Model Predictive Control of Vehicles on Urban Roads for Improved Fuel Economy

By Md Abdus Samad Kamal, Masakazu Mukai, Junichi Murata, Taketoshi Kawabe. IEEE Transactions on Control Systems Technology, 2013

409 citations recorded by the source corpus.

Subfields: Automotive Engineering, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/94ae0c2b3f62b84b4090c7ba28d25bb5554b78bb

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Automotive Engineering

1. Ardalan Vahidi
2. Antonio Sciarretta

In Control and Systems Engineering

1. Markos Papageorgiou
2. Ardalan Vahidi
3. Antonio Sciarretta

Citations in the corpus

• Energy saving potentials of connected and automated vehicles (2018, methodology): “fuel economy via polynomial metamodel in [74] yield reported gain for merging period only &merge”
• Automated and Cooperative Vehicle Merging at Highway On-Ramps (2017, neutral): “For the latter, we use the polynomial metamodel proposed in [58] that yields vehicle fuel consumption as a function of the speed, v , and control input, where estimates the fuel consumed by a vehicle traveling at a constant speed v ( t ) , and ˙ f accel = u ( t ) · ( r is the additional fuel…”
• A platoon based cooperative eco-driving model for mixed automated and human-driven vehicles at a signalised intersection (2018, methodology): “Kamal et al. (2013) predicted the dynamics of the preceding vehicle based on the information from inter-vehicle communication and considered the signal status of the upcoming intersections to compute the optimal vehicle control input for fuel economy by an MPC method.”