Abstract
Vehicle platooning is of great importance in future autonomous driving and intelligent transportation systems, due to its advantages in road safety, traffic efficiency, energy consumption and exhaust emissions. This paper focuses on the scalability performance of platooning control, which aims to achieve long platoon size under the premise of ensuring consensus behavior of the platooning vehicles. However, in classical platooning schemes such as ACC (adaptive cruise control) and CACC (cooperative adaptive cruise control), as the number of platoon members increases, the communication range of the leader and the cascaded sensor delay affect the scalability of platoon. In this paper, a scalable platooning scheme, CACC-granulation, is proposed to improve the scalability of platooning based on a novel information flow topology. The granulating method is used to solve the problem of limited communication range of leader for CACC by forwarding their own information to platoon members through some vehicles. The CACC-granulation granulates platoon information flow topology and enhances the platoon scalability by reducing information flow topology matrix. Simulation experiments are conducted to verify the consensus and scalability performance of CACC-granulation. Compared with other two platooning schemes which can get long platoon size, i.e., ACC-cascade and ACC-CACC-integration, the simulation results indicate the performance advantages of the proposed CACC-granulation, which not only meets the consensus of platooning control, but also enhances the scalability of platooning control.
Highlights
Vehicle platooning is one of the important application scenarios in future autonomous driving, aiming to improve road safety, increase traffic efficiency, and decrease energy consumption and exhaust emissions [1], [2]. vehicle platooning is a group of vehicles in a closely linked manner, nose-totail, so that the vehicles move like a train with virtual string attached between vehicles [3], [4].This paper focuses on the longitudinal control of the platoon
The results show that CACC-granulation can achieve best scalability, i.e., can maintain consensus for a long platoon size
Because we focus on the novel information flow topology to improve the scalability of vehicle platooning, the assumptions of the other components are as follows: (1) Vehicle longitudinal dynamics include the engine, drive line, brake system, aerodynamics drag, etc
Summary
Vehicle platooning is one of the important application scenarios in future autonomous driving, aiming to improve road safety, increase traffic efficiency, and decrease energy consumption and exhaust emissions [1], [2]. vehicle platooning is a group of vehicles in a closely linked manner, nose-totail, so that the vehicles move like a train with virtual string attached between vehicles [3], [4]. The information flow topologies and wireless communication quality significantly impact the performance of platooning control [12]–[14]. This paper explores to improve the scalability of platooning control from the perspective of information flow topology. The information flow topology dictates the pattern of communication between vehicles and is essential for effective platoon control, plays a critical role in the design and performance analysis of platooning control strategies. CACC-granulation uses a novel information flow topology, which is proposed based on the idea of granulation in artificial intelligence [30], [31]. The results show that CACC-granulation can achieve best scalability, i.e., can maintain consensus for a long platoon size.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
