2016-2015 · 39 2016-2015 & The International Traffic Safety and Analysis Grope (IRTAD), (2015),...
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2005
Azrin. H. N. 1960. “Effects of punishment intensity during variable-interval
reinforcement”, Journal of Exp Anal Behavior 3(2), 123-142.
Carr, A. F. Schnelle J. F. & Kirkhne R. E. 1980. Police crackdowns and
slowdowns: a naturalistic evolution of changes in police traffic.
Behavioral Assessment 2, 33-41.
European Transport Safety Council (ETSC), 1999.
Jurdan J. & Bunkley, N. 3 March 2008. Pioneer in Quality Control Dies. New
York: New York Times, p. 103.
Rothengatter T. 1982. “The effect of police surveillance and law
enforcement on driver behavior”. Current Psychological reviews 2, 349-
358.
Honig W. K. 1977. Handbook of operant behavior. New Jersey: prentice-
Hall.
Nilsson, E., Sjogren. O. 1981. Relationships between enforcement, traffic
speeds and traffic accidents. Paper presented at the International
Symposium on the Effects of Speed Limits on Traffic Accidents and Fuel
Consumption, Ireland.
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2016-201527
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David Weisburd, Elizabeth Groff and Sue Ming Yang, (2012), The Criminology of Place: Street Segments and Our Understanding of the crime Problem, Oxford University press.
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Hakkert, Pollak and Peled, 2013GIS
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2016-201531
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http trasportation. :2016org.il sites default files pirsum ilanatalemot1-3-16.pdf
1998
2014 2013
http www.rsa.gov.il siteCollectioDocuments D7%9E%D7%
Elvik R. and Vaa T., (2014), The Handbook of Road Safety Measures, New
York: Amsterdam, Elsevier Science.
Hakkert S., Yelinek A. and Efrat E., (1990), “Police Surveillance Methods
and Police Resource Allocation Models” in Proc. Of OEDC Conf. on
Enforcement and Rewarding Strategies and Effects, Danish Road
Directorate, Copenhagen.
Hauer E., (1996), “Identification of Sites with Promise” in Transportation
Research Record, 1542, pp. 54-60.
Kapiow L. and Khavell S., (2001), Any Non-welfares Method of Policy
Assessment Violates the Pareto Principle, Harvard Law School and
National Bureau of Economic Research.
Miaou P. S., (1994), “The Relationship between Truck Accidents and
Geometric design of road section: Poisson Versus negative binomial
regressions”, in Accident Analysis and Prevention, 26(4), pp. 471-482.
Pollak K., Peled A. and Hakkert S., (2013), “Geo-Based Statistical Models
for Vulnerability Prediction of Highway Network Segment”, in ISPRS:
International Journal of Geo-Information, 3(2), pp. 619-637.
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The International Traffic Safety and Analysis Grope (IRTAD), (2015), Road
Safety Annual Report.
Weisburd D., Groff E. and Yang Sue-Ming, (2012), The Criminology of Place:
Street Segments and Our Understanding of the crime Problem, Oxford
University press.
Weisburd D. and Clarke R., (1994), “Diffusion of Crime Control Benefits:
Observations on the Reverse of Displacement” in Crime Prevention
Studies, 2, pp. 184-165.
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2016-201549
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Cameron M., Newstead S., Diamantopoulou K., Oxley P. 2003. The
interaction between speed camera enforcement and speed-related
mass media publicity in Victoria. Report No. 201. Monash University –
Accident research center.
Elvik. R., 2013. A re-parameterisation of the Power Model of the relationship
between the speed of traffic and the number of accidents and accident
victims. Accident Analysis and Prevention, 50(1), 854-860.
