1 1 1 1 1 1 1 1 0 1 0 1 0 Trip Generation Rates at Park-and- Ride (PnR) Facilities with Regional Bus and Light Rail Service: A Supplement to ITE Trip Generation Data Ravi Palakurthy (Corresponding Author) Regional Transportation District Broadway, Suite 00 Denver, CO 00 Phone: (0) - Email: Ravikumar.Palakurthy@RTD-Denver.com Li-Wei Tung, Ph.D. Regional Transportation District Broadway, Suite 00 Denver, CO 00 Email: Li-Wei.Tung@RTD-Denver.com Lee Cryer Regional Transportation District Broadway, Suite 00 Denver, CO 00 Email: Lee.Cryer@RTD-Denver.com Lacy Bell, P.E. Regional Transportation District Broadway, Suite 00 Denver, CO 00 Email: Lacy.Bell@RTD-Denver.com, words [, + Figures x 0 + Tables x 0]
1 1 1 ABSTRACT A Park-and-Ride (PnR) is a parking facility with connections to public transit service. The ITE (Institute of Transportation Engineers) Trip Generation Manual, th Edition, presented trip generation rates separately for PnR facilities with bus and light rail service; however, the small sample sizes (maximum sample size is six studies) and outdated trip generation rates (between 10s and 000s) may not be an accurate representation for transportation engineers and planners to correctly estimate the traffic impacts of PnR facilities. This paper describes a comprehensive trip generation study that was performed at 0 Regional Transportation District (RTD) PnR facilities in the Denver region with regional bus and light rail transit service. Similar to the ITE manual, weighted average trip rates and regression equations are estimated and produced in this study. The sample size and variation in the data collected in this study can be used as a good representation for computing trip generation locally, or for being applied to cities with similar transit systems and PnR design criteria. #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 1 0 1 1. INTRODUCTION A Park-and-Ride (PnR) is a parking facility that provides connections to public transit services. Transit passengers can be dropped off or leave their vehicles at the facility and transfer to a bus or train and thus avoid traffic congestion and expensive city parking. PnR facilities provide local and regional access to transit, consolidate demand for service, and can reduce vehicle trips and traffic congestion. PnR facilities are generally located in suburban areas or at stations with multiple transit choices. PnR facilities can be seen as a transport compromise, converting fulltrip drivers into part-trip riders (1, ). However, there is little research on analyzing trip generation at PnR facilities. The Institute of Transportation Engineers (ITE) Trip Generation Manual () presented trip generation data separately for PnR facilities with bus and light rail service; however, small sample sizes (three studies for weekday average trip ends per occupied space) and outdated trip generation data (e.g., between 10s and the 000s) may not be an accurate representation for transportation engineers and planners to estimate trip generation rates and to measure the traffic impacts of these facilities. The Southern New Hampshire Planning Commission (SNHPC) published a local trip generation manual, Trip Generation Study, to develop local trip generation rates for land use types in the region for which ITE data is lacking (). They conducted the trip generation analysis at two PnR facilities along I- in New Hampshire. However, a small sample size once again yielded insufficient and inadequate trip generation results. Also, trip generation rates at facilities with light rail service were not included. This paper describes a trip generation study that was performed at 0 Regional Transportation District (RTD) PnR facilities in the Denver region with regional bus and light rail transit service. This study is aimed to produce locally generated trip rates and to supplement the trip rate data in the ITE manual. In the next section, data collection methodology is discussed. Then the data analysis and vehicle trip generation rates are provided in the following sections.. DATA COLLECTION RTD has PnR facilities with 1, parking spaces primarily serving light rail and regional bus services. In this study, 0 PnR facilities with transit service were sampled to determine trip generation data for RTD PnR facilities. RTD conducted counts at only 0 out of the PnRs due to limited resources and funding. In order to maximize the utility of available resources, all the PnRs along our light rail system and several bus PnRs were selected. The bus PnRs are selected to be the representative of the system reflecting different service levels and PnR geographical locations. Some bus PnRs in remote locations and PnRs that are very