RVTD On-Board Passenger Study

Transcription

1 2014 RVTD Planning Department 12/31/2014

2 EXECUTIVE SUMMARY In the fall of 2014, RVTD conducted an on-board passenger survey. The survey was created by RVTD planners using methods from previous on-board studies as a design reference. The self-administered surveys were distributed across all routes and time periods within RVTD s schedule. The survey was administered on November 17 th through November 22 nd. RVTD well exceeded its goal of 931 by collecting a total of 1801 survey responses over the 1-week period. This document will describe the objectives, methodology, procedures, and findings of the 2014 on-board passenger survey project. PROJECT OVERVIEW The project tasks were divided up and assigned to employees within the RVTD support services department. Presurvey tasks included survey instrument design, sampling methodology development, survey instruction development, and assignment of survey administration to RVTD employees. Rider alerts, survey instruments, clipboards, writing utensils, and collection boxes were placed in all of RVTD s fixed route vehicles. Approximately ten (10) RVTD employees volunteered to help administer the survey, which involved distributing and collecting survey forms, explaining the survey objectives, and assisting with completing the survey forms. Post-survey tasks included transferring data from the paper forms into an electronic database, creating a database structure for easy querying, and importing the data into ESRI s mapping environment for spatial analysis. KEY FINDINGS The primary objectives of the 2014 passenger survey were to examine rider demographics and examine rider travel behavior characteristics. The results of the survey are utilized in route planning and modeling, which can have lasting impacts on both the funding and operational characteristics of the transit system. The secondary objective was to make evaluations the expanded service hours, which will inform decisions on short-term service cuts in the spring of Some important findings from the analysis of the riders are summarized below: 33% of passenger indicated work as their trip origin, 26% indicated work as their destination Percent passengers who bicycled to the bus stop increased by 75% since Percent passengers who would not make the trip if bus service weren t available is up 18% since 2011 Percent passengers using the bus 5 days or more is up 66% since 2011 Percent passengers holding a valid driver s license fell by 21% since % of passengers are employed, either full or part time, which is up 6% since 2011 Percent passengers enrolled in school fell by 32% since 2011 Percent passengers who don t own vehicles rose by 21% since % of passengers claim a household income of $10,000 or less Percent passengers with a household income of $50,000 or more fell by 33% since % of Early AM passengers use the bus 6 days a week (significantly higher than other time periods) 85% of the Early AM passengers are employed (significantly higher than other time periods) 16% of Saturday passengers are using the bus for work, 15% for shopping Splitting the route 10 in Talent would affect 17% of outbound passengers (786 people per day) Splitting the route 10 in Talent would affect 64% of inbound passengers (1352 people per day) 2

3 TABLE OF CONTENTS CONTENTS Executive summary... 2 Project Overview... 2 Key Findings... 2 Table of Contents... 3 List of Figures... 4 Survey Methods... 7 Sampling Plan... 7 Stratified Random Sampling... 7 survey assignments... 8 Survey Instrument... 9 Survey Procedures Data Processing Geocoding Quality control data weighting and expansion Weight Factor Expansion factor Survey Results Historical Analysis Route Analysis Weekday Analysis Saturday Analysis Spatial Analysis Transfer Analysis

4 LIST OF FIGURES Table 2.1: RVTD Weekly Ridership by Route 7 Table 2.2: Prescribed Sample Sizes by Stratum.8 Table 2.3: Trip Assignments 8 Table 2.4: Survey Instrument.9 Table 2.5: Collected Survey Counts.10 Table 2.6: Calculated Weight Factors by Route and Time Period..11 Table 2.7: Calculated Weight/Expansion Factor by Route and Time Period..12 Table 3.0: Historical Data 13 Table 3.1: Transfer to Current Bus..14 Table 3.2: Transfer from Current Bus.14 Table 3.3: Origin Place by Route 15 Figure 3.4: Percent Medical Trips: 2011 vs Table 3.5: Origin Mode by Route 16 Figure 3.6: Percent Bike Trips: 2011 vs Table 3.7: Travel Time to Bus Stop by Route.17 Table 3.8: Destination Place by Route 17 Table 3.9: Destination Mode by Route.18 Figure 3.10: Percent Walking to Destination by Route.18 Table 3.11: Travel Time from Bus Stop to Destination by Route.19 Table 3.12: Bus Service Not Available by Route.19 Figure 3.13: Percent Passengers Driving if Bus Service wasn t Available.20 Table 3.14: Trip Frequency by Route.20 Figure 3.15 Percent Passengers using the Bus over 5 Days per Week 21 4

