moreVE Local Policy Options UNDER CONSTRUCTION

====================================THIS IS A DUMP OF UNSHAPED EXCERPTS....TBD

5. Inputs -- Pricing [Add table like in ODOT UG, maybe better in best practices?]

Pricing is one of the most effective and market-based policy in reducing vehicle miles travelled, promoting healthy active modes, and reducing energy use and emissions. In VE the following pricing types combine to make up the travel costs faced by households relative to household budget:

• Energy Costs to run vehicles and associated variable use taxes; This includes fuel and/or electricity costs, gas taxes, mileage (i.e. VMT) taxes, congestion taxes (typically only implemented in the statewide version), carbon taxes, pay-as-you-drive (PAYD) insurance, and parking pricing. Per Mile Fees (Gas, VMT, Carbon in 2005$)(DEFAULT) Several per mile fees combine to make up the roadway travel costs faced by households in RSPM. As discussed above they are typically default values used consistently across the state for each modeled year. They reside in the costs.csv file, as shown in Table 4 and 5.

  • Fuel & Electricity Costs – Cost for fuel and or electricity to run vehicles. This is defined as the average cost of gasoline fuels excluding taxes in dollars per gasoline equivalent gallon.
  • Gas Tax – Taxes on gasoline (in dollars per gallon)
  • VMT Fee– Road user fee collected from all vehicles per mile travelled (in dollars per vehicle mile)

• Congestion Charges – The fee collected to manage congestion, by charging a higher price during congested periods, and thereby reducing demand and freeing capacity for higher value users such a freight movement. Separate price schemes can be set by year to be imposed only during severe or extreme congestion (in 2005 dollars per vehicle mile, where imposed (congestion_charges.csv)

• Other costs of vehicle ownership and use that the household pays directly; This includes vehicle depreciation, vehicle maintenance, tires, finance charges, insurance, and registration. These costs primarily affect vehicle ownership, including CarService substitution with indirect impacts on VMT.

• External costs that are paid for by society as a result of the household's vehicle travel; This includes social and environmental costs that accrue to society but are not typically paid for by vehicle users. These costs include air pollution, climate change, energy security, safety, noise, and other resource impacts(e.g., water pollution). Social costs are calculated on a per VMT, per gallon, or per metric ton of CO2 basis so that they can be added to other taxes for scenarios in which it is assumed that some or all of these external costs will be paid by drivers.

• Road system costs; This includes costs for roadway expansion, other modernization projects, preservation, operations, maintenance and administration. These costs were developed for the STS to compare with total vehicle use taxes (e.g. gas, mileage, congestion) to determine whether sufficient revenues were generated to cover costs.

• Parking pricing is a trip-based cost, commonly paid for at one or both ends of a trip, and sometimes paid for on a monthly basis. The standard practice for handling parking pricing in urban travel demand models is to include it in the trip costs for auto travel. GreenSTEP handles parking pricing in a more general way within a household budget framework, where overall travel costs impact a household’s daily VMT. Two types of parking costs are addressed in the model - parking costs at places of employment and parking costs at other places. Daily parking costs are calculated for each household and added in with other variable costs. This includes fees for parking at workplace (including cash-out policies) and for non-work trips.

• Pay-as-you-drive (PAYD) insurance is automobile insurance that is paid strictly on a mileage traveled basis, rather than on a lump-sum periodic basis. On average, PAYD insurance does not change the amount that households pay for insurance. However, since the cost of PAYD to the motorist varies with the number of miles driven, there is an incentive to reduce travel to save money. It has been estimated that a PAYD insurance rate of 4 to 6 cents per mile, could reduce VMT from light vehicles by about 3.8%. In RSPM the estimated effect of PAYD insurance will depend on what other travel costs are being paid as well, influencing the VMT estimated based on travel costs relative to the household budget. RSPM requires input on the proportion of households in the full Metropolitan area buying car insurance using PAYD (payd.csv). A cost of 5 cents per mile (2005$) of PAYD insurance is used, a default value estimated through literature review and testing (payd.csv),*

ITS/Operations programs

ITS impact is modeled within RSPM, through speed reductions from basic and enhanced traffic operations, and active management of speed smoothing operational programs. Average speed on roadways in RSPM, is calculated as a function of congestion level and the type and amount of deployment of traffic operations programs. An average speed is associated with each roadway functional class (freeway or arterial) and congestion level. Those speeds are modified depending on the cumulative effect of user-specified deployment of the following traffic operations programs:

• Freeway ramp metering - Metering freeways can reduce delay by keeping mainline vehicle density below unstable levels. It creates delay for vehicles entering the freeway, but this is typically more than offset by the higher speeds and postponed congestion on the freeway facility. The Urban Mobility Report cites a delay reduction of 0 to 12%, with an average of 3%, for 25 U.S. urban areas with ramp metering. Only urban areas with Heavy, Severe, and Extreme freeway congestion can benefit from ramp metering in RSPM
• Freeway incident management - Incident Response programs are designed to quickly detect and remove incidents which impede traffic flow. The UMR study reports incident-related freeway delay reductions of 0 to 40%, with an average of 8%, for the 79 U.S. urban areas with incident response programs. This reflects the combined effects of both service patrols to address the incidents and surveillance cameras to detect the incidents. Effects were seen in all sizes of urban area, though the impacts were greater in larger cities.
• Arterial access management– Access management on arterials can increase speeds by reducing the number of enter/exit points on the arterial and reduce crashes by reducing conflict points. Although improvements such as raised medians can reduce throughput by causing turning queue spillback during heavy congestion, other types of access management, such as reduced business ingress/egress points, show consistent benefits system-wide.
• Arterial signal coordination – Traffic signal coordination, particularly for adaptive traffic signals, can reduce arterial delay by increasing throughput in peak flow directions. UMR and other analysis estimates delay reductions of up to 6-9% due to signal coordination, with more potential savings from more sophisticated control systems. An average arterial delay savings was found to be about 1%.
• Enhanced ITS/Speed Smoothing programs– Insufficient aggregate performance data is available for a number of other current and future ITS/operations strategies. These include: speed limit reductions, speed enforcement, and variable speed limits that reduce the amount of high-speed freeway travel; advanced signal optimization techniques that reduce stops and starts on arterials; and truck/bus-only lanes that can move high-emitting vehicles through congested areas at improved efficiency.
• Other Ops programs – Ability within VE allows flexibility within the model to accommodate future enhancements (other_ops.csv, other_ops_effectiveness.csv). Further research and significant program investment would be needed to justify benefits in these enhanced ITS programs.

Inputs specifying the level of deployment of several roadway Intelligent Transportation System (ITS) programs, determine the area roadway speeds which influence fuel efficiency.

Eco-Driving Practices (autos and trucks)

Eco-driving involves educating motorists on how to drive in order to reduce fuel consumption and cut emissions. Examples of eco-driving practices include avoiding rapid starts and stops, matching driving speeds to synchronized traffic signals, and avoiding idling. Practicing eco-driving also involves keeping vehicles maintained in a way that reduces fuel consumption such as keeping tires properly inflated and reducing aerodynamic drag. In RSPM, fuel economy benefits of improved vehicle maintenance are included in the eco-driving benefit. A default 19% improvement in vehicle fuel economy is assumed Vehicle operations and maintenance programs (e.g. eco-driving) based on policy assumptions about the degree of deployment of those programs and the household characteristics. Vehicle operating programs (eco-driving) reduces emissions per VMT

The fuel economy of all household vehicles of participating households is increased by a factor representing the average fuel economy gains of persons who are trained in eco-driving techniques. An RSPM input (speed_smooth_ecodrive.csv) specifies the proportion of light duty vehicle drivers who exhibit eco-driving habits. The same file makes similar assumptions on the proportion of other (commercial,heavy truck) drivers who are eco-drivers.

Transportation Options Programs

In RSPM, each household is assigned as a participant or not in a number of travel demand management programs (e.g. employee commute options program, individualized marketing) based on policy assumptions about the degree of deployment of those programs and the household characteristics. Individual households are also identified as candidate participants for car sharing programs based on their household characteristics and input assumptions on the market penetration of car sharing vehicles.

Workplace TDM Programs

Level of deployment assumptions for TDM (at work and home locations) lead to reduced VMT, diverting travel to other modes. Car Sharing reduces VMT through changes in auto ownership and per mile costs. Employee commute options (ECO) programs are work-based travel demand management programs. They may include transportation coordinators, employer-subsidized transit passes, bicycle parking, showers for bicycle commuters, education and promotion, carpool and vanpool programs, etc. The default assumption is that that ECO programs reduce the average commute DVMT of participating households by 5.4%. It is assumed that all work travel of the household will be reduced by this percentage if any working age persons are identified as ECO participants The proportion of employees participating in ECO programs is a policy input at the district level (prop_wrk_eco.csv). The input assumes workers participate in a strong employee commute options programs (e.g., free transit pass, emergency ride home, bike rider facilities, etc.).

Individualized Marketing Program

Individualized marketing (IM) programs are travel demand management programs focused on individual households in select neighborhoods. IM programs involve individualized outreach to households that identify residents’ travel needs and ways to meet those needs with less vehicle travel. Customized to the neighborhood, IM programs work best in locations where a number of travel options are available. RSM assumes that households participating in an IM program reduce their DVMT by 9% based on studies done in the Portland area. IM programs target work as well as non-work travel and produce larger reductions than ECO work-based programs. Only the IM reduction is used for households that are identified as participating in both ECO and IM programs.