under-utilized were not included for data collection because even though the PnRs are for transit use, anecdotal evidence suggests that those remote PnRs are primarily being utilized for non-transit related purposes. Of the 0 PnR facilities, 1 facilities provide regional bus service and the remaining facilities provide light rail service. At RTD, regional bus service provides longer distance service across the region, make few stops, and often operate along controlled access facilities. Regional bus service also provides service primarily during peak periods between major trip origin and destination points in the region. Most facilities (but not all) also include local or feeder bus service to connect passengers to the regional bus or light rail service. Figure 1 illustrates the #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 1 0 1 locations of RTD PnR facilities, and the study facilities are marked with stars (for PnR facilities with light rail service) and triangles (for PnR facilities with regional bus service). The study PnR facilities were number coded in the figure, and the full names of PnR facilities can be found in the Figure. In this study, the PnR facilities covered all light rail corridors outside of downtown Denver (i.e., Southeast, Southwest, and West Corridors) and covered major regional bus corridors. The PnRs located along the rail lines are served by light rail at a frequency of 1 minutes or less. These rail lines primarily serve downtown area, the largest business and employment center in the City of Denver. The rail lines also serve two universities University of Colorado - Denver and University of Denver from the suburban and urban areas. The bus PnRs in the study mostly are served by regional bus with high frequency ( 1 minutes) service during the A.M. and P.M. peak periods. These regional buses mainly connect the downtown Denver area with satellite cities in the region (e.g., City of Boulder). Traffic data collected as a part of this study included: maximum accumulation, entry and exit counts at 1-minute intervals, vehicle occupancy counts during peak periods, and non-motorized counts. Data were collected on weekdays in Spring 01 to represent average weekdays. One-day of data were collected for each PnR facility. Care was taken not to collect data during bad weather days, holidays, and spring/summer breaks for universities to ensure that the data collected reflected average weekday use. Traffic counts were collected using traffic cameras. Cameras at each site were placed at all possible vehicle entry and vehicle exit points and were placed at a height where the number of vehicle occupants could be accurately viewed. The number of cameras at each PnR facility varied depending on its layout and surrounding conditions. Many PnR locations required multiple cameras to collect the data accurately. The placement of cameras was at all access points for most of the facilities. However, at one facility, Broadway Marketplace (#1 in Figure 1), the parking facility is shared with adjacent commercial establishments, so the cameras were placed in the portion of facility designated as transit parking to ensure that all transit-related trips were accurately captured and collected. Data processing was completed manually by technicians. Vehicles from all videos at each site were manually counted and recorded for the complete hour period. To ensure accuracy and reliability of the data, various quality assurance and quality control checks (QA/QC) were conducted as a part of data collection and data processing. The QA/QC process for field work was to verify that all access points of a site were accounted for by physically going through the entire site. Also while processing the data, any odd activity at the facility was documented. Video data was reviewed one more time for accuracy in instances with unexpected results. Maximum vehicle accumulation data collected in this study was compared to the RTD s quarterly parking utilization reports to validate the study data quality, and maximum vehicle accumulation data seemed valid after that comparison. Communication between the field technician and the data processor was very frequent to ensure the data was processed accurately. #1-01 Revised Paper
1 FIGURE 1 Study Park-and-Ride locations. #1-01 Revised Paper
