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Pangwei Wang

Bio: Pangwei Wang is an academic researcher from North China University of Technology. The author has contributed to research in topics: Collision avoidance & Collision. The author has an hindex of 1, co-authored 2 publications receiving 4 citations.

Papers
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Journal ArticleDOI
TL;DR: In this paper, a cooperative collision avoidance (CCA) model was developed to improve the effectiveness of the collision avoidance system of connected vehicles by using a combination of following vehicle deceleration and leading vehicle acceleration.
Abstract: Connected vehicle technology exchanges real-time vehicle and traffic information through vehicle-to-vehicle and vehicle-to-infrastructure communication. The technology has the potential to improve traffic safety applications such as collision avoidance. In this paper, a novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed. Unlike traditional collision avoidance models, which relied mainly on emergency braking, the proposed CCA approach avoided collision through a combination of following vehicle deceleration and leading vehicle acceleration. Through spacing policy theory and nonlinear optimization, the model calculated the desired deceleration rate for the following vehicle and the acceleration rate for the leading vehicle, respectively, at each time interval. The CCA approach was then tested on a scaled platform with hardware-in-the-loop simulation embedded with MATLAB/Simulink and a car simulator pack...

4 citations

01 Jan 2017
TL;DR: A novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed and shown that the proposed model can effectively avoid rear-end collisions in a three-vehicle platoon.
Abstract: Connected vehicle technology exchanges real-time vehicle and traffic information through vehicle-to-vehicle and vehicle-to-infrastructure communication. The technology has the potential to improve traffic safety applications such as collision avoidance. In this paper, a novel cooperative collision avoidance (CCA) model that could improve the effectiveness of the collision avoidance system of connected vehicles was developed. Unlike traditional collision avoidance models, which relied mainly on emergency braking, the proposed CCA approach avoided collision through a combination of following vehicle deceleration and leading vehicle acceleration. Through spacing policy theory and nonlinear optimization, the model calculated the desired deceleration rate for the following vehicle and the acceleration rate for the leading vehicle, respectively, at each time interval. The CCA approach was then tested on a scaled platform with hardware-in-the-loop simulation embedded with MATLAB/Simulink and a car simulator package, CarSim. Results show that the proposed model can effectively avoid rear-end collisions in a three-vehicle platoon.

1 citations


Cited by
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Journal ArticleDOI
TL;DR: A joint control model is developed which optimizing the speeds of the connected vehicles and coordinating signals along an arterial simultaneously to achieve lower signal delay and higher throughput.

37 citations

Journal ArticleDOI
TL;DR: In this article , a distributed model predictive control (MPC) algorithm is proposed for connected vehicle platoon with a focus on switching communication topologies and control strategy under abnormal communications, which can effectively achieve group consensus, improve vehicular running safety and increase road capacity.
Abstract: Vehicular platoon control can effectively achieve group consensus, improve vehicular running safety and increase road capacity. However, some constraints exist in practical situations due to the limitations of traffic environment in time-varying metrics (time-delay, packet-dropout or interruption) in wireless communication systems. In this work, a distributed model predictive control (MPC) algorithm is proposed for connected vehicle platoon with a focus on switching communication topologies and control strategy under abnormal communications. Firstly, the predecessor-leader following is selected as the basic communication topology, by which the switching communication topology and the desired vehicle spacing policy are established. Secondly, the platoon control algorithm of connected vehicles is established and a set of constraints is analyzed. Thirdly, the ${\mathcal{ L}}_{2} $ -norm string stability criterion and the asymptotic stability criterion are considered within the proposed MPC. Finally, a co-simulation platform for connected vehicle platoon is developed based on Prescan/Matlab/V2X communication simulator. In addition, the platoon control algorithm is tested in three traffic scenarios including normal communication, leading vehicle with abnormal communication and following vehicle with abnormal communication. The experiments demonstrate that the communication topologies in different communication environments can be switched well in real time through the proposed platoon control algorithm. In addition, the string stability, the consistency of vehicle spacing, speed and acceleration are proven to be guaranteed simultaneously.

17 citations

Journal ArticleDOI
TL;DR: Simulation and road test experiment results demonstrate that the proposed method is effective to avoid rear-end collision by emergency steering manoeuvre and some aspects, like vehicle lateral stability, emergency manoeuvre selection and simultaneously emergency manoeuvres are discussed as well in this work to apply this collision avoidance method into practical application.
Abstract: Rear end collision is one hazard accident for an autonomous vehicle. Emergency braking has already been deeply researched and applied into some new model vehicles to avoid rear-end collision or mitigate its impacts. Emergency steering is another promising method to enhance vehicle safety; this kind of collision avoidance approach remains to be carefully studied. To fill this gap, this work proposes an emergency steering based rear-end collision avoidance approach concerning required safe distance as safety index. Vehicle dynamics, Tire Slip Angle and Segal lateral force model, are concerned to obtain the vehicle states. Monte Carlo simulation is executed to determine the value of required safe distance when encountering with a stationary and a suddenly decelerating target vehicle at different velocities. Safe Distance Margin and quantised influence two indexes are proposed to assess the influence of measurement uncertainty. Simulation and road test experiment results demonstrate that the proposed method is effective to avoid rear-end collision by emergency steering manoeuvre. Moreover, some aspects, like vehicle lateral stability, emergency manoeuvre selection and simultaneously emergency manoeuvres are discussed as well in this work in order to apply this collision avoidance method into practical application.

9 citations

Proceedings ArticleDOI
01 Aug 2017
TL;DR: A Monte Carlo sampling based Imminent Collision Detection algorithm (MCICD) is presented to achieve improved accuracy by faithfully modeling the noise distributions of the sensor measurements to perform the FPR/FNR analysis for any given collision detection system.
Abstract: Imminent collision detection is an important problem for automotive safety, and is critical for driving assistance systems and fully autonomous vehicles. Imminent collision detection systems require very low false alarm rate, due to the potential outcome of the detection result. Most current approaches are based on Kalman filter or its variants and tend to have degraded accuracy when the underlying noise models deviate from the Gaussian assumption. In this paper, we present a Monte Carlo sampling based Imminent Collision Detection algorithm (MCICD) to achieve improved accuracy by faithfully modeling the noise distributions of the sensor measurements. We further demonstrate a Monte Carlo sampling framework to perform the FPR/FNR analysis for any given collision detection system, as the criterion to evaluate the performance of different collision detection approaches. Experiments with synthetic data and a laser scanner based prototype system have been conducted to validate our approach.

2 citations