Fuel efficiency

Algorithm

Control (management)

Harmonization

Engineering

Transport engineering

Aerospace engineering

Real-time computing

Constraint (computer-aided design)

Computer science

Acoustics

Electronic speed control

Classical mechanics

Geology

Oceanography

Mechanical engineering

Physics

Simulation

Testbed

Mathematics

Automotive engineering

Artificial intelligence

Geometry

Acceleration

Speed limit

Control theory (sociology)

Baseline (sea)

Reduction (mathematics)

Electrical engineering

IEEE Transactions on Intelligent Transportation Systems

This paper addresses the problem of controlling the speed of a number of automated vehicles before they enter a speed reduction zone on a freeway. We formulate the control problem and provide an analytical, closed-form solution that can be implemented in real time. The solution yields the optimal acceleration/deceleration of each vehicle under the hard safety constraint of rear-end collision avoidance. The effectiveness of the solution is evaluated through a microscopic simulation testbed and it is shown that the proposed approach significantly reduces both fuel consumption and travel time. In particular, for three different traffic volume levels, fuel consumption for each vehicle is reduced by 19-22% compared to the baseline scenario, in which human-driven vehicles are considered, by 12-17% compared to the variable speed limit algorithm, and by 18-34% compared to the vehicular-based speed harmonization (SPD-HARM) algorithm. Similarly, travel time is improved by 26-30% compared to the baseline scenario, by 3-19% compared to the VSL algorithm, and by 31-39% compared to the vehicular-based SPD-HARM algorithm.

Optimal Control for Speed Harmonization of Automated Vehicles