5 Table 3.16: Valid Driver s License by Route..21 Table 3.17: Gender by Route 22 Table 3.18: Age by Route..22 Figure 3.19: Route 2 Age Distribution 2011 vs Table 3.20: Ethnicity by Route.23 Table 3.21 Employment Status by Route.24 Figure 3.22 Percent Students by Route 2011 vs Table 3.23: Household vehicles by Route.25 Figure 3.24: Percent Passengers owning Zero Vehicles 2011 vs Table 3.25: Household Size by Route..26 Table 3.26 Household Employment by Route..26 Figure 3.27: Percentage of Households with Zero Employed People 2011 vs Table 3.28: Household Income by Route.27 Figure 3.29: Percent Passengers with Household Income of $50K and higher 2011 vs Table 3.30: Time of Day Distribution (Weekday)..29 Figure 3.31: Time of Day Distribution 2011 vs (Weekday)..29 Table 3.32: Transfer Before by Time of Day (Weekday)..30 Table 3.33: Transfer After by Time of Day (Weekday).30 Table 3.34: Origin Place by Time of Day (Weekday)..31 Table 3.35: Access Mode by Time of Day (Weekday) 31 Table 3.36: Destination Place by Time of Day (Weekday)..32 Table 3.37: Egress Mode by Time of Day (Weekday).32 Table 3.38: Trip Frequency by Time of Day (Weekday).33 Table 3.39: Gender by Time of Day (Weekday)..33 Table 3.40: Age by Time of Day (Weekday)..34 5

6 Table 3.41: Ethnicity by Time of Day (Weekday)..34 Table 3.42: Employment Status by Time of Day (Weekday).35 Table 3.43: Household Vehicles by Time of Day (Weekday) 35 Table 3.44: Household Income by Time of Day (Weekday) 36 Table 3.45: Distribution of Origin Purpose by Destination Purpose (Weekday).36 Table 3.46: Distribution of Access by Egress Modes (Weekday) 37 Figure 3.47: Distribution of Ridership by Route: Weekday vs. Saturday..37 Figure 3.48: Trip Purpose by Route: Weekday vs. Saturday..38 Figure 3.49: Employment Status: Weekday vs. Saturday 38 Figure 3.50: Ethnic Distribution: Weekday vs. Saturday.39 Figure 3.51: Trip Frequency: Weekday vs. Saturday.39 Figure 3.52: Bus Service not Available: Weekday vs. Saturday.40 Figure 3.53: Trip Destination distribution by Zone; Origin: Central Medford (All Routes).41 Figure 3.54: Trip Destination Distribution by Zone; Origin: Route 10, North of Talent Figure 3.55: Trip Destination Distribution by Zone; Origin: Route 10, South of Talent.. 43 Figure 3.56: Trip Destination Distribution by Zone; Origin: Route 10, Talent...44 Figure 3.57: Trip Destination Distribution by Zone; Origin: Route 60, Central Medford..45 Figure 3.58: Trip Destination Distribution by Zone; Origin: Route 60, White City.46 Figure 3.59: Trip Destination Distribution by Zone; Transfer from Route Figure 3.60: Trip Destination Distribution by Zone; Transfer from Route 2 48 Figure 3.61: Trip Destination Distribution by Zone; Transfer from Route Figure 3.62: Trip Destination Distribution by Zone; Transfer from Route Figure 3.63: Trip Destination Distribution by Zone; Transfer from Route Figure 3.64: Trip Destination Distribution by Zone; Transfer from Route Figure 3.65: Trip Destination Distribution by Zone; Transfer from Route

7 SURVEY METHODS SAMPLING PLAN RVTD has 7 unique routes serving approximately 30,000 per week. Ridership is distributed unevenly across the routes, with approximately half of the ridership occurring on the route 10 alone. Ridership is also highly influenced by time of day, with a disproportionate number of riders in the 1pm to 5pm peak period. It was necessary to develop a sampling plan that captured the correct number of responses proportionate to the irregular ridership patterns. The following table shows the RVTD routes with their respective weekly ridership numbers, broken out by the three time periods: Weekday, Evening, and Saturday. Table 2.1: RVTD Weekly Ridership by Route Route Weekday Evening Saturday Total 1 Airport West Medford Ashland RVMC Jacksonville Central Point White City Total STRATIFIED RANDOM SAMPLING RVTD s first objective in creating a sampling plan was proportionate weighting across all routes and time periods, which meant that pure random sampling wasn t an option. Given the constraints, it was determined that a stratified random sample would be appropriate. This multi-stage approach distributed samples across two strata: 1. Route, 2. Time period. RVTD first calculated the required sample size using a certified online sample calculator. Given the total weekly ridership of 30,575, it was calculated that a sample size of 665 was required to achieve a 99% confidence level with a 5% margin of error. In order to meet RVTD s secondary objective, the expanded service evaluations, the sampling plan included a 20% oversampling of the evening and weekend service. This added 266 trips for a grand total of 931 survey responses required. A stratification factor was developed using the proportion of ridership attributable to each stratum (route/time period). Special stratification factors were developed for the weekday and evening oversampling periods. The stratification factor was applied to the weekly ridership numbers resulting in the final stratified sample size requirements for the study. The resulting dataset would be used in generating trip assignments in which RVTD employees would distribute survey forms. 7

8 The following table shows the stratified sample size for each route and time period (including the 20% oversample during evenings and weekends. Table 2.2: Prescribed Sample Sizes by Stratum Route Weekday Evening Saturday Total 1 Airport West Medford Ashland RVMC Jacksonville Central Point White City Total SURVEY ASSIGNMENTS The sampling plan included a survey assignment method which paired RVTD employees with specific trips during the weeklong survey period. A trip quota was developed by dividing the sample size requirements for each stratum by the estimated average response number per trip assignment. The following table shows the stratified trip quota for the week. Table 2.3: Trip Assignments Route Weekday Evening Saturday Total 1 Airport West Medford Ashland RVMC Jacksonville Central Point White City Total Using a random number generating formula in excel, random trips were generated for each stratum and posted to a Google document where RVTD employees could sign up as their schedules would allow. Early in the sampling period, it became apparent that we underestimated the number of responses that could be collected during a trip, thus allowing a significant number of the trips later in the week to be eliminated. Trips were eliminated randomly within their respective stratum; while some trips were kept on to maintain a balanced sample. 8

