Abstract
The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. This paper presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWARN) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness to these traffic conditions and ultimately reduce the crash frequency on urban freeways. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 WB where the event frequency prior to the systems installation was 11.9 crashes per million vehicles traveled and 111.8 near crashes per million vehicles traveled. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWARN system showed the event frequency reduced to 9.34 crashes per million vehicle traveled and 51.8 near crashes per million vehicle traveled. The result shows a 20% decrease of crash frequency and the feasibility of the proposed methodology.
| Original language | English (US) |
|---|---|
| Title of host publication | 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 762-767 |
| Number of pages | 6 |
| ISBN (Electronic) | 9781509064847 |
| DOIs | |
| State | Published - Aug 8 2017 |
| Event | 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Naples, Italy Duration: Jun 26 2017 → Jun 28 2017 |
Publication series
| Name | 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings |
|---|
Other
| Other | 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 |
|---|---|
| Country | Italy |
| City | Naples |
| Period | 6/26/17 → 6/28/17 |
Fingerprint
Keywords
- Active Traffic Management
- Queue Warning
Cite this
Design, specification, implementation and evaluation of a freeway queue warning system. / Liu, Zhejun; Dirks, Peter; Hourdos, John.
5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings. Institute of Electrical and Electronics Engineers Inc., 2017. p. 762-767 8005615 (5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Design, specification, implementation and evaluation of a freeway queue warning system
AU - Liu, Zhejun
AU - Dirks, Peter
AU - Hourdos, John
PY - 2017/8/8
Y1 - 2017/8/8
N2 - The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. This paper presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWARN) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness to these traffic conditions and ultimately reduce the crash frequency on urban freeways. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 WB where the event frequency prior to the systems installation was 11.9 crashes per million vehicles traveled and 111.8 near crashes per million vehicles traveled. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWARN system showed the event frequency reduced to 9.34 crashes per million vehicle traveled and 51.8 near crashes per million vehicle traveled. The result shows a 20% decrease of crash frequency and the feasibility of the proposed methodology.
AB - The formation and propagation of queues on urban freeways is an unavoidable result of the ever-increasing traffic demand. This paper presents the design, specification, implementation and evaluation of an infrastructure based Queue Warning system (QWARN) that is capable of detecting dangerous traffic conditions, i.e. crash-prone conditions, on freeways and delivering warning messages to drivers, in order to increase their alertness to these traffic conditions and ultimately reduce the crash frequency on urban freeways. This study utilizes measurements of individual vehicle speeds and time headways at two fixed locations on the freeway mainline. The Queue Warning system was implemented at the right lane of a 1.7-mile-long freeway segment of Interstate 94 WB where the event frequency prior to the systems installation was 11.9 crashes per million vehicles traveled and 111.8 near crashes per million vehicles traveled. The control algorithm assesses the dangerousness of the given traffic condition and responds with a warning result based on a multi-metrics traffic evaluation model. The system translates the warning result into readable messages and delivers them to the two sets of signs located upstream of the detection zone. A three-month investigation of the operations of the QWARN system showed the event frequency reduced to 9.34 crashes per million vehicle traveled and 51.8 near crashes per million vehicle traveled. The result shows a 20% decrease of crash frequency and the feasibility of the proposed methodology.
KW - Active Traffic Management
KW - Queue Warning
UR - http://www.scopus.com/inward/record.url?scp=85030235043&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85030235043&partnerID=8YFLogxK
U2 - 10.1109/MTITS.2017.8005615
DO - 10.1109/MTITS.2017.8005615
M3 - Conference contribution
AN - SCOPUS:85030235043
T3 - 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
SP - 762
EP - 767
BT - 5th IEEE International Conference on Models and Technologies for Intelligent Transportation Systems, MT-ITS 2017 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
ER -