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Automated Traffic Enforecment_Resnick Slide Presentation1Diusaa pined "cc' uoiuTdp pup uaiiasaN :�uau�aa,zo�u� at��.�,I pal_iuioinV Automated Traffic Enforcement: Research and Opinion by David Resnick VS. s Stati f�a Safety uesti J; eking oints Legal ss� � es: It Gets Messy Automated Traffic Enforcement: Research and Opinion by David Resnick U Automated Traffic Enforcement: Research and Opinion by David Resnick etflk t I 4\ .may \\V./- JONATHON RAMSEY Correspondert AOL Autcs Do Red Light Cameras Reduce Accidents? Critics Insist They May Do The Opposite flip ORIGINAL Posted: Aug 27, 2010 U Automated Traffic Enforcement: Research and Opinion by David Resnick That simple question has four answers: Yes, No, Maybe, and It Depends. But it takes a lot of research, a lot of reading, and a lot of money to come to any of these conclusions. JONATHON RAMSEY Correspondent, AOL Autos Do Red Light Cameras Reduce Accidents? Critics Insist They May Do The Opposite epORIGINAL Posted: Aug 27, 2010 YES NO MAYBE U • • Automated Traffic Enforcement: Research and Opinion by David Resnick After looking at more than ten studies on both sides of the red light camera argument. the general trends stand up quickly. What is behind them are lots of asterisks and disclaimers, however. such that every one of those four answers is qualified. di, 'Nish" JONATHON RAMSEY ;;orrespondont AOL Autos Do Red Light Cameras Reduce Accidents? Critics Insist They May Do The Opposite eCRIGINAL Posted: Aug 27, 2010 t • .1 • Automated Traffic Enforcement: Research and Opinion by David Resnick Who's Behind The Data? This is why, frankly, the best answer to the question, "Do red light cameras reduce or cause accidents ? ", is that it depends on who you ask. JONATHON RAMSEY Correspondent, AOL Autos Do Red Light Cameras Reduce Accidents? Critics Insist They May Do The Opposite epORIGINAL Posted: Aug 27. 5 WHO'S THIS? Automated Traffic Enforcement: Research and Opinion by David Resnick That's why you get lots of politicking and doubletalk even in studies that appear to show conclusive evidence of a particular trend. and then more doublespeak when concerned parties get hold of those studies. On top of that you have the liquid nature of statistics itself and the varying methodologies and accepted scientific practices used to gather them. 111111 t1"1.1 JONATHON RAMSEY Correspordo ~t AOL Autos Do Red Light Cameras Reduce Accidents? Critics Insist They May Do The Opposite ORDINAL Posted: Aug 27, 2010 • Automated Traffic Enforcement: Research and Opinion by David Resnick l Crash distance from intersection, in feet, to be considered as an intersection - related crash by different states and cities I SID T OE ONMD:2 :MD INAOM • 0 to 30 0 to 25 -50 Texas Chicago 0 to 100 Arizona, North Carolina, ... Figure 1 -1 — Different crash distances by state and city O to 150 FHWA, Illinois, Virginia, ... 0 to 200 California, ... The standard Distance From Intersection used in many states as well as the Federal Highway Administration(FHWA) is 100 feet or higher. From a study done in Florida ■ • Automated Traffic Enforcement: Research and Opinion by David Resnick Urban Transit Institute Transportation Institute North Carolina Agricultural & Technical State University B402 General Classroom Building 1601 East Market Street Greensboro, NC 27411 Telephone: (336) 334- Fax: (336) 334 -7093 Internet Home Pa • GG cat. edu/ —traninst U.S. Dep, a��.