Application of Mobile Mapping technology within a Roads ... - CiteSeerX

International Global Navigation Satellite Systems Society IGNSS Symposium 2007 The University of New South Wales, Sydney, Australia 4 – 6 December, 2007

Application of Mobile Mapping Technology within a Roads and Traffic Authority Dennis Robert Entriken* School of Surveying & Spatial Information Systems, UNSW, Australia Ph: +61 2 9598 7731, Fax: +61 2 9598 7794, Email: [email protected]

Chris Rizos School of Surveying & Spatial Information Systems, UNSW, Australia Ph: +61 2 9385 4205, Fax: +61 2 9313 7493, Email: [email protected]

ABSTRACT This paper describes the application of Mobile Mapping Technology within a Roads and Traffic Authority to assist individual business units, and the organisation as a whole, to achieve operational objectives. The authors discuss a specific implementation of a Mobile Mapping System and describe the different datasets produced from that technology, as well as how the derived data can be used within different business units to extract information and/or aid decision support. Some specific examples of applying Mobile Mapping Technology will be described, showing how such utilisation leads to the provision of better services to clients in terms of efficiency and road user safety. Mobile Mapping Technology within a Roads and Traffic Authority is becoming increasingly recognised as an essential technology. KEYWORDS: Mobile Mapping, Video Log, Road Imaging, GPS/INS/Video,

Roads and Traffic Authority. * Dennis Entriken works for the Roads and Traffic Authority of NSW, managing their Mobile Mapping System, known as GIPSICAM. Dennis designed and developed the current generation GIPSICAM system, GCv3.

1. INTRODUCTION The primary objective of a Roads and Traffic Authority is the management of the road network within its jurisdiction, to ensure efficient traffic flow and safe roads. The road network may comprise of tens, hundreds or thousands of kilometres of road carriageway, consisting of various asset components such as road pavements, lanes, road shoulders, bridges, tunnels, culverts, vehicle ferries, rest areas, traffic lights, roundabouts, medians, guardrails, guideposts, signs and line marking (Roads and Traffic Authority, 2007). An important part of managing a road network is building and maintaining an inventory of assets. Xiong and Floyd (2004) stated that a “Vehicle-based Mobile Mapping System (MMS) proved to be an effective technology for sign inventory and has the potential for many other types of roadway features and characteristics” and that “these features can be very effectively captured with MMS images.” This statement is verified by the experience of the Roads and Traffic Authority of NSW (RTA) with their GIPSICAM MMS. However, an MMS has much more to offer then just building an inventory of assets. Other Roads and Traffic Authorities within Australia have also recognised the potential of a MMS. Queensland Main Roads built a MMS in the 1990’s and still operate it today. The remaining states outsource the road image data collection of their state road network to commercial MMS operators here in Australia, the most popular of which is the Australian Roads Research Board (ARRB) Hawkeye 2000 system. A list of organisations with MMS technology in Australia includes: x Roads and Traffic Authority of NSW x QLD Main Roads x ARRB group (ARRB, 2007) x Geomatic Technologies (Geomatic Technologies, 2007) x Pavement Management Services (PMS, 2007) x Puredata (Puredata, 2007) x Cardno (Cardno, 2007) 2. GIPSICAM GIPSICAM is a Mobile Mapping System (MMS), developed in-house by the Roads and Traffic Authority of NSW (RTA), to survey the NSW state road network. The word GIPSICAM is an acronym for “Global-Inertial Positioning Systems Image Capture for Asset Management” (Greening, 2003). 2.1 A brief history of GIPSICAM

In the mid 1990’s the RTA started to realise the potential of rapid data collection techniques to efficiently collect large volumes of asset data along the state roads within NSW. It was found that this type of data collection was more efficient than manual collection techniques in terms of cost and time required to collect the data. During this time the RTA experimented with simple Video Log systems as a precursor to the development of GIPSICAM.

