Name
Abstract | ||
|---|---|---|
This work investigates the incorporation of a risk metric based on time to collision for Adaptive Cruise Control applications on multi-lane motorways. To improve the fuel-efficiency and safety, a stochastic model predictive control approach is suggested that limits the violation probability of the imposed risk metric. For this reason, a Bayesian network is used to predict the probability distributions of the surrounding vehicles' future motion based on actual measurements. Subsequently, these distribution functions are incorporated into a stochastic model predictive control algorithm. The novel strategy is evaluated in simulation using an artificial evaluation cycle and shows significant improvements in terms of fuel efficiency and safety in comparison to conventional Adaptive Cruise Control when sharp cut-off maneuvers occur. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CCTA.2017.8062524 | 2017 IEEE Conference on Control Technology and Applications (CCTA) |
Keywords | Field | DocType |
multilane motorways,safety,Bayesian network,probability distributions,distribution functions,stochastic model predictive control algorithm,fuel efficiency,Adaptive Cruise Control applications,stochastic model predictive control,risk metric,vehicles,risk constrained control,violation probability,sharp cut-off maneuvers | Risk metric,Cruise control,Control theory,Model predictive control,Stochastic process,Bayesian network,Probability distribution,Time to collision,Engineering,Fuel efficiency | Conference |
ISBN | Citations | PageRank |
978-1-5090-2183-3 | 0 | 0.34 |
References | Authors | |
8 | 3 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Dominik Moser | 1 | 4 | 0.87 |
| Luigi del Re | 2 | 131 | 31.55 |
| Stephen Jones | 3 | 5 | 1.21 |