TY - GEN
T1 - M2M-enabled real-time Trip Planner
AU - Cerritos, Eduardo
AU - Lin, Fuchun
N1 - Publisher Copyright:
© 2014 IEEE.
PY - 2014
Y1 - 2014
N2 - Uncertainty is a key factor that prevents a commuter from using public transportation system. More and more transportation agencies are incorporating real-time Trip Planners to empower commuters with opportune information. However, such systems require continuous status updates from the vehicles and involves expensive communication cost. In this paper we propose an architecture that takes advantage of Machine-to-Machine Communication concepts and provides a degree of intelligence to the vehicles, to alleviate unnecessary communication between the vehicles and the Trip Planner.
AB - Uncertainty is a key factor that prevents a commuter from using public transportation system. More and more transportation agencies are incorporating real-time Trip Planners to empower commuters with opportune information. However, such systems require continuous status updates from the vehicles and involves expensive communication cost. In this paper we propose an architecture that takes advantage of Machine-to-Machine Communication concepts and provides a degree of intelligence to the vehicles, to alleviate unnecessary communication between the vehicles and the Trip Planner.
KW - Intelligent Transportation Systems
KW - Machine-to-Machine Communication
KW - Trip Planner
UR - http://www.scopus.com/inward/record.url?scp=84988304444&partnerID=8YFLogxK
U2 - 10.1109/PADSW.2014.7097902
DO - 10.1109/PADSW.2014.7097902
M3 - Conference contribution
AN - SCOPUS:84988304444
T3 - Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS
SP - 886
EP - 891
BT - 2014 20th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2014 - Proceedings
PB - IEEE Computer Society
T2 - 20th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2014
Y2 - 16 December 2014 through 19 December 2014
ER -