1 1 1 1 1 1 1 1 0. DATA ANALYSIS METHODOLOGY Data collected from the PnR facilities were then analyzed to estimate the trip ends and PnR vehicle accumulation patterns. A trip end is a single or one-direction vehicle movement with either exiting or entering inside a study site (). The following sections will discuss those two major elements of this study..1 Park-and-Ride Vehicle Accumulation PnR vehicle accumulation can be defined as the number of vehicles parked in a PnR facility at any time during a day. During the data collection period, the total number of vehicles entering and exiting the facility was aggregated at 1-minute intervals. Vehicle accumulation (i.e., number of vehicles parked in the facility) for each 1-minute period was estimated using Equations 1 and. The number of parked vehicles at the end of interval i, CP i, was equal to the sum of the number of parked vehicles at the beginning of the analysis interval, CP i-1, and the sum of the number of vehicles entering the facility during interval i, CI i, minus the number of vehicles existing the facility during interval i, CO i. By calculating the number of parked vehicles for each interval for a study period (i.e., -hour in this study), the maximum vehicle accumulations were observed. CP i = CP i-1+ CI i CO i (1) CP i+1 = (CI i+1 CO i+1 )+CP i () 1 0 1 0 1 Where CP i = Number of vehicles parked in the facility during interval i, CI i = Number of vehicles entering the facility during interval i, CO i = Number of vehicles exiting the facility during interval i, and i = a given analysis interval. Through the PnR vehicle accumulation, not only can the overall facility utilization patterns be observed, but maximum occupied parking space can also be estimated. The occupied parking space will be used as the independent variable to estimate the dependent variable, number of trip ends.. Vehicle Trip Generation by Predominant Transit Modes Vehicle entering and exiting counts were used to estimate trip generation rates for daily, A.M. /P.M. peak hours, and peak hour entry/exit distributions. Analysis was conducted to determine the weighted average number of trip ends per occupied space and per parking space. However, in this paper, only occupied spaces were chosen rather than total parking spaces to show actual PnR demand, which is important for future PnR planning. Additionally, the trip generation rates were estimated by different predominant transit modes served at PnR facilities in this study (e.g., regional bus and light rail). Average daily and peak hour trip generation rates by transit modes are presented in weighted average because the sites with a high variance do not disproportionately affect the mean. The weighted average trip generation rates (by predominant transit modes) are estimated using Equation. #1-01 Revised Paper
1 1 1 1 1 1 1 1 1 0 1 0 1 0 1 WR (bus,rail) = N a=1 (CI a + CO a ) () N a=1 OP a Where WR O = Weighted average number of trip ends per occupied space for all study facilities by transit mode, OP a = Occupied parking spaces at Facility a, CI a = Number of entering vehicles at Facility a, CO a = Number of exiting vehicles at Facility a, and N = Total number of PnR facilities per transit mode. In Equation, the weighted average trip generation rate, WRo, was estimated by taking a sum of entries, CI a, and exits, CO a, across all study PnR facilities by transit mode (N) and dividing it by the sum of all occupied spaces, OP a, across all study PnR facilities by transit mode (N).. DATA ANALYSIS.1 Park-and-Ride Vehicle Accumulation In this study, the maximum PnR vehicle accumulation was used to estimate the occupied parking spaces at facilities. Figure presents the maximum vehicle accumulation and total parking spaces at each study facility. The figure grouped the facilities based on the types of transit service available at those facilities. The numeric value within each pair of parentheses is the identification code for a facility. Fifteen facilities are served by regional bus, and the remaining facilities primarily are served by light rail service along with local bus service. The local bus service at light rail stations is generally feeder bus service intended to feed the light rail stations but not compete with the light rail service. Trips made by using only bus service at light rail PnR facilities are significantly low. Thus, the effect of bus-only trips is neglected for these facilities. Similarly, the local or feeder bus trips at regional bus PnR facilities are relatively low, and thus, the effect of those trips is also not considered in this study. In Figure, the total number of parking spaces for the 0 study facilities is,0. The maximum vehicle accumulation at 0 study facilities is 1,1 spaces. The overall percent accumulation is 0%. Broken down by predominant transit mode, % of parking spaces are found to be occupied at the facilities with regional bus service and % of parking spaces are occupied at the facilities with light rail service. The average number of occupied spaces at the facilities with regional bus service is spaces and 