sc4 workshop 1: roberto baldessari: the use of big data for public transport performance measurement
TRANSCRIPT
Using Big Data to Improve Public Transport PerformanceRoberto BaldessariNEC Laboratories [email protected]
BigDataEurope WorkshopOctober 7th, 2015Palais des Congrès, Bordeaux
2 Using Big Data to Improve Public Transport Performance
NEC’s Transportation Business ▌Public Transportation
Bus AVL, AFC, ETA, Passenger Info (leader in JP)Scheduling and communication systems
▌Road InfrastructureHighway traffic controlHybrid camera-based traffic counting / HOV5.8 GHz “ITS Spot” and ETC road-side systems
▌Fleet ManagementDrive recorders, ecoDriving, fleet tracking/insurance,
accident database▌Automotive on-board
V2X platform (HW and SW)Mono-vision image recognition systemNissan Leaf Li-Ion batteries76 GHz radar for Adaptive Cruise Control
▌Automotive ITHPC, Product Data Management & Production Control in
all continents▌Automotive After-market
5.8 GHz on-board ETC with card reader
3 Using Big Data to Improve Public Transport Performance
What is “Big Data” for NEC
▌Platforms: parallel, in-memory, vector▌Acquisition: IoT, M2M,
pre-processing▌Analytics: deep
learning, HML, SIAT
IoT Platform
4 Using Big Data to Improve Public Transport Performance
Public Transit – Quality Incentive Contracts
▌BackgroundLarge cities adopting QICs based on KPIs
like Excess Waiting Time (EWT) London introduced 3:2 incentive/penalty
schemes, Singapore has followedRegularity is the goal, rather then
absolute punctuality
▌Data analytics reveal 1) Current EWT performance2) Worst performing routes3) Key bottlenecks on the route4) Causes for dwell time at bottlenecks5) Time table improvement margin
Source: Singapore LTA
5 Using Big Data to Improve Public Transport Performance
EWT Profile and Optimization from AVL Data
▌Bus operators and municipalities/ authorities often don’t know how their public transit scores
▌Simple analytics derives hot spots to attack in order to reduce EWT
Focus for improvement
6 Using Big Data to Improve Public Transport Performance
Bus Load Profile from AVL Data
▌Load profile simply based onAVL data (GPS + flags)Current schedule (reverse
engineered)▌70% accuracy vs passenger
counters▌Surrogate / complement to APC
systems
AVL Data Current Schedule
Supervised ML
TypicalBus Load Profiles
Morning peak run
Evening peak run
7 Using Big Data to Improve Public Transport Performance
Automating Schedule Coverage
▌Generate new or review existing schedule coverage
▌Automated time-consuming, error-prone task
▌Large KPI improvement potential
AVL Data
Unsupervised ML
Schedule Clusters
Optional APC Data
Suggested Change
8 Using Big Data to Improve Public Transport Performance
Bus Driving Analysis▌Visualization of vehicle travel path, alerts and events▌Analysis targets▌Planned KPI vs actual▌Fuel consumption and other parameters
9 Using Big Data to Improve Public Transport Performance
Bus Driving Analysis BenefitsFuel saving (up to 20%) by improving drivers’ behavior•Monitor, Analyze, Correct (counseling and training), Continuous Feedback
Safety• Identify trend and potentially dangerous patterns
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10 Using Big Data to Improve Public Transport Performance
Public Transportation Big Data Vision
▌Combine conventional and new sources▌Public safety and
transport▌Value co-creation
through data stores / IoT platforms▌Personalized guidance
and incentive▌Customer feedback▌Events as a benchmark
Video-based Crowd Behavior Analysis
Crowd Counting
AFC Tap-in & tap-out
Sensor-based Crowd Detection
Event ticketing
Transport App
