@article{(Open Science Index):https://publications.waset.org/pdf/10010008,
	  title     = {Energy Benefits of Urban Platooning with Self-Driving Vehicles},
	  author    = {Eduardo F. Mello and  Peter H. Bauer},
	  country	= {},
	  institution	= {},
	  abstract     = {The primary focus of this paper is the generation of
energy-optimal speed trajectories for heterogeneous electric vehicle
platoons in urban driving conditions. Optimal speed trajectories are
generated for individual vehicles and for an entire platoon under
the assumption that they can be executed without errors, as would
be the case for self-driving vehicles. It is then shown that the
optimization for the “average vehicle in the platoon” generates similar
transportation energy savings to optimizing speed trajectories for
each vehicle individually. The introduced approach only requires the
lead vehicle to run the optimization software while the remaining
vehicles are only required to have adaptive cruise control capability.
The achieved energy savings are typically between 30% and 50%
for stop-to-stop segments in cities. The prime motivation of urban
platooning comes from the fact that urban platoons efficiently utilize
the available space and the minimization of transportation energy in
cities is important for many reasons, i.e., for environmental, power,
and range considerations.},
	    journal   = {International Journal of Transport and Vehicle Engineering},
	  volume    = {13},
	  number    = {2},
	  year      = {2019},
	  pages     = {94 - 100},
	  ee        = {https://publications.waset.org/pdf/10010008},
	  url   	= {https://publications.waset.org/vol/146},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 146, 2019},
	}