DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CAMERA DETECTED OFFENCE PROGRAM (CDOP)

Transcription

1 DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CAMERA DETECTED OFFENCE PROGRAM (CDOP) by Newstead, S.V. & Cameron, M.H. June, 2012 Report No. Final

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3 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE REPORT DOCUMENTATION PAGE Report No. Date ISBN ISSN Pages Final June (online) Title and sub-title: Development of an evaluation framework for the Queensland Camera Detected Offence Program (CDOP) Author(s): Newstead, S.V. & Cameron, M.H. Sponsoring Organisation(s): This project was funded through a contract with Queensland Transport and Main Roads Abstract: The Queensland Camera Detected Offence Program (CDOP) covers management and operation of all modes of camera based traffic enforcement in Queensland. Currently this includes the mobile speed camera program, the red light camera program and fixed speed cameras and has recently been expanded to include point to point cameras and combined speed and red light cameras. This study develops a statistically valid evaluation framework for measuring the performance of the CDOP in terms of its effect on crash frequency, severity and social costs to the community in Queensland. The evaluation framework developed incorporates the impacts of different camera types, both existing and future, and potential interactions between camera types. The framework developed also articulates the use of available speed monitoring data as an intermediate measure of CDOP effectiveness. To prove the efficacy of the developed framework the study applied the developed framework to existing data with a by-product of the trial being estimates of the effects of the CDOP during It was estimated that the CDOP was associated with an overall 23% reduction in all police reported crashes and 24% reduction in fatal and hospitalisation crashes across Queensland in This represents a saving of over 5,700 crashes of all severities and over 1,100 fatal and serious injury crashes, translating to savings to the community of nearly $600M and $450M, respectively. Over 95% of the savings associated with the program derive from the mobile speed camera program which is the CDOP technology that covers by far the largest proportion of the crash population in Queensland. Application of the evaluation framework to some elements of the CDOP that were first implemented post 2008, including point to point cameras and fixed digital speed and red light cameras, remains to be shown in future applications of the framework. Key Words: speed camera, red light camera, evaluation, statistical analysis, Disclaimer This report is disseminated in the interest of information exchange. The views expressed here are those of the authors, and not necessarily those of Monash University Reproduction of this page is authorised. Monash University Accident Research Centre, Building 70, Clayton Campus, Victoria, 3800, Australia. Telephone: , Fax: DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP iii

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5 Preface Project Manager / Team Leader: Dr Stuart Newstead Research Team: Professor Max Cameron Ms Voula Stathakis Contributor Statement Stuart Newstead: Study design, literature review, evaluation framework design, crash data analysis and report preparation Max Cameron: Study design, literature review, evaluation framework design, speed data analysis and report preparation Voula Stathakis: Literature search and summary Ethics Statement Ethics approval was not required for this project. DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP v

6 Contents GLOSSARY OF ABBREVIATIONS AND TERMS... VIII EXECUTIVE SUMMARY... X REVIEW OF CDOP COMPONENTS AND EVALUATION LITERATURE REVIEW...X EVALUATION FRAMEWORK SPECIFICATION... XII DATA REQUIREMENTS...XVI RESULTS OF TEST RUN... XVII CONCLUSIONS AND RECOMMENDATIONS... XVII 1. BACKGROUND AND AIMS CAMERA TYPES, MODES OF OPERATION AND LIKELY MODES AND SCOPE OF EFFECTIVENESS RED LIGHT CAMERAS FIXED SPOT-SPEED CAMERAS COMBINED RED LIGHT SPEED CAMERAS POINT TO POINT CAMERAS MOBILE SPEED CAMERAS MAGNITUDES OF LOCAL EFFECTS OF OVERT AND COVERT CAMERAS LITERATURE REVIEW EVALUATION DESIGNS FOR PROGRAMS WITH LOCALISED EFFECTS...11 The Randomised Controlled Trial The Simple Before After Comparison The Quasi Experiment The Empirical Bayes Approach Summary of Methods for Measuring Localised Program Effects EVALUTION DESIGNS FOR PROGRAMS WITH GENERALISED OR DISPERSED EFFECTS...19 Forced Quasi Experiment Before-After Comparison Summary of Evaluation Designs for Programs with Generalised Effects STATISTICAL METHODS FOR LOCALISED AND GENERALISED EVALUATION DESIGNS...23 Statistical Distributions of Crash Data Established Statistical Analysis Techniques THE PROPOSED EVALUATION FRAMEWORK AND ANALYSIS METHODS EVALUTION OF FIXED CDOP ELEMENTS General Issues with Evaluation Design Evaluation Design for Intersection Cameras Evaluation Design for Mid Block Located Fixed Speed Cameras Statistical Methods for Fixed Camera Evaluation EVALUATION OF THE MOBILE SPEED CAMERA PROGRAM Evaluation Design Statistical Methods COMBINED ESTIMATE OF STATE-WIDE CDOP CRASH EFFECTS MEASURING PROGRAM EFFECTS ON SPEEDS Speed Monitoring Data at Fixed Camera Locations Use of Speed Measurement Data from Existing Cameras...64 vi MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

