Use of Probe Vehicles to Measure Road Ride Quality

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Presentation transcript:

Use of Probe Vehicles to Measure Road Ride Quality Samer W. Katicha Senior Research Associate, Center for Sustainable transportation Infrastructure

Outline Smoothness for asset management Probe vehicles The experiment IRI calculation from profile IRI calculation from vertical acceleration measurements Sensitivity analysis Conclusions Center for Sustainable Transportation Infrastructure

Smoothness for asset managment

Infrastructure Condition/ Performance Indicators → Pavements Service and User Perception Physical Condition Structural Integrity / Load-Carrying Capacity Safety and Sufficiency Environmental Impact Serviceability (PSI, IRI) Distress (PCI) Deflection (FWD) Friction (FN)/ Macrotexture Tire/Pav. Noise Rolling Resistance

Asset Management Strategic level Network level Project level Performance monitoring Network level Pavement management Project level Smoothness Specification Research  LTPP Center for Sustainable Transportation Infrastructure

Information Quality Levels HIGH LEVEL DATA Strategic Level Business Processes System Performance IQL-5 Performance Monitoring Information Quality Levels Network Level Planning and IQL-4 Structure Condition Performance Evaluation Program Analysis or IQL-3 Ride Friction Distress Detailed Planning The various IQLs requires different levels of detail and quality in the collected data to support the corresponding decision-making processes, which translate into different methods and frequencies of data collection. Therefore, it is imperative for the determination of data needs to pre-specify the decision level of interest. The tailoring of the data collected for effective decision-making within the decision level can lead to more specific and focused data collection efforts. This is illustrated in the following section for the project selection decision level. This plot was adapted from: Bennett, C. and W.D. Paterson, "A Guide to Calibration and Adaptation of HDM-4," in The Highway Development and Management Series, The World Bank, Washington, D.C., 2000. Project Level Project Level or IQL-2 Detailed Programming Project Detail or IQL-1 Research LOW LEVEL DATA

Probe Vehicles

Can we use probe (or regular) vehicles for road infrastructure health monitoring? At least for supporting high-end strategic- and network-level decisions?

Pavement Assessment and Management Applications Enabled by the Connected Vehicles Environment – Proof-of-Concept Objective: To use data collected from probe vehicles to extract information that could be used to remotely and continuously determine road infrastructure health

The experiment

Profile and Acceleration Data Profile data: Collected at the Virginia Smart Road Every 30 mm (1.2 in) Probe vehicle acceleration data: Every 2100 mm (7 ft) Center for Sustainable Transportation Infrastructure

Data Sampling Problem Center for Sustainable Transportation Infrastructure

Quarter Car Model kb Cb kt Center for Sustainable Transportation Infrastructure

Quarter Car Model Center for Sustainable Transportation Infrastructure

Accuracy of Numerical Calculation Center for Sustainable Transportation Infrastructure

The Probe Vehicle 2007 Ford Fusion Car parameters: Test Speed: Same as golden car Close enough Test Speed: 50 mph Center for Sustainable Transportation Infrastructure

IRI Calculation Center for Sustainable Transportation Infrastructure

IRI Comparisons Calculated IRI: Problems with quarter car model: Follow the same trend Sample over 2 m makes a difference Problems with quarter car model: Probe vehicle acceleration results from the full car response Approximate full car with average of profile felt by the four wheels Center for Sustainable Transportation Infrastructure

“Full Car” IRI Center for Sustainable Transportation Infrastructure

Sensitivity Analysis (Sampling) Center for Sustainable Transportation Infrastructure

Sensitivity Analysis (Quarter Car Parameters) Center for Sustainable Transportation Infrastructure

Sensitivity Analysis (Sampling) Suspension Stiffness Suspension Damping Tire Stiffness Mass Ratio Center for Sustainable Transportation Infrastructure

Conclusions Same IRI trend between probe vehicle and profiler: Effect of data sampling Effect of full vs. quarter car Effect of probe vehicle car parameters Use of the data: To much uncertainty/variation for detailed analysis Maybe useful for strategic level Center for Sustainable Transportation Infrastructure

Blacksburg, VA