Smart Infrastructure for Urban Mobility

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Transcription:

Smart Infrastructure for Urban Mobility Stephen F. Smith

TRAFFIC CONGESTION costs $121 billion per year in the US produces 56 billion pounds of CO2 annually 40% of time spent on surface streets in urban areas is spent idling

POORLY TIMED SIGNALS are one big reason why Those signal systems with adaptive capabilities have inherent limitations Vast majority of intersections run fixed plans Only detect and respond to traffic that is already Designed for average traffic conditions stopped and waiting Begin aging the moment they are installed Unable to respond to real-time events Are designed strictly for arterials

Scalable Urban Traffic Control www.surtrac.net Goal: Real-'me op'miza'on of traffic flows for urban (grid) road networks Penn Ave./Penn Circle Technical Approach: Decentralized control Coordinated ac/on Research Progress 2010-11: Development of core approach 2011-12: East Liberty pilot deployment 2013-15: Expansion of pilot test site 2015: Integra'on with connected vehicle technology Benefits True real-'me response Mul'ple dominant flows Scalable, incremental deployment Mul'-modal op'miza'on

Signal Control as a Distributed Online Planning Problem Controller Sensors Intersec'on Scheduler 1. Current traffic condi'ons are extracted from sensor data streams 2. System computes phase schedule that op'mizes flow at intersec'on and sends commands to the controller when it is 'me to change phases Intersec'on Scheduler Controller 3. Schedule is communicated to downstream neighbors to indicate what is coming 4. Rolling Horizon: Scheduling cycle is repeated every few seconds

Surtrac in East Liberty Penn Circle Test Site (Jun 2012): % Improv. Travel Time Bakery Square Expansion (Nov 2013): % Improv. Travel Time # of Stops # of Stops Wait Time Emissions AM rush 30% 29% 48% 24% Mid Day 33% 53% 50% 29% PM rush 23% 9% 36% 18% Evening 18% 35% 28% 14% Overall 26% 31% 41% 21% Wait Time Emissions AM rush 17% 34% 33% 16% Mid Day 21% 37% 38% 18% PM rush 29% 45% 46% 25% Overall 24% 40% 42% 21%

m Ave e r t Ce n nue Highland Ave Bau rd leva u o B enue Fifth Av In the field...! intelligent traffic signals surtrac.net @surtrac info@surtrac.net 25% lower travel times 40% less time idling 30-40% fewer stops 21% lower emissions Pen na ven ue Key Capabilities True real-time response to traffic conditions Manages multiple dominant flows Scalable to road networks of arbitrary size Multi-modal optimization

Pittsburgh Smart City Challenge Vision

Integration with Connected Vehicle Technology m Bau rd leva u o B C re A ent ue ve n Highland Ave Better sensing Use of mode, route info. Incident detection and real-time re-routing 24 intersec=ons are equipped with DSRC Radio Communica=ons enue Fifth Av Pen na ven ue

Sharing Vehicle Route Information Basic Concept Connected Vehicle (CV) shares its route with the network Intersections incorporate this info. into local optimization Initial Results Average delay is significantly improved CVs receive immediate benefit Little adverse effect and overall flow efficiency improves with level of penetration

The Longer View As CV technology emerges the signal network will provide the gateway to realtime control information AI planning and machine learning techniques will be a key enabler