The first generation GIPSICAM system (GCv1) was developed in 1996-1997, in co-operation with ARRB, to collect road video data for the proposed upgrade of the Pacific Highway. GCv1 consisted of two CCTV cameras that were aligned for stereo positioning, analogue video, DGPS and the ARRB-built GIPSITRAC INS. In 1997 GCv1 was used to measure road cracking on the Sydney to Newcastle Freeway. Then in 1998 GCv1 was used to capture road video data for the Tasmanian state road network. The Sydney Olympics in 2000 required road video of all the Olympic routes. This was the catalyst for the development of the second generation GIPSICAM system (GCv2). GCv2’s primary upgrades consisted of the move to digital video to increase the quality of the road video data and the further development of software for the processing and display of the data. It was after the 2000 Olympics that the potential of the GIPSICAM system was truly realised within the RTA. Since then the GIPSICAM system has been used to routinely survey all the state roads within NSW. 2.2 A brief overview of GIPSICAM v3

GIPSICAM v3 (GCv3) refers to the current generation Mobile Mapping System (MMS) utilised within the RTA. GCv3 was developed in-house by the RTA throughout 2005 and became operational in March 2006. See Figure 1.

Figure 1. The Roads and Traffic Authority’s GCv3 vehicle

The core components of the GCv3 vehicle are: x Mercedes-Benz Sprinter vehicle, with extensive after-market custom modifications, providing a reliable, spacious, comfortable, OH&S friendly and protective environment for both staff and equipment, to ensure safe, efficient and accurate surveys. x DGPS receiver with real-time OmniSTAR corrections, which provides the primary absolute positioning of the vehicle trajectory. x GPS receiver, which is the backup absolute positioning instrument. It logs autonomous GPS data that can be post-processed with GPS base station data to provide supplementary absolute position data, when required. It also provides navigation information to the vehicle operator. x Fibre optic gyroscope (FOG), which provides the direction of travel of the vehicle, which in turn is used to determine relative positioning via dead reckoning (DR). x Laser-based optical sensor, which provides data on distance travelled. x Digital readout odometers, which use the vehicle ABS pulses to determine distance travelled. x Four IEEE 1394a mega-pixel progressive scan digital video cameras, with a selection of wide-angle, standard and telephoto mega-pixel lenses, which are used to collect high resolution digital video. x Dual processor server, mounted in a custom-built vibration-dampened computer rack, which provides the computer processing power within the vehicle. x Operator console consisting of a 15” flat panel monitor mounted on a custom-built monitor arm, an optical Marble Mouse and a flexible mini-keyboard. x Two independent electrical/power systems, each with their own battery bank and alternator for charging. One electrical system for the vehicle and the other for the MMS equipment. The MMS circuit has a 12V power conditioner and a power inverter to provide 240V. External 240V mains power can also be connected to the vehicle for the running of equipment in the workshop as well as charging up batteries. x GIPSITRAC INS, providing relative positioning and vehicle attitude, comprising of: o GPS receiver, which is used for GIPSITRAC sensor synchronisation. o Two micro-electromechanical system (MEMS) gyroscopes, which are used to determine the direction of travel and the horizontal radius of the vehicle path. o Two accelerometers, one placed in a longitudinal orientation and the other in a transverse orientation, which are used to determine the grade, cross-fall and vertical radius of the vehicle path. o Rotational speed sensor, used in conjunction with a manufactured 40-toothed steel cog that is fitted in-line with the driveshaft, which is used for GIPSITRAC sensor synchronisation and also provides data on the distance travelled. o Microprocessor, which controls GIPSITRAC sensors and all I/O functions. The GCv3 vehicle surveys more than one third of the 17,623km of state road in NSW each survey season, which is from October through to March. Roads are surveyed in both directions, rather than just having a camera “point out the back of the vehicle and across to the other side of the road”. There are also tight controls on image quality with procedures defining hours of data collection and direction of survey relative to the time of the day and the month of the year. The emphasis is on collection of accurate, high quality data rather than quantity. See Figure 2.

Figure 2. Front and side camera road images from GCv3

The data collected by the GCv3 vehicle is post-processed back in the office to produce the following outputs: ƒ Road centreline vector data. ƒ Georeferenced “drive-along-the-road” imagery. ƒ Georeferenced road geometry data (grade, crossfall, horizontal and vertical radius). Road images are captured every 10m along the road, in both directions. See Figure 3.

Figure 3. GCv3 georeferenced road image positions displayed on ©SKM orthophotography data

The processed data is then distributed/replicated immediately via the RTA’s wide-area network (WAN) to nine dedicated Novell severs at the larger RTA offices throughout NSW. Smaller offices utilise standalone Ethernet drives or external USB drives which have the data duplicated onto them at regular intervals.

