Vehicular networks using the IEEE 802.11p standard: An experimental analysis

Teixeira, Fernando A.; Silva, Vinicius F. e; Leoni, Jesse L.; Macedo, Daniel F.; Nogueira, José Marcos S.

doi:10.1016/j.vehcom.2014.04.001

Cited by 111 publications

(62 citation statements)

References 6 publications

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“…Moreover, on-board sensors are quite sensitive to temporary occlusion which might be caused by objects which are blocking the sensor's FOV. V2V communication based on ITS-G5 may allow omnidirectional communication with a range up to 1000 m and relative speeds up to 30 m /s [11]. Such values have been observed even under real-world conditions as reported in [12].…”

Section: B Perception By Communicationmentioning

confidence: 88%

“…This set includes the Cooperative Awareness Basic Service which mandates each road user participating in a V2X network to transmit periodically their station type, time, position, velocity and many other parameters in a CAM. This rather comprehensive description of an object state in combination with a communication range of up to 1000 m [11] makes CAM data appealing candidates for multisensor data fusion.…”

Section: B Perception By Communicationmentioning

confidence: 99%

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Multi-sensor data fusion for checking plausibility of V2V communications by vision-based multiple-object tracking

Obst¹,

Hobert

Reisdorf

2014

2014 IEEE Vehicular Networking Conference (VNC)

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Automated vehicles require an adequate and reliable perception of the surrounding world in order to make good decisions. Using vehicle-to-vehicle (V2V) communication to exchange location data (i.e. time, position, heading and speed) can improve the perception beyond the capabilities of traditional on-board sensors (e.g. radar, lidar). However, it is vital to trust the data before it is being used. Cryptographic mechanisms can protect the exchange and authenticity of data but do not guarantee the correctness of the content. In this paper we present a vision-based multi-object tracking system for checking the plausibility of V2V communication. The system is addressing the challenge of fusing relative sensor observations as provided by a MobilEye vision-system with time-delayed absolute GNSS-based measurements from Cooperative Awareness Messages (CAMs) as provided by V2V. The plausibility check is implemented in a prototype and based on a state-of-the-art multiple-object tracking algorithm. The proposed system is evaluated and validated under real-world conditions by conducting several test drives under urban conditions.

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Section: B Perception By Communicationmentioning

confidence: 88%

Section: B Perception By Communicationmentioning

confidence: 99%

Multi-sensor data fusion for checking plausibility of V2V communications by vision-based multiple-object tracking

Obst¹,

Hobert

Reisdorf

2014

2014 IEEE Vehicular Networking Conference (VNC)

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“…Finally, in [21] and [22], the throughput and packet delivery performance of the IEEE 802.11p protocol is studied in V2V and V2I scenarios with different speeds of movement. However, to the best of our knowledge, none of the authors utilize the measured intra-vehicle channel models to evaluate the bit error rate (BER) for the IEEE 802.11p standard.…”

Section: Literature Surveymentioning

confidence: 99%

In-vehicle channel sounding in the 5.8-GHz band

Kukolev

Chandra

Mikulasek

et al. 2015

J Wireless Com Network

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The article reports vehicular channel measurements in the frequency band of 5.8 GHz for IEEE 802.11p standard. Experiments for both intra-vehicle and out-of-vehicle environments were carried out. It was observed that the large-scale variations (LSVs) of the power delay profiles (PDPs) can be best described through a two-term exponential decay model, in contrast to the linear models which are suitable for popular ultra-wideband (UWB) systems operating in the 3-to 11-GHz band. The small-scale variations (SSVs) are separated from the PDP by subtracting the LSV and characterized utilizing logistic, generalized extreme value (GEV), and normal distributions. Two sample KolmogorovSmirnov (K-S) tests validated that the logistic distribution is optimal for in-car, whereas the GEV distribution serves better for out-of-car measurements. For each measurement, the LSV trend was used to construct the respective channel impulse response (CIR), i.e., tap gains at different delays. Next, the CIR information is fed to an 802.11p simulation testbed to evaluate the bit error rate (BER) performance, following a Rician model. The BER results strongly vouch for the suitability of the protocol for in-car as well as out-of-car wireless applications in stationary environments.

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“…There is considerable number of limitations in IEEE 802.11p [3,23]. As it is contention-based, it does not provide a limit on access delays.…”

Section: Introductionmentioning

confidence: 99%