9 SURVEY INSTRUMENT RVTD has completed an on-board passenger survey every three years in its recent history. The last two surveys have been contracted out to qualified research firms, who developed custom survey instruments to meet study objectives. Since the global objectives for the study haven t changed significantly since 2011, RVTD determined that many elements in the previous survey instrument could be carried forward to the 2014 study. Minor modifications were made to the instrument, and the final draft was reviewed and approved by ODOT modeling specialists. The questionnaire was designed to obtain information in three major categories: O/D travel patterns, access and egress modes, and rider demographics. The following table shows the data elements collected on the survey instrument. Table 2.4: Survey Instrument Data Element id sd route time tfrom tto place1 mode1 travel1 stop1 city1 city2 place2 stop2 mode2 travel2 freq altmode alttime dl vehic hhsize hhemp gen age eth empstatus jobcount hhincome altserve Data Description RespondentID ServiceDay Route you are currently riding: Approximate time right now: Did you transfer to this bus? If yes, from which route? Will you transfer after this bus? If yes, to which route? What kind of place are you coming from? How did you get to the first bus stop on your trip? How long did it take you to get to the bus stop? What bus stop did you board this bus at? Bus Stop ID No. In what city did you board this bus? What City is your final destination in? What kind of place are you going to? Where do you plan to get off this bus? How will you get to your destination from the last bus stop on your trip? How long will it take to get to your destination from the bus stop? How many days a week do you use transit? If bus service were not available, how would you make this trip? Are you able to make this trip at a different time of day? Do you have a valid driver's license? How many working vehicles are available to your household? Including yourself how many people live in your household? Including yourself how many people in your household are employed? What is your gender? What is your age? What is your ethnicity? Are you...(fill in all that apply) If employed list number of jobs you hold. (Choose 0 if not employed) What was your total household income in 2013 before taxes? Would you use a route with limited service between 5-7am and 6-8pm 9

10 SURVEY PROCEDURES All RVTD fixed route vehicle were outfitted with a survey collection box, writing utensils, clipboards, and blank survey forms. Pre-stocking each vehicle ensured that surveyors would be completely prepared to survey passengers, regardless of their random trip assignment. For the purposes of preserving admin staff time, bus operators were occasionally asked to administer the survey on the lower ridership trips. A schedule was posted online with a brief instructional memo on how to administer the survey. In past surveys, a significant effort went into recruitment and training of survey staff. One benefit of using RVTD employees was that it required very little training. All employees are inherently familiar with RVTD s transit system and clientele, which was an advantage over using hired staffing services. At the end of each day, survey collection boxes were emptied and sorted into route and time period stacks. Responses were tracked for each survey stratum and adjustments were made accordingly to the remaining survey quota. By the end of the week, RVTD had far exceeded the required sample size, while maintaining the prescribed stratification balance. The following table shows the final response counts for each route and time periods. Table 2.5: Collected Survey Counts Route Weekday Evening Saturday Total Prescribed Balance Actual Balance % 3.29% % 7.02% % 47.33% % 8.01% % 1.30% % 12.48% % 20.56% Total DATA PROCESSING All data entry was performed manually by RVTD employees, which took approximately two weeks to complete. Workers were instructed to take pre-sorted stacks of paper survey forms and follow a web link to the online data entry interface. The Survey Monkey system allowed multiple users to concurrently enter data, while aggregating all information into a master database. GEOCODING Previous surveys relied on complex methods of decoding the O/D data. These methods involved data cleaning, joining, and matching using ESRI software. Due to the limitations of the software and survey designs, a significant amount of manual data interpretation was also required, mostly to be performed by RVTD employees. For the 2014 study, RVTD tried a different approach. Instead of trying to match O/D data on the survey form to xy coordinates, we instead matched to a 6-digit stop ID value. Workers were instructed to interpret O/D data on the 10

11 paper survey form and then, using Google maps, identify the corresponding stop ID value and enter the 6-digit code into the electronic form. Using this method eliminated any need for post-processing the O/D data because a 1 to 1 relationship now existed between the O/D survey data and RVTD s existing stops database. QUALITY CONTROL Workers were instructed to inspect the form for obvious errors and conflicting data before entering the data electronically. A simple sanity check was developed for identifying faulty survey information. Workers first checked the response to Question #1: what route are you on?. Next, the workers checked the response to Question #7: What stop did you board this bus at?. If the bus stop in Q7 didn t match the route indicated in Q1, then workers were instructed to make an attempt at deciphering the survey response, and failing that, reject the response from the survey. DATA WEIGHTING AND EXPANSION Analytic weights are necessary to needed to develop estimates of population parameters. In RVTD s case, the oversampling of evening and Saturday trips further necessitated the use of analytic weights. Without the use of weights, data is subject to known and unknown biases. WEIGHT FACTOR Data collection on public transit presents unique challenges to data collection. Sampling cannot occur on all routes simultaneously, and a surveyor is limited to population about his particular trip. From a cost efficiency standpoint, a surveyor must collect as many surveys as possible, which sometimes results in a disparity in sample distribution. To correct the disparity, weights were calculated using observed ridership figures for each population (route/time). Weight factors for each population were calculated using the following: Table 2.6: Calculated Weight Factors by Route and Time Period Route Weekday Evening Saturday

