Fei Xie's research while affiliated with China Automotive Engineering Research Institute and other places

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Publications (5)

Burgers and mKdV equation for car-following model considering drivers’ characteristics on a gradient highway
Article
  • Aug 2018
In this paper, we propose a new car-following model considering driver's timid and aggressive characteristics on a gradient highway. Based on the control theory, the linear stability analysis of the model was conducted. It shows that the stability of traffic flow on the gradient highway varies with the drivers' characteristics and the slope. Adopti...
Distributed robust $${{\varvec{H}}}_{\varvec{\infty }}$$H∞ control of connected eco-driving system with time-varying delay and external disturbances in the vicinity of traffic signals
Article
  • Mar 2018
In order to improve traffic efficiency and reduce fuel consumption and CO\(_{2}\) emission, most existing models are considered as an optimization problem. However, these models cannot provide a satisfactory solution when nonlinear time-varying system and external disturbances are investigated for connected vehicles in the vicinity of traffic signa...
The schematic diagram of the vehicle platoon.
Velocity variation of all vehicles for manual driving.
The snapshots of the velocity of all vehicles at different times for...
Velocity variation of all vehicles for automated driving.
+3 The snapshots of the velocity of all vehicles at different times for...
Switched Cooperative Driving Model towards Human Vehicle Copiloting Situation: A Cyberphysical Perspective
Article
Full-text available
  • Feb 2018
Development of highly automated and intelligent vehicles can lead to the reduction of driver workload. However, it also causes the out-of-the-loop problem to drivers, which leaves drivers handicapped in their ability to take over manual operations in emergency situations. This contribution puts forth a new switched driving strategy to avoid some of...

Citations

... Milan é s et al. [25] proposed a car-following model that uses adaptive cruise control and cooperative adaptive cruise control technology, considering parameters such as the error between the headway and the expected headway, the headway error weight, the speed difference weight and the differential weight of the headway. For non-planar road scenarios, Sun et al. [26] proposed a suitable car-following model suitable that considers the driver's uncertainty characteristics. Li et al. [27] explored the effect of a two-sided lateral gap with uncertain velocity on the stability of the traffic flow on a curved road. ...
Reference: Modeling and Analysis of Car-Following for Intelligent Connected Vehicles Considering Expected Speed in Helical Ramps
... These studies have focused on using the longitudinal dynamics of a vehicle to estimate the vehicle mass. Most current techniques for estimating vehicle mass rely on longitudinal and lateral vehicle dynamic models [4][5][6][7][8][9][10][11][12]. ...
Reference: Simultaneous Estimation of Vehicle Mass and Unknown Road Roughness Based on Adaptive Extended Kalman Filtering of Suspension Systems
... Because the vicinity of traffic signals can provide the functions such as gathering, steering and evacuation for traffic flows, the vehicles drive and stop periodically in this area with the change of traffic signals. It is easy to decline the performance of cooperative driving, reduce traffic efficiency, increase energy consumption and even lead to traffic accidents (such as rear-end collision) due to internal uncertainties, external perturbations, delays and other factors [27][28][29][30][31][32]. ...
Reference: Robust control for cooperative driving system of heterogeneous vehicles with parameter uncertainties and communication constraints in the vicinity of traffic signals
... The following lemma is helpful to the conclusion of this paper: Lemma 1. [40] For any constant matrix Z > 0, scalar 2 > 1 ≥ 0, ≠ 0 and vector function x ∶ [t − 2 , t − 1 ] → ℝ n , one has ...
Reference: Cyber‐physical description and CPS‐based pinning approach of mixed traffic