Metropia’s platform, powered by AI-based algorithms, data analytics and behavioral economics, provides a multidimensional demand management framework (route, departure time and mode) to support transportation system congestion-management strategies and policies.
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Updates on Metropia’s Total Mobility MaaS&T platform
Total Mobility, Metropia’s next generation platform, will transcend the traditional MaaS concept in the US to incorporate system performance and introduce the Mobility-as-a-Service & Tool (MaaS&T) platform. As a leading provider of MaaS&T, Metropia is rapidly enhancing the features and resources made available to agencies to manage demand and operations of their networks. Selected elements of the Total Mobility platform have already been released and others will be brought to our markets over the next several quarters with full deployment expected in Q4 2018.
Total Mobility Platform elements include:
Real-Time Traffic Estimation and Prediction Engine. An upgraded AI-based travel time prediction engine combines historical and real-time data as well as pattern recognition techniques to accurately estimate traffic conditions including turning movement delays at major signalized intersections.
Routing Engine. The completely revamped routing algorithm considers the time-varying turn delays at intersections and junctions provided by the travel time prediction engine, yielding more intuitive time-saving routes during both peak and off-peak hours. Together, the new prediction and routing engines generate highly accurate routes in terms of time estimation. The en route rerouting capability will further ensure that users will receive the best route in response to unexpected traffic conditions during their drive.
INDUCE Behavioral Engine. The INDUCE behavioral engine observes and analyzes a user’s travel activities through multiple AI-based algorithms to develop a deep understanding of their transportation patterns and mode preferences. Based on that analysis, personalized and contextual relevant mobility recommendations are presented along with tailored, incremental incentives designed to encourage users to experiment with alternative modes. The core of the INDUCE behavioral engine currently supports ARPA-E’s “Connected Traveler” and will be applied to upcoming active demand management projects for BART (CA) and CHT (Taiwan).
DynusT. The DynusT dynamic traffic assignment (DTA) model continues to advance with methodological enhancements. DynusT is now capable of performing assignments utilizing variable value-of-time (VoT) for individual trips without increasing run-time when compared to the fixed VoT case. This advanced capability has been successfully applied to the CT-RAMP activity-based model (ABM) and DTA integration for Atlanta and Columbus.
Stay tuned for exciting platform updates in upcoming editions of our Movement newsletter.
Metropia to Develop the Houston-Galveston Regional Dynamic Traffic Assignment Model for TxDOT
Commissioned by TxDOT and through project partner AECOM, Metropia is employing its DynusT/DynuStudio platform to develop, calibrate and validate an eight-county Dynamic Traffic Assignment Model for the Greater Houston-Galveston area to support TxDOT’s operational planning activities.
This model will help TxDOT understand the complex mobility dynamics between transportation infrastructure, land use development, alternative transportation options and active demand management strategies.
Metropia is Powering BART’s Phase 2 Perks Program
Metropia is powering the Bay Area Rapid Transit’s BART Perks 2 pilot program which aims to reduce train car overcrowding in the Transbay Tube and throughout the system. To achieve this, Metropia developed an AI-based crowding prediction model and is deploying its AI-based INDUCE behavioral engine. INDUCE delivers personalized incentives and communication messages to BART peak-hour riders, encouraging them to adjust their departure time to enhance their BART experience and reduce the overall BART crowding situation.
Metropia is Awarded US Army Corps of Engineers Contract to Study Impacts of Flooding in the Southern California Area
The US Army Corps of Engineers (USACE) contracted Metropia to perform a traffic assessment pertaining to flood-related road closures and evacuation planning in the southern California area.
Metropia will utilize its DynusT/DynuStudio Dynamic Traffic Assignment (DTA) platform to calibrate and validate a sub-regional DTA model. The model will simulate flood-related road closure scenarios and perform an in-depth regional transportation analysis to establish and evaluate evacuation routes. The outputs of the model will provide critical inputs for the Corps’s economic loss assessment model.