12 EXPANSION FACTOR Given finite resources for data collection, RVTD was not able to collect responses for every trip taken during the sampling period. Sample expansion expands the weighted sample to reflect the population ridership at the system-wide level. Table 2.7: Calculated Weight/Expansion Factor by Route and Time Period Route Weekday Evening Saturday

13 SURVEY RESULTS Weight and expansion factors were added to the master data table and imported into an online statistical analysis tool (Statwing). The following analysis was performed within the Statwing tool, where the weight and expansion factors were applied to the analysis. The results are divided into five sections: Historical Analysis, Route Analysis, Weekday Analysis, Saturday Analysis, and Spatial Analysis HISTORICAL ANALYSIS For the purpose of identifying historical trends, key data points were gathered from the past 4 passenger surveys. Growth is apparent in the percentage passengers between 19 and 64. Passengers whose trips to the bus stop take 5 minutes or less appears to be shrinking. Table 3.0: Historical Data Age between 19 and 64 74% 77% 87% 90% No Driver's license 69% 63% 66% 68% Walked to bus stop 73% 72% 88% 88% 5 minutes or less to bus stop 69% 57% 49% 36% Annual household Income less than $15K 50% 36% 58% 66% Using the bus for work 24% 29% 18% 20% Using the bus at least 5 days per week 54% 50% 42% 1 69% Wouldn t make the trip if bus service weren't available 26% 34% 31% 38% 1 Question was phrased at least 5 trips per week during this survey. 13

14 ROUTE ANALYSIS Many of the tables within the route and weekday sections are tables that were included in the 2011 passenger survey, and have been updated for Statistically significant changes from 2011 are noted when applicable. The majority of riders did not transfer to their current bus (66%), but transfers were even less common on longer routes (10, 60, 40). Of the riders who did transfer, the majority transferred from the routes 10 and 60. Riders on the routes 24 and 30 were more likely to have transferred from the route 2 2. Table 3.1: Transfer to Current Bus Did Not Transfer 1 59% 5% 5% 13% 2% 2% 3% 10% 2 49% 2% 9% 7% 4% 2% 8% 18% 10 76% 2% 3% 7% 2% 1% 3% 6% 24 53% 1% 11% 12% 11% 0% 5% 6% 30 29% 0% 16% 34% 0% 11% 0% 11% 40 57% 2% 5% 17% 1% 2% 7% 10% 60 61% 4% 6% 15% 0% 1% 3% 10% Total 66% 2% 5% 11% 2% 1% 4% 9% 25% of passengers surveyed intended on transferring to another bus. Passengers on the Route 24 were most likely to transfer, usually to the routes 2, 10, and 60. Passengers on the route 2 were significantly more likely to transfer to the route 60 than any other route. Passengers on the route 30 were most likely to transfer to the route 10. A somewhat less visible trend was transfers from the route 60 to and from the route 40. Overall Transfer rates to and from buses increased slightly from Table 3.2: Transfer from Current Bus Did Not Transfer 1 71% 0% 8% 10% 1% 0% 8% 2% 2 66% 0% 6% 7% 4% 0% 2% 14% 10 83% 1% 4% 3% 2% 0% 3% 4% 24 49% 5% 11% 10% 5% 2% 7% 10% 30 62% 1% 5% 21% 0% 5% 0% 5% 40 69% 2% 4% 12% 1% 2% 4% 6% 60 74% 1% 6% 7% 1% 1% 8% 3% Total 75% 1% 5% 7% 2% 1% 4% 5% 2 When adjusted for ridership. 14

15 Over half of the passengers (59%) surveyed said they were coming from home. Of the passengers not coming from home, 33% indicated work as their trip origin, down 23% from the 2011 survey. Of the passengers not coming from home, 17% were coming from school, which is nearly the exact percentage from Route 30 passengers were significantly more likely to state shopping as their origin, which university trips also higher than expected. Table 3.3: Origin Place by Route Home Work or workrelated Other University, School Shoppi ng Medical Services Recreational, Social Social Services 1 60% 12% 11% 5% 9% 2% 1% 0% 2 64% 12% 8% 3% 3% 5% 2% 3% 10 58% 14% 7% 9% 7% 2% 4% 1% 24 60% 11% 1% 5% 5% 16% 2% 0% 30 49% 13% 0% 16% 21% 0% 0% 1% 40 69% 10% 12% 3% 3% 2% 1% 1% 60 57% 15% 10% 5% 2% 6% 2% 1% Total 59% 13% 8% 7% 5% 4% 3% 1% On the route 24, 16% indicated medical services as their origin; a 300% increase over the 2011 survey. Route 60 saw a nearly proportional decrease in the number of passengers stating medical services as their origin. Figure 3.4: Percent Medical Trips: 2011 vs % 16% 14% 12% 10% 8% 6% % 2% 0% Total 15

