TY - GEN
T1 - Quick and autonomous platoon maintenance in vehicle dynamics for distributed vehicle platoon networks
AU - Sarker, Ankur
AU - Qiu, Chenxi
AU - Shen, Haiying
N1 - Publisher Copyright:
© 2017 ACM.
PY - 2017/4/18
Y1 - 2017/4/18
N2 - Platoon systems, as a type of adaptive cruise control systems, will play a significant role to improve travel experience and roadway safety. The stability of a platoon system is crucial so that each vehicle maintains a safety distance from its proceeding vehicle and can take necessary actions to avoid collisions. However, current centralized platoon maintenance method cannot meet this requirement. We suggest to use a decentralized platoon maintenance method, in which each vehicle communicates with its neighbor vehicles and self-determines its own velocity. However, a vehicle needs to know its distance from its preceding vehicle to determine its velocity, which is unavailable in vehicle communication disconnection caused by vehicle dynamics (i.e., node joins and departures). thus, a formidable challenge is: how to recover the platoon quickly in vehicle dynamics even when the distance information is unavailable? To handle this challenge, we first profile a succeeding vehicle's velocity to minimize the time to recover the connectivity hole with its preceding vehicle and ?nd that the profiles are almost the same at the beginning regardless of its current velocity and distance to its preceding vehicle. Accordingly, we devise a strategy, in which a succeeding vehicle uses its stored common velocity profile when it is disconnected from its preceding vehicle and then adjusts its velocity once the connection is built. Experimental results from simulation show the efficiency and effectiveness of our decentralized platoon maintenance method.
AB - Platoon systems, as a type of adaptive cruise control systems, will play a significant role to improve travel experience and roadway safety. The stability of a platoon system is crucial so that each vehicle maintains a safety distance from its proceeding vehicle and can take necessary actions to avoid collisions. However, current centralized platoon maintenance method cannot meet this requirement. We suggest to use a decentralized platoon maintenance method, in which each vehicle communicates with its neighbor vehicles and self-determines its own velocity. However, a vehicle needs to know its distance from its preceding vehicle to determine its velocity, which is unavailable in vehicle communication disconnection caused by vehicle dynamics (i.e., node joins and departures). thus, a formidable challenge is: how to recover the platoon quickly in vehicle dynamics even when the distance information is unavailable? To handle this challenge, we first profile a succeeding vehicle's velocity to minimize the time to recover the connectivity hole with its preceding vehicle and ?nd that the profiles are almost the same at the beginning regardless of its current velocity and distance to its preceding vehicle. Accordingly, we devise a strategy, in which a succeeding vehicle uses its stored common velocity profile when it is disconnected from its preceding vehicle and then adjusts its velocity once the connection is built. Experimental results from simulation show the efficiency and effectiveness of our decentralized platoon maintenance method.
UR - http://www.scopus.com/inward/record.url?scp=85019041218&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85019041218&partnerID=8YFLogxK
U2 - 10.1145/3054977.3054998
DO - 10.1145/3054977.3054998
M3 - Conference contribution
AN - SCOPUS:85019041218
T3 - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
SP - 203
EP - 208
BT - Proceedings - 2017 IEEE/ACM 2nd International Conference on Internet-of-Things Design and Implementation, IoTDI 2017 (part of CPS Week)
PB - Association for Computing Machinery, Inc
T2 - 2nd IEEE/ACM International Conference on Internet-of-Things Design and Implementation, IoTDI 2017
Y2 - 18 April 2017 through 20 April 2017
ER -