7 4.4.3 Use of State-wide Speed Monitoring Surveys DATA REQUIREMENTS FOR THE EVALUATION FRAMEWORK SPATIAL DATA CRASH DATA CAMERA OPERATIONS DATA SPEED DATA PROGRAM COST DATA AND ASSOCIATED PROGRAM ACTIVITY DATA TEST RUN OF THE EVALUATION FRAMEWORK CRASH ANALYSIS Data Red Light Cameras Fixed Spot Speed Cameras Mobile Speed Cameras Spatial Effects Mobile Speed Cameras Localised Time Based Effects State-wide Estimates of CDOP Effectiveness SPEED SURVEY DATA ANALYSIS Risk-weighting of speed measurements Urban 50 km/h limit speeds Urban 60 km/h limit speeds Rural speeds Urban speeds from sites with speed limits greater than 60 km/h DISCUSSION AND CONCLUSIONS DEVELOPMENT OF THE EVALUATION FRAMEWORK FOR ESTIMATING CRASH EFFECTS APPLICATION OF THE FRAMEWORK TO ESTIMATE 2008 CRASH REDUCTIONS SPEED AND RED LIGHT RUNNING MONITORING DATA RELATED ISSUES STEMMING FROM THE TEST RUN CONCLUSIONS RECOMMENDATIONS REFERENCES APPENDIX A: ESTIMATED YEARLY CRASH EFFECTS IF THE MOBILE SPEED CAMERA PROGRAM BY CRASH SEVERITY LEVEL AND POLICE REGION APPENDIX B: SUMMARY CDOP ABSOLUTE CRASH SAVINGS AND CRASH COST SAVINGS BY POLICE REGION AND CRASH SEVERITY DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP vii

8 Term / Abbreviation ARIMA CDOP GLOSSARY OF ABBREVIATIONS AND TERMS Meaning Auto Regressive Integrated Moving Average a statistical analysis method for correlated time series data Camera Detected Offence Program DCA Definition for Classifying Accidents a method of classifying road crashes by type of event (e.g. rear end, run off road etc) Empirical Bayes Method A statistical inference method in which the prior distribution of crashes between sites is estimated from crash data across all potential treatment sites. GEE Generalised Estimating Equation a statistical regression analysis technique that allows correlation between data observations (such as found in time series or repeated measures data) to be accommodated. GIS Geographical Information System a computer program which maps and relates information spatially Human capital crash cost A method of determining the cost of a road crash to the community based on the actual cost of all the associated events (property damage, medical costs, lost productivity etc) Negative Binomial A form of statistical regression analysis used to model count data and regression contingency tables. It assumes the response variable has a Negative Binomial distribution and assumes the logarithm of the response variable can be modelled by a linear combination of a set of independent variables. Poisson regression A form of statistical regression analysis used to model count data and contingency tables. It assumes the response variable has a Poisson distribution and assumes the logarithm of the response variable can be modelled by a linear combination of a set of independent variables. PtP Point to Point Speed Camera System an automated enforcement system designed to measure average speed over a length of road. Quasi experiment A scientific study design similar to the randomised controlled trial (see next) except selection of participants to receive the intervention is not random. Randomised controlled A scientific study design where study subjects are randomly assigned trial to one of two groups with one group being given an intervention and both groups then followed to assess the difference in an outcome of interest being attained Regression to the mean A phenomena where by Relative Risk Simpson s Paradox SLA Speed bins The risk of an outcome in one situation or group relative to another (e.g. in males relative to females) A situation in statistical analysis where the outcome effects of an action are estimated incorrectly (and more typically in the wrong direction) due to the failure of the analysis to account for the effect of another factor effecting the outcome but associated with the factor of interest Statistical Local Area local geographical areas defined by the Australian Bureau of Statistics Ranges of speed into which individual speed observations are classified for analysis (e.g. 0-5kph, 5-10kph etc) viii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

9 Speed enforcement tolerance Test of homogeneity TMR Traffic/crash migration Willingness to pay crash cost Zero inflation The amount over the speed limit a motorist can travel before a traffic offence notice will be issued A statistical test to establish whether a countermeasure has achieved the same outcome effect over multiple sites Transport and Main Roads a Queensland Government department When implementation of a countermeasure causes traffic and resulting crashes to move to another site A method of determining the cost of a road crash to the community based on a survey of the population s opinion of what it would be willing to pay to prevent a crash and associated injury outcome When count data has more observations with zero counts than predicted by the statistical distribution being used to describe the data DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP ix

