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OVERVIEW OF ROAD USER EFFECTS MODELS

OVERVIEW OF ROAD USER EFFECTS MODELS. Overview of Presentation. Introduction RUE components in HDM-4 Mechanistic modelling Speed Prediction Speed Flow and Traffic Interactions. Fuel Consumption Tyre Consumption Maintenance and Repairs Capital Costs Oil Consumption Travel Time

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OVERVIEW OF ROAD USER EFFECTS MODELS

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  1. OVERVIEW OF ROAD USER EFFECTS MODELS

  2. Overview of Presentation Introduction RUE components in HDM-4 Mechanistic modelling Speed Prediction Speed Flow and Traffic Interactions Fuel Consumption Tyre Consumption Maintenance and Repairs Capital Costs Oil Consumption Travel Time Safety/Accidents

  3. Components of Road User Effects

  4. Key Changes from HDM-III • Unlimited number of representative vehicles • Reduced maintenance and repair costs • Changes to utilisation and service life modelling • Changes to capital, overhead and crew costs • New fuel consumption model • New oil consumption model • Changes to speed prediction model • Use of mechanistic tyre model for all vehicles

  5. New Features in HDM-4 • Effects of traffic volume on speed, fuel, tyres and maintenance costs • Non-motorised transport modelling • Effects of road works on users • Traffic safety impact • Vehicle emissions impact

  6. Factors Influencing RUE Most important factors contributing > 70% of RUC

  7. RUE Components • MT Vehicle operating costs (VOC) • MT Travel time costs (TTC) • NMT Time and operating costs (NMTOC) • Accident costs (AC) RUE = RUC + Emissions + Noise RUC = VOC + TTC + NMTOC + AC

  8. Computational Logic • Calculate Free Speed for each vehicle type • Calculate for each traffic flow period: • Traffic flow in PCSE/hr • Vehicle operating speed (Speed-flow curve) • Speed change cycle (Acceleration noise) • Vehicle operating costs • Travel time costs • Accident costs

  9. Mechanistic Models • Predict that the RUE are proportional to the forces acting on the vehicle • By quantifying the magnitude of the forces opposing motion one can establish fuel and tyre consumption • Mechanistic models allow for changes in vehicle characteristics • Flexible when trying to apply the models to different conditions.

  10. Forces Opposing Motion • Calculates: • aerodynamic resistance (Fa) • rolling resistance (Fr) • gradient resistance (Fg) • curvature resistance (Fcr) • inertial resistance (Fi) • Uses more detailed equations than HDM-III

  11. Speed Prediction

  12. Speed Model • Based on HDM-III probabilistic speed model • Free speed predicted to be a function of constraining speeds • Desired speed - f(driver behaviour) • Drive speed - f(power-to-weight ratio) • Roughness - f(roughness and suspension) • Curves - f(radius of curvature) • Braking - f(downgrade length, brakes)

  13. Vehicle Speed Models • Desired speeds • User specified for 2-lane road • Adjusted for Width, Friction, NMT, Speed Limit • Free speeds • Uphill (steady state) • Downhill (steady state) • Constrained by limiting factors • Operating Speeds • Calculated for traffic flow periods • Adjusted for Speed-Flow effects

  14. Desired Speeds • VDES = f (VDES2, CW) • VDESIR0 = VDES*XFRI*XNMT • VDESIR = min(VDESIR0,PLIMIT*ENFAC/3.6) • VDES2 = Specified desired speed on a 2- lane road • VDES = Calculated desired speed • VDESIR0 = Adjusted for NMT & side-friction • VDESIR = Adjusted for speed limit enforcement • PLIMIT = Posted speed limit in km/h • ENFAC = Enforcement factor (1.10) • XFRI = Roadside friction factor • XNMT = Non-motorised transport factor • CW = Carriageway Width

  15. Effect of Width on Speed

  16. Free Speeds Constrained by: • Desired Speed (VDESIR) • Drive Power (VDRIVE) • Braking Power (VBRAKE) • Road Curvature (VCURVE) • Riding Quality (VROUGH)

  17. Speed Model Form Model form:

  18. Examples of Speed Predictions

  19. Traffic Interactions • HDM-III did not consider traffic interactions • HDM-95 considered effects of traffic interactions on speeds but not on VOC (fuel but only through speed reduction) • HDM-4 has expanded the HDM-95 approach to consider other VOC components

  20. Acceleration-Volume Effects Increased VOC consumption due to traffic congestion

  21. Model Basis • 3-Zone speed-flow model predicts that, as flows increase so do traffic interactions • As interactions increase so do accelerations and decelerations • HDM-4 adopted concept of ‘acceleration noise’ - the standard deviation of acceleration

