TY - GEN
T1 - Recouping Efficient Safety Distance in IoV-Enhanced Transportation Systems
AU - Xiong, Kai
AU - Leng, Supeng
AU - He, Jianhua
AU - Wu, Fan
AU - Wang, Qing
N1 - Funding: European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie grant agreement No 824019.
PY - 2019/5/1
Y1 - 2019/5/1
N2 - Internet-of-Vehicles (IoV) has the potentials of enhancing automatic driving in various transportation environment. However, there is very little investigation on quantifying the potential influence of automatic driving applications with the road efficiency in IoV. This paper studies the connection of safety distance to the road congestion under different IoV resource conditions. We propose an elastic wave equation model to reveal the relation between safety distance and road congestion. It can be found that the propagation speed of road congestion is largely affected by the safety distance. To recoup the efficient road safety and alleviate road congestion, an optimization problem is formulated with cooperative communication and computing via platoons that aims to minimize the total safety distance. Since the optimization is a complicated 0–1 programming problem, we propose a practical resource allocation algorithm and solve the problem through Lagrangian relaxation. Simulation experiments show that the proposed algorithm leads to near-optimal results with low complexity but no overhead of vehicular information exchange.
AB - Internet-of-Vehicles (IoV) has the potentials of enhancing automatic driving in various transportation environment. However, there is very little investigation on quantifying the potential influence of automatic driving applications with the road efficiency in IoV. This paper studies the connection of safety distance to the road congestion under different IoV resource conditions. We propose an elastic wave equation model to reveal the relation between safety distance and road congestion. It can be found that the propagation speed of road congestion is largely affected by the safety distance. To recoup the efficient road safety and alleviate road congestion, an optimization problem is formulated with cooperative communication and computing via platoons that aims to minimize the total safety distance. Since the optimization is a complicated 0–1 programming problem, we propose a practical resource allocation algorithm and solve the problem through Lagrangian relaxation. Simulation experiments show that the proposed algorithm leads to near-optimal results with low complexity but no overhead of vehicular information exchange.
KW - Internet of vehicles
KW - IoV
KW - elastic wave equation
KW - road traffic congestion
KW - safety distance
UR - https://ieeexplore.ieee.org/document/8761641
UR - http://www.scopus.com/inward/record.url?scp=85070239744&partnerID=8YFLogxK
U2 - 10.1109/ICC.2019.8761641
DO - 10.1109/ICC.2019.8761641
M3 - Conference publication
SN - 978-1-5386-8089-6
VL - 2019-May
BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings
PB - IEEE
T2 - ICC 2019 - 2019 IEEE International Conference on Communications (ICC)
Y2 - 20 May 2019 through 24 May 2019
ER -