Urban traffic Eco-Driving: Speed advisory tracking

The evaluation of the benefits of an Eco-Driving assistance system is carried out in the urban environment in presence of traffic lights. The traffic evolution is modeled macroscopically with the Urban Variable-Length Model [1] in a variable speed limits framework. Under the assumption of equal boundary flows, the vehicles in a road section dispose themselves according to well defined equilibrium conditions which are dependent on the traveling speed in the free-flow part of the section. Given certain initial traffic conditions, an optimal speed limit for the section can be found in order to drive the system to an efficient equilibrium state. Further analysis of the equilibrium conditions and the stability properties of the system is conducted in this work. The system is proved to be controllable, under the working hypotheses, and a controller is designed to simulate the response of the drivers compliant to the eco-speed advisory. A sub-optimal control strategy is finally proposed also in the case of unequal boundary flows.

[1]  A Schadschneider,et al.  Optimizing traffic lights in a cellular automaton model for city traffic. , 2001, Physical review. E, Statistical, nonlinear, and soft matter physics.

[2]  Carlos Canudas de Wit,et al.  A New Variable-length Cell Model for Traffic Systems , 2014 .

[3]  Carlos Canudas de Wit,et al.  Best-effort highway traffic congestion control via variable speed limits , 2011, IEEE Conference on Decision and Control and European Control Conference.

[4]  Markos Papageorgiou,et al.  Store-and-forward based methods for the signal control problem in large-scale congested urban road networks , 2009 .

[5]  Bart De Schutter,et al.  Optimal coordination of variable speed limits to suppress shock waves , 2005, IEEE Transactions on Intelligent Transportation Systems.

[6]  M J Wooldridge,et al.  Fuel saving and other benefits of dynamic advisory speeds on a multilane arterial road , 1984 .

[7]  Markos Papageorgiou,et al.  ALINEA: A LOCAL FEEDBACK CONTROL LAW FOR ON-RAMP METERING , 1990 .

[8]  Andreas Hegyi,et al.  SPECIALIST: A dynamic speed limit control algorithm based on shock wave theory , 2008, 2008 11th International IEEE Conference on Intelligent Transportation Systems.

[9]  J. Archer,et al.  The Impact of Lowered Speed Limits in Urban/Metropolitan Areas , 2008 .

[10]  Riccardo Minciardi,et al.  A macroscopic traffic model for real-time optimization of signalized urban areas , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[11]  Carlos F. Daganzo,et al.  Urban Gridlock: Macroscopic Modeling and Mitigation Approaches , 2007 .

[12]  Bart De Schutter,et al.  Efficient network-wide model-based predictive control for urban traffic networks , 2012 .

[13]  Bart De Schutter,et al.  Constrained optimal steady-state control for isolated traffic intersections , 2010, Control Theory and Technology.

[14]  P. Olver Nonlinear Systems , 2013 .

[15]  Carlos Canudas de Wit,et al.  Urban traffic Eco-Driving: A macroscopic steady-state analysis , 2014, 2014 European Control Conference (ECC).

[16]  Bart De Schutter,et al.  Integrated Model Predictive Traffic and Emission Control Using a Piecewise-Affine Approach , 2013, IEEE Transactions on Intelligent Transportation Systems.

[17]  Bart De Schutter,et al.  Model predictive control for freeway traffic using discrete speed limit signals , 2013, 2013 European Control Conference (ECC).

[18]  R S Trayford,et al.  FUEL ECONOMY INVESTIGATION OF DYNAMIC ADVISORY SPEEDS FROM AN EXPERIMENT IN ARTERIAL TRAFFIC , 1984 .