The DOI matches its Crossref record; 29 of the 29 references it cites were found in a registry or an index.
A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection
Abstract
Abstract The advancements in communication and sensing technologies can be exploited to assist the drivers in making better decisions. In this paper, we consider the design of a real-time cooperative eco-driving strategy for a group of vehicles with mixed automated vehicles (AVs) and human-driven vehicles (HVs). The lead vehicles in the platoon can receive the signal phase and timing information via vehicle-to-infrastructure (V2I) communication and the traffic states of both the preceding vehicle and current platoon via vehicle-to-vehicle (V2V) communication. We propose a receding horizon model predictive control (MPC) method to minimise the fuel consumption for platoons and drive the platoons to pass the intersection on a green phase. The method is then extended to dynamic platoon splitting and merging rules for cooperation among AVs and HVs in response to the high variation in urban traffic flow. Extensive simulation tests are also conducted to demonstrate the performance of the model in various conditions in the mixed traffic flow and different penetration rates of AVs. Our model shows that the cooperation between AVs and HVs can further smooth out the trajectory of the latter and reduce the fuel consumption of the entire traffic system, especially for the low penetration of AVs. It is noteworthy that the proposed model does not compromise the traffic efficiency and the driving comfort while achieving the eco-driving strategy.
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Cites
Dynamical model of traffic congestion and numerical simulation
Bando, M., Hasebe, K., Nakayama, A., Shibata, A., & Sugiyama, Y. (1995) · Physical Review E · doi:10.1103/physreve.51.1035 · Cited by 3,013
SNOPT: An SQP Algorithm for Large-Scale Constrained Optimization
Gill, P. E., Murray, W., & Saunders, M. A. (2005) · SIAM Review · doi:10.1137/s0036144504446096 · Cited by 2,834
Generalized force model of traffic dynamics
Helbing, D., & Tilch, B. (1998) · Physical Review E · doi:10.1103/physreve.58.133 · Cited by 1,169
Asadi, B., & Vahidi, A. (2011) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2010.2047860 · Cited by 727
Rao, A. V., Benson, D. A., Darby, C., Patterson, M. A., Francolin, C., Sanders, I., & Huntington, G. T. (2010) · ACM Transactions on Mathematical Software · doi:10.1145/1731022.1731032 · Cited by 651
Using connected vehicle technology to improve the efficiency of intersections
Ilgin Guler, S., Menendez, M., & Meier, L. (2014) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2014.05.008 · Cited by 481
Model Predictive Control of Vehicles on Urban Roads for Improved Fuel Economy
Kamal, M. A. S., Mukai, M., Murata, J., & Kawabe, T. (2013) · IEEE Transactions on Control Systems Technology · doi:10.1109/tcst.2012.2198478 · Cited by 449
A multivariable regulator approach to traffic-responsive network-wide signal control
Diakaki, C., Papageorgiou, M., & Aboudolas, K. (2002) · Control Engineering Practice · doi:10.1016/s0967-0661(01)00121-6 · Cited by 438
Self-citationJiang, H., Hu, J., An, S., Wang, M., & Park, B. B. (2017) · Transportation Research Part C: Emerging Technologies · doi:10.1016/j.trc.2017.04.001 · Cited by 337
Optimal vehicle trajectory planning in the context of cooperative merging on highways
Ntousakis, I. A., Nikolos, I. K., & Papageorgiou, M. (2016) · Transportation Research Part C Emerging Technologies · doi:10.1016/j.trc.2016.08.007 · Cited by 316
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A Survey on Cooperative Longitudinal Motion Control of Multiple Connected and Automated Vehicles
Wang, Z., Bian, Y., Shladover, S. E., Wu, G., Li, S. E., & Barth, M. J. (2020) · IEEE Intelligent Transportation Systems Magazine · doi:10.1109/mits.2019.2953562 · Cited by 316
Metadata
- Authors
- Zhao, W., Ngoduy, D., Shepherd, S., Liu, R., & Papageorgiou, M.
- Venue
- Transportation Research Part C: Emerging Technologies
- Publisher
- Elsevier BV
- Published
- 2018-10
- Volume
- 95
- Pages
- 802-821
- ISSN
- 0968-090X (ISSN-L)
- OpenAlex
- W2884394246
- Cited by
- 357
- References
- 29
- FWCI
- 13.96
- Type
- journal article
- Language
- en
- Open access
- closed
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- Zhao, W., Ngoduy, D., Shepherd, S., Liu, R., & Papageorgiou, M. (2018). A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection. Transportation Research Part C: Emerging Technologies. https://doi.org/10.1016/j.trc.2018.05.025
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