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Improving video rating performance – focusing on user & interface
 

Improving video rating performance – focusing on user & interface

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    Improving video rating performance – focusing on user & interface Improving video rating performance – focusing on user & interface Presentation Transcript

    • Improving video rating performance – focusing on User & Interface Geoffrey Yu, ARRB Group Ltd Interaction Design Association (IxDA) Brisbane 21 st June 2011
    • Welcome and who are we?
      • Geoffrey Yu – Consultant , Safe Systems, QLD/NT branch
      • ARRB Group Limited
      • Note: Formerly known as Australian Road Research Board
      • Not Assassination Records Review Board (see Wikipedia.org )
      Function provide research, consulting and information services to the road and transport industry Expertise road safety , asset management, pavement /structural analysis, car parking, data collection, etc. Clients government/ road authorities (local, state, federal, overseas), int’l aid agencies (World Bank), transport (logistics, mining), etc.
    • Overview
      • Context – project domain
      • Task – project work
      • User – what is video rating
      • Interface: Excel – overview of original system
      • Interface: Raven – overview of new system
      • Findings – learnings from new system
      • Ideas? – future thoughts!
    • Context: road safety
      • Global issues
      • About 1.3 million people are killed on world's roads each year
      • Expected to increase to 1.9 million by 2020
      • 90% occur in developing countries
      • Source: www.decadeofaction.org , UN’s Decade of Action 2011-2020
      • Local issues
      • Last 10 years about 17,000 people killed on Australian roads
      • Additionally about 220,000 were hospitalised (serious injuries)
      • Average: 5 deaths and 60 serious injury cases everyday
      • Source: www.ausrap.org , Australian Road Assessment Program
    • Task – road assessment
      • Various methods of assessing road parameters :
        • Pre => use design plans, analyse historical data
        • In-situ => onsite inspections and observations
        • Post => data collection of site, process back in office
      • Modern data collection equipment allows for efficient and safer assessment of roadways (and is repeatable !)
      • Typical data collected:
        • Multi camera (4-5) setup with high resolution (>1080p)
        • Geotagged video (~10 cm accuracy)
      • Other equipment (optional/advanced):
        • Pavement laser scan (road profiling – rutting and roughness)
        • Environment laser scan (object detection using 3D point cloud)
    • Hawkeye 2000 Network Survey Vehicle
    • User – video rating
      • Use a video viewer to examine/observe road parameters:
        • Hawkeye Processing Toolkit (ARRB)
        • DVR Viewer (QDTMR)
        • AssetLoc (RTA NSW)
        • Or any geotagged video/images
      • Parameters are assessed according to project scope :
      Crack Trees Poles Asset Safety
    • Interface – Excel (Original)
    • Interface – Excel Input form Lookup tables
    • Design – Excel
      • Target user and expected usage:
        • Low computer-level skills
        • Limited resources (e.g. time) to conduct a risk assessment
        • Small number of sites or “hot spots” would be conducted
        • Utilised as a field tool (in-situ inspection) at each site
      • Market and project changes after initial development:
        • Road authorities saw benefits in assessing their major roadways
        • Risk assessments increased in popularity = increased demand
        • More assessments = more data input = more data processing
        • New expectations to integrating (e.g. GIS) and presenting results
    • Primary issues – Excel
      • Usability
        • data input errors (input raw calculation values using lookups!)
        • i.e. high utilisation of user memory
        • lack of task scope (what roads to rate, completion status)
        • i.e. poor communication of system status and task
        • Result => User overwhelmed! => Quality & Quantity reduced
      • Data management
        • Multiple raters = multiple spreadsheets (manual sync of data!)
        • i.e. high levels of data manipulation and handling
        • Data must be manually validated (e.g. typos not auto checked!)
        • i.e. data can easily be corrupted (e.g. 1.8 and 18, difference?)
        • Result => Data is double-handled! => Efficiency reduced
    • Scope for improvement – Raven
      • A more efficient and reliable solution was needed due to the increased market demand for risk assessments
      • Business case was put forward, with internal project approved
      • Total of 4 months (part-time load) for delivery given
        • Initial design – 1 month
        • Coding and development – 2 month
        • Beta testing – 1 month
      • Solution was to tackle the primary issues , trying to solve the most problems with minimal effort / least cost (80:20 rule?)
      • Designed for in-office tool assessing roads at 100 m intervals
    • Design – Raven System process……Brainstorm issues/solutions……System architecture Etc……
    • System – Raven Video Server Rater Rater Results
    • Interface – Raven
      • Main screen
    • Interface – Raven
      • Rating form – midblocks
    • Key features – Raven
      • Usability
        • Familiar standard, business (neutral) looking interface
        • User task-oriented layout of UI elements
        • Inclusion of status bar and completion status
        • Number of perceived rating forms reduced (5 to 2 types)
        • Input options are explicit and predefined (no lookup tables!)
      • Data management
        • Data validation is implicit by providing predefined options
        • Centralisation of multiple rating sources
        • Duplicated rating work is reduced (1 rater per road section)
        • Rating task is verified against a (predefined) rating list (scope)
    • Effects of using Raven over Excel
      • User performance
        • Reduced typos and other user input issues => increase quality
        • Reduced feeling of being overwhelmed (i.e. memory and layout)
        • More confident in performing (repetitive) task (system trust)
        • More confident in task delivery => increase task visibility
        • Increased user satisfaction (don’t want to use Excel anymore!)
      • Project performance
        • Increased rating output 2x (consistently better than Excel)
        • Reduced data issues (i.e. user errors, duplication and corruption)
        • Project manager has better control and awareness of task
        • Reduced overheads/resource waste => increases profit margin!
    • Learnings & future enhancements
      • Currently Raven has been used to assess the majority of QLD state and local (regional significance) roads => ~100,000 km !!
      • Small changes focusing on user task and process issues can positively affect user performance and project outcomes
      • Raven was a prototype / proof of concept
        • can rating performance be improved (primary issues)?
      • Raven has minor bugs => minimal affect on usability and project outcomes (for now!!)
      • Other features/improvements that were not implemented:
        • Mass data editor (table/spreadsheet to fix data issues)
        • Highlight (colour) rating issues (increase user communication)
        • Help / reference system (rating guide / issues)
        • Reporting engine (risk charts, risk maps, etc.)
    • Other ideas?
      • Integration of other data
        • GIS (Shapefiles, Google maps, etc.)
        • Traffic data (crash, volume, etc.)
      • Template rating form => flexible for other assessments
      • Highlight image regions for assessment (rating assistance)
      • Automatic video/image detection (machine vision)
    • Road ends here? Thank you and safe driving!