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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Metropia’s TOTAL MOBILITY’s Transit-Hailing Product Increases Transit Agency Mobility Options
In Q3 of 2018, Metropia deployed TOTAL MOBILITY’s Transit-Hailing product as part of the AMORE project funded by the Federal Transit Administration (FTA) Mobility-on-Demand (MOD) program and Tucson’s Regional Transportation Authority (RTA). Transit-Hailing pairs the convenience and innovation of ridesharing services with the affordability and community benefit of public transit, adding custom mobility options to the transit system.
Metropia’s Transit-Hailing’s unique, fluid approach allows agencies and fleet operators to provide a higher level of service to passengers while maximizing fleet efficiency. Key to that efficiency are the two classifications and responses to service requests: Priority and Same Day reservations.
Priority reservations are booked in advance no later than the evening prior to service. Those Priority reservations are run through Metropia’s algorithms to determine the number of vehicles and types of vehicles (e.g. sedan, van, or wheelchair accessible vehicles) as well as shift durations needed to efficiently meet scheduled demand. Driver schedules and routes are then dynamically adjusted to meet origin-destination and departure times with the goal of pairing passengers into to carpools for increased efficiency. Priority reservations effectively serve as the “hailing” component of Transit-Hailing, where Priority service demand determines the supply of vehicles, itinerary, and routes for the day ahead.
As the name implies, Same Day reservations are requests for service placed after the driver schedules and routes have been established by Priority reservations. With the supply of vehicles, routes, and shifts already established, the service more closely mirrors a traditional transit system. But Transit-Hailing differs in that it maintains flexibility to accommodate Same Day requests for service during times when vehicles have spare capacity and doing so will not impair service levels of pre-scheduled and Priority trips.
As Priority demand increases, the Transit-Hailing system may determine convenient, central pick-up and drop-off locations for carpool companions, along with optimal service times. By accommodating trips in this fashion, the system is able to balance service levels with optimized network utilization to reduce costs.
For the latest news on TOTAL MOBILITY, visit Metropia.info.
AMORE Pilot Program Launch Features TOTAL MOBILITY's Transit-Hailing Product
(Tucson, AZ) July 2018 -- The Regional Transportation Authority’s AMORE project launched its pilot program to introduce Transit-Hailing and increase access to public transit in the suburb communities of Rita Ranch, Civano, and Vail.
As the technology provider for AMORE, Metropia deployed custom Transit-Hailing apps for both passengers and participating AMORE drivers. Over 25% of respondents to the AMORE website have officially joined the pilot program, with use cases ranging from seniors in high school to senior citizens, from first-mile/last-mile connections to public transit to full door-to-door service. Throughout the pilot program, participants provide feedback on their experiences with the AMORE app and services as the program refines its operations in preparation for a full launch to the public in the fall of 2018. AMORE is funded by the FTA’s Mobility on Demand initiative, which seeks to introduce innovative community-driven solutions to transportation challenges.
Maricopa Association of Governments Selects Metropia for ABM-DTA Integration Consultation
The Maricopa Association of Governments (MAG) has selected Metropia as one of the few qualified consultants in four areas of expertise: Activity-based Model (ABM); Dynamic Traffic Assignment (DTA) Model Development; Data Collection, Management and Visualization; and Operations Planning.
Metropia will provide MAG assistance in these four critical disciplines in the planning and development of MAG transportation forecasting tools and in support of MAG planning and forecasting activities. These efforts include selecting and implementing the best suitable DTA software for integration with the existing MAG ABM model; researching and implementing the advanced methodologies in the integrated ABM-DTA modeling system; and collecting, analyzing and visualizing the data required and produced by the ABM-DTA modeling system. DynusT, currently licensed and supported by Metropia, will be utilized as the DTA platform to support activities under this project including ABM-DTA integration, analysis of congestion-management strategies, and more.
Metropia Partners with WSP and INRIX to Provide Analysis to CTRMA
Metropia's platform has been deployed in Austin since late 2015 and supported CTRMA's effort to manage congestion during the construction of the Mopac Expess Lanes. The deployment is continuing after the construction was completed and a plethora of data pertaining to mobility, reliability and travel patterns have been and are acquired that could be used to support operations, strategies and other activities pertaining to the decision-making process. In 2018 Q2 Metropia partnered with WSP and INRIX to provide Origin-Destination travel pattern analysis to CTRMA to support their needs pertaining to the Mopac Express Lanes.
Metropia Applies AI & Behavioral Economics to BART Perks 2 Program
In the Bay Area Rapid Transit’s BART Perks 2 program, Metropia’s INDUCE behavior engine is providing the critical enabling technology and methodology to help BART identify peak-hour commuters and offer alternate departure times and incentives. The goal is to cost-effectively reduce peak hour crowding at specific times and segments on the BART system. Metropia is applying the Deep Neural Network (DNN) AI model to predict the time-varying crowding level for all station segments. Behavioral economics combined with dynamic transit assignment techniques are also employed in this project. After nearly a year of development, the technical development is almost complete and Perks 2 is scheduled to be launch in Q3/Q4 2018.