10 EXECUTIVE SUMMARY The Queensland Camera Detected Offence Program (CDOP) covers management and operation of all modes of camera based traffic enforcement in Queensland. Currently this includes the mobile speed camera program, the red light camera program and fixed speed cameras, and has recently been expanded to include point to point cameras and combined speed and red light cameras. Covert operation of the mobile speed cameras commenced in April 2010 and is currently confined to a proportion of deployments in urban areas. The broad objective of this project was to develop a scientifically robust and statistically valid method for measuring the performance of the CDOP in terms of its effect on crash frequency, severity and social costs to the community in Queensland. The evaluation framework developed was required to incorporate the impacts of different camera types, both existing and future, and to articulate the use of available speed monitoring data as an intermediate measure of CDOP effectiveness. To prove the efficacy of the developed framework the study included a trial application of the framework on past data with a byproduct of the trial being estimates of the effects of the CDOP during To meet these objectives, the project was divided in to the following stages: 1. Brief review of the types of traffic enforcement cameras in operation in Queensland and their likely modes and scope of effectiveness 2. Literature review of existing evaluation frameworks and methodologies relevant to the CDOP 3. Develop and specify the CDOP evaluation framework to estimate effects on crash frequency and severity, crash costs and travel speeds related to all elements of the CDOP. Specify appropriate statistical modelling techniques to be employed in the evaluation framework 4. Determine and specify what data are required to support the evaluation framework, 5. Test run the framework using past data with a required by-product of the test run being estimates of CDOP effectiveness during 2008 REVIEW OF CDOP COMPONENTS AND EVALUATION LITERATURE REVIEW Each CDOP camera type was reviewed with respect to its likely sphere of influence on crashes and speeds in both time and space. The likely mechanism of effectiveness, such as visual presence at the site, time of operation, or number of infringements issued, was also considered. Estimation of likely camera effects was informed by a review of previous evaluations of each camera technology, where available, and of like technologies for new camera types. A summary of each technology, the likely sphere of influence, and mechanisms of effectiveness derived from the review is as follows: x MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

11 CDOP Element Sphere of Influence Mechanism of Influence Red Light Localised to intersection where camera is placed Primary: placement of camera and associated signage Combined Speed and Red Light (intersection) Spot Speed (midblock) Point to point average speed Mobile Speed (overt) Mobile speed (covert) Localised to intersection where camera is placed Localised to site of camera location within a 1-3 km radius Localised to the road length covered by the point to point system up to 1km upstream of the start of the length and up to 10km downstream of the length Localised to the site of operation (1km in urban areas, 5km in rural areas) with possible secondary effects generalised over space Generalised in space over the region of operation, with some secondary localised effects around the camera site Secondary: infringement notice issue Primary: placement of camera and associated signage Secondary: infringement notice issue Primary: placement of camera and associated signage Secondary: infringement notice issue Primary: placement of camera and associated signage Secondary: infringement notice issue Primary: definition of a site of operation and placement of camera Secondary: infringement notice issue Primary: infringement notice issue Secondary: definition of a site of operation and placement of camera Review of the likely sphere of influence of the CDOP elements showed all could be defined to have a local sphere of influence in space of varying size. Review of the literature showed the most appropriate study design for assessing the effectiveness of road safety countermeasures, whilst controlling for the potential confounding effects of other factors affecting crash outcomes, is the quasi experiment. The quasi experiment compares crash history from before to after implementation of a countermeasure with parallel changes at a suitably chosen set of control or comparison sites. The control sites must be chosen to adequately reflect the influences on crash risk of all factors other than the countermeasure being evaluated at the treatment site. The net difference in change in crash DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP xi

12 risk, from before to after countermeasure implementation between treatment and control sites, represents the net effect of the countermeasure being evaluated. The quasi experiment can be applied to crash data aggregated over the before and after periods or to data presented as a time series depending on the crash numbers at the treatment sites being evaluated. Poisson or Negative Binomial statistical generalised linear regression models were identified as being the appropriate statistical methods to apply to aggregated data whilst Poison or Negative Binomial Generalised Estimating Equations were the recommended statistical methodology for time series data. Three important potential sources of bias were identified in applying the quasi experimental framework. The first is Simpson s Paradox which arises from over aggregation of data across heterogeneous treatment sites. This can be avoided by analysing data at the individual treatment site level. The second is regression to the mean which is an artefact of the non random selection of sites for application of the countermeasure based on high past crash history. This can be avoided by sampling pre countermeasure implementation crash data over a sufficiently long period which is not coincident with the time period of crash data by which the site was chosen for treatment. The final source is accident migration which results from the countermeasure substantially altering travel patterns around the implementation site and hence resulting in the migration of the crash problem from or to another site. This is generally only a problem for countermeasures that substantially affect mobility and can be avoided by including measures of traffic flow in the design. EVALUATION FRAMEWORK SPECIFICATION Measurement of Crash and Crash Cost Effects Based on the results of the literature review and review of likely CDOP sphere and mechanism of crash effects, an evaluation framework was developed. The evaluation framework developed for the CDOP was based on the quasi experiment but treated fixed elements of the CDOP differently to the mobile speed camera program. The evaluation framework for the fixed CDOP elements was similar to a traditional accident black-spot evaluation design due to the likely predominating localised effects of the fixed cameras. For each CDOP element a hypothesised sphere of influence was defined specifying the likely geographical reach in crash effects associated with the camera placement. The spheres of influence were informed by both the literature review and the geographical characteristics of the sites at which the cameras were placed. A set of one or more control sites were then specified to be matched to each camera site based on a set of criteria including physical characteristics of the camera location and proximity to other camera sites. The proximity to other camera sites was specified in order to control for overlapping camera effects. The analysis models are specified to be able to measure any synergistic effects of overlapping enforcement types on crash outcomes. The sphere of influence defined for each CDOP camera type and the corresponding control matching criteria are summarised in the following table. xii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