RSPM district-level inputs for IM programs (imp_prop_goal.csv) include an overall assumption for the percentage of households participating in an IM program. A minimum population density of 4,000 persons per square mile necessary to implement a successful IM program and the requirement that the household reside an urban mixed-use district. The number of households identified as participating is the minimum of the number needed to meet the program goal or the number of qualifying households.

Vehicle/Fuels Technology Inputs

Vehicle and Fuel Technology are expected to change significantly during the next 20-50 years as vehicles turn-over and the newer fleets are purchased. The characteristics of the fleet of new cars and trucks are influenced by federal CAFÉ standards as well as state energy policies and promotions. Local areas can contribute through decisions about the light-duty fleet used by local transit agencies and by assisting in deployment of electric vehicle charging stations and their costs in work and home locations, but otherwise have less influence on the characteristics of the future vehicle fleet, including auto, light truck, and heavy truck vehicles. As a consequence, the RSPM inputs on vehicle and fuel technology are largely specified at the state level. These include inputs that reflect the default assumptions included in the Metropolitan GHG target rules and a more aggressive future as specified in the Oregon Statewide Transportation Strategy. These will both be available to provide sensitivity test to assess their impact on energy use and GHG emissions in the metropolitan area.

The key local contribution to these inputs is the bus electric/fuels inputs; although defaults can be used if no additional local data is available. These variables are briefly summarized below.

Vehicle age, fuel economy, and congestion

Several input files specify vehicle attributes and fuel economy for autos, light trucks, heavy truck, and transit vehicles. Four vehicle powertrain types are modeled :

• ICE - Internal Combustion Engines having no electrical assist;
• HEV - Hybrid-Electric Vehicles where all motive power is generated on-board;
• PHEV - Plug-in Hybrid Electric Vehicles where some motive power comes from arging an on-board battery from external power supplies;
• EV - Electric Vehicles where all motive power comes from charging an on-board battery from external power supplies.

Household owned vehicles -- sales mix; %LtTrks & veh age from household and the regional trends for its area. These combine with sales mix (powertain mix). Each Powertrain in each year has an associated fuel efficiency and power efficiency assumptions for PHEVs (MPG for PHEVs in charge-sustaining mode). For EVs and PHEVs, battery range is specified.
All other vehicles -- skip sales and jump directly to the mix of vehicles on the road in the modeled year, adjusted by inputs.

User inputs on vehicle age adjustment factors by vehicle type and year. The purpose of this input is to allow scenarios to be developed which test faster or slower turn-over of the vehicle fleet Households and commercial fleets operate a mix of passenger autos and light trucks or SUVs. This mix has an impact on fuel economy. In RSPM a file contains base year and target values for the proportion of the passenger vehicle fleet that is light trucks for each Metropolitan division (lttruck_prop.csv),

NOTE: the actual EV-HEV split depends on whether enough households have their 95Th percentile daily travel within the EV battery range

Vehicle Fuel Technology

A second set of inputs specifies the attributes of the fuels and their contributions to GHG emissions (fuel_co2.csv). This file contains information on lifecycle CO2 equivalent emissions by fuel type in grams per mega joule of fuel energy content. Fuel types are ultra-low sulfur diesel (ULSD), Biodiesel, reformulated gasoline (RFG), CARBOB (California Reformulated Gasoline Blendstock for Oxygenate Blending), Ethanol, compressed natural gas (CNG), LtVehComposite. The latter category is a blend of the carbon values of all of the fuel types relative to the proportions in which they were used in 1990. This allows the model to be more easily run to simulate lower carbon content of fuels without having to specify the relative proportions of each specific fuel type. The additives in fuel sold that contribute to GHG emissions. These include the average ethanol proportion in gasoline and biodiesel proportion in diesel (auto_lighttruck_fuel.csv, comm_service_fuel.csv, heavy_truck_fuel.csv).

Fuel Mix Shares (the remaining share is assumed to be diesel fuel):

• PropGas – The proportion of bus miles using gasoline
• PropCng – The proportion of bus miles using compressed natural gas

Biofuel Additives:

• DieselPropBio – The biodiesel proportion of diesel fuel used
• GasPropEth – The ethanol proportion of gasoline used

Electric Emissions Rate (Co2e lbs/ kwhr) of electricity consumed

Since electricity generation varies across the state, a local input to the model is the average cost and GHG emission rates of the local area. The average cost of electricity per kilowatt hour (kWh) in dollars across the metropolitan study area is included in the file costs.csv, while the emissions rate (in average pounds of CO2 equivalents generated per kilowatt hour of electricity consumed by the end user) by district and forecast year is found in a separate input file (power_co2.csv). Statewide default values for these inputs are available, if no local source is obtained.