Recouping Efficient Safety Distance in IoV-Enhanced Transportation Systems

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

PY - 2019/7/15

Y1 - 2019/7/15

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 - elastic wave equation

KW - Internet of vehicles

KW - IoV

KW - road traffic congestion

KW - safety distance

UR - https://www.scopus.com/pages/publications/85070239744

U2 - 10.1109/ICC.2019.8761641

DO - 10.1109/ICC.2019.8761641

M3 - Conference contribution

AN - SCOPUS:85070239744

SN - 9781538680896

T3 - IEEE International Conference on Communications

SP - 1

EP - 6

BT - 2019 IEEE International Conference on Communications, ICC 2019 - Proceedings

PB - Institute of Electrical and Electronics Engineers

T2 - 2019 IEEE International Conference on Communications, ICC 2019

Y2 - 20 May 2019 through 24 May 2019

ER -