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[panel3]詹景堯博士

MC2013
August 28, 2013
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 [panel3]詹景堯博士

MC2013

August 28, 2013
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  1. Ching-Yao Chan California PATH (Partner for Advanced Transportation Technology) University

    of California at Berkeley The 18th Mobile Computing Workshop (MC2013) Miaoli, Taiwan August 28, 2013 Panel III Trend of Big Data
  2. The Destiny of Big Data “It’s impossible to move, to

    live, to operate at any level without leaving traces, bits, seemingly meaningless fragments of personal information.” “The future has already arrived. It is just not evenly distributed yet.” -William Ford Gibson (1948~), author who coined the expression “cyberspace”
  3. Big Data in Transportation Systems Infrastructure Vehicle Road Users Traffic

    Monitoring, Route Guidance, Traffic Management Traveler Information, Demand Management, Emergency Rescue Location Based Services, Driver Monitoring & Assistance Vehicle states, Envrionment, Diagnostic, & Control Customer History, Patterns & Behaviors Roadway states, Environment, events, parking, work zones, etc.
  4. PATH Connected Traveler Safe-Trip 21, Modal Integration Next bus 2

    min Next station in 2 min Modal integration via Vehicle Infrastructure Integration  Dynamic traveler information - through web, handheld, station information interface  Dynamic parking information  Dynamic transit operation - based on bus probes and real-time O-D data
  5. PATH Foresighted Driving Alert A Safe Trip 21 Project Bottleneck

    Traffic Queue Backup into mainline Alert Drivers Approaching Upstream Limited Visibility Due to Roadway Geometry Auditory & Visual Alerts
  6. Extending Alerts to Bay Area Highway Network About 1650 NAVTEQ

    triggers and more than 520 SpeedInfo triggers in Bay Area.
  7. Transportation Services based on Big Data • Proven Concept –

    Technically, it is doable with today’s technology. – Enrichment of functions and ease of use are keys. • Benefits – Customers perspectives – private business models – Public perspectives – public investment justification • What should be pursued next? – Most viable business models, supported by private user fees (comfort, convenience, etc.) – High public investment returns (efficiency, environment, safety, etc.)
  8. Do We Have a Chance? Skills We are technically as

    strong as anyone. Market Forces But, it may be quite challenging.
  9. Big Data (for Transportation) • Opportunity? – Viability demonstrated by

    some players already. – Growth seems very likely. • Local or Global? – Applications and services must be tailored locally. – The presence of global players indicate the business cases are global. • Strategic Positioning? – Our strengths to leverage?? – Our weakness to overcome??