1 spaces for the facilities with light rail service. The facilities with light rail service have a higher occupancy rate than the facilities with regional bus service. A higher occupancy rate found at the facilities with light rail service may be due to the differences in service levels. The light rail corridors operate all-day long, whereas most of the regional bus routes operate mainly during the A.M. and P.M. peak periods. Typically, the regional bus service is only provided inbound towards Denver in the A.M. peak periods and return service in the P.M. peak period. Some of the regional bus routes do provide bi-directional all-day service similar to light rail but typically with less frequency. #1-01 Revised Paper
1 The PnR facilities with light rail service are grouped by light rail corridors. In Figure, one can find that most facilities located along the Central, Southwest and Southeast corridors have high parking utilization; however, the facilities along the West Corridor have high vacancy rates. This observation can be further confirmed by the ridership recorded for the West corridor. The West Corridor has the lowest ridership of all RTD light rail corridors. Through the vehicle accumulation patterns and parking utilization, the sizes of the existing parking facilities can be adequately re-evaluated for future PnR planning. For example, the facilities along the West Corridor and other locations with low parking utilization can be assessed for possible changes to other purposes/land uses such as transit oriented development (TOD). #1-01 Revised Paper
Parking Spaces 1,00 1,00 1,00 1,00 1,000 00 00 00 00 0 1 Maximum Accumulation Unused Capacity Regional Bus Central Southwest (Light Rail) (Light Rail) Southeast (Light Rail) West (Light Rail) th & Coffman ( 1 ) Airport Blvd. & 0th Ave. ( ) Olde Town Arvada ( ) Parker ( ) Stapleton ( ) Thornton ( ) US- & Bridge Street ( 1 ) Wagon Road ( 1 ) Ward Road ( 1 ) Table Mesa ( ) US- & Broomfield ( ) US- & Church Ranch ( ) US- & Flatiron ( ) US- & McCaslin ( ) US- & Westminster Center ( 1 ) 0th & Downing Station ( 1 ) Broadway Marketplace ( 1 ) I- & Broadway Station ( 1 ) Englewood Station ( 1 ) Evans Station ( 0 ) Littleton-Downtown Station ( 1 ) Littleton-Mineral Station ( ) Arapahoe at Village Center Station ( ) Belleview Station ( ) Colorado Station ( ) County Line Station ( ) Dayton Station ( ) Dry Creek Station ( ) Lincoln Ave. Station ( ) Nine Mile Station ( 0 ) Orchard Station ( 1 ) Southmoor Station ( ) University of Denver Station ( ) Yale Station ( ) Decatur-Federal Station ( ) Sheridan Station ( ) Lakewood-Wadsworth Station ( ) Oak Station ( ) Federal Center Station ( ) Jefferson County Govt. Center Golden Station ( 0 ) FIGURE Park-and-Ride vehicle accumulations. #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 1 0 1. Vehicle Trip Generation Traffic counts recorded from the facilities were used to estimate trip generation rates for daily, A.M. and P.M. peak hours. Entry/exit distributions for each PnR facility were also prepared. Prior to the estimation of trip generation rates at facilities by different predominant transit modes, trip generation rate at each facility and the associated distributions were evaluated. To accurately estimate trip generation rates, outliers were identified and removed from the analysis. The trip generation rate at a PnR facility is calculated based on Equation. R a = (CI a+co a ) OP a () Where R a = Trip generation rate at Facility a, CI a = Number of entering vehicles at Facility a, CO a = Number of exiting vehicles at Facility a, and OP a = Occupied parking spaces at Facility a. The daily trip generation rates for 0 study facilities were then computed and plotted to observe the distributions of trip generation rates by two transit modes. From the plots, shown in Figures (a) and (b), three locations were defined as outliers and were excluded from the analysis as a part of quality control process. The three locations, marked in Figures (a) and (b), were identified based on the unusually high trip rates as compared to the rest of the group. Also, the abnormally high trip rates for these three PnR facilities can be reasonably explained as below. a) US- & Bridge Street (Regional Bus): The daily trip rate for this station was. which was unusually high compared to the average trip rate of.. During the data collection it was observed that the PnR was being used as a parking facility by the patrons of the adjacent fitness facility. As a result, the trip rate was skewed and did not reflect trip generation from transit usage. b) 0 th & Downing Station (Light Rail): The daily trip rate for this location was 1.1, which was unusually high compared to the average