RTA staff members may then access the GIPSICAM data using RTA-developed software or commercial GIS software such as ESRI ArcGIS. The GIPSICAM dataset consists of approximately 3,900,000 standard resolution front camera images taking up about 350GB of file space, for the complete state road network. With the addition of side camera data from GCv3, the GIPSICAM dataset will expand to approximately 7,800,000 standard resolution front and side camera images requiring about 700GB of file space. The high resolution front and side camera images from GCv3 are not currently distributed to all GIPSICAM data servers/drives due to space limitations, with complete network coverage expected to total between 1.6TB and 1.8TB. Historical GIPSICAM datasets are maintained on a single server and accessed by RTA staff members via the RTA intranet. 3. ROUTINE APPLICATIONS OF THE GIPSICAM DATA WITHIN THE RTA “The RTA employs about 6,900 staff in more than 180 offices throughout NSW, including 129 motor registries” (Roads and Traffic Authority, 2007). There are currently 1,800 RTA staff members that use GIPSICAM data on a regular or semiregular basis to perform their duties. Excluding motor registry staff members, who deal more with licensing and registration, it becomes apparent that a very high percentage of RTA staff use GIPSICAM data. The “Regional Operations and Engineering Services”, “Major Infrastructure” and “Network Management” directorates, as well as Road Safety branch, are the biggest users. 3.1 Road centreline vector data

The GIPSICAM road centreline data is used as a primary data source in the maintenance of the NSW classified roads dataset. So how is the GIPSICAM road centreline data produced? GPS/DGPS data is susceptible to errors caused by surrounding buildings, landforms and trees. GPS/DGPS signal can be lost or degraded underneath tree canopies, in tunnels, next to very tall buildings and cliffs, and in mountainous areas. Errors such as multipath, which is where GPS signals bounce off other objects before being received by the GPS receiver and thus give a false pseudorange distance and hence an incorrect position, are prevalent in areas of tall buildings, bridges and cliffs. The number of available satellites and the satellite geometry can also affect the accuracy of the GPS/DGPS position results. Thus, while DGPS data can be accurate to less than one metre (2D) in favourable locations with good visibility and geometry conditions, DGPS can still be affected by signal loss/degradation, multipath and bad satellite geometries, which will reduce the accuracy of DGPS data (Leica Geosystems Inc, 1999). INS systems can determine relative position, based on the previous position plus information measured from the INS sensors and an odometer. Errors that occur are cumulative and thus, while an INS system may be accurate for short periods of time, the INS-determined positions will become less and less accurate with time if relied upon as the sole positioning technology

(Ford et al, 2004). As already mentioned, DGPS is susceptible to errors from signal loss/degradation, multipath or bad satellite geometry, however DGPS can provide discrete positions to sub-metre accuracy. On the other hand, INS data is not affected by signal loss/degradation, multipath or bad satellite geometry, and is thus continually available, although it suffers from cumulative errors. However, if DGPS and INS are combined then advantage can be taken of sub-metre accurate discrete positions supplemented by continuously available INS data (Li et al, 2005). The RTA has developed a Least Squares adjustment program that combines the DGPS data from the DGPS/GPS receivers and the INS data from GIPSITRAC and the FOG to generate accurate GCv3 vehicle position and attitude information. See Figure 3. The GCv3 vehicle surveys “undivided carriageway” in both directions, always driving in the through-lane closest to the road centreline. Thus, if one averages the vehicle position data for both directions then the result is an approximation of the location of the true road centreline. The GCv3 vehicle surveys “divided carriageway”, such as on a freeway or a road with a concrete median down the centre of the road, in the normal direction of traffic flow, but always driving in the centre through-lane if there are three lanes, or always driving in the left lane through-lane if there is only two lanes, or always driving in the through-lane if there is only one lane. Thus the vehicle position data is an approximation of the actual carriageway centreline, with the exception of two lane roads where an offset is applied to the vehicle position data to generate an approximation of the actual carriageway centreline. Approximating the road centreline as described above is a much simpler method of accurately determining the location of the road centreline, as opposed to methods that try to extract the centreline line markings from georeferenced images. In areas of good DGPS, the GIPSICAM-derived centreline data is accurate to better than one metre. In more challenging environments such as in the CBD with tall buildings, through a state forest with tree canopy above the road, or through any of Sydney’s tunnels, then the centreline data accuracy will be diminished. Based on comparisons with other datasets such as 10cm orthophotography and field survey data, RTA staff estimate the horizontal accuracy of the statewide GIPSICAM-derived vehicle position dataset to be sub-two-metres (95% confidence interval). The use of the OmniSTAR HP DGPS correction service would potentially increase this accuracy to the decimetre level (OmniSTAR, 2005), while utilising real time kinematic (RTK) technology would potentially increase the accuracy to the centimetre level (Wikipedia, 2007). Pre-2005, the NSW road centreline data maintained by the NSW Department of Lands was acknowledged as being inaccurate and a project was established with the aim of increasing the accuracy of the dataset (Department of Lands, 2005). The RTA and the NSW Department of Lands came to an agreement that the RTA would build and maintain an accurate NSW classified roads centreline dataset that would be provided to the NSW Department of Lands and other state government departments. The RTA created the new dataset with the alignment of the state roads based primarily on GIPSICAM centreline data, supplemented with highresolution orthophotography and road design data. Newly built and/or gazetted state roads and roads with altered alignments are surveyed by the

