Identification of human skill and its application to an automatic driving system - an approach from hybrid dynamical system

Automatic driving of trains can significantly reduce the energy cost and enhance the operating efficiency and safety. The automatic train driving system has to be an embedded system that can run onboard with low power, which necessitates an efficient inference model. In this article, a level-wise driving knowledge induction approach is proposed for embedded automatic train driving systems. The coincident driving patterns in the records of drivers with different experience levels suggest the suitability of a driving experience knowledge rule induction approach. We design a two-level learning approach to obtain both the driving experience pattern in fuzzy rule-based knowledge form and the detailed parameters of velocity and gear by regression learning methods. With 8.93% energy consumption reduction compared with average human drivers, the experiments indicate the effectiveness of our approach.

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Mathematical Analysis of an Epidemic-Species Hybrid Dynamical System

Mathematical Problems in Engineering ◽

10.1155/2014/810312 ◽

2014 ◽

Vol 2014 ◽

pp. 1-11 ◽

Cited By ~ 2

Author(s):

Jing Hui ◽

Jian-Hua Pang ◽

Dong-Rong Lin

Keyword(s):

Dynamical System ◽

Hopf Bifurcation ◽

Local Stability ◽

Orbital Stability ◽

Species Hybrid ◽

Hybrid Dynamical System ◽

Mathematical Analyses ◽

Existence Of Equilibria ◽

Impulsive Releasing ◽

Infected Prey

We consider an epidemic-species hybrid dynamical system. The disease is spread among the prey only and the infected prey can reproduce virus. The predator only eats the infected prey. Mathematical analyses are given for the system with regard to the existence of equilibria, local stability, Hopf bifurcation, and the orbital stability of the Hopf bifurcating limit cycle. We further analyse the system under impulsive releasing of virus and predator.

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Pathogen evolution in switching environments: A hybrid dynamical system approach

Mathematical Biosciences ◽

10.1016/j.mbs.2012.06.004 ◽

2012 ◽

Vol 240 (1) ◽

pp. 70-75 ◽

Cited By ~ 2

Author(s):

József Z. Farkas ◽

Peter Hinow ◽

Jan Engelstädter

Keyword(s):

Dynamical System ◽

System Approach ◽

Hybrid Dynamical System ◽

Pathogen Evolution ◽

Dynamical System Approach

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Automatic driving system of plant protection robot based on differential GPS

Automatic Control, Mechatronics and Industrial Engineering ◽

10.1201/9780429468605-4 ◽

2019 ◽

pp. 23-29

Author(s):

X.M. Xia ◽

C.S. Ai ◽

Y.C. Du

Keyword(s):

Plant Protection ◽

Differential Gps ◽

Driving System ◽

Automatic Driving

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Research on Automatic Train Driving Based on Fuzzy Proportion Integration Differentiation Iterative Control

E3S Web of Conferences ◽

10.1051/e3sconf/202128302021 ◽

2021 ◽

Vol 283 ◽

pp. 02021

Author(s):

Zhengsheng Qi ◽

Bohong Liu ◽

Mengmeng Wang

Keyword(s):

High Speed ◽

Convergence Condition ◽

Vital Role ◽

Fuzzy Pid ◽

Parameter Uncertainties ◽

Efficient Operation ◽

Transportation Services ◽

Driving System ◽

Automatic Driving ◽

Iterative Control

Automatic train driving system is an important subsystem of train operation control system, which can provide passengers with punctual, accurate, efficient and fast transportation services. At the same time, the accurate stop, comfort and stability of the train is an important index to measure the control performance of the train automatic driving system, and the accurate stop plays a vital role in the efficient operation of the train. Based on the characteristics of high-speed train parking, an accurate parking algorithm based on fuzzy PID iterative control was proposed to solve the problem of low parking accuracy caused by frequent switching of control output. On the basis of solving the differential equation of the train braking model, the gradient of the system is obtained, and then the learning parameters of the convergence condition are obtained to overcome the repeated uncertainty in the stopping stage. The simulation results show that the fuzzy PID iterative control for asymptotic stability is an effective method to realize the precise parking of trains, and has strong robustness against the train parameter uncertainties and external disturbances.

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Influences of Single-Lane Automatic Driving Systems on Traffic Efficiency and CO2 Emissions on China’s Motorways

Applied Sciences ◽

10.3390/app112211032 ◽

2021 ◽

Vol 11 (22) ◽

pp. 11032

Author(s):

Haokun Song ◽

Fuquan Zhao ◽

Zongwei Liu

Keyword(s):

Co2 Emissions ◽

Penetration Rate ◽

Connected Vehicles ◽

Driving System ◽

Traffic Efficiency ◽

Automatic Driving ◽

Driving Behaviors ◽

Road Capacity ◽

Long Time ◽

Carbon Dioxide Co2

There are big differences between the driving behaviors of intelligent connected vehicles (ICVs) and traditional human-driven vehicles (HVs). ICVs will be mixed with HVs on roads for a long time in the future. Different intelligent functions and different driving styles will affect the condition of traffic flow, thereby changing traffic efficiency and emissions. In this paper, we focus on China’s expressways and secondary motorways, and the impacts of the ‘single-lane automatic driving system’ (SLADS) on traffic delay, road capacity and carbon dioxide (CO2) emissions were studied under different ICV penetration rates. Driving styles were regarded as important factors for scenario analysis. We found that with higher volume input, SLADS has an optimizing effect on traffic efficiency and CO2 emissions generally, which will be more significant as the ICV penetration rate increases. Additionally, enhancing the aggressiveness of driving behavior appropriately is an effective way to amplify the benefits of SLADS.

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