trip rate of.. The reason for this high rate can be attributed to two reasons: 1) extremely small size of parking lot (i.e., spaces) and its proximity to downtown. Significant entering and exiting traffic throughout the day is possible due to people checking the availability of an open spot but leaving the location upon finding that the facility is full. ) Another reason might be that people parking in that lot might be traveling to downtown for a shorter time period (e.g., attend meetings) rather than commuting for a full work day. c) Arapahoe at Village Center Station (Light Rail): The daily trip rate for this location was. which was significantly higher than the average rate of.. After the review of camera locations for this PnR along with its layout and surrounding streets, the high trip rate was attributed to some through traffic that was not related to the PnR. #1-01 Revised Paper
Vehicle trip ends Vehicle trip ends 1 1 (a) 1 0-00 00 00 00 1,000 1,00 1,00 1,00 1,00 Occupied Spaces (Regional Bus) FIGURE (a) Daily trip generation rates at PnR facilities with regional bus service. 1 (b) 1 (c) 0-00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 Occupied Spaces (Light Rail) FIGURE (b) Daily trip generation rates at PnR facilities with light rail service. #1-01 Revised Paper
1 1 1 1 1 1..1 Weighted Average Trip Rate The A.M. and P.M. peak periods for the Denver region are observed to be :00-:00 AM and :00-:00 PM, respectively. However, to be consistent with the formats presented in the ITE Trip Generation Manual, trip generation rates were estimated for one hour data during A.M. peak period (:00 :00 A.M.) and P.M. peak period (:00 :00 P.M.). Trip generation rates showed one hour weighted average number of trip ends per occupied space at PnR facilities with regional bus and light rail service. Table 1 summarizes the comparisons of trip generation rates at the facilities with different predominant transit modes during different analysis time periods. The values shown here are weighted average trip rates. Thus, the number of trips generated by a PnR facility is estimated by multiplying the number of occupied spaces with the weighted average trip rate. The weighted trip rate methodology assumes a linear relationship with the intercept at the origin (). A small standard deviation means less dispersion and that the model fits the data better. TABLE 1 Weighted Average Daily and Peak Hour Trip Generation Rate per Occupied Space Daily AM Peak Hour (:00 :00 AM) PM Peak Hour (:00 :00 PM) 1 1 1 0 1 Park-and- Ride Type Weighted average Range of rates S.D. Weighted average Range of rates S.D. Weighted average Range of rates S.D. Regional Bus.0.0-. 0. 0.0 0.1-0. 0.1 0. 0.-0. 0.1 Light Rail.1.-.1 1. 0.1 0.1-0. 0.1 0. 0.-1. 0. All..0-.1 1.0 0. 0.1-0. 0.1 0. 0.-1. 0. The count data collected was also analyzed to estimate the directional distribution (i.e., entry-exit percentages) for daily, A.M. and P.M. peak hours. Table illustrates the directional distribution for all the facilities and by different transit modes. TABLE Directional Distribution Summaries by Park-and-Ride Type Park-and-Ride Type Daily Entry % Daily Exit % AM Peak Hour Entry % AM Peak Hour Exit % PM Peak Hour Entry % PM Peak Hour Exit % Regional Bus 0% 0% % 1% 1% % Light Rail % 1% % 1% % % All % 1% % 1% % % This study yielded a daily trip generation rate of.0 vehicle trip ends per occupied space for the PnR facilities with regional bus service, with 0% of vehicles entering and 0% of vehicles exiting the facility. A daily trip rate of.1 vehicle trip ends per occupied space was found for the PnR facilities with light rail service. The daily entry number was slightly less than the daily exit number at facilities with light rail service. This phenomenon might be attributed to some vehicles parked at facilities overnight, and overnight parking is allowed at RTD PnR facilities #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 with a minimum charge. High entry numbers and high exit numbers were also found at all facilities during A.M. and P.M. peak hours, respectively. This observation verified that the majority of parking spaces were utilized for trips made in the peak hours consistent with commute to work patterns. Also note that the trip generation rates estimated in this study included the trips made by Kiss-and-Ride passengers at PnR facilities. A Kiss-and-Ride passenger is a transit rider who is dropped off and picked up by a companion without parking the car in the facility. It would be ideal to separate out these trips even though the filed observation results proved that the percentage of Kiss-and-Ride passengers on RTD s system is relatively insignificant; however, due to