Dr. Yi-Chang Chiu Leads MOTC Discussion on the Role of AI in Transportation
(Taipei, Taiwan) Metropia’s Dr. Yi-Chang Chiu shared his expertise in the application of AI in transportation through a presentation to the Ministry of Transportation and Communications (MOTC), “Will Artificial Intelligence Make Public Transportation Gain Competitiveness? If so, how?” Dr Chiu’s overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) detailed how they delineate from one another and how each is best applied to solve different types of transportation challenge.
In the public transit sector, a unique opportunity is emerging in the area of demand responsive transit system (DRTS), also known as ‘microtransit’ or ‘transit-hailing’. Dr. Chiu stressed the importance of carefully selecting Operations Research (OR) methods such as vehicle routing to optimize system planning and operations. AI-related techniques are more applicable addressing system demand, as user needs and behaviors are too complex and difficult to be modeled by traditional OR or statistical methods.
As an example of these principles in action, Dr. Chiu shared updates on AMORE, an FTA funded Mobility-on-Demand MoD) project. For AMORE, Metropia applies AI techniques to optimize routing and to trigger behavior changes by piquing interest in transit among non-transit users.
Chunghwa Telcom to License TOTAL MOBILITY’s INDUCE Behavior Engine in Support of MaaS Projects
In August 2018, Metropia signed an agreement with Chunghwa Telcom (CHT), the largest telecom company in Taiwan, to license Total Mobility’s INDUCE behavior engine in support of CHT’s UMAJI MaaS project. INDUCE employs various statistical, machine-learning and AI-based algorithms, data analytics, and behavioral economics experiment mechanism to deliver personalized mobility recommendations and incentives.
In addition to providing highly-personalized and contextually-relevant mobility options to users of the new UMAJI MaaS app, the project's long-term goal is for INDUCE to intelligently apply various types of information and incentives to trigger and sustain user behaviors which meet both personal and system mobility goals.
Dr. Yi-Chang Chiu Leads ITS Taiwan MaaS forum
(Taipei, Taiwan) Metropia’s Dr. Yi-Chang Chiu served as a commentator and panelist for an Intelligent Transportation Systems (ITS) Taiwan forum focused on applying MaaS business models to address tourism and urban commute challenges.
Metropia is serving as the advisor in user behavior change for a joint project of the Ministry of Transportation and Communications (MOTC) and Chunghwa Telcom which utilizes the Business Model Canvas concept in B2C, B2B and B2G applications. Alongside Dr. Muhan Wang, MOTC Director of the Office of Science and Technology Advisors, Dr. Chiu presented how MaaS service providers can deliver different but equally strong value propositions to commuters, business, and governments alike, improving both personal mobility and transportation system performance simultaneously. Understanding the long-term return-on-investment is instrumental for governments in determining the initial and ongoing operating costs of the MaaS platform and in establishing contractual relationships with the MaaS service providers.
Metropia and CECI Collaborate to Advance Taiwan's Transportation R&D
Metropia and Taiwan’s China Engineering Consultants Inc (CECI) signed an Memorandum of Understanding (MOU) in June 2018. For nearly fifty years, CECI has been the most reputable non-profit engineering organization focused on advancing and integrating critical technological know-how in both traditional and emerging transportation fields. The MOU allows both entities to collaborate in the area of Intelligent Transportation Systems, Mobility-as-a-Service, active demand management and transportation system management and operations. Metropia will offer CECI the insight, technologies, and methodologies to help further its mission of advancing Taiwan’s transportation research and development.
In The News
Dr. Vassilis Papayannoulis Presents Behavior Modification Findings at National Congestion Pricing Conference
(Washington, DC) Dr. Vassilis Papayannoulis was invited to the FHWA-sponsored 2018 National Congestion Pricing Conference to present how Total Mobility’s INDUCE behavior engine can effectively alter travel choices and contribute to congestion management.
Dr. Papayannoulis presented results from Metropia’s deployments in Austin and El Paso, TX as well as behavior analysis pertaining to experiments conducted utilizing Metropia’s enhanced Mobility Options Discovery and Engagement (MODE)® behavior approach, which is incorporated in Metropia’s next generation Total Mobility platform. MODE® is an iterative behavior trigger and reinforcement process which involves observing the user’s behavior, learning the user’s behavior, finding personalized mobility options, triggering the desired behavior change, and reinforcing the new behavior. Based on the analysis, 4% of the sampled users, on average, altered their departure time and 34% percent of the sampled users were engaged to learn more about their personally-relevant mobility options, including transit costs, departure times, and routes for their particular commute.
Dr. Vassilis Papayannoulis Presents Metropia's MaaS&T Framework at MaaS Market Conference
(Atlanta, GA) Metropia’s Dr. Vassilis Papayannoulis shared details of the FTA-funded AMORE project during the MaaS Market conference in May. The 2-day conference brought together transport project leaders and technology experts from from around the world to provide examples of leading Mobility-as-a-Service (MaaS) developments and was also featured in the May-June 2018 ITS International issue.
As the technology provider for AMORE, Metropia serves as the MaaS&T Service Provider and RubyRide as the MaaS&T Service Operator deploying multi-pickup/drop-off dynamic transit-hailing and social carpooling services. The MaaS&T platform supports Metropia’s Mobility Options Discovery and Engagement (MODE)® behavior modification approach. MODE® is an iterative behavior trigger and reinforcement process which observes and learns a user’s behavior, finds personalized mobility options, then triggers and reinforces the new behavior change through incentive-based gamification.