13 CDOP Fixed Element Hypothesised Sphere of Influence Matching Criteria for Control Sites Red Light & Combined Speed and Red Light (intersection) Spot Speed (midblock) Point to Point average speed At the intersection of installation Secondary restriction to target crash DCA types Same road as the camera is installed on within a 1km distance from the camera site Primary: the length of road within the PtP camera system Secondary: the length of road from each end of the PtP site to 5km from this point (for divided roads the halo should only include the lanes outbound from the PtP site in each direction) 1. Statistical Local Area (SLA) 2. Intersection control 3. Intersection geometry 4. Speed Limit 5. Divided or undivided Road 6. Number of lanes 7. Traffic volume (range), if data is available 8. Matching by overlay of mobile camera sites (within the same proximity of mobile speed camera sites) 9. Matching by similar prior treatment crash history 1. Statistical Local Area (SLA) 2. Speed Limit 3. Divided or undivided Road 4. Number of lanes 5. Traffic volume (range), if data is available 6. Proximity of mobile speed camera sites 1. Statistical Local Area (SLA) 2. Speed Limit 3. Divided or undivided Road 4. Number of lanes 5. Traffic volume (range), if data is available 6. Proximity of mobile speed camera sites The only exception to the above analysis design is for fixed cameras installed on new road infrastructure (such as the Clem7 tunnels). In this instance a cross sectional evaluation design was specified where crash rates within the camera sphere of influence will be compared to those on unenforced roads of similar characteristic, in a cross sectional manner, with sites matched or standardised by traffic volumes. DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP xiii

14 For each analysis model a minimum of 3 but ideally 5 years crash data prior to camera installation were specified for analysis to minimise regression to the mean bias. Poisson or Negative Binomial regression analysis was identified as most appropriate to analyse the crash data for the fixed camera elements with the more appropriate error distribution of the two dictated by the data. Data for analysis was aggregated into a single count of crashes in the before and after camera installation period at both treatment and control sites. The analysis models specified considered data on a site by site basis to avoid Simpson s Paradox. In addition, a range of model specifications were developed to allow assessment of average camera crash effects at various levels of aggregation, anywhere from at individual camera sites, to average effects within police regions, and to average effects across Queensland as a whole. Separate models were specified for each crash severity level. The modelling framework also allowed the potential to measure varying camera after-installation crash effects provided sufficient data are available for analysis. One instance in which the after installation period will need to be specified in at least 2 periods will be if there is significant delay between installation of the camera and its activation to commence enforcement. In this instance the time from installation to activation is one period and the time after activation another. Results of each of the analysis models specified were estimates of the net percentage reduction in crashes associated with each camera type considered. Using the observed after installation crash data, the percentage crash savings were converted into absolute crash savings. The absolute crash savings were then converted in to social cost savings to the broader Queensland community using human capital based social costs for road crashes by crash severity level estimated by the Commonwealth Government Bureau of Transport, Infrastructure and Regional Economics. The evaluation framework specified for the mobile camera program was a refinement of the evaluation framework previously applied to the mobile camera program in Queensland. It also followed a quasi experimental design specified as follows: Treatment areas are defined as areas within a 1km radius of the centre of the speed camera zone in built up areas (roads with speed limits up to 80km/h) and within a 4km radius from the camera zone centre in open road areas (roads > 80km/h speed limit). Crashes are then labelled as in a treatment area if they are within the defined radius of influence from any camera site. Crashes associated with other CDOP elements should be excluded from the defined treatment areas for mobile camera sites as the combined effects of the mobile camera program and fixed CDOP element are already estimated by the methods described previously. Control areas are those remaining areas outside the defined radius of influence of the speed camera zone centres. Areas with CDOP fixed enforcement should be excluded from the controls also. Control areas are matched for analysis by police region of operation and broad speed zone of location (=<80km/h, >80km/h). Speed zone has been used as a proxy for level of urbanisation within police region since a robust definition of urban and rural areas is often difficult to make operational from information available in the crash data. It will still result in matching of road types with similar characteristics. xiv MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

