## Bibliographic Entry Details

, “A Vehicular Networking Perspective on Estimating Vehicle Collision Probability at Intersections,” IEEE Transactions on Vehicular Technology (TVT), vol. 63, no. 4, pp. 1802–1812, May 2014

### Abstract

Finding viable metrics to assess the effectiveness of Intelligent Transportation Systems (ITS) in terms of ’safety’ is one of the major challenges in vehicular networking research. We aim to provide a metric, an estimation of the vehicle collision probability at intersections, that can be used for evaluating Inter-Vehicle Communication (IVC) concepts. In the last years, the vehicular networking community reported in several studies that safety enhancing protocols and applications cannot be evaluated based only on networking metrics like delays and packet loss rates. We present an evaluation scheme that addresses this need by quantifying the probability of a future crash, depending on the situation in which a vehicle is receiving a beacon message (e.g., a CAM or a BSM). Thus, our criticality metric also allows for fully distributed situation assessment. We investigate the impact of safety messaging between cars approaching an intersection using a modified road traffic simulator that allows selected vehicles to disregard traffic rules. As direct result we show that simple beaconing is not as effective as anticipated in suburban environments. More profoundly, however, our simulation results reveal more details about the timeliness (regarding the criticality assessment) of beacon messages, and as such, can be used to develop more sophisticated beaconing solutions.

### Bibtex

@article{joerer2014vehicular,
author = {Joerer, Stefan and Segata, Michele and Bloessl, Bastian and Lo Cigno, Renato and Sommer, Christoph and Dressler, Falko},
doi = {10.1109/TVT.2013.2287343},
title = {{A Vehicular Networking Perspective on Estimating Vehicle Collision Probability at Intersections}},
pages = {1802--1812},
journal = {IEEE Transactions on Vehicular Technology (TVT)},
issn = {1939-9359},
publisher = {Institute of Electrical and Electronics Engineers (IEEE)},
month = {5},
number = {4},
volume = {63},
year = {2014}
}