GCv3 vehicle, and the new centreline data is used to maintain the NSW classified roads centreline dataset. The NSW classified roads centreline dataset is available in the RTA via ESRI SDE and can be displayed in ESRI ArcMap with other RTA corporate data. It is also used as the framework for the spatial component of the RTA’s Road Asset Maintenance System (RAMS). 3.2 Georeferenced road images

As the well-known proverb goes, “a picture is worth a thousand words”. This is certainly true when it comes to terrestrial road images, as an image can reveal so much information. To be able to look at an image and instantly “see” what asset items are present and what their condition was at the time the image was captured has proved very useful within the RTA. Add to this the capability to extract asset position, dimension, condition and attribute information and one starts to realise the potential of an MMS. See Figure 4.

Figure 4. GCv3 georeferenced road image

By far the most common application of MMS road images is, as mentioned, as a visual inspection of the road condition/characteristics. This statement is confirmed by Meers (2007) who states “the images are most commonly used for simply ‘visualising’ a section of road whether it is to confirm one's mental image of the section, or create a new understanding of the road and it's environment for those that are not familiar with it, or to pick exact locations of certain features in relation to others”.

The advantage of using the road images as a visual data source is that in most cases the RTA staff members do not need to travel to a specific location or worksite to undertake their work. “In terms of occupational health and safety (OH&S), one of the major benefits of utilising the road images is the level of protection given to RTA staff by allowing them to perform their duties in a safe environment rather than having to actually walk out onto the road” stated Dunlop (2007). Alternatively, the road image data could be used to prepare for an actual roadside inspection. This saves time and money in unnecessary travel. Avoiding unnecessary travel to a roadside location is particularly important in remote areas such as in the “Western” and “South-West” regions of NSW. In the case of historical data there is no substitute for an image record. Lastly, the ability to capture an asset inventory quickly, easily and accurately without the need to travel onsite is an inexpensive and easily repeatable data collection process. Examples of road image use include: x Asset inspection, identification, validation and remaining life determination by asset managers, maintenance planners, designers and engineers. x Asset inventory data collection for import into the RTA’s Road Asset Maintenance System (RAMS) or the RTA’s corporate GIS. x Asset quantification (position, width, height, length, area). x Road safety audit and analysis of safety related assets. x Critical habitat and environmental corridor determination/inspection by environmental officers. x Surveillance of maintenance and construction works by surveillance officers. x Sharing a “common frame-of-reference”, as in looking at the same road image, when talking to other RTA business units. x Scoping of works with stakeholders such as local government and contractors. x Verification of segment markings on the side of the road. x Inspection of current and historical image data to show the presence/absence or condition of assets and the roadside environment. x Visualisation of road geometry and road condition data. x Verification and geocoding of crash sites from police reports. 3.3 Georeferenced road geometry data

“GIPSITRAC provides an accurate and comprehensive record of the geometry of a road” (Roper, 2003). GIPSITRAC is an acronym for “Global and Inertial Positioning System Integration for Tracking Route Alignment and Crossfall” (ARRB, 1995). The GIPSITRAC “box” was first designed and built by ARRB in the early 1990’s. In its initial configuration, GIPSITRAC consisted of two gyros, two accelerometers and a sensor to measure distance. The original purpose of the GIPSITRAC was to collect road geometry data relative to a linear reference system. Later a GPS was added to GIPSITRAC, and finally a video time-code interface, to become part of the first generation GIPSICAM system (GCv1). Using data from the gyroscopes, accelerometers and the mechanical odometer, the GIPSICAM system can calculate road geometry information, specifically grade, crossfall, horizontal radius and vertical radius. Other RTA software can derive and display additional information such as horizontal curvature, vertical curvature, advisory speed, transverse (centripetal) acceleration, vertical acceleration, longitudinal acceleration, combined vertical/transverse acceleration, combined longitudinal/transverse acceleration, stop sight

