A Tale of Time Travel Year 2018

Transcription

1 A Tale of Time Travel Year

2 Question: 2 2

3 Answer: Integrated Modeling for Road Condition Prediction (IMRCP) Kyle Garrett, Synesis Partners Nancy Powell, MoDOT/KC Scout 3

4 So what is it? Historic Data (Weather & Traffic) Real Time Data (Weather & Traffic) Hydrology/ASOS NW 8-Hr Fluctuating Road Condition Prediction for TMCs, Travelers and Maintenance 4 4

5 Project Background Program Objectives Applications and Benefits System Functions and Demonstration Deployment Demonstration Examples Deploying an IMRCP 5

6 Partners in the Project 6

7 IMRCP Program Objective: An Integrated, Predictive System Incorporating real-time and archived data and results from an ensemble of forecast and probabilistic models Fusing them to PREDICT current and future overall road/travel conditions For travelers, transportation operations, and maintenance 7

8 IMRCP Ingested Data Sources Special Events Work Zones and Winter Ops Atmospheric, Road Weather and Hydrology Traffic and Incidents 8 8

9 Benefits and Applications IMRCP predictions can extend operator awareness from current to likely future traffic and road conditions/risks Management strategies can be more accurately implemented and communicated to travelers Operators and travelers can then make betterinformed decisions Enacting controls (VSL, ramp metering, gates ) Deploying maintenance and traveler assistance Changing (delaying, re-routing) travel plans 9

10 The Science Within the Model 10 10

11 IMRCP Functions 11

12 Kansas City Study Area Selection Study area needed a combination of congested traffic, alternative routes, highly variable weather and hydrologically challenging areas KC was selected from among several possible study areas Good data availability Good working relationships with local agencies 12

13 Study Area Data Sources 13

14 IMRCP User Interface The IMRCP system uses a web-based interface Time-variable map Notifications Reports Administrators send user names, passwords and instructions to authorized users 14

15 Simplicity of the Map Interface with Time Travel Slider Bar Zoom Controls View Weather Condition Data View Alerts Create a Report or Subscription View Road Condition Data Time Selector 1 min. Refresh Notifications Date/Time Function 15

16 Viewing Road Condition Data Road Condition Layers Road Network Model Pavement State Pavement Temperature Pavement Flood Depth Pavement Snow Depth Traffic Traffic Speed Traffic Density Traffic Flow Routes 16

17 Viewing Road Condition Specifics 17

18 Viewing Weather Condition Data Weather Condition Layers Air Temperature Surface Visibility Wind Gust Speed Wind Speed Precipitation Rate & Type NWS Alerts Radar 18

19 Viewing Alerts Alert Layers Traffic alerts (incidents, work zones ) Road condition alerts Weather alerts All alerts 19

20 Receiving Notifications Notification Types Unusual Congestion Incident Flooded Road Ice on Bridge Heavy Precipitation Medium Winter Precipitation Heavy Winter Precipitation Low Visibility 20

21 Creating Reports/Subscriptions 21

22 Early results using IMRCP on 4/28/17 22

23 Present Version 23

24 Planning New Deployments The IMRCP system was built around existing data sources and forecast methods IMRCP code was built with a USDOT open-source license Deploying the IMRCP to new areas would require developing additional road models and data sources 24

25 Deployment Activities Gather stakeholders and define the scope Set up the computing infrastructure Build the local road network model Identify and build the traffic demand model Identify and build collectors for local data sources Traffic and operations/incident data Road weather and hydrology, if available Winter maintenance and work zones Special events Calibrate the traffic demand model Integrate with operations 25

26 IMRCP Phase 3 Expand the KC model to cover the entire bi-state KC Scout metro Deploy an alternative statistical traffic model to run alongside the more deterministic TrEPS model Upgrade the TrEPS traffic model with adaptive scenarios to demonstrate and assess the relative advantages Improve the user interface and experience Engage a broader stakeholder community 26

27 Questions? Discussion? Thanks for your time! 27

28 Contacts Project Manager: Gabe Guevara, FHWA Principal Investigator: Kyle Garrett, Synesis Partners Lead User: Nancy Powell, MoDOT/ KC Scout 28