Road User Effects Christopher R. Bennett Director - Data Collection Ltd.

Overview of Presentation äIntroduction äRUE components in HDM-4 äMechanistic modelling äSpeed Prediction äSpeed Flow and Traffic Interactions äFuel Consumption äTyre Consumption äMaintenance and Repairs äCapital Costs äOil Consumption äTravel Time äSafety/Accidents

Components of Road User Effects

Key Changes from HDM-III äUnlimited number of representative vehicles äReduced maintenance and repair costs äChanges to utilisation and service life modelling äChanges to capital, overhead and crew costs äNew fuel consumption model äNew oil consumption model äChanges to speed prediction model äUse of mechanistic tyre model for all vehicles

New Features in HDM-4 äEffects of traffic volume on speed, fuel, tyres and maintenance costs äNon-motorised transport modelling äEffects of road works on users äTraffic safety impact äVehicle emissions impact

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

RUE Components lMT Vehicle operating costs (VOC) lMT Travel time costs (TTC) lNMT Time and operating costs (NMTOC) lAccident costs (AC) RUE = RUC + Emissions + Noise RUC = VOC + TTC + NMTOC + AC

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

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

Forces Opposing Motion äCalculates: l aerodynamic resistance (Fa) l rolling resistance (Fr) l gradient resistance (Fg) l curvature resistance (Fcr) l inertial resistance (Fi) äUses more detailed equations than HDM-III

Speed Prediction

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

Vehicle Speed Models lDesired speeds é User specified for 2-lane road é Adjusted for Width, Friction, NMT, Speed Limit lFree speeds é Uphill (steady state) é Downhill (steady state) é Constrained by limiting factors lOperating Speeds é Calculated for traffic flow periods é Adjusted for Speed-Flow effects

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

Effect of Width on Speed

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

Speed Model Form Model form:

Examples of Speed Predictions

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

Fuel Increases with Accelerations

Model Basis ä3-Zone speed-flow model predicts that, as flows increase so do traffic interactions äAs interactions increase so do accelerations and decelerations  HDM-4 adopted concept of ‘ acceleration noise ’ - the standard deviation of acceleration

Acceleration Noise

 Modelled using two components: traffic induced and ‘ natural ’ noise äTraffic noise function of flow äNatural noise function of: driver ’ s natural variations driver ’ s natural variations l road alignment l roadside friction l non-motorised transport l roughness

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

Model Parameters äTwo basic model parameters used: l idle fuel rate l fuel conversion efficiency factor äParameters can be readily derived from other fuel models äA range of values provided for different vehicle types from various published sources

Effect of Speed on Fuel Consumption

Implications of New Model äLower rates of fuel consumption than HDM-III for many vehicles äEffect of speed on fuel significantly lower for passenger cars äConsiders other factors; e.g. surface texture and type äModel can be used for congestion analyses

Effects of Traffic Interactions on Fuel äSimulation model part of HDM-Tools äRun as calibration routine once unless vehicle characteristics changed äUses Monte Carlo simulation of a vehicle travelling down a road with different levels of acceleration noise äDetermines additional fuel as function of noise äResults in matrix of values of dFUEL vs Mean Speed vs Acceleration Noise

Effects Traffic Interactions on Fuel Consumption

Tyre Consumption äTread wear l amount of the tread worn due the mechanism of the tyre coming into contact with the pavement surface äCarcass wear l combination of fatigue and mechanical damage to the tyre carcass - affects number of retreads

Factors Influencing Tyre Consumption

Types of Tyre Models MECHANISTIC äDetailed models äRelate tyre consumption to fundamental equations of motion äDeveloped from controlled experiments EMPIRICAL äUsually aggregate models äBased on fleet survey data

Retreads äIf tyre carcass is serviceable tyres will often be retreaded (recapped) äCommon with commercial vehicles äThe likelihood of surviving for retread depends on tyre technology and operating conditions äDecrease in tyre life with increasing number of retreads

Tyre Life and Survival vs No. of Retreads

Effect of Congestion on Tyre Consumption

Parts and Labour Costs Vehicle maintenance and repair costs: äUsually largest single component of VOC  In HDM-III user ’ s had choice of Kenya, Caribbean, India and Brazil models äAll gave significantly different predictions äMost commonly used Brazil model had complex formulation äFew studies were found to have calibrated model

Brazil Parts - Roughness

Adjusted Roughness

Parts Model Parameters äEstimated from HDM-III Brazil model äExponential models converted to linear models which gave similar predictions from IRI äRoughness effects reduced 25% for trucks äFor cars, roughness effects same as for trucks äFor heavy buses, roughness effects reduced further 25%

Implications of Changes

Congestion Effects äParts consumption is assumed to increase under congested conditions äUse equation: l PARTS = PARTS (1 + CPCON dFUEL) äDefault value for CPCON is 0.10 indicating that a 100% increase in fuel results in a 10% increase in parts

Utilisation and Service Life HDM-III äContained three utilisation methods: l Constant Kilometreage l Constant Hours l Adjusted Utilisation äContained two service life methods: l Constant Service Life de Weille ’ s Varying Service Life de Weille ’ s Varying Service Life

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

Optimal Life Method äProposed by Chesher and Harrison (1987) based upon work by Nash (1974) äUnderlying philosophy is that the service life is influenced by operating conditions, particularly roughness äRelates life -- and capital costs -- to operating conditions

OL Method

Application of OL Method äHDM Tools contains a calibration routine for the OL method äUser defines the replacement vehicle value, an estimated lifetime utilisation, and the roughness where this lifetime utilisation applies äSoftware establishes the effect of roughness on lifetime utilisation

Example of Roughness on Lifetime Utilisation

Capital Costs HDM-III äUsed 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)

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

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

Example of OL Roughness on Depreciation

Interest Costs äInterest costs are the replacement vehicle price multiplied by the following equation: äFunction of speed and hours worked as well as the interest rate

Oil Consumption äHDM-III only function of roughness äModel contains two components l Fuel use due to contamination l Fuel use due to operation which is proportional to fuel use

Travel Time Components äPassenger Working Hours äPassenger Non-Working Hours äCrew Hours

Accident Rates and Exposure äThe accident rate is the number of accidents divided by the exposure äThe exposure is calculated differently for intersections and sections

Modelling Approach äHDM-4 does not contain predictive models äUses a series of look-up tables äAccidents function of data in HDM-4 database

VOC Calibration Procedure (Level 1) äVehicle mass & ESAL äRoad Capacity & Speed-Flow factors äVehicle service life äVehicle Utilisation (Annual KM & Hours) äDesired speed äVehicle engine power, speed (rpm) & braking äTyre characteristics (type, rubber volume, etc) äVehicle depreciation äAerodynamic factors

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