Regional Multi-Modal Mobility Program (RM3P)

rm3p logo

The Northern Virginia Transportation Authority teamed up with the Virginia Department of Transportation (VDOT) and the Department of Rail and Public Transportation (DRPT) to co-sponsor a Regional Multi-Modal Mobility Program (RM3P), aiming to use collaboration and data to improve the functioning of the multimodal transportation system in Northern Virginia — which is consistent with NVTA’s vision for the region.

Visit the RM3P Website

The programs goals include:

oneOptimization: Predicts and manages traffic disruptions to keep travel efficient.  

two Reliability: Provides accurate, real-time travel times for better trip planning.

threeTraveler’s Choice: Offers real-time, multi-modal options for flexible travel decisions.​​​​​​​

RM3P Program Elements

dataData-Exchange Platform

The Data-Exchange Platform (DEP) will be a reliable, continuously updated, cloud-based data storage and exchange system. It will be used by regional partners and third-party providers to capture, process, and exchange information on real-time and historic multi-modal travel conditions. This platform will feed necessary data to other RM3P program elements and disseminate value-added and full-grown data produced by these elements.

Ai-Based Decision Support System

The AI-Based Decision Support System (AI-DSS) will help predict the impact of disruptions to the transportation network and provide coordinated response options to agencies. The tool for operators will use travel data to monitor emerging conditions and recommend plans for coordinated, multi-agency responses to congestion, incidents, and events.

Commuter Parking Information System

The Commuter Parking Information System (CPIS) will entail a real-time app-based  parking availability information system that provides reliable information about parking space availability at lots serving bus, vanpool, and carpool commuters.

Download the ParkZen App

Dynamic Incentivization

Dynamic Incentivization (DI) will be a data-driven system offering the public incentives to modify their travel choices and behaviors in response to real-time travel conditions. The incentives will be offered by regional agencies and third-party providers.

Download the GoMyWayVA App

Multi-modal Analytical Planner (Deferred): The Multi-Modal Analytical Planner (MMAP) will be a collaboration tool for transportation service providers to pinpoint unmet needs in the transportation network.

How It All Comes Together: RM3P in Action

Four sets of technologies, referred to as program elements, have been developed and deployed as part of RM3P. These technologies are designed to improve the efficient exchange of information between stakeholder agencies, to provide a platform and recommendations to operators and service providers to enable them to respond to incidents more quickly and effectively, and to provide information and tools for users to take advantage of available commuter parking lots so they can plan their trips to avoid congestion. The four program elements are outlined in the story below.

RM3P Database Icon

DEP
Data-Exchange
Platform

AI-Based Decision Support System

AI-DSS
AI-Based Decision
Support System

Dynamic Incentivization

DI
Dynamic
Incentivization

Commuter Parking Information Services

CPIS
Commuter Parking
Information Services

7:00 AM

SCENE ONE

A Typical Morning Commute

It's 7:00 AM on a rainy weekday in the Northern Virginia region. Thousands of commuters are hitting the roads, buses, and trains to start their day. Suddenly, a crash occurs on I-95. Left unchecked, this could trigger miles of backups, late arrivals, and wasted time for everyone in the corridor.

7:01 AM

SCENE TWO

Data at the Speed of Light

Within seconds, the Data-Exchange Platform (DEP) begins to pull together information from across the region:

  • Incident information from regional agencies.
  • Traffic speed sensors along I-95.
  • Transit and parking data from connected systems.
  • Weather updates from the National Weather Service.
  • Traffic and vehicle data from third-party providers.

This creates a unified, cohesive picture of what's happening on the network and is quickly available to agencies and partners.

Visit the DEP website

RM3P Cloud Animation
7:05 AM

SCENE THREE

Turning Data Into Foresight

The AI-Based Decision Support System (AI-DSS) gets to work:

  • Forecasts how impacts of the crash will ripple across the corridor and region.
  • Predicts when and where congestion will peak.
  • Suggests strategies – e.g., adjusting signal timings and coordinating with transit agencies – to traffic operation centers to reduce impacts.

Instead of reacting after the fact, agencies are now able to act before gridlock sets in.

7:10 AM

SCENE FOUR

Helping Commuters Make Better Choices

Next, Dynamic Incentivization (DI) engages directly with commuters through the GoMyWayVATM app:

  • Drivers heading toward I-95 see in-app alerts about the crash.
  • They're offered incentives to delay their trips, shift to alternate routes, or use transit.

By spreading out demand away from the incident, RM3P keeps the system flowing more smoothly for everyone.

RM3P Wheel Animation
7:12 AM

SCENE FIVE

Making Parking Seamless

Meanwhile, the Commuter Parking Information Services (CPIS) brings parking data together across the region.

  • Available parking occupancy data from regional transit agencies is consolidated and pushed through DEP.
  • Crowdsourced inputs, including the ParkZen app, are also pushed through DEP and used to monitor parking conditions at designated commuter lots.
  • App users get commuter parking lot availability such as parking lot A has limited availability or parking lot B has plenty of availability.

For commuters, this means less circling, more certainty, and smoother transfers to transit.

7:15 AM

SCENE SIX

Better Outcome for All

By 7:15 AM, the impact of the incident has been substantially mitigated and adapted to current conditions.

  • DEP unified current data shared quickly across agencies, technologies, and tools, making inter-agency, multi-modal collaboration possible.
  • Travelers took incentives and rerouted earlier, avoiding the worst congestion.
  • Agencies coordinated proactively, guided by a common, fast operating picture.
  • Parking decisions were easier and faster, informed by continuous data flows.

What could have been a frustrating morning became a more manageable commute, powered by connected data working behind the scenes.

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