budget constraints and possible extensive labor commitments, these trips were included in the estimation of the PnR trip rates. Several observations are made based on the trip generation data collected: 1) One major observation made from the data was that there is a high parking space turn over during the course of a day. For example there are.0 trips per day per occupied space at a regional bus only PnR facility. With daily 0% entry and 0% exit split, it can be estimated that there are 1. entries and 1. exits per occupied space. These 1. entries per occupied space indicate that each parking space is occupied more than once. In other words, it can be interpreted that if there are 0 parking spaces in a facility, there will be 1 entries and exits or % of parking spaces are being turned over (being occupied) more than once. ) The trip rates and ranges for PnR facilities with predominantly light rail service were higher than the PnR facilities with regional bus service. The differences can be partly attributed to the following two reasons: a) Level of service and service span being provided were different between the two types of PnR facilities. All PnR facilities with light rail service in the district have all day service with service frequencies ranging from 1 minutes to 0 minutes; however, most of the study PnR facilities with regional bus service have excellent peak period service but very limited if any midday or off-peak bus service. b) The trip rate differences can also be partly attributed to the location of the PnR facilities. Several of the PnR facilities with light rail service are within or on the edges of the City and County of Denver. People have easy access to those facilities and use light rail system to downtown to engage in different activities. However, PnR facilities with regional bus service are located in suburban areas, and the users usually intend to park for a full day to work in downtown. Hence, the turn over and trip generation rates are low. In addition to weighted average trip rate, regression equations are provided in the following section to predict trip generation at PnR facilities using a different approach.... Regression Equations #1-01 Revised Paper
T = Daily Vehicle Trip Ends (Regional Bus) 1 1 1 1 1 1 1 1 1 A regression equation provides an estimate of the best fit equation for the data points. Regression equations are developed for regional bus and light rail PnR facilities and for daily, A.M. and P.M. peak hours. Scatterplots are developed with trip ends on the y-axis and the number of occupied spaces on x-axis. A linear best fit curve is used to develop the regression equation. Unlike the weighted average trip rate, the regression equation is not forced to pass through the origin. The following figures illustrate the regression equations that have been developed. The coefficient of determination (R ) represents the percentage of the variation in trips generated that is explained by the variance of the independent variable size. The R value is a statistical measure of the how well the regression equation approximates the real data points. In other words, a higher R value indicates a better fit between the data points and the regression equation. As seen in the following figures, the R values are around 0.0 which indicates a good fit between the data points and the regression equation. Some efforts were made to fit the data with some non-linear regression models; however, none of those results revealed a better fit than the linear regression model. Therefore, the linear regression was adopted and is consistent with methods addressed in the ITE Trip Generation Manual. Trip generation for facilities with regional bus service 000 000 000 T =.x -.1 R² = 0. 000 000 000 00 0 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces 1 0 1 Actual Data Points Average Rate Fitted Curve FIGURE (a) Park-and-Ride with regional bus service (daily). #1-01 Revised Paper
T= P.M. Peak Hour Vehicle Trip Ends (Regional Bus) T= A.M. Peak Hour Vehicle Trip Ends (Regional Bus) 1 0 00 00 00 T = 0.1x -.1 R² = 0.1 00 00 0 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces 1 FIGURE (b) Park-and-Ride with regional bus service (A.M. peak). 0 Actual Data Points Average Rate Fitted Curve 00 00 T = 0.1x -.0 R² = 0. 00 00 00 0 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces Actual Data Points Average Rate Fitted Curve FIGURE (c) Park-and-Ride with regional bus service (P.M. peak). #1-01 Revised Paper