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Data:
P - number of poles (p= 1,..,P)
Q - number of groups of poles (i.e. cities, hot spots) (q = A,B,C,D…,Q)
STq - poles located in group q (STq P)
J - number of different types of punishments (j = 1,…J)
I - number of traffic courts (i=1,..,I)
E - number of tickets (for all types) that the encoder unit can handle
K - types of speed enforcement levels (function of speed limit) (k=1,..,K)
– expected number of tickets per type j produced at pole p at
speed enforcement level k during planning period
– expected % tickets per type j produced at pole p at speed enforcement
level k that go to court (the owner of the vehicle can ask for a court
summons instead of a fine)
– maximum number of court summons that Traffic Court i can handle
per planning period, i = 1,.., I
– expected utility of % of enforcement time at pole p at enforcement level k
during planning period (i.e. maximum reduction in road accidents
according to Power Model)
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Decision variables
Xpk - % of time a camera at pole p is operated at speed enforcement level
k during planning period
Maximum Utility The
Power Model
1) Encoder unit capacity
2) Court unit capacity
3) Spatial constraints
4) Equality constraints
k=1,..,K5) The maximum is100%
≤1
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2016-2015 54
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2016-2015 56
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2016-2015 58
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2016-2015 60
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2016-201561
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2016-2015 62
Cody WF., Kreulem JT., Krishna V., Spangler WS. 2002. The integration of
business intelligence and knowledge management. IBM System Journal
41(4), 697-713.
Elbashir MZ., Collier PA., Davern MJ. 2008. Measuring the effects of business
intelligence systems: The relationship between business process and
organizational performance. International Journal of Accounting
Information Systems 9, 135–153.
Negash S., Business intelligence. 2004. Communications of the Association
for Information Systems, 13, 177-195.
Nenortaitė J., Butleris R. 2009. Improving business rules management
through the application of adaptive business intelligence technique.
Information Technology and Control 38(1), 21-28.
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2016-201565
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2016-2015 66
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2016-201567
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2016-2015 68
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2016-201569
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2016-2015 70
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Vehicle Information System
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2016-201571
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NHTSA, 2011)
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2016-2015 72
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2016-2015 74
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2016-201575
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2016-2015 76
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2016-201577
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2016-2015 78
2014
Carney, C., McGehee, D., Harland, K., Weiss, M., Raby, M. 2016. Using
Naturalistic Driving Data to Examine Teen Driver Behaviors Present in
Motor Vehicle Crashes, 2007-2015. AAA Foundation for Traffic Safety.
CARRS (Centre for Accident Research & Road Safety-Queensland)-Mobile
phone use & distraction while driving .Research & Road Safety(2012).
Queensland “State of the Road Centre of Accident
Dragutinovic, N., Twisk, D. 2005. A literature review. Use of mobile phones
while driving – effects on road safety. SWOV - Institute for road
safety research.
Gorman, R. 2014. One in four car accidents caused by cell phone use while
driving but only five percent blame on texting. Mail on line news
National Safety Council. 2012. Understanding the distracted brain. Why
driving while using hands-free cell phones is risky behavior. White paper.
NHTSA (National Highway Traffic Safety Administration). 2011. Mobile
phone use: A growing problem of driver distraction.
Pew Research Center. 2015. U.S. Smartphone Use in 2015.
Walsh SP., White, KM., Hyde, MK., Watson B. 2008. Dialling and Driving:
Factors Influencing Intensions to Use a Mobile Phone While Driving.
Accidents Analysis and Prevention. 40(6), 1893-1900.
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2016-2015 80
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2016-2015 82
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2016-2015 84
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OECD
2016-201589
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ETSC (2016). France - road deaths increase as speeds creep up. ETSC 1.
IRTAD (2016). Road Safety Annual Report.
Kaufman EJ., Wiebe DJ.(2016). Impact of State Interlock Laws on Alcohol Involve
Crash Deaths in the United State. Am J Public Health, 106(5), 865-871.
OECD-ITF. (2016). Halving the Number of Road Death in Korea.
RSA (2016). Fatal Collisions 2008-2012 Alcohol as a Factor. Road Safety
Authority, Ireland.
WHO (2015). World Health Organization web site.
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2016-2015 100
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