�•, %'r portation Research and Special Programs Administration Washington, DC 20590 July 2004 ■ Automated Traffic Enforcement: Research and Opinion by David Resnick Urban Transit Institute Transportation Institute North Carolina Agricultural C Technical State University B402 General Classroom Building 1601 East Market Street Greensboro, NC 27411 Telephone: (336) 334'" "Fax: (336) 334 -7093 Internet Home Pa • c[ u, •cat.edu/--traninst U.S. Depa nsportation Research and Special Programs Administration Washington, DC 20390 July 2004 Using a large data set including 26 months before the introduction of RLCs. we analyze reported accidents occurring near 303 intersections over a 57 -month period. for a total of 17.271 observations. Automated Traffic Enforcement: Research and Opinion by Urban Transit Institute Transportation Institute North Carolina Agricultural & Technical State University B402 General Classroom Building 1601 East Market Street Greensboro, NC 27411 Telephone: (336) 334 — Fax: (336) 334 -7093 Internet Home Paa f cG at, icat.edu /—t aninst U.S. Depa sportation Research and Special Programs Administration Washington, DC 20590 July 2004 avid Resnick Employing maximiun likelihood estimation of Poisson re ession models. we find that: The results do not support the view that red light cameras reduce crashes. Instead. we find that iu s are associates witn liner levels oI many types aim seventy categories 01 crasues. U • • Automated Traffic Enforcement: Research and Opinion by David Resnick U.S. Deportment or Trons c*totion r Federal Highway Administration FHWA Home Feedback SUMMARY REPORT Research Home This summary report is an archived publication and may contain dated technical, contact, and link information Federal Highway Administration > Publications > Research > Safety > Safety Evaluation of Red -Light Cameras — Executive Summary Publication Number: FHWA- HRT -05 -049 Date: April 2005 Safety Evaluation of Red -Light Cameras Executive Summary • • Automated Traffic Enforcement: Research and Opinion by David Resnick In U S D000nmae cd Ronfpotot on Federal Highway Adminlstrahon FHWA Home SUMMARY REPORT I Feedback This summary report is an archived publication and may contain dated technical, contact, and link Information federal Hallway Admml^traticzn > Publication, > Research > safety > Safety Evaluation of Red-Light Cameras - Executive Summary Publication Number: FHWA- HRT -05 -049 Date: April 2005 Safety Evaluation of Red -Light Cameras — Executive Summary Results Because the intent of the research was to conduct a multijurisdictional study representing different locations across the United States. the aggregate effects over all RLC sites in all jurisdictions was of primary interest. Table 1 shows the combined results for the seven jurisdictions. There is a significant decrease in right -angle crashes. but there is also a significant increase in rear end crashes. Automated Traffic Enforcement: Research and Opinion by David Resnick U Automated Traffic Enforcement: Research and Opinion by David Resnick USF COLLEGE OF PUBLIC HEALTH Barbara Langland- Orban, PhD, Etienne E. Pracht, PhD, John T. Large, PhD ABSTRACT In February 2011, the Insurance Institute for Highway Safety (IIHS) disseminated their research study that compared red light running traffic fatalibi rates between cities that implemented red light camera (RLC) programs with cities that did not. The IIHS researchers concluded cities that used RLCs had a significantly larger percentage reduction in both red light running (RLR) fatality rates and total fatality rates at signalized intersections. Our review reveals