15 Crashes are aggregated for analysis within the police region, speed zone and treatment and control area classification in a time series. Aggregation on a yearly time basis is recommended to maintain statistical power but still facilitate time based analysis of camera effect. It also allows the comparison of time based intermediate measures and estimation of the relationship between time based camera crash effects and other time based supporting activities such as road safety publicity and speed behaviour. Assessment of the crash effects of the mobile camera program are made by comparing trends in crash outcomes in the treatment areas over time with those in the corresponding control areas using Negative Binomial Generalised Estimating Equation statistical modelling methods. Changes in the enforcement tolerances are not expected to fundamentally change the mechanisms by which the mobile camera program, or in fact any of the fixed CDOP elements if they are also affected, influence crash outcomes. A secondary evaluation component was also specified for the mobile camera program which aims to measure time based crash effects associated with operation of a mobile camera at each site or the issuance of infringement notices from each camera operation session. This analysis had the purpose of informing optimal site visitation frequency for the mobile camera program. The evaluation framework component specified a time based grid of influence. The grid was specified with a row for each camera location and time period (typically days, weeks or months depending on the available data). Each grid cell was then labelled according to the time since the previous operation of a camera at each site. Crash counts related to each camera site were then overlaid on the analysis grid and compared to the time since camera operation layer for each site. Logistic or Poisson regression models were the applied to the crash count data, depending on the density of the crash data in the grid predicting each cell crash outcome as a function of camera site and time since operation of a camera. The evaluation framework assesses the effects of change to covert enforcement for the mobile speed camera program in 2 ways. The first tests for step changes in the control crash series relative to the treatment crash series at the point of covert operations being introduced. This is achieved by comparing changes in both the treatment and control series of the particular strata where the covert enforcement is being used to those in a neighbouring stratum were covert enforcement has not been implemented. The second way that the framework assesses the effect of change is to apply the analysis of time based camera effects to examine for a change in the duration of time based effects. This change would be in response to covert camera operations related to operation of the camera as well as issuing offence notices for each camera session Each of the component evaluations for CDOP elements produces estimates of crash and crash cost savings associated with the camera installation, categorised by police region and crash severity. The final stage of the evaluation framework for crashes and crash costs specifies the mechanism for combining the estimates by police region and crash severity to produce state-wide estimates of the crash and crash cost effects associated with the CDOP. The evaluation framework describes how these can be produced on an annual basis. DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP xv

16 Measurement of Effects on Travel Speeds Two levels of evaluation of the effects of the CDOP on travel speeds were specified in the evaluation framework. The first focuses on the state-wide measurement of speed compliance in Queensland and is based on the twice yearly state-wide speed surveys conducted by Transport and Main Roads. It proposes a summary measurement of speeding behaviour termed the risk weighted aggregate speed profile. This summary measure is constructed by characterising the speed measurement at each speed survey site according to the frequency of speed observations in each travel speed range or bin. Using appropriate relationships between speed and crash risk identified in the literature, the crash frequency in each speed bin is multiplied by the corresponding risk estimate and the products summed across all speed bins. Data are then aggregated across survey sites to give an aggregate measure of speed behaviour across Queensland that can be compared across surveys. This means of summarising the speed data is hoped to best relate to crash outcomes since it is based on a crash risk weighting of observed speeds. A number of summary measures are proposed based on various measures of crash risk related to speed identified in the literature. The most appropriate measure for long term monitoring of speed behaviour will be determined when there is sufficient overlap between the crash analysis and speed surveys to identify which speed measurement best correlates with measured crash outcomes. The second level of evaluation of the effects of the CDOP on travel speeds is based on speed measurements at specific fixed camera locations. The evaluation framework recommends that speed measurements be carried out at each new fixed camera location both before and after camera installation and at a set of matched control sites. Net changes in speed behaviour associated with each camera installation can then be measured. Summary risk weighted measures of speed behaviour are also recommended for use in this context. DATA REQUIREMENTS A range of data to facilitate application of the evaluation framework was identified. Spatial Data: Electronic map based data that can be related to spatially mapped crash data is critical to both give each camera location used under the CDOP as well as to relate the proximity of police reported crashes to each of the camera locations. Each camera site in the spatial map should be assigned a unique identifier and tagged with the CDOP camera type. Crash Data: Unit record data on all crashes reported to police in Queensland is required, labelled by the distance to the nearest CDOP camera site. Crash data also need to be labelled with an identifier of the camera site which can be linked to camera type, dates of installation, activation and operational measures. Crashes in the vicinity of multiple camera sites should have a label attached for each camera site in proximity. The crash data needs to cover a sufficient period before installation of cameras under the CDOP (with 3-5 years being considered appropriate). It needs to include critical data fields such as crash severity, vehicle types involved, road type, speed limit, police district, road name and intersecting roads. Camera Operations Data: The location of each fixed and mobile camera site in Queensland is required. For fixed cameras, dates of installation and activation of xvi MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

