Evaluation of penalty and enforcement strategies to combat speeding offences among professional drivers: A Hong Kong stated preference experiment

Cited 39 time in webofscience Cited 0 time in scopus
  • Hit : 147
  • Download : 0
Speeding has been a great concern around the world due to the occurrence and severity of road crashes. This paper presents an evaluation of the effectiveness of different penalty and camera-based enforcement strategies in curbing speeding offences by professional drivers in Hong Kong. A stated preference survey approach is employed to measure the association between penalty and enforcement strategies and drivers' speed choices. Data suggest that almost all drivers comply with speed limits when they reach a camera housing section of the road. For other road sections, a panel mixed logit model is estimated and applied to understand the effectiveness of penalties and enforcement strategies on driver's speeding behaviors. Driving-offence points (DOPs) are found to be more effective than monetary fines in deterring speeding offences, albeit there is significant heterogeneity in how drivers respond to these strategies. Warning drivers of an upcoming camera-based enforcement section increased speed compliance. Several demographic and employment characteristics, driving history and perception variables also influence drivers' choices of speed compliance. Finally, besides penalty and enforcement strategies, driver education and training programs aimed at addressing aggressiveness/risk-taking traits might help reduce repeated speeding offences among drivers.
Publisher
PERGAMON-ELSEVIER SCIENCE LTD
Issue Date
2020-02
Language
English
Article Type
Article
Citation

ACCIDENT ANALYSIS AND PREVENTION, v.135

ISSN
0001-4575
DOI
10.1016/j.aap.2019.105366
URI
http://hdl.handle.net/10203/298940
Appears in Collection
GT-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 39 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0