T= A.M. Peak Hour Vehicle Trip Ends (Light Rail) T = Daily Vehicle Trip Ends (Light Rail) 1 Trip generation for facilities with light rail service 000 1 000 000 T =.1x + 1. R² = 0. 000 000 000 00 0 00 00 00 00 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces Actual Data Points Average Rate Fitted Curve FIGURE (a) Park-and-Ride with light rail service (daily). T = 0.x +. R² = 0.0 00 00 00 0 0 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces Actual Data Points Average Rate Fitted Curve FIGURE (b) Park-and-Ride with light rail service (A.M. peak). #1-01 Revised Paper
1 T= P.M. Peak Hour Vehicle Trip Ends (Light Rail) 00 00 00 00 00 00 00 0 0 T = 0.x + 1. R² = 0.01 0 00 00 00 00 1,000 1,00 1,00 1,00 1,00,000 X= Number of Occupied Spaces 1 1 1 1 1 1 1 1 1 0 1 Actual Data Points Average Rate Fitted Curve FIGURE (c) Park-and-Ride with light rail service (P.M. peak).... Trip Generation Application Principles In the previous sections, weighted average rates and regression equations were provided to be used for trip generation estimation at facilities with regional bus and light rail service. The principles for choosing the appropriate method (between weighted average rate and regression equation) to predict the trips are same as the procedures recommended in the ITE Trip Generation Manual. Three major criteria used to select the best estimate methods in the study are: 1) data points 0, ) R values 0., and ) standard deviation (of weighted average rate) 1%. Based on the three criteria, the best method to estimate trip generation by different land uses is recommended. The recommended methods are as follows, 1) Facilities with regional bus service: The study consisted of 1 PnR facilities which is less than the recommended minimum threshold (e.g., 0 data points) for using the regression equation. Following the number of data points, the R 0. and standard deviation 1% are used as major following determination criteria. For all three time periods, the minimum R is 0.0 and all standard deviation values are less than 1% of weighted average rates. Therefore, either the regression equations or the weighted average rates can be used to predict the trip generation. However, ITE recommends choosing a method that best fits the data points at the size of independent variable in question (). ) Facilities with light rail service: There are PnR facilities with light rail service in the study which is more than minimum threshold for adopting the regression equations to predict the trip generation of a facility. Also, the R values are all greater than 0., and all standard deviation values are less than the 1% of weighted average rates. Therefore, #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 1 0 1 1 according to the ITE manual, the regression equations are recommended for trip predictions at facilities with light rail service. In the next section, the comparisons of trip generation are made between this study and the data prepared in the ITE Trip Generation Manual.. ITE TRIP GENERATION COMPARISONS The data from this study was then compared to data from the ITE Trip Generation Manual, th Edition (). Table below compares four ITE trip generation characteristics such as the number of data points, trip rates, standard deviation, and R values side by side between the two datasets. The bus data were compared with ITE Land Use 00 PnR Lot with Bus Service and the light rail data were compared with ITE Land Use 0 Light Rail Transit Station with Parking from the ITE Trip Generation Manual. Data is shown for average trip generation per occupied space for two ITE land use codes. Overall, weighted average trip rates and standard deviation values were generally much lower in this study compared to the information in the ITE manual, shown in Table. The only exception was the daily trip rate for the facilities with light rail service which had same trip rate in both data sets. Three reasons were found for potentially contributing to the differences in those statistics. First, ITE provided the daily trip generation rates based on the data collected from three studies with bus service and two studies with light rail service. Conversely, in this study, data were collected from 1 PnR facilities with regional bus service and facilities with light rail service. Based on the ITE s own recommendations, the trip generation rates for the two land uses provided in the manual needed to be used carefully because of the insufficient number of data points. As a result, the information (e.g., weighted average rate and regression equation) in the ITE manual is insufficient and cannot be generally applied to the two land uses. Also, it can be seen from the table that the study presented here contained considerably higher sample sizes compared to the ITE data for all three different time periods. In addition to the sample size, the data presented in the ITE manual are outdated. The trip data for the