16 88% of passengers walked to the bus from their origin location. The route 2 was the most commonly walked at 96%. Routes 30, 60, and 24 were the most commonly biked routes. Interestingly, route 24 carries nearly the same number of biking passengers per day as the route 40, which experiences nearly 3 times the ridership. Table 3.5: Origin Mode by Route Walk/Wheelchair Skateboard By Car Bicycled 1 92% 0% 4% 5% 2 96% 0% 0% 4% 10 87% 1% 5% 7% 24 89% 1% 2% 8% 30 84% 0% 5% 11% 40 93% 2% 2% 3% 60 84% 1% 5% 10% Total 88% 1% 4% 7% A significant biking increase, across all routes, has occurred since System-wide, passengers who bicycled to the bus stop has increased by 75%. The biggest increases occurred on the routes 30, 1, and 24. Figure 3.6: Percent Bike Trips: 2011 vs % 10% 8% 6% 4% % 0% Total 16

17 36% of passengers travel less than 5 minutes from their origin to the bus stop. Routes 10 and 30 passengers tend to have the shortest travel times. Travel time isn t significantly influenced by travel mode, except that passengers traveling by car have slightly longer travel times. Less than 5 minutes Table 3.7: Travel Time to Bus Stop by Route 5-9 minutes minutes minutes minutes more than 30 minutes 1 29% 20% 33% 6% 5% 8% 2 22% 27% 34% 8% 8% 1% 10 43% 20% 22% 7% 6% 3% 24 32% 20% 21% 15% 12% 0% 30 41% 11% 42% 0% 0% 6% 40 28% 23% 29% 8% 9% 3% 60 30% 23% 27% 13% 4% 3% Total 36% 21% 25% 9% 6% 3% Most passengers were traveling home (33%), and 26 percent were going to work (up 6% from 2011). Riders on the routes 1, 10, 40, and 60 were most likely to be traveling to work. 10% of passengers were traveling to school, with the highest percentage occurring on the route 40 (15%). Passengers on the route 40 are three times more likely than any other route to indicate social services as their destination. Passengers on the routes 2 and 30 were more likely than other routes to have shopping as their destination (15-16%). The only case where a destination response exceeded home was medical services on the route 24 (39%). Table 3.8: Destination Place by Route Work or workrelated Recreational, Social University Medical Social Home School Shopping Other Services Services 1 28% 26% 8% 9% 19% 7% 1% 2% 2 36% 15% 7% 15% 9% 11% 4% 2% 10 34% 27% 12% 10% 7% 4% 3% 2% 24 32% 11% 6% 4% 6% 39% 2% 0% 30 47% 16% 11% 16% 11% 0% 0% 0% 40 25% 30% 15% 10% 7% 4% 3% 7% 60 35% 31% 6% 7% 10% 8% 2% 1% Total 33% 26% 10% 10% 8% 7% 3% 2% 17

18 89% of passengers walk from the bus stop to their destination, which is down over 4% from The percentage of passengers biking to their destination grew by 50% since Tables 3.5 and 3.9 suggest a general shift from walking to biking across all routes since Table 3.9: Destination Mode by Route Walk/Wheelchair Skateboard By Car Bicycled 1 94% 5% 1% 0% 2 96% 3% 0% 1% 10 89% 7% 3% 1% 24 88% 11% 0% 1% 30 89% 11% 0% 0% 40 90% 4% 4% 1% 60 84% 11% 3% 1% Total 89% 1% 3% 8% Figure 3.10: Percent Walking to Destination by Route 105% 100% 95% 90% 85% % 75% Total 18

19 36% of passengers travel less than 5 minutes from the bus stop to their final destination. Passengers on route 10 tend to have the shortest travel times, while passengers on the 1, 24, and 60 tend to have the longest. Over 27% of passengers on the route 24 have egress trips longer than 15 minutes. Many of these long trips are made by bicycle, suggesting that passengers are using the route 24 to access destinations many miles away from the route. Passengers traveling on the routes 1 and 30 are more likely to have travel times greater than 30 minutes, and are also the least likely to have used a car to get to or from the bus stop. These routes appear to be serving a greater percentage of passengers with no other travel options, and therefore will walk or bike further than the average passenger will tolerate. Table 3.11: Travel Time from Bus Stop to Destination by Route Less than 5 minutes 5-9 minutes minutes minutes minutes more than 30 minutes 1 29% 20% 33% 6% 5% 8% 2 22% 27% 34% 8% 8% 1% 10 43% 20% 22% 7% 6% 3% 24 32% 20% 21% 15% 12% 0% 30 41% 11% 42% 0% 0% 6% 40 28% 23% 29% 8% 9% 3% 60 30% 23% 27% 13% 4% 3% Total 36% 21% 25% 9% 6% 3% 38% percent of passengers said that they would not make the trip that they were on if bus service was not available (up 18% from 2011). Passengers on the route 10 were most likely to say they wouldn t make the trip (43%). In both the 2011 and 2014 surveys, passengers on the route 1 were the most likely to take a taxi, suggesting that passengers traveling to and from the airport have transportation options outside of RVTD. Passengers on the route 30 are most likely to drive at 16%. Walk/ Wheelchair Table 3.12: Bus Service Not Available by Route Drive Ride with someone else Taxi Bicycle/ Skateboard Would not make this trip 1 42% 3% 5% 13% 5% 31% 2 35% 1% 14% 7% 3% 39% 10 20% 9% 14% 2% 12% 43% 24 41% 3% 6% 7% 18% 25% 30 32% 16% 18% 11% 5% 19% 40 29% 5% 18% 8% 8% 32% 60 23% 6% 15% 3% 15% 38% Total 25% 7% 14% 4% 11% 38% 19