17 each camera are required along with information on any camera downtime. For mobile speed camera sites, required is the date the camera site became operational, the dates and times a camera was present at each location, and information about the range of dates of infringements issued from each discrete camera operation. Speed Data: Data on both general speed monitoring in Queensland and specific speed monitoring associated with the installation of fixed cameras is required o General Speed Monitoring Data: Data from Queensland comprehensive speed monitoring surveys conducted twice yearly at around 135 sites across Queensland, in both rural and urban areas across a range of speed zones, is required. Full extracts of the data will be required for each survey period from May 2009 onwards in either in unit record format or aggregated within speed bins. o Specific site speed monitoring data: Speed and red light infringement monitoring data is required for new fixed camera sites, both before and after installation and at a suitable set of control sites, to monitor speed and red light compliance related to the fixed camera technologies. RESULTS OF TEST RUN The evaluation framework developed was successfully applied to estimate the effects of each camera type in operation before 2008 on crash frequency and severity. From this, the effects of the CDOP on crash frequency and costs were able to be estimated. The test run also identified where the evaluation framework needed fine tuning or optimising when being applied to real world data. It also identified requirements for additional or modified data to better support the framework. However, none of these changes fundamentally changed the basis of the evaluation framework developed. It was estimated that the CDOP was associated with an overall 23% reduction in all police reported crashes and 24% reduction in fatal and hospitalisation crashes across Queensland in This represents a saving of over 5,700 crashes of all severities and over 1100 fatal and serious injury crashes, translating to savings to the community of nearly $600M and $450M, respectively. Over 95% of the savings associated with the program derive from the mobile speed camera program, which is the CDOP technology that covers by far the largest proportion of the crash population in Queensland. CONCLUSIONS AND RECOMMENDATIONS Overall, this study has been successful in developing a comprehensive evaluation framework through which the crash and associated speed behaviour effects of the Queensland CDOP can be assessed on an annual basis. The framework covers all existing camera based enforcement technologies in place under the CDOP and can be readily extended to consider future technologies that might be incorporated. The efficacy of the framework has been demonstrated by successfully applying it to the estimated crash effects associated with the CDOP in the year Application of the evaluation framework to some elements of the CDOP that were first implemented post 2008, including point to point cameras and fixed digital speed and red light cameras, remains to be shown in future applications of the framework. DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP xvii

18 Based on numerous issues identified in developing and applying the evaluation framework for the Queensland CDOP, a number of recommendations related to the future application of the CDOP evaluation framework are made. Broadly the recommendations are for: 1. Continued periodic application of the framework to monitor CDOP crash effects 2. Enhancements to data systems to support the future application of the framework 3. Undertake regular and systematic speed / red light compliance monitoring at fixed camera sites before and after camera installation 4. Undertake future comparisons of the recommended general speed monitoring measures with crash outcomes xviii MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

19 1. BACKGROUND AND AIMS The Queensland Camera Detected Offence Program (CDOP) is jointly managed by the Department of Transport and Main Roads (TMR) and the Queensland Police Service (QPS) and covers management and operation of all modes of camera based traffic enforcement in Queensland. Currently this includes the mobile speed camera program, the red light camera program and fixed speed cameras and has recently been expanded to include point to point cameras and combined speed and red light cameras. Covert operation of the mobile speed cameras commenced in April 2010 and is currently confined to a proportion of deployments in urban areas. The broad objective of this project was to develop a statistically valid method for measuring the performance of the CDOP in terms of its effect on crash frequency, severity and costs to the community in Queensland. The evaluation framework developed was required to incorporate the impacts of different camera types, both existing and future, and potential interactions between camera types.the framework developed was also required to articulate the use of available speed monitoring data as an intermediate measure of CDOP effectiveness. To prove the efficacy of the developed framework the study was required to trial application of the framework on past data with a by-product of the trial being to estimate the effects of the CDOP during To meet these objectives, the project has been divided in to the following stages: 1. Brief review of the types of traffic enforcement cameras in operation in Queensland and their likely modes and scope of effectiveness 2. Literature review of existing evaluation frameworks and methodologies relevant to the CDOP 3. Develop and specify the CDOP evaluation framework and design including mobile and fixed speed cameras, red light cameras, combined red/light speed and point to point cameras on: a. Crash frequency and severity b. Crash costs c. Travel speeds 4. Develop appropriate statistical modelling techniques to be employed in the evaluation framework 5. Determine and specify what data are required to support the evaluation framework, including determining which data are critical and which are desirable 6. Test run the framework using past data with a required by-product of the test run being estimates of CDOP effectiveness during 2008 DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP 1

