Abstract
| Original language | English |
|---|---|
| Title of host publication | Australasian Transport Research Forum 2015 Proceedings |
| Editors | S Travis Waller, Hanna Grzybowska, Emily Moylan, Matthew Jones, Sherri Fields |
| Place of Publication | Sydney NSW Australia |
| Publisher | Australasian Transport Research Forum |
| Pages | 1-10 |
| Number of pages | 10 |
| Publication status | Published - 2015 |
| Event | Australasian Transport Research Forum 2015 - Sydney, Australia Duration: 30 Sep 2015 → 2 Oct 2015 Conference number: 37th http://atrf.info/conference.aspx |
Conference
| Conference | Australasian Transport Research Forum 2015 |
|---|---|
| Abbreviated title | ATRF 2015 |
| Country | Australia |
| City | Sydney |
| Period | 30/09/15 → 2/10/15 |
| Internet address |
Keywords
- Safety
- Tram-involved crash frequency
- Random effects negative binomial model
Cite this
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Examining route section level tram-involved crash frequency using the random effects negative binomial model. / Naznin, Farhana; Currie, Graham; Logan, David; Sarvi, Majid.
Australasian Transport Research Forum 2015 Proceedings. ed. / S Travis Waller; Hanna Grzybowska; Emily Moylan; Matthew Jones; Sherri Fields. Sydney NSW Australia : Australasian Transport Research Forum, 2015. p. 1-10.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
TY - GEN
T1 - Examining route section level tram-involved crash frequency using the random effects negative binomial model
AU - Naznin, Farhana
AU - Currie, Graham
AU - Logan, David
AU - Sarvi, Majid
PY - 2015
Y1 - 2015
N2 - Safety is an overriding concern in design, operation and development of light rail systems including trams or streetcars as they impose crash risks on road users in terms of crash frequency and severity. The aim of this study is to identify the key traffic, transit and route factors that influence tram-involved crash frequencies along tram route sections in Melbourne. A random effects negative binomial (RENB) regression model was developed to analyse crash frequency data obtained from Yarra Trams, the tram operator in Melbourne tram network. The RENB modelling approach can account for spatial and temporal variations within observation groups in panel count data structures by assuming that the group specific effects are randomly distributed across locations. The results identify many significant factors affecting crash frequency. They are, in order of affect; tram stop spacing (-0.43), tram route section length (0.31), tram signal priority (-0.263), general traffic volume (0.17) and tram lane priority (-0.148). Platform stops (-0.09) and service frequency (0.004) also influence crash frequency. Findings provide useful insights on route section level tram-involved crashes in an urban tram or streetcar operating environment. The method described represents a useful planning tool for transit agencies hoping to improve safety performance.
AB - Safety is an overriding concern in design, operation and development of light rail systems including trams or streetcars as they impose crash risks on road users in terms of crash frequency and severity. The aim of this study is to identify the key traffic, transit and route factors that influence tram-involved crash frequencies along tram route sections in Melbourne. A random effects negative binomial (RENB) regression model was developed to analyse crash frequency data obtained from Yarra Trams, the tram operator in Melbourne tram network. The RENB modelling approach can account for spatial and temporal variations within observation groups in panel count data structures by assuming that the group specific effects are randomly distributed across locations. The results identify many significant factors affecting crash frequency. They are, in order of affect; tram stop spacing (-0.43), tram route section length (0.31), tram signal priority (-0.263), general traffic volume (0.17) and tram lane priority (-0.148). Platform stops (-0.09) and service frequency (0.004) also influence crash frequency. Findings provide useful insights on route section level tram-involved crashes in an urban tram or streetcar operating environment. The method described represents a useful planning tool for transit agencies hoping to improve safety performance.
KW - Safety
KW - Tram-involved crash frequency
KW - Random effects negative binomial model
UR - http://atrf.info/
M3 - Conference Paper
SP - 1
EP - 10
BT - Australasian Transport Research Forum 2015 Proceedings
A2 - Waller, S Travis
A2 - Grzybowska, Hanna
A2 - Moylan, Emily
A2 - Jones, Matthew
A2 - Fields, Sherri
PB - Australasian Transport Research Forum
CY - Sydney NSW Australia
ER -