Co-dependent workplace, residence and commuting mode choice: Results of a multi-dimensional mixed logit model with panel effects

Cities ◽  
2020 ◽  
Vol 96 ◽  
pp. 102448
Author(s):  
Jia Guo ◽  
Tao Feng ◽  
Harry J.P. Timmermans
Urban Studies ◽  
2010 ◽  
Vol 47 (11) ◽  
pp. 2445-2459 ◽  
Author(s):  
Liang Long ◽  
Jie Lin ◽  
Kimon Proussaloglou

2019 ◽  
Vol 46 (4) ◽  
pp. 322-328 ◽  
Author(s):  
Pengfei Liu ◽  
Wei (David) Fan

This study employs a mixed logit model approach to evaluate contributing factors that significantly affect the severity of head-on crashes. The head-on crash data are collected from Highway Safety Information System (HSIS) from 2005 to 2013 in North Carolina. The effects that vehicle, driver, roadway, and environmental characteristics have on the injury severity of head-on crashes are examined. The results of this research demonstrate that adverse weather, young drivers, rural roadways, and pickups are found to be better modeled as random-parameters at specific injury severity levels, while others should remain fixed. Also, the model results indicate that driving under the influence of alcohol or drugs, grade or curve roadway configuration, old drivers, high speed limit, motorcycles will increase the injury severity of head-on crashes. Adverse weather condition, two-way divided road, traffic control, young drivers, and pickups will decrease the injury severity of head-on crashes.


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