20 On almost all routes, passengers were less likely than in 2011 to drive, ride with someone else, taxi, or bicycle. For many passengers, travel options involving a car seem to be diminishing. Figure 3.13: Percent Passengers Driving if Bus Service wasn t Available 30% 25% 20% 15% 10% % 0% Total 46% of passengers use the bus 6 days a week. Passengers on the route 10 are most likely to use the bus more than 5 days per week, but are also more likely to use the bus just once per week. 1 day a week Table 3.14: Trip Frequency by Route 2 days a week 3 days a week 4 days a week 5 days a week 6 days a week 1 8% 1% 4% 18% 30% 40% 2 5% 3% 9% 10% 33% 39% 10 6% 2% 6% 15% 22% 49% 24 2% 1% 13% 17% 24% 42% 30 0% 6% 6% 31% 24% 34% 40 5% 3% 11% 19% 18% 44% 60 3% 2% 11% 11% 26% 47% Total 5% 3% 8% 15% 23% 46% 20

21 70% of passengers use the bus 5 days a week or more, which is up 66% since 2011, suggesting a general shift from less frequent riders to more frequent riders. Figure 3.15 Percent Passengers using the Bus over 5 Days per Week 80% 70% 60% 50% 40% 30% % 10% 0% Total 67% of RVTD passengers don t have valid driver s licenses. Routes 2 and 24 have the highest proportion of riders with no license at 80% and 77% respectively. Passengers on the route 30 are the most likely to have a license. The percentage of driver s license holding passengers fell by 21% since 2011, with the biggest decreases occurring on the routes 2, 24, and 40. Table 3.16: Valid Driver s License by Route Route Yes No 1 37% 63% 2 20% 80% 10 39% 61% 24 23% 77% 30 49% 51% 40 27% 73% 60 26% 74% Total 32% 68% 21

22 Male passengers make up 52% of transit users overall. Route 60 has the highest percentage of male passengers at 60%. Route 30 has the highest percentage of female passengers at 71%. Table 3.17: Gender by Route Route Male Female 1 48% 52% 2 51% 49% 10 52% 48% 24 53% 47% 30 29% 71% 40 44% 56% 60 60% 40% Total 32% 68% Age distribution remains relatively even, with the exception of the route 30, which has a higher percentage of passengers over the age of 65 (21%). Route 40 has a somewhat higher percentage of young riders, with over 66% of passengers under the age of 40. Table 3.18: Age by Route Route or over 1 7% 42% 43% 7% 2 3% 35% 55% 7% 10 7% 44% 41% 8% 24 6% 49% 35% 9% 30 0% 37% 42% 21% 40 11% 55% 31% 4% 60 6% 49% 41% 4% Total 40% 7% 46% 7% 22

23 Since 2011, the only statistically significant change occurred on the route 2, where fewer very (and very old) people are now using the route. The data shows a general shift to the middle range ages. Figure 3.19: Route 2 Age Distribution 2011 vs % 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% or over % of transit users are white, which dipped nearly 4% since Hispanics made up the next highest group at 8% 3. Routes 1 and 30 have virtually no black passengers, while the route 30 has the highest percentage minority composition of any route with nearly 17% Hispanic passengers. 71% of the Asian passengers are found on the route 10, and are nearly absent on all other routes (except the route 40). Generally, routes 40 and 60 are the most diverse routes in the system, while routes 1 and 24 are the least. Route Asian Table 3.20: Ethnicity by Route Black/ African American Hispanic Native American White Other 1 0% 0% 12% 1% 87% 0% 2 0% 1% 10% 5% 76% 8% 10 3% 3% 7% 4% 78% 6% 24 0% 5% 2% 3% 87% 3% 30 0% 0% 17% 0% 72% 11% 40 3% 4% 6% 8% 77% 3% 60 0% 5% 11% 5% 75% 4% Total 2% 3% 8% 5% 78% 5% 3 Due to a known non-response tendency in Spanish speaking passengers, this figure is almost certainly underestimated 23