the 2011 III-IS study is logically flawed and violates basic scientific research methods that are required for a study's findings to be valid. It has neither internal nor external validity. Correctly interpreting its model's results actually shows that cities using RLCs had an estimated higher rate of red light running fatalities, specifically 25 %, than cities that did not use RLCs in the period "after" cameras were used. The red light running fataliol rate as well as the total fatality rate at all signalized intersections in cities that used cameras was higher in both the "before" and "after" time periods, Florida Public Health Review, 2012,- 9, 1 -8. IDiusaN pinpa Aq uoiuIdp pup uaiiasaj :4uauIaoJoJu[ DTJJPJJ palPumjnivr U • • Automated Traffic Enforcement: Research and Opinion by David Resnik More than 99% of violations have no safety impact. Isnoori pup apoci ' ' • • . . . ' ., ..ikI - :A:4'VA ;Sr " n`" • 4.'1.1— riff II • • -I— " ir 1111W Cif - , ,11■11. 11 .I.DPdtUT AWE'S OU DAELI SUOpPIOT.A. JO %66 U1E?1L4 ORE ID!usa21 MAPCI Aq uompdo pUP tpiPasaN :411DLUDDJOJUI DUJPJLL palpumlnv U • Automated Traffic Enforcement: Research and Opinion by David Resnick More than 99% of violations have no safety impact. "In this picture the stop line would apply as the stopping point. For purposes of violations, vehicle would need to break the plane of the stop line after the light turns red ". «auTl do rs alp Jo od 4Dltim pug appian alp Jo iulod 4JTum S'ulpnpu! uo!P •ioTA P sail .T1suoD letim Jo LT.Ta�T.TD atp Ouplas uT panloAuT aq pinom tratil pig „`alDTtiaA a41 jo i.TPd pTPmJOJ Isom atp„ jo iulod aDuaiapai t sasn Ajip.Taua0 • pa.T suing Tupq alp Jai p Dull do4s ay_ jo auPid a44 IPa.Tq Off. paau pinom ajDTtlaA `suoT4PJOTn Jo sasodind Jod •4ulod OuTddo4s aqi SP Aiddp pinom Dull do/s 344 ainpTd uI„ • p duzi J(4 JPS OU 3A1 q SUO9PjO!A JO %66 ui141. DIM 'iDtusaN pTn u Act uoTUTdp pUL' LlDJP SDJ :4uatuaDJoJu1 DTJJP.T1, pa4Ptuo4nv • • • Automated Traffic Enforcement: Research and Opinion by David Resnick More than 99% of violations have no safety impact. "In this picture the stop line would apply as the stopping point. For purposes of violations, vehicle would need to break the plane of the stop line after the light turns red. generally uses a reference point of "the most forward part of the vehicle," but the would be involved in setting the criteria of what constitutes a violation including which point of the vehicle and which point of the stop line. These fine details would not be worked out until after an ordinance passes." of Da Y 6, gar- ' �.. -vs ' Ir •4aeduJt �I.ajPs OU DAP SUO!4Pi0!A JO %66 uElp a.zo1,A1 )piusaI pinPQ i(q uoTLIIdQ pup LIDIPDSDN :luaLUaaamid Duja J palPtuo 1ny • N Automated Traffic Enforcement: Research and Opinion by David Resnick More than 99% of violations have no safety impact. • • Dodge and University -1111IMEEEPIPMr" PFLIPApCsuuad puP ?Hi •IDEdUll APJPS OU DAN SUOpPIOIA JO %66 UP-11 D.10]Al ,pusas pupci q uoiu!do puP tpipasaN :luaulaamjul Dujau palPtuolny Automated Traffic Enforcement: Research and Opinion by David Resnick r ►Air_•` ,,.II! �:�LiiS .... SUOI4PIOIA PL1 WPD itiOii pa! - z Suoi4PIoin PJaUJPD 4.I40ii pa! - o Suoi4L'lIJ /SOuIU.ieM pupil - oL rein f suoppl D/s uiuJLM DIJJPJ4 - 1 I AEA ui smog g :suopDI DIJJI?i11uaaaJ oMI SSaDXj L,iaulE� �j�tusa� pineu Aq LIOiuido put? 14DIPDS ».:4LIDUIaAiOJuj DIJJPLEI pa4PLUO4nV ■ U • Automated Traffic Enforcement: Research and Opinion by David Resnick Camera Excess Two recent traffic actions: 8 hours in all May 131 - traffic warnings /citations