20 2. CAMERA TYPES, MODES OF OPERATION AND LIKELY MODES AND SCOPE OF EFFECTIVENESS A first consideration in the development of an evaluation framework for the Queensland CDOP was to consider the likely mechanism of effectiveness of the various camera types. This facilitated design of a framework that allows measurement of the camera effects in the appropriate space and time duration of influence. A brief summary of each type of traffic infringement camera in use in Queensland follows with discussion of its mode of operation and intended or likely mechanism of behaviour change and consequently crash reduction effects. 2.1 RED LIGHT CAMERAS Cameras for enforcement of red light infringements were one of the first forms of camera based automated enforcement to be introduced on a wide scale. They have been in operation in a number of jurisdictions around the world for many decades and have been operational in Queensland since The majority of fixed red light cameras operate on wet film technology and are designed to detect vehicles infringing a red traffic signal at an intersection. They can enforce both through traffic as well as right turning traffic where there is full or partial control of the right turn phase by the signals. Installation of the camera is such that it generally only enforces one leg of the intersection driven by the need for the traffic signals to be in view of the camera for evidentiary reasons with 2 photographs of the infringing vehicle being taken to verify it is moving. Sites for camera placement are understood to be chosen on the basis of high rates of red light infringing characterised by specific crash types related to these infringements such as right turn against and right angle crashes. Red light cameras are placed and operated in an overt manner with the cameras being clearly visible on pole mountings on the roadside. In Queensland there is no accompanying signage to alert motorists of the presence of the camera (apart from eight trial sites). Infringement notices issued from the cameras also clearly denote the location at which the infringement occurred. Based on the relative conspicuous placement of red light cameras in Queensland, their fixed nature and the statement of location on the infringement notice, it can be expected that the effects of the cameras on crashes are likely to be highly localised to the sites where the cameras are placed. Most of the existing evaluation studies, which are summarised by Retting and colleagues (Retting, Ferguson et al. 2003), also assume the effects to be localised at or within close proximity of the camera site. Whether the effects of the camera are localised to the intersection leg on which it is placed or spill over to the whole intersection are not clear. The spill over effects may be related to the use of accompanying signage on other legs warning of the presence of a camera, as is used in Victoria, or the visibility of the cameras from other legs. Primary mechanisms of deterrence associated with red light cameras identified in the evaluation studies are the overt physical presence of the camera and accompanying signage and the receipt of a traffic infringement by offending motorists. Given the overt nature of the program, the former is likely to be stronger.released under RTI - DTMR 2 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

21 2.2 FIXED SPOT-SPEED CAMERAS There are relatively few published evaluations of the crash effects of fixed speed cameras from which to glean information on likely effects. From those that are published it appears that fixed speed cameras are generally used as a black spot type treatment at locations where speeding has been identified as a primary driver of identified elevated crash risk (Cameron & Delaney 2006; Wilson, Willis et al. 2010). The most relevant evaluation for the Australian context of fixed speed cameras is that of the NSW fixed speed camera program (ARRB 2005). Effects estimated for this program are highly localised to within 3km of the camera site, possibly reflecting the high visibility signage used in conjunction with the cameras as part of this program. Although not specifically evaluated, the high visibility of the NSW program also suggests the primary mechanism of deterrence is the presence of the camera with infringement notices issued acting as a secondary deterrence for infringing drivers. Deterrence related to camera visibility is also demonstrated in the Norwegian program (Elvik 1997) where speed cameras are not always present in the fixed roadside boxes. Whether strongly localised deterrence is maintained when accompanying signage of the cameras is not used is unknown but considered likely. Lack of accompanying signage, however, might lead to a shift in the deterrence mechanism towards receipt of the infringement notice. One of the few other evaluations of fixed speed cameras was conducted for the U.K. camera program (Gains 2005). Installation of the cameras in the U.K. program being evaluated was carried out in large numbers at relatively close proximity (within 0.5km). Unlike the other programs evaluated, there was some suggestion that the U.K. program may have achieved generalised effects (that is effects beyond the areas local to the camera sites) across the trial regions in which the cameras were situated. Whether this was a true generalised effect or simply a reflection of the density of camera operations is hard to identify. Furthermore, the generalised effects were only identified in early evaluations and not in the latest evaluation, suggesting that the population may learn and adapt to the specific locations of the fixed cameras over time. Based on the previous evaluations, it is likely that fixed cameras will have strongly localised crash effects at the camera site with deterrence primarily driven by the presence of the camera. With regards to use of signage under the CDOP, TMR has advised that: Each fixed speed camera site will have: A minimum of one sign positioned within one kilometre of the camera site in the direction being enforced; if suitable sign locations cannot be found within one kilometre, this distance may be increased; wherever possible, motorists who enter from on-ramps or side roads should encounter at least one sign on the approach to a camera site; the signs will be installed in the following order: 1. FIXED SPEED CAMERA AHEAD FOR ROAD SAFETY (placed furthest from the camera site) DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP 3

