TSSM BI-WEEKLY MEETING and Stakeholder Update July 10th, 2017

Meeting Topics Review current schedule Critical need chapter drafts due on November 21st Progress checkpoints and self-assessment July 21st (one-third checkpoint) September 21st (two-thirds checkpoint) Re-open comment tracking site in September Chapter review assignments in September Review interest level per chapter Seek consensus on technical topics Chapter outlines, VC&V definitions Intermediate need topics (optional)

Outreach Timeline (draft) July 10th ~1/3rd checkpoint Traffic analysis PFS TRB Task Force Stakeholder webinar #3 (annotated outline review) Start project 2016 2017 2018 2019 Interviewed 16 PFS states TRB Mid-Year HCQSC (Sturrock) September 18th ~2/3rd checkpoint Assign chapter reviews* Traffic analysis PFS TRB Task Force ITE SimCap & TENC** TRB SimSub & others** * re-open comment tracking site ** contact Chris/David if interested

Interest Level per Chapter Chapter 5: Defining the Problem Chapter 6: Data Chapter 7: Creating the Model Chapter 8: VC&V Chapter 9: Output & Visualization

Chapter 5 (Defining the Problem) Scoping overview Questions simulation can and cannot answer Connecting simulation objectives to project purpose Estimating effects of business/regulatory/emerging technologies Geographic limits Time periods and timeframes for analysis Baseline scenario Build alternatives Operating conditions (e.g., cluster analysis) Performance measures Externalities (e.g., spillover effects, demand effects) Verification and validation checks Documentation

Chapter 6 (Data) Two candidate outlines Data type-oriented outline Network data, traffic data, control data, IT subsystem data, operating condition data Analysis type-oriented outline Data needs assessment; types and sources; fusion and aggregation Simple facility analysis, corridor analyses, city-wide needs, annual reliability context, multimodal consideration Success stories Other considerations Data requirements for meso, macro, micro analyses

Chapter 7 (Creating the Model) Page 1: Initialization and Equilibrium Network Development (5 pages) Page 2: Conventional Windows-based data entry Page 3: Data entry over a ‘bitmap background’ Page 4: Pre-processors Page 5: Importing detailed traffic data Page 6: Raw data entry Geometric Data (6 pages) Page 1: Links Page 2: Nodes Page 3: Link-node versus link-link connections Page 4: Link lengths and curvature Page 5: Super-elevation and grade Page 6: Lane-specific data Traffic Data (9 pages) Page 1: Origin-destination volumes and matrices Page 2: Intersection turn movement volumes Page 3: Conditional turn movements Page 4: Lane utilization and pre-positioning Page 5: Off-ramp exit volumes Page 6: Multi-period volumes Page 7: Vehicle fleet composition Page 8: Driver characteristics Page 9: Headway and saturation flow rate Control Data (9 pages) Page 1: Pre-timed traffic signal control Page 2: Actuated traffic signal control Page 3: Actuated traffic signal detectors Page 4: Ramp meters Page 5: Freeway detectors Page 6: Sign controlled intersections Page 7: Freeway warning signs Page 8: Toll plazas Page 9: Roadway pricing Operating Condition Data (8 pages) Pages 1-2: Demand variability Pages 3-4: Weather Page 5: Incidents Page 6: Pavement quality Page 7: Work zones Page 8: Special events

Chapter 8 (Verification and Validation) Software logic reflects system behavior (software developers) Input data correctly describe the system (users) At the end: logic is okay and the input data are clean. Validation Model predictions match observed system behavior (users) Model parameters correctly adjusted (Calibration) At the end: parameters are suitably tuned and model predicts observed behavior to an acceptable degree. Static and Dynamic Conditions Static: steady state behavior Dynamic: transient behavior

Potential Problems Verification Validation Logic (theory) is flawed (developers) Software incorrectly implements the logic (developers) Model is being used outside its applicable domain Network is incorrectly specified Controls employed are incorrect Validation Operating conditions are incorrectly specified System performance is incorrectly described Parameter values are incorrectly specified Model produces invalid results for untested situations

Hierarchical Checking Used for both verification and validation Checks performed on Individual elements Subsystems Clean datasets – inputs for which the outputs are known. Overall system Focus on System dynamic trends (temporal and spatial) Travel times (OD, route) Queue dynamics (length, delay) Travel rates (speeds) for individual segments Vehicle inputs processed (entered and exited)

Consistency in Terminology Verification: The process of determining that a model implementation accurately represents the developer’s conceptual description of the model and the solution to the model. Validation: The process of determining the degree to which a model is an accurate representation of the real world from the perspective of the intended uses of the model. Calibration: The tuning of model parameters to achieve some degree of agreement with existing validation experiments Adapted from: Oberkampf, Trucano, and Hirsch, 2002; and Schlesinger, 1979

Definitions in the TAT Verification: Process where the software developer and other researchers check the accuracy of the software implementation of traffic operations theory. Perhaps should also focus on verifying that the input data correctly describe the system being studied. Calibration: Process where the analyst selects the model parameters that cause the model to best reproduce field-measured local traffic operations conditions. Performed using some of the field data. This is effectively part of the validation. Valid results cannot be obtained without calibration. Validation: Process where the analyst checks the overall model-predicted traffic performance for a street/road system against field measurements of traffic performance, such as traffic volumes, travel times, average speeds, and average delays. Performed based on field data not used in the calibration process.

Intermediate Need Topics (optional) Mesoscopic simulation approach Examples of multi-scale modeling Uncertainty analysis Discussion of models at the discrete level e.g., car-following, dynamic traffic assignment, cell transmission Content of Chapter 7 (Creating the Model) Content of Chapter 9 (Output Processing, Analysis, Presentation)

Questions and Answers Thank You