o - red light camera violations July 7o - traffic warnings /citations 2 - red light camera violations TOTAL 201 - traffic warnings /citations 2 - red light camera violations Vin,., -110 GS ,1.... smog ZI uT SUO!41 ?IOTA iuSTI pal ooh papodai SUOI4PIOTA P.IaWPD 44 Ij pal - Z SUO9PjOin PJaLUPD 4LiOii pa! - z SUOI4PIOIA P.IDLUPD 44 ii pa.i - o SUOI4P1TJ /SOUTUJPM DIJJI?J4 - IOZ suoi4PliD /SOuTLIilM JIJpil - oL April SUOT4P4TD /SOUIUJPM DIJpil - APB jp? UI smog 8 : SUOT4DP D!JJPJ4 4uaaa.I OMJJ SSaDX[ P.IaLUPJ 1Diusa2i THAPci uoiuIdp pup tlaipasaj :4u3m DJOJuI pupal, pall upo1nv • • Automated Traffic Enforcement: Research and Opinion by David Resnick Yellow Light Intervals 1:Pf • Automated Traffic Enforcement: Research and Opinion by David Resnick Yellow Light Intervals Topic No. 750 - 000 -005 Traffic Engineering Manual Signals June 2002 Revised: June 2010 Section 3.6 STANDARDIZATION OF YELLOW AND ALL- RED INTERVALS FOR SIGNALIZED INTERSECTIONS U Automated Traffic Enforcement: Research and Opinion by David Resnick Yellow Light Intervals APPROACH SPEED (MPH) YELLOW INTERVAL (SECONDS) 25 3.0 30 3.2 35 3.6 40 4.0 45 4.3 50 4.7 55 5.0 60 5.4 65 5.8 • • Automated Traffic Enforcement: Research and Opinion by David Resnick Ihese intervals are the required minimums. If necessary a: a "a to ',pment limitations, round computed values up to the next 0.5 second." Yellow Light Intervals APPROACH SPEED (MPH) YELLOW INTERVAL (SECONDS) 25 3.0 30 3.2 35 3.6 40 4.0 45 4.3 50 4.7 55 5.0 60 5.4 65 5.8 U • Automated Traffic Enforcement: Research and Opinion by David Resnick Yellow Light Intervals Formula 3.6 -1 1.47v Y = t+ 2(a + Gg) Where: Y= length of yellow interval, sec. t = perception- reaction time, (Use 1 sec.). v= speed of approaching vehicles, in mph. a = deceleration rate in response to the onset of a yellow indication. (Use 10 ft /sect) g = acceleration due to gravity. (Use 32.2 ft /sect) G = grade, with uphill positive and downhill negative. (percent grade /100) "These intervals are the required minimums. If necessary and due to equipment limitations, round computed values up to the next 0.5 second." U • • Automated Traffic Enforcement: Research and Opinion by David Resnick The key elements of the strategic direction of the company are: • Reduction of risk in the business, particularly in the USA where Redflex currently assumes almost all of the risks in shared programs: • Maximising revenue from existing, renewed and new contracts: • Investigation of new sources of revenue from existing customers: from. 2011 Annual Report • Automated Traffic Enforcement: Research and Opinion by David Resnick The next slide shows a segment excerpt from KRQE in Albuquerque, NM broadcast on Feb 27, 2012 The key elements of the strategic direction of the company are: • Reduction of risk in the business. particularly in the USA where Redflex currently assumes almost all of the risks in shared programs: • Maximising revenue from existing, renewed and new contracts: • Investigation of new sources of revenue from existing customers: from 2011 _ - _ __ Annual Report Automated Traffic Enforcement: Research and Opinion by David Resnick ?.iDtusa21 p!»PQ Act LTOIu!do put' 4DJ1aSaN :1LIaLLIaDJOJIYI Dlljal1, paw-mop-iv • • Automated Traffic Enforcement: Research and Opinion by David Resnick ii‘til 0 WA ' 0 I ilrer.4W 'it- P: OC WI. 4 ii2.I1 RV ACLUAMERICAN CIVIL LIBERTIES UNION Automated Traffic Enforcement: Research and Opinion by David Resnick MID imp IOW M. a or Buol Mike ',1-71n. 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