facilities with bus service was dated between 10s and the 000s, and the data from the light rail facilities was collected during 1-1. The third reason is the sample variation. The PnR facilities included in this study are of varying sizes ( 1,) and varying occupancy characteristics (% - 0%) while the data in ITE manual had low number of data points analyzed by occupied parking spaces. By comparing the two datasets, one can find that the data and trip generation estimated in this study provided more practical and up-to-date information to users attempting to estimate the trip generation at these two land uses. The sample size and variation in this study can be used as a good representation to calculate the trip generation locally, or for being applied to the cities with the similar transit systems, service characteristics, and PnR design standards. The standard deviation values along with R values provided some degree of assurance for the use of trip rates from this study. The above statements are valid for the all the compared time periods daily, A.M. peak hour, and P.M. peak hour. #1-01 Revised Paper
TABLE Trip Generation Comparisons ITE and RTD (Local) Data Daily Trip Generation Rate per Occupied Spaces Comparisons PnR Data Point Weighted Average S.D. R ITE RTD ITE RTD ITE RTD ITE RTD Bus 1..0.1 0. n/a 0. Light Rail.1.1 n/a 1. n/a 0. 1 A.M. Peak Hour Trip Generation Rate per Occupied Spaces Comparisons PnR Data Point Weighted Average S.D. R ITE RTD ITE RTD ITE RTD ITE RTD Bus 1 1. 0.0 1.1 0.1 n/a 0.1 Light Rail 1 1.1 0.1 n/a 0.1 n/a 0. 1 1 1 1 1 1 1 1 0 1 P.M. Peak Hour Trip Generation Rate per Occupied Spaces Comparisons PnR Data Point Weighted Average S.D. R ITE RTD ITE RTD ITE RTD ITE RTD Bus 1 0.1 0. 0.1 0.1 1 0.0 Light Rail 1 1. 0. n/a 0. n/a 0.. CONCLUSIONS This study was designed to produce RTD PnR trip generation rates to be used for planning and analysis of these facilities. This effort has the added benefit of providing data to other transit agencies and supplementing the limited PnR data in the ITE manual. However, some other variables such as transit service levels, transit connections to destinations, and the geographic locations of the PnRs should be closely examined before directly adopting the trip generation rates provided in this study. General characteristics of the studied PnRs are included in the previous sections. ITE trip generation data represented an average of nationally collected trip data. Denver region (local) trip rates may vary from these nationally averaged rates because of the factors such as facility locations, user behavior, and availability of transportation system (i.e., freeway, major arterial, local streets, etc.) and the presence of any other major trip generators. Any user attempting to adopt the trip rates presented in this study should also be aware of the following limitations that went into this study. The limitations are as follows, a) Non-transit related parking: A few of PnR facilities in the study are adjacent to retail establishments which may increase the probability of non-transit related trips being recorded. The majority of non-transit related trips were removed during QA/QC procedures. However, some trips may still be included. b) Parking on the street when the facility is full: There are a few PnR facilities in the study that are at capacity which leads spillover vehicles to be parked on nearby side streets. #1-01 Revised Paper
1 1 1 1 1 1 1 1 0 1 0 This study did not account for those trips because they were not observed in the data collection cameras at entry and exit points of the PnR facilities. The trip generation rates for transit PnR facilities in the ITE Trip Generation Manual are insufficient and outdated. Despite its importance, such data collection and analysis is not often a top priority for the transit agencies across the country. This study can be of great value and assistance to other similar transit agencies in their planning efforts even with the minor limitations mentioned above. REFERENCES 1. Turnbull, K. F., R. H. Pratt, J. E. Evans, and H. S. Levinson. Park and Ride/Pool: Traveler Response to Transportation System Changes. TCRP Report, Chapter., 00.. KOK, E. A., J. Morrall, and Z. Toth. Trip Generation Rates for Light Rail Transit Park- And-Ride Lots., 1.. Institute of Transportation Engineers. Trip Generation Manual. th Edition. Washington, D.C.: 01.. Southern New Hampshire Planning Commission, Trip Generation Study, 0. http://www.snhpc.org/pdf/trip%0generation%0report.pdf. Access May 1, 01.. Texas Department of Transportation, Texas Trip Generation Manual. 1 st Edition, 01. http://www.snhpc.org/pdf/trip%0generation%0report.pdf. Access May, 01. #1-01 Revised Paper