appendices
Appendix 1 Proof of Lemma 1
Proof
For any u, the numerator f(u) is positive and it does not influence the sign of f(u). We consider the denominator \(\phi (u)\) of f(u):
As \(0<\eta < \gamma \alpha ^{-2}\), it is obvious that \(\phi (0)<0\). Moreover, \(\phi (\infty )=\eta >0\). And for \(u>0\), \(\phi '(u)=\gamma u \exp (-\alpha u)>0\). So there is a unique \(B>0\) such that \(\phi (B)=0\) and for \(u\in [0, B)\), \(\phi (u)<0\). Then the result of 1) follows.
We write \(g(u)=f(u)\exp (\alpha u)\). It follows from
and (37) that
Therefore
Notice that it follows from 1) that for \(u\in [0,B)\), the above function is not zeros at u and hence (36) follows. That is, f is a solution to (37) on [0, B).
As f(u) is continuous at any \(u\in [0,B)\), (38) is a proper definition to F(u). It follows from \(f(u)<0\) that F(u) is decreasing. From its definition, we have that \(F(0)=0\). Finally, to prove that \(F(B-0)=-\infty \), we only need to prove that for some \(\delta >0\),
Now we study
where \(\phi (u)\) is given in (39). As for \(u>0\), \(\phi '(u)=\gamma u \exp (-\alpha u)>0\),
Moreover, it follows from \(f(B-0)=-\infty \) that \(1/f(B-0)=0\). Therefore, there is a constant C and \(\delta >0\) such that for \(u\in [B-\delta , B]\)
and hence \(f(u) \le C^{-1}(u-B)^{-1}\). So we can obtain
Appendix 2 Proof of Theorem 3
.
We write \(\alpha =\frac{2v\beta ^2}{\sigma ^2\lambda _0^2}>0\), \(\gamma =\frac{2\beta }{\sigma ^2}>0\) and let \(\eta \) be a positive number such that \(\eta < \gamma \alpha ^{-2}\). It follows from 3) of Lemma 1 that F has an inverse \(F^{-1}: (-\infty , 0] \rightarrow [0, B)\) such that \(F^{-1}(-\infty )= B\) and \(F^{-1}(0)= 0\). We write
We will show that u(t, y) given by (34) satisfies (10) at any (t, y) such that \(\lambda _0 y+v\beta t\ne 0\).
Let \(k=v\beta /\lambda _0\). It is clear that \(u_t(t,y)=ku_y(t,y)\) for \(\lambda _0 y+v\beta t\ne 0\). Substituting \(u_t(t,y)=ku_y(t,y)\) into (10), we have
And hence
where C is a constant.
We will show that for \(C=0\), (50) has two solutions: \(u(t,y)=0\) and \(u(t,y)=F^{-1}\left( y+\frac{v\beta }{\lambda _0}t\right) \) and hence u(t, y) given by (34) is a weak solution to (50). It is clear that \(u(t,y)=0\) is a trivial solution. Substituting \(b(u,u_y)\) given in (33) into (50) and notice \(C=0\), we have that \(\bar{u}(y)=u(0,y)\) satisfies
The coefficient of \(\bar{u}\) in the above (51) is \(-\lambda _0k+v\beta =0\), that follows from \(k=v\beta /\lambda _0\), and the coefficient of \(\bar{u}_y\) is \(-k^2+v^2\beta ^2\lambda _0^{-2}=0\). Hence (51) yields
Consider the inverse \(y=y(\bar{u})\) of \(\bar{u}=\bar{u}(y)\). Substituting
into (52), we have that
Let \(f(\bar{u})=y_{\bar{u}}\), then we have
As \(\alpha =\frac{2v\beta ^2}{\sigma ^2\lambda _0^2}\) and \(\gamma =\frac{2\beta }{\sigma ^2}\), the above (55) and (37) is the same one. It follows from Lemma 1 that \(y(\bar{u})=F(\bar{u})\). Therefore \(\bar{u}=F^{-1}(y)\) is a solution to (51), and hence \(u(t,y)=F^{-1}\left( y+\frac{v\beta }{\lambda _0}t\right) \) is a solution to (50).
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Liu, J., Ma, WX. & Duan, Q. A nonlinear evolutionary equation modelling a dockless bicycle-sharing system. J Ambient Intell Human Comput 14, 10431–10440 (2023). https://doi.org/10.1007/s12652-022-03700-8
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DOI: https://doi.org/10.1007/s12652-022-03700-8