TY - GEN
T1 - Automated Classification of Different Congestion Types
AU - Karl, Barbara
AU - Kessler, Lisa
AU - Bogenberger, Klaus
N1 - Publisher Copyright:
© 2019 IEEE.
PY - 2019/10
Y1 - 2019/10
N2 - Congestion on freeways can be caused by different sources and therefore needs different treatment for traffic control and optimization. Advanced traffic analysis is required to improve traffic efficiency. This paper presents a definition of four congestion types, (a) Jam Wave, (b) Stop and Go, (c) Wide Jam, and (d) Mega Jam. Through virtually driving trajectories passing a spatio-temporal area, the type of a congestion can be automatically determined. Each congestion can be categorized depending on certain parameters. A sensitivity analysis and a parameter optimization are conducted.
AB - Congestion on freeways can be caused by different sources and therefore needs different treatment for traffic control and optimization. Advanced traffic analysis is required to improve traffic efficiency. This paper presents a definition of four congestion types, (a) Jam Wave, (b) Stop and Go, (c) Wide Jam, and (d) Mega Jam. Through virtually driving trajectories passing a spatio-temporal area, the type of a congestion can be automatically determined. Each congestion can be categorized depending on certain parameters. A sensitivity analysis and a parameter optimization are conducted.
UR - http://www.scopus.com/inward/record.url?scp=85076809768&partnerID=8YFLogxK
U2 - 10.1109/ITSC.2019.8917410
DO - 10.1109/ITSC.2019.8917410
M3 - Conference contribution
AN - SCOPUS:85076809768
T3 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
SP - 2312
EP - 2317
BT - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2019 IEEE Intelligent Transportation Systems Conference, ITSC 2019
Y2 - 27 October 2019 through 30 October 2019
ER -