  22. Acceleration Noise

  23. Acceleration Noise • Modelled using two components: traffic induced and ‘natural’ noise • Traffic noise function of flow • Natural noise function of: • driver’s natural variations • road alignment • roadside friction • non-motorised transport • roughness

  24. Fuel Consumption • Replaced HDM-III Brazil model with one based on ARRB ARFCOM model • Predicts fuel use as function of power usage: IFC = max(MinFuel,  Ptot)

  25. Model Parameters • Two basic model parameters used: • idle fuel rate • fuel conversion efficiency factor • Parameters can be readily derived from other fuel models • A range of values provided for different vehicle types from various published sources

  26. Effect of Speed on Fuel Consumption

  27. Implications of New Model • Lower rates of fuel consumption than HDM-III for many vehicles • Effect of speed on fuel significantly lower for passenger cars • Considers other factors; e.g. surface texture and type • Model can be used for congestion analyses

  28. Effects of Traffic Interactions on Fuel • Simulation model part of HDM-Tools • Run as calibration routine once unless vehicle characteristics changed • Uses Monte Carlo simulation of a vehicle travelling down a road with different levels of acceleration noise • Determines additional fuel as function of noise • Results in matrix of values of dFUEL vs Mean Speed vs Acceleration Noise

  29. Effects Traffic Interactions on Fuel Consumption

  30. Tyre Consumption • Tread wear • amount of the tread worn due the mechanism of the tyre coming into contact with the pavement surface • Carcass wear • combination of fatigue and mechanical damage to the tyre carcass - affects number of retreads

  31. Factors Influencing Tyre Consumption

  32. Types of Tyre Models MECHANISTIC Detailed models Relate tyre consumption to fundamental equations of motion Developed from controlled experiments EMPIRICAL Usually aggregate models Based on fleet survey data

  33. Retreads • If tyre carcass is serviceable tyres will often be retreaded (recapped) • Common with commercial vehicles • The likelihood of surviving for retread depends on tyre technology and operating conditions • Decrease in tyre life with increasing number of retreads

  34. Tyre Life and Survival vs No. of Retreads

  35. Effect of Congestion on Tyre Consumption

  36. Parts and Labour Costs Vehicle maintenance and repair costs: • Usually largest single component of VOC • In HDM-III user’s had choice of Kenya, Caribbean, India and Brazil models • All gave significantly different predictions • Most commonly used Brazil model had complex formulation • Few studies were found to have calibrated model

  37. Brazil Parts - Roughness

  38. Adjusted Roughness

  39. Parts Model Parameters • Estimated from HDM-III Brazil model • Exponential models converted to linear models which gave similar predictions from 3 - 10 IRI • Roughness effects reduced 25% for trucks • For cars, roughness effects same as for trucks • For heavy buses, roughness effects reduced further 25%

  40. Implications of Changes

  41. Congestion Effects • Parts consumption is assumed to increase under congested conditions • Use equation: • PARTS = PARTS (1 + CPCON dFUEL) • Default value for CPCON is 0.10 indicating that a 100% increase in fuel results in a 10% increase in parts

  42. Utilisation and Service Life HDM-III • Contained three utilisation methods: • Constant Kilometreage • Constant Hours • Adjusted Utilisation • Contained two service life methods: • Constant Service Life • de Weille’s Varying Service Life

  43. Utilisation and Service Life • HDM-4 has either constant or ‘Optimal Life’ service life • Utilisation function of hours worked for work vehicles; lifetime kilometreage for private vehicles

  44. Optimal Life Method • Proposed by Chesher and Harrison (1987) based upon work by Nash (1974) • Underlying philosophy is that the service life is influenced by operating conditions, particularly roughness • Relates life -- and capital costs -- to operating conditions

  45. OL Method

  46. Application of OL Method • HDM Tools contains a calibration routine for the OL method • User defines the replacement vehicle value, an estimated lifetime utilisation, and the roughness where this lifetime utilisation applies • Software establishes the effect of roughness on lifetime utilisation

  47. Example of Roughness on Lifetime Utilisation

  48. Capital Costs HDM-III • Used a simple linear model for depreciation • Affected by operating conditions through the effects of speed on utilisation and speed on service life (de Weille’s method)

  49. Depreciation in HDM-4 • Depreciation calculated multiplying the replacement vehicle price by the following equation: • The replacement vehicle price is reduced by a residual value which can be a function of roughness • The denominator is the lifetime utilisation which may be constant or predicted with the OL method to be a function of roughness

  50. Constant Service Life • Equations depend on the percentage of private use: • LIFEKM = LIFE x AKM < 50% • LIFEKM = S x HRWK x LIFE > 50%

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