24 56% of passengers are employed, either full or part time, which is up 6% since Conversely, the percent of unemployed passengers fell to 15% (a 32% decrease from 2011). Routes 60 and 10 have the highest percentage of employed passengers, while the routes 24, 40, and 2 have the highest unemployed. Route Full-time worker Table 3.21 Employment Status by Route Part-time worker Homemaker Unemployed University/ other student Retired 1 27% 23% 5% 18% 9% 18% 2 20% 25% 6% 21% 12% 17% 10 31% 28% 3% 11% 16% 11% 24 17% 24% 8% 30% 5% 17% 30 16% 46% 0% 5% 11% 22% 40 25% 26% 3% 22% 14% 10% 60 41% 17% 2% 16% 10% 15% Total 31% 25% 3% 15% 13% 13% The most significant change since 2011 was the 32% decrease in percent students system-wide. The decrease occurred on all routes, but most dramatically on the route 24 which dropped 89% from 2011 levels. Figure 3.22 Percent Students by Route 2011 vs % 45% 40% 35% 30% 25% 20% % 10% 5% 0% Total 24

25 Well over half of transit users do not have vehicles in their households. Passengers on the routes 2,1, and 30 are the least likely to own vehicles. Passengers on the routes 10 and 60 are the most likely to own vehicles. Table 3.23: Household vehicles by Route Route None or more 1 77% 21% 1% 1% 2 78% 15% 4% 2% 10 58% 28% 11% 3% 24 67% 20% 12% 1% 30 76% 19% 0% 5% 40 62% 21% 15% 2% 60 59% 23% 7% 11% Total 62% 24% 10% 5% Percent total passengers owning zero vehicles rose 23% since 2011, with the biggest increases occurring on the routes 24 and 30. Figure 3.24: Percent Passengers owning Zero Vehicles 2011 vs % 80% 70% 60% 50% 40% 30% % 10% 0% total 25

26 42% of passengers have 3 or more people living in their household, which fell 21% since Route 60 and 2 tend to have the largest households, while route 30 has the smallest. Table 3.25: Household Size by Route Route None or more 1 1% 41% 11% 47% 2 7% 27% 16% 49% 10 3% 30% 29% 38% 24 4% 24% 28% 44% 30 2% 38% 26% 33% 40 8% 25% 28% 39% 60 3% 26% 21% 50% Total 4% 28% 25% 42% 75% of passengers have households with at least one working person, which rose 4% since Routes 10 and 60 are the most likely to have passengers with employed people living in their household, while routes 2 and 24 are the least. Table 3.26 Household Employment by Route Route None or more 1 32% 46% 16% 6% 2 36% 36% 19% 10% 10 20% 42% 27% 11% 24 39% 29% 22% 10% 30 28% 24% 43% 5% 40 27% 42% 22% 10% 60 25% 39% 22% 15% Total 24% 40% 24% 11% 26

27 The most significant decreases in household employment occurred on the routes 2, 24, which saw roughly 30% decline in the percentage of passengers with an employed person in their household. Route 30 reversed that trend with a similar increase. Figure 3.27: Percentage of Households with Zero Employed People 2011 vs % 45% 40% 35% 30% 25% 20% % 10% 5% 0% total Almost half (47%) of transit RVTD s passengers claim a household income of $10,000 or less, which rose about 10% since Passengers on the routes 1,2,24 and 40 tend to have lower household incomes, while passengers on the routes 10 and 60 have the highest. Route Less than $10,000 Table 3.28: Household Income by Route $10,000- $14,999 $15,000- $24,999 $25,000- $49,999 $50,000- $74,999 $75,000 or more 1 55% 22% 8% 12% 3% 0% 2 57% 17% 19% 4% 2% 0% 10 44% 20% 17% 11% 6% 2% 24 57% 15% 16% 6% 4% 1% 30 33% 56% 5% 6% 0% 0% 40 57% 17% 15% 9% 2% 0% 60 43% 20% 19% 13% 2% 3% Total 47% 19% 17% 11% 4% 2% 27

28 The most significant change since 2011 was the decrease in percentage of higher income passengers. Passengers with household incomes of $50K or more decreased by a third, with the biggest decreases occurring on the routes 1, 30, 40, and 60. Figure 3.29: Percent Passengers with Household Income of $50K and higher 2011 vs % 16% 14% 12% 10% 8% 6% % 2% 0% Total 28

29 WEEKDAY ANALYSIS Time periods are divided into 5 segments for the weekday analysis. Early AM (5:00am 6:29am), AM Peak (6:30am 8:30am), Mid-day (8:31am - 1:59pm), PM Peak (2:00pm 5:30pm) and Evening (5:31pm 8:15pm). Trips were surveyed during all 5 segments and appropriately weighted for ridership. Predictably 4, Mid-day has the highest percent ridership. Table 3.30: Time of Day Distribution (Weekday) Time Period Count Percent of Data Early AM % AM Peak % Mid-day % PM Peak % Evening % Since 2011, service was added to the evening hours resulting in an expected shift of ridership to the evening time period. A less pronounced, but statistically significant, shift to the Early AM time period has also occurred since Figure 3.31: Time of Day Distribution 2011 vs (Weekday) 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% Early AM AM Peak Mid-day PM Peak Evening Mid-day is 5.5 hours long, making it considerably longer than the other time periods, and therefore has more ridership. 29