Chunghwa Telcom and Metropia to Bring MaaS&T Solutions to Taiwan
Chunghwa Telcom (CHT), Taiwan’s largest mobile phone and internet service provider, and Metropia have signed a Memorandum of Understanding to deliver Metropia’s MaaS&T solutions throughout Taiwan. Metropia’s incentive-based platform, particularly the AI-based INDUCE behavioral engine, will be utilized to alter commuter behavior in the Taipei-to-Yilan region. The INDUCE integration is set to be completed in 2018. Additionally, the collaboration will allow CHT and Metropia to conduct research on commuter behavior and motivations through Metropia’s data analytics services.
Dr. Yi-Chang Chiu Leads MaaS&T Workshops for Taiwan’s Ministry of Transportation and Communications
In 2017-2018, at the invitation of Taiwan’s Ministry of Transportation and Communications, Metropia’s Dr. Yi-Chang Chiu hosted four MaaS&T workshops. After introducing the MaaS&T concept and framework, Dr. Chiu demonstrated how it will deliver a stronger transportation system management outcome versus a traditional Mobility-as-a-Service (MaaS) framework. MaaS&T incorporates system objectives and provides a platform for agencies to implement an expanded range of Active Demand Management (ADM) strategies and benefit from enhanced data analytics capabilities (Tool).
In the News
Metropia's MaaS&T framework Touted at TRB
(Washington, DC) Metropia’s Dr. Yi-Chang Chiu was invited by the USDOT ITS Joint Program Office to serve on the panel for “TSMO in the Age of On-Demand Mobility” at TRB’s annual meeting in January. Dr. Chiu shared the ability of Metropia’s MaaS&T framework to balance Transportation Systems Management & Operations (TSMO) with Active Demand Management. By addressing these two critical dimensions of traffic management in tandem, Metropia directly benefits commuters while meeting agency objectives.
Metropia Joins Industry Experts in Exclusive USDOT - FHWA Transportation Policy Symposium
In February, Metropia’s Dr. Vassilis Papayannoulis, was invited by USDOT and FHWA to join 25 leading transportation experts for the Transportation Policy Symposium on “Transportation Data Policy and Governance for Systems Management and Data-Driven Decision Making.” The panel addressed emerging challenges and opportunities in the utilization of transportation data in the key areas of sound policy, planning, investment, and system management.
Metropia & NREL Exhibit “Connected Traveler” Project at ARPA-E Energy Innovation Summit
Metropia’s Dr. Vassilis Papayannoulis joined colleagues from the National Renewable Energy Laboratory (NREL) at the Advanced Research Projects Agency-Energy (ARPA-E) Energy Innovation Summit to exhibit their ARPA-E-funded “Connected Traveler” project, which utilizes Metropia’s incentive-based platform to explore user mobility option choices and energy consumption. Currently, Metropia is testing user response to various incentive schemes and energy-related messaging. The ARPA-E project will be completed in July 2018 and more results will be published soon.
Metropia’s Incentive-Based Approach to Mobility on Demand Presented In USDOT Webinar
In the fourth installment of USDOT’s Mobility on Demand webinar series—”Incentive Based Approaches”—Dr. Yi-Chang Chiu, presented Metropia’s success in applying behavioral economics to influence commuter behavior and decision making. Metropia is leveraging these same principles to expand commuter mobility options in its Tucson-based FTA Mobility on Demand (MOD) Sandbox pilot project--AMORE.
Dr. Yi-Chang Chiu served as a Panelist at IEEE Green Tech Smart City Conference
(Austin, TX) As a member of April’s IEEE Green Tech Smart City conference panel “Enabling Socially-Responsible Travel through Technology: Opportunities and Challenges,” Dr. Yi-Chang Chiu joined speakers from the University of Texas at Austin, City of Austin, and WAZE to share Metropia’s insights in employing behavioral economics to increase usage of carpooling and adjusting departure time to enhance a motorist’s travel experience and achieve system mobility goals. Metropia’s findings indicate that 5-10% of drivers are willing to shift their departure time out of rush hour and overall incentives have proven to be effective in increasing carpooling. Metropia’s data analytics have identified key socio-demographic factors which contribute to such behavior adoption, particularly when backed by our incentive-based offers. Through Metropia’s micro-survey feature and other user-engagement tools, agencies are able to accurately target the right audience with the right message at the right time to trigger the desired behavior change.