distance and K value (Roads and Traffic Authority, 2006). The accuracy of the GIPSITRAC box according to its design specifications (ARRB, 1995) is: x Grade: 0.2% x Crossfall: 0.2% x Curvature: 0.1 radian/km Known limitations of the surveyed GIPSITRAC road geometry data include (Roads and Traffic Authority, 2006): x Geometry data is valid for GIPSITRAC/GIPSICAM vehicle path only. x Horizontal and vertical radii can be affected by the skills and experience of the driver. Examples: vehicle entry and exit angle of a curve; oversteering and understeering through corners; vehicle “wander”. x Grade can be affected by the skills and experience of the driver. Examples: braking heavily; accelerating heavily. x Crossfall can be affected by cross-winds and centrifugal forces acting on vehicle suspension when going around corners. The limitations affecting the road geometry data are minimised by ensuring the GIPSICAM drivers are skilled drivers, are very experienced at driving the GIPSICAM vehicle and are aware of the situations that may affect the accuracy of the road geometry data. The estimated accuracy (95% confidence interval) of the road geometry data, as surveyed by GIPSICAM, is (Roads and Traffic Authority, 2006): x Grade: ±1% x Crossfall: ±2% x Radii: ±20% The advantage of collecting road geometry data via an MMS rather than traditional surveying methods is a matter of time and cost. An MMS can survey 80km of road per hour. While the accuracy of the data collected by traditional surveying methods is more accurate, the rate at which traditional survey methods collect data cannot compete with a MMS in terms of throughput. The road geometry data is georeferenced so it can be displayed and analysed in a GIS. The RTA has developed a computer program that plots and correlates road geometry data, including derived data, for analysis. The georeferenced road images are also linked to the road geometry data for visual inspection, feature interrogation or asset extraction. The use of the road geometry data within the RTA is increasing rapidly, with the Road Safety Branch finding the data particularly useful for analysing accident data. Designers are also finding the geometry data a useful tool to be used in conjunction with the RTA developed Brownfields Design Guide, a road design guide that describes solutions to designing safe roads with limited funds. See Figure 5.

Figure 5. A plot of GCv3 road geometry data

Examples of road geometry data use include: x Analysis of accident data by correlating accident sites against road geometry. x Pavement rehabilitation projects using the Brownfields Design Guide. x Heavy vehicle route planning. x Bus route safety analysis. x NSW road network safety analysis. x Road-water runoff determination. x Historical enquiries involving road geometry. 4. SPECIFIC APPLICATIONS OF THE GIPSICAM DATA WITHIN THE RTA A short description of a selection of MMS related projects undertaken within the RTA is given below. 4.1 Asset data collection

The RTA has been conducting an inventory of all lanes data, on all NSW state roads, for the past 18 months using GIPSICAM’s georeferenced road images. The lanes information collected includes primary and second functions, and is comprehensive in terms of detail and state road coverage. The lanes data is imported into the RTA’s Road Asset Maintenance System (RAMS). Road Safety Branch used GIPSICAM’s georeferenced road images to conduct an inventory of “crash related” road assets within rural areas while building their Rural Roads Stereotypical Crash Rates database. Assets collected included speed signs, crash barriers, pavement surface

type, road shoulder width, median width, bridges, run-off areas and accesses/driveways. Analysing crash location data against the “crash related” asset data collected from the road images, staff from Road Safety Branch were able to determine parameters that appeared to influence crash rates on rural roads, which yielded a mechanism for determining average crash rates for different stereotypes of rural road (Chee, 2005). According to Tang (2007), “Safer Roads Section is currently undertaking a study to review and update the analysis methods and data within the Rural Roads Stereotypical Crash Rates database”. GIPSICAM data will be used to conduct the update of the “crash related” road assets inventory. The RTA conducts an annual inventory of road features related to pavement skid resistance. The features extracted from the GIPSICAM georeferenced image data are traffic light controlled intersections, pedestrian crossings, school crossings, railway level crossings and roundabouts. The data is then available for use in safety related projects. 4.2 Road pavement crack mapping

The RTA has a RoadCrack vehicle, which is capable of accurately measuring the width of cracks in the road pavement and classifying the cracking (Roads and Traffic Authority, 2005), however no record of crack length is collected and no visual record is maintained. A trial project is about to commence to utilise GIPSICAM for road pavement crack mapping, as a supplement data source to the RoadCrack data. 4.3 Accurate measuring of distance