30 25% of transit users made transfers prior to the route they were surveyed on. As expected, passengers transferring from buses are fewest in the Early AM period. Interestingly, transfer rates were slightly higher on the route 10 during this period. Table 3.32: Transfer Before by Time of Day (Weekday) Did not Transfer Early AM 82% 0% 6% 8% 0% 1% 1% 2% AM Peak 79% 1% 3% 6% 2% 0% 4% 4% Mid-day 71% 1% 7% 7% 2% 1% 5% 6% PM Peak 77% 2% 4% 7% 1% 0% 4% 5% Evening 74% 2% 2% 7% 3% 1% 3% 7% Total 75% 1% 5% 7% 2% 1% 4% 9% 24% of transit users intended to make transfers after the route they were surveyed on. Transfer rates are highest in the Early AM and Midday periods, and are drastically reduced in the Evening period. Passengers who did intend to transfer were most likely to do so to the route 10, especially in the Early AM and AM Peak Time Periods. Route 60, which has a level of service equal to the Route 10 in the Early AM period, produces 50% fewer transfers than the route 10. Transfer rates appear to even out among all routes as the day progress, and are almost equal by day s end. Table 3.33: Transfer After by Time of Day (Weekday) Did not Transfer Early AM 60% 5% 6% 17% 2% 1% 1% 8% AM Peak 65% 1% 4% 14% 1% 1% 3% 11% Mid-day 62% 3% 5% 11% 3% 1% 5% 10% PM Peak 68% 3% 5% 9% 1% 2% 3% 9% Evening 80% 1% 6% 5% 0% 0% 4% 4% Total 66% 2% 5% 11% 2% 1% 4% 9% 30

31 Roughly 85% of passengers in the Early AM and AM Peak periods are coming from home, which drops sharply after the Mid-day. By the Evening time period, only a quarter of passengers are coming from home. Passengers coming from work or school are highest in the PM Peak and Evening time periods. Significantly more passengers are traveling from work in the Early AM than AM peak or Mid-day, suggesting that many passengers are using the bus to travel home from night shifts. Recreational and Shopping trips are more much more likely to occur in the Evening time period. Home Table 3.34: Origin Place by Time of Day (Weekday) University /School Shopping Recreational /Social Work or workrelated Medical Services Social Services Other Early AM 85% 2% 0% 0% 10% 1% 0% 2% AM Peak 86% 0% 1% 1% 4% 3% 0% 5% Mid-day 65% 6% 5% 2% 7% 5% 2% 7% PM Peak 38% 11% 6% 2% 27% 4% 1% 9% Evening 25% 13% 10% 7% 27% 1% 2% 15% Total 59% 7% 5% 3% 13% 4% 1% 8% 88% of people walk from their origins to the bus stop during the weekdays. Walking is slightly less common in the Early AM period and most common during the Mid-day period. A higher proportion of passengers who bicycle to the bus stop occur during the Early AM and Evening time periods. A significantly higher proportion of passengers who access the bus stop by car occur during the AM Peak period. Table 3.35: Access Mode by Time of Day (Weekday) Walk/Wheelchair Bicycled By Car Skateboard Early AM 78% 15% 5% 2% AM Peak 85% 5% 10% 1% Mid-day 92% 5% 2% 1% PM Peak 89% 7% 3% 1% Evening 83% 10% 4% 2% Total 88% 7% 4% 1% 31

32 70% of passengers in the evening are traveling home, a figure that dips to 59% in the PM Peak, and then drops sharply in the mid-day or earlier. 68% of passengers in the Early AM are traveling to work, which dips to 46% in the AM peak, and then drops off sharply in the Mid-day. A higher proportion of passengers traveling to University/School occur in the AM Peak time period. Home Table 3.36: Destination Place by Time of Day (Weekday) University /School Shopping Recreational /Social Work or workrelated Medical Services Social Services Other Early AM 13% 6% 1% 1% 68% 7% 0% 4% AM Peak 11% 25% 3% 0% 46% 7% 2% 5% Mid-day 23% 11% 13% 3% 23% 10% 5% 11% PM Peak 59% 4% 7% 2% 17% 4% 0% 7% Evening 70% 4% 7% 4% 6% 1% 0% 7% Total 34% 11% 9% 3% 27% 7% 3% 8% 89% of passengers intend to walk from the bus to their destination. Walking is slightly less common in the Early AM period. Bicycling to the destination is more common in the Early AM and Evening periods Table 3.37: Egress Mode by Time of Day (Weekday) Walk/Wheelchair Bicycled By Car Skateboard Early AM 79% 16% 3% 2% AM Peak 91% 6% 3% 1% Mid-day 92% 6% 1% 1% PM Peak 87% 8% 5% 1% Evening 84% 10% 4% 2% Total 89% 8% 3% 1% 32

33 Transit users in the Early AM and AM Peak periods are more likely to use the bus 6 days a week or more (69% and 60% respectively). Riders who use the bus less than 2 days a week are virtually non-existent in the same time period. Table 3.38: Trip Frequency by Time of Day (Weekday) 1 day a week 2 days a week 3 days a week 4 days a week 5 days a week 6 days a week Early AM 2% 0% 7% 3% 19% 69% AM Peak 1% 0% 4% 10% 25% 60% Mid-day 5% 3% 9% 17% 25% 41% PM Peak 7% 2% 9% 15% 24% 44% Evening 7% 5% 7% 18% 20% 43% Total 5% 2% 8% 15% 23% 47% Males make up 63% of the Early AM time period and 59% of the evening period. Am peak is the only time period where females are the slight majority at 