22 2. FIXED SPEED CAMERA 24 HOURS FOR ROAD SAFETY (placed closest to the camera site); and where road width or other factors affect the visibility of fixed speed camera signs, additional signs should be installed for example, signs installed on both sides of a three lane motorway. N.B. the Department s preference is for two signs at each site however if not practical only one sign will be installed. Consequently, halo effects can be expected with the CDOP at least 1 kilometre either side of the fixed camera locations. 2.3 COMBINED RED LIGHT SPEED CAMERAS Cameras at signalised intersections which detect both red-light running and speeding infringements are a recent technology. The principal reason for installing these combination cameras is to reduce red-light running crashes and also to reduce the risk and severity of the remaining crashes. The first objective is the same as for traditional red-light cameras whilst it could also be expected that the threat of detection for speeding by the cameras may encourage a proportion of motorists to travel at lower speeds through the intersection. As such the cameras appear to be consistent in objective with both the red light and fixed spot-speed cameras. Geographical reach in effectiveness and likely deterrence mechanism is likely to be similar to both single function camera types. The only published evaluation of the effects of this enforcement method is for three such cameras in Canberra (Brinson 2002). Results in terms of changes in speeds and reductions in crashes varied from site to site and results from the analysis were deemed inconclusive. For the purpose of this study then, it is likely that the effects of the combined red light and speed cameras will be highly localised to the intersection and perhaps the leg on which the camera is installed. Possible halo effects on other intersection legs and up and down each intersecting road for some distance are also possible. Spread of the halo might be related to the use of accompanying signage. TMR advised that the fixed digital speed and red light cameras will be signed where it is safe and practical to do so. At this stage only one sign will be installed. Consequently for the CDOP, crash effects will most likely be localised to the site with deterrence driven by both the camera presence and the issuing of infringement notices. 2.4 POINT TO POINT CAMERAS Point-to-point (PtP) camera technology uses a number of cameras mounted at staged intervals along a particular route. The cameras are able to measure the average speed between two points and/or the spot speed at an individual camera site, although the latter mode of enforcement has not been used in the PtP installations in Victoria up to the end of 2010 it is being considered for future use. In order to measure the average speed between two points, the cameras must be linked to one another and/or the images and times at which they were captured must be linkable remotely in some way. The average speed is then determined by dividing the distance travelled by the time taken to travel between the 4 MONASH UNIVERSITY ACCIDENT RESEARCH CENTRE

23 two points. The distance between two camera sites may vary from as low as 300 meters to up to tens of kilometres. There are few published evaluations of PtP camera systems. The most detailed of these is the evaluation the U.K. PtP system installed on Nottingham s main link road from the M1 Motorway in July 2000 (Keenan 2002). Two cameras were mounted along the enforced 40 mph road length approximately 0.5 kilometres apart. Compared with traditional wet-film spot-speed fixed cameras, the study found that the spot-speed fixed cameras have a sitespecific effect whereas the point-to-point camera system has a link-long influence on drivers and their speeds, despite enforcement being visible only at the start and end of the enforced road length. In July 2005, the Scottish government launched a pilot scheme of PtP cameras on a 46 km section of the A77 highway in the Strathclyde area. It is described as a complex route including single and dual carriageways with varying speed limits. The southern section is a winding and challenging coastal road in South West Scotland. The route had experienced 20 road deaths and 95 serious injuries over the five-year period Published descriptions of the system are unclear: apparently there are 14 camera sections, averaging 0.5 mile in length, between which the pairs of cameras are switched on periodically. The cameras are supported by around 50 safety camera warning signs with the message average speed speed cameras and a camera symbol. The intention is to deter speeding along the full length of the route. However, the system does not appear to measure average speeds along contiguous sections of the route nor over the whole route. This may relate to the varying speed limit zones along the highway covered. A preliminary evaluation of the Strathclyde A77 system by Transport Scotland has found that there was a statistically significant 20% reduction in reported injury crashes (including fatal) during the first two years of operation on the route, compared with crash experience during the previous three years (A77SG 2007). After three years of operation, fatal and serious injury crashes were reduced by 29.3% and slight injury crashes were reduced by 15.6% (A77SG 2008). Based on this evidence, it is likely that the CDOP PtP cameras will provide deterrence along the full length of road between the PtP start and end gantries. If the cameras are also operated in spot mode there may also be some additional deterrence effects at the camera gantry sites. Point to point cameras systems will be signed in Queensland. There will be one prominent sign installed in the direction of enforcement within approximately one kilometre of the first camera in the point-to-point system. A second prominent sign installed in the direction of enforcement within approximately one kilometre of reaching the last camera in the point-to-point system. If a suitable sign location cannot be established within one kilometre of the first or second camera, this distance may be altered but only within reason. The presence of signage will most likely localise the effects of the PtP system to within the signed area with possible halo effects downstream of the covered link. Possible additional localised effects will be related to the use of the PtP system in spot mode. DEVELOPMENT OF AN EVALUATION FRAMEWORK FOR THE QUEENSLAND CDOP 5