When state roads are created or modified, the network geometry within RAMS is updated to reflect the new state of the state road network. A critical attribute required is the length of the new/modified section of road. This length can be obtained by measuring the distance from the start to the end of the new/modified section of road using the georeferenced road images. Another certified “distance measuring” procedure that can be utilised involves using the GCv3 vehicle. The GCv3 vehicle has three independent distance measuring devices, which are a laser-based odometer under the front of the vehicle, a mechanical-based odometer builtin to the driveshaft and an odometer fitted to the vehicle ABS system. The section of road or part of a road that needs to be measured very accurately can be driven in the GCv3 vehicle and the three calibrated odometers will provide three sets of accurate, independent and comparative distances. 4.4 School bus routes

The NSW Ministry of Transport (MOT) and the RTA are currently conducting a trial surveying school bus routes. The project has two proposed outcomes, which are the collection of road geometry data and lane width data to be used as part of a MOT school bus route risk assessment, and the collection of road images for planning and as a visual record of the routes. 4.5 Road longsections (heights)

The alignment data produced by GIPSICAM utilises absolute positions from an OmniSTAR corrected DGPS as anchor points to “tie-in” the relative positioning data acquired from the dead reckoning (DR) system. As mentioned previously, utilising a more accurate source of absolute positions would increase the accuracy of the alignment data that is produced. This concept has been utilised in a recent project for RTA’s Survey Section, using traditional survey methods and GIPSICAM DR data. The project involved the accurate representation of a road centreline longsection, to within 100mm, to be used as a frame-of-reference for a hydrological investigation on a road that was known to have flooding issues. Data was collected at irregular intervals along the road section using traditional survey methods. The survey data was then combined with the GIPSICAM DR data from a GIPSICAM survey of the section of the road to produce an accurate road alignment, from which the longsection information was extracted. 4.6 Regional Forest Agreements project

National Park Estate legislation was enacted in 2000, 2002 and 2003 which enabled the transfer of title of specific state forest, nature reserve and conservation areas to National Park Estate (Clark, 2005). However, before the transfer of title was to take place, an adjustment of the description of the land to be transferred needed to occur. In particular, the RTA needed to ensure that no classified roads road reserves were included in the Regional Forest Agreement. GIPSICAM centreline data was used as a reference alignment dataset for determining if a road reserve needed closer investigation, as well as a verification dataset for data collected by traditional survey methods to accurately determine road reserve boundaries. See Figure 6.

Figure 6. GIPSICAM centreline data used in the RFA project

4.7 Historical record searches

RTA staff regularly source historical GIPSICAM data to determine past road conditions or to verify the presence or absence of a roadside asset. A common search request is “provide all GIPSICAM road images between point A and point B on road C, between the dates of xx/xx/xxxx and yy/yy/yyyy”. Other typical requests include “verify the existence of sign type A at location B on the date xx/xx/xxxx” or “verify the speed limit at location A on the date xx/xx/xxxx”. Historical road geometry data is also requested, with grade and crossfall being the two primary parameters of interest. Use of historical GIPSICAM data by RTA staff is increasing each year, and the GIPSICAM road image and road geometry data has been recognised as an important historical record of the NSW state roads. 3. CONCLUSIONS Mobile Mapping System (MMS) data is now routinely used throughout the RTA; from the Road Safety Branch using the GIPSICAM data to make roads safer; to Regional Operations and Engineering Services Directorate using the GIPSICAM data to build, maintain and inspect roads, bridges and other road assets; to the Network Management Directorate using GIPSICAM data to manage traffic and the road network; it can be seen that a MMS such as the RTA’s GIPSICAM is vital technology to a Roads and Traffic Authority. The high number of RTA staff from various directorates who utilise the GIPSICAM data to perform their duties, many on a daily basis, verifies the importance of MMS technology to a Roads and Traffic Authority such as the RTA. ACKNOWLEDGEMENTS The authors would like to acknowledge and thank the following Roads and Traffic Authority staff for sharing their knowledge and experience regarding their use of the GIPSICAM system: Dunlop S, Dunn M, Gillies J, Greening S, Levett S, Meers P, Owen C, Pierce R, Pratt D, Salkeld D, Smith R, Tang J, Vickery J The authors would also like to acknowledge and thank Lihua Wu for proofreading this paper. Views expressed in this paper are those of the authors, and are not necessarily the views of the Roads and Traffic Authority of NSW.

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