Research on Vehicle Automatically Tracking Mechanism in VANET

Wang, Lin; Zhang, Shukui; Wang, Xiaoning; Zhang, Yang

doi:10.1155/2013/592129

Cited by 5 publications

(3 citation statements)

References 13 publications

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“…The vehicle jerk degree represents the change rate of the vehicle's longitudinal acceleration [27]. The magnitude of this vehicle jerk can be expressed as follows:…”

Section: ) Vehicle Jerkmentioning

confidence: 99%

Control Strategy for Electric Startup of P2.5-PHEV Based on Slope Memory and Driver’s Startup Intention

Wei

Kan

et al. 2021

IEEE Access

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P2.5 plug-in hybrid electric vehicles (P2.5-PHEVs) exhibit high transmission efficiencies and no power interruption in the shifting and mode switching process; thus, they have broad application prospects. The power transmission in a PHEV under pure electric startup does not entail the clutch, and the initial torque of the motor is often set under the condition that the maximum allowable slope should not lead to backward sliding, which leads to the problems of excessive jerk in small-slope startup and catapulting when startup occurs downhill. The optimal method is to set different initial torques according to different gradients; however, the vehicle would still be in the pre-startup stage, making it impossible to estimate the slope using a dynamic method. In view of the foregoing problems, according to an analysis of pure electric startup dynamics, a slope-memory-based strategy for estimating and storing the slope during the vehicle movement before parking is proposed. During startup, the initial torque is set according to the memorized slope. In the processes of startup and acceleration, the driver's startup intention is identified, and different jerk control targets are set. The torque of the acceleration process is controlled according to the set initial torque and jerk target. Simulation results indicate that the maximum jerk of the proposed strategy is reduced by 23.6% for startup on a 5% ramp and by 57.5% for startup at 15% downhill; thus, the strategy mitigates the problems of the excessive jerk and catapult for startup on a small slope.

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“…The vehicle jerk degree represents the change rate of the vehicle's longitudinal acceleration [27]. The magnitude of this vehicle jerk can be expressed as follows:…”

Section: ) Vehicle Jerkmentioning

confidence: 99%

Control Strategy for Electric Startup of P2.5-PHEV Based on Slope Memory and Driver’s Startup Intention

Wei

Kan

et al. 2021

IEEE Access

View full text Add to dashboard Cite

show abstract

“…These networks have a wide range of commercial and military applications such as video surveillance, smart home, traffic monitoring, and antiterrorism [2][3][4]. Among these, the technique of automatically detecting the initial movement of objects is used in many applications including security, face recognition and tracking, gesture analysis, extraction of vehicular volume of traffic statistics, analysis of aerial photographs, and humanmotion understanding [5][6][7][8][9]. This technique of detecting moving objects is basic and important.…”

Section: Introductionmentioning

confidence: 99%

An Approach to Segmenting Initial Object Movement in Visual Sensor Networks

Jang

Cha

2014

International Journal of Distributed Sensor Networks

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This paper suggests a new method to extract the initial movement of moving objects in digital image data obtained in visual sensor networks. First, consecutive images are received as input. Then, the frames are partitioned into nonoverlapping square blocks of pixels, and finally, the block-based motion vectors, which represent the movement information between two adjacent frames, are extracted from the received images using a block-matching algorithm. The extracted motion vectors are subsequently applied to an outlier-elimination algorithm called robust estimation to discriminate between the background motion vectors and those of noise or moving objects. The motion vectors corresponding to the noise or objects are clustered with an unsupervised clustering algorithm to segment the individual moving objects. Experimental results prove that the proposed method can effectively detect the initial movement of objects in various indoor and outdoor environments.

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“…Vehicular Ad hoc Networks [1][2][3] (VANETs) are distributed, self-organized communication networks composed of moving vehicles and are thus characterized by very high nodal mobility and limited degrees of freedom in the mobility patterns. The discussed IEEE 1609 Wireless Access in Vehicular Environments [4] (WAVE) draft is being developed for VANETs applications mainly considering safety-related scenarios, such as cooperative forward collision warning [5,6] (CCW) systems, traffic signal violation warning [7] systems, and lane change warning [8] systems, and at the same time taking account of some requirements from nonsafetyrelated applications [9].…”

Section: Introductionmentioning

confidence: 99%

Connectivity Analysis for Free-Flow Traffic in VANETs: A Statistical Approach

Chen

Pei

et al. 2013

International Journal of Distributed Sensor Networks

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Intervehicle communication gives vehicles opportunities to exchange packets within the limited radio range and self-organized in Ad Hoc manner into VANETs (Vehicular Ad Hoc Networks). However, due to issues such as the high mobility, insufficient market penetration ratio, and lacking of roadside units, connectivity is actually a big problem in VANETs. In addition, relying only on the direct connectivity in most of the previous works, say broadcasting which provides one-hop connections between nodes is far from the continuously growing application demands in VANETs, such as inter-vehicle entertainments, cooperative collision avoidances, and inter-vehicle emergency notifications. Therefore, the indirect connectivity from multihop forwarding is also a necessary complement especially for the case where direct connection is hardly achieved. In this paper, we define a new metric, that is, available connectivity, to consider both direct and indirect connectivity. After analyzing the statistical properties of direct and indirect connectivity in vehicular environment, the available connectivity is proposed and quantified for practical usage. Numerical results show that our available connectivity could provide correct and useful references for protocols design and performance improvements of different applications.

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Research on Vehicle Automatically Tracking Mechanism in VANET

Cited by 5 publications

References 13 publications

Control Strategy for Electric Startup of P2.5-PHEV Based on Slope Memory and Driver’s Startup Intention

Control Strategy for Electric Startup of P2.5-PHEV Based on Slope Memory and Driver’s Startup Intention

An Approach to Segmenting Initial Object Movement in Visual Sensor Networks

Connectivity Analysis for Free-Flow Traffic in VANETs: A Statistical Approach

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