Project Description

Carmakers are racing to develop self-driving cars to use in fleets of robo-taxis in order to tap into this potentially lucrative new market. The successful deployment of robo-taxis crucially depends
on the profit of the ride-sharing fleet operating companies, and how efficiently the resources are used by these companies. The goal of proposed research is to provide theoretical foundations and
a unifying framework for control of autonomous fleet providers. 

Start Date

05/01/2019

Postdoc Qualifications

PhD in Electrical Engineering, Computer Science, Math, Statistics, OR, or related areas. 

Co-advisors

Vaneet Aggarwal, IE, vaneet@purdue.edu, https://engineering.purdue.edu/CLANLabs

Shweta Singh, ABE, singh294@purdue.edu, https://sites.google.com/site/shwetasinghlab/ 

References

1. M. Zhu, X.-Y. Liu, F. Tang, M. Qiu, R. Shen, W. Shu, and M.-Y. Wu, “Public vehicles for future urban transportation,” IEEE transactions on intelligent transportation systems, vol. 17, no. 12, pp. 3344–3353, 2016.

2. N. Agatz, A. Erera, M. Savelsbergh, and X. Wang, “Optimization for dynamic ride-sharing: A review,” European Journal of Operational Research, vol. 223, no. 2, pp. 295–303, 2012.

3. S. Chawla, J. D. Hartline, D. L. Malec, and B. Sivan, “Multi-parameter mechanism design and sequential posted pricing,” in Proceedings of the forty-second ACM symposium on Theory of computing. ACM, 2010, pp. 311–320.

4. A. Ghosh and V. Aggarwal, “Control of charging of electric vehicles through menu-based pricing,” IEEE Transactions on Smart Grid, vol. PP, no. 99, pp. 1–1, 2017.

5. B. J. Coltin and M. Veloso, “Towards ridesharing with passenger transfers,” in Proceedings of the 2013 International Conference on Autonomous Agents and Multi-agent Systems, ser. AAMAS ’13.