Determination of Specific Vehicle Technologies

International Sustainable Systems Research Center 21573 Ambushers Street Diamond Bar, CA 91765

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Overview: The video taping process allows an effective means of determining the distribution of vehicle types on urban streets, to establish vehicle counts, and to establish the relative amount of driving. However, unless licenses plate numbers are captured and the local licenses plate data base contains information on the specific technologies then it is not possible for the researcher to know the specific technologies of the passenger vehicles, trucks, buses, and other types of vehicles that are operating on the streets. Thus, a means must be found to identify specific vehicle technologies. There is no specific approach that will work for all vehicle categories. Some thought must be given to how appropriate vehicle specific information should be collected. It should be noted in this discussion that it is tempting to pick up a database from vehicle registrations to establish the distribution of technologies on the roads. However, this can be very misleading. Since most vehicles are required to be registered, the data base does not indicate how likely the various vehicle technologies are to be driven. Data from vehicle registrations is referred to as the “static fleet”. The person performing an emission inventory is interested in knowing the amount that vehicles are actually operated. This fleet distribution is referred to as the “dynamic fleet”. The IVE study is interested in the “dynamic fleet” and care should be taken that the data collected properly represents this fleet. Passenger Vehicles/2-Wheel Technologies: In order to make accurate estimates of the distribution of specific passenger vehicle and 2-Wheel technologies operating on urban roads, two approaches have been used. One way to collect this information is to survey on-street parking and parking lots. Vehicles are parked on the street in commercial areas in the proportion that they are driven. Thus, the distribution of vehicle technologies identified in a parking lot study are directly applicable to vehicle emissions modeling. Care should be taken to avoid residential streets. On residential streets, cars and 2-Wheelers can remain on the street out of proportion to how they are driven. Also, the family’s good vehicle is often locked up and the distribution of on-street vehicles are the very old vehicles in these areas. Use of a lot of this data would bias the sample. Grocery stores and parking lots housing vehicles involved in daily commuting are the best places to collect data. On-street parking in commercial areas can also be good places to look. A typical data sheet for recording vehicle data is illustrated at the end of this paper. In Los Angeles, licenses plate data proved to be useful and since the licenses plates were collected from video sampling, the technologies identified were thus consistent with driving fractions (the dynamic fleet). Inspection/Maintenance (I/M) data was used in Mexico City. This data also proved to be useful. However, since all vehicles are required to go through I/M regardless of how much they are driven, the I/M database does not present technologies in the proportion of how they are driven on the street. Thus, the data had to be adjusted according to the odometer readings of the vehicles which are recorded in the Mexico City data. The use of vehicle registrations can also leave out vehicles that legally or illegally evade the requirement to be registered.

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Depending upon the location, 2-Wheelers are used in essentially the same manner as passenger vehicles for commuting. In other cases, 2-Wheelers are used more for deliveries. In this latter case, contact with the delivery companies, brief interview with operators, or other approaches similar to those used for trucks, buses, and taxis may prove valuable. Truck Technologies: The determination of on-road technologies for trucks can be very difficult. It is not possible to do parking lot surveys for these vehicles because they are not parked typically in accessible parking lots. Most trucks are diesel and the variety of technologies is small so that there is not a lot of technologies to consider. The following discussions describe approaches used in other urban areas:

• Pune, India: A station where trucks stop to pay fees was found. Trucks were inspected and the drivers were quizzed to develop a database of truck technologies that is indicative of the distribution of on-road operations.

• Sao Paulo, Brazil: The license plates of trucks were video taped and the numbers entered into an excel spread sheet. These numbers were supplied to the motor vehicle authority, which had records on the technology of the truck. Since the licenses were recorded from the urban roads then the distribution that we observed should be consistent with the dynamic fleet.

• Beijing, China: Trucking companies were contacted and data collected concerning the technologies in their fleets. We had no way to determine if some technologies tended to be driven more than others. We were forced to assume that they were driven proportional to the rate that they appeared in the respective fleets.

Bus Technologies: The determination of on-road technologies for buses can also be difficult depending upon the location. In some cases, the bus companies themselves keep accurate records, which can be valuable. Most buses are diesel and the variety of technologies is small so that there is not a lot of technologies to consider. The following discussions describe approaches used in other urban areas:

• Pune, India: The bus companies were contacted, and it was found that they had very accurate records on their buses including engine technology, size, and exact driving amounts.

• Santiao, Chile: The Inspection/Maintenance data for buses was used. This data is of course from the static fleet, but it is the best that it available to this point in time.

• Nairobi, Africa: Buses here are primarily large van type vehicles called Matatus. Vehicle operators were surveyed to determine the technology distributions.

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Taxi Technologies/3-Wheel Technologies: Taxis and 3-Wheel vehicles tend to congregate at certain locations. Thus, the best way to collect taxi information is to go to several of these taxi stops and collect appropriate technology on the taxis. There can be a tendency for taxi drivers to disconnect odometers and thus produce erroneous readings and in the case of 3-Wheelers there may or may not be an odometer. Many taxi drivers seem to know how much they drive per day, which can be useful information; although we have found that they remember their best days more than their bad days. Thus, care should be taken in interpreting their driving estimates. Number of Vehicles to Sample: As is the case for all statistical analysis, the more data the better. However, costs and time limits often limit how many vehicles are surveyed. It has been our goal to survey enough vehicles so that vehicle populations down to 1% will show up in the survey. In the case of passenger vehicles there tend to be a large variety of vehicle technologies. Thus, we typically attempt to collect data on 800 to 1,200 vehicles in a study. A single survey team consisting of a person to identify technologies and a person to record data can normally collect data on 100 to 120 vehicles per day. Thus over a 6 day period, two teams can collect data on 1,200 vehicles. There are a much lower variety of truck, bus, 2-wheeler, and 3-wheeler technologies and even taxis tend to conform to a more limited range of vehicle types. We normally seek to collect information on 50 to 100 of each of these classes of vehicles. As noted before, more data is always better. Conduct of Parked Vehicle Surveys: Parked vehicle surveys can consist of two types. In one case, vehicles are looked at while they are parked and data recorded. In the other case, drivers are sought out as they park their cars or as they enter grocery stores, businesses, and shopping areas. There are advantages and disadvantages to each approach. In the case of parked vehicles, there can be concern about unknown persons looking inside of vehicles. This can be typically avoided if proper documentation is carried and explanations are given to vehicle owners if they return to their vehicles while they are being inspected. Parking lot owners also need to be apprised of studies in their parking lots. Most vehicle owners will be happy to provide the researcher with information in a survey, but they are often ignorant of their vehicle technology and control systems. If drivers are caught as they leave their vehicles then the survey team can do the interview and also look at the vehicle. The problem here is that this approach can be very slow. Gasoline/diesel refueling stations have been suggested, but the rate of vehicles coming into the station can be slow. In any of the survey approaches, it is normally most efficient to have a vehicle expert and a student or some other person to record data. As discussed earlier, two or more teams can be used to increase data production. Experienced local mechanics are often very knowledgeable about identifying engine technology, model year and such. They can also be knowledgeable about catalyst technology but care should be taken to insure this fact.

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Analysis of Vehicle Surveys: It has been found that a spreadsheet program such as Excel can be an excellent database management solution for these types of data collection exercises. Normally, it is arranged for a student to enter the data into the spreadsheet program the next day after the data is collected. This way, any data recording problems can be identified early in the data collection process. Once data has been entered into the spreadsheet program then the sorting features of the spreadsheet can be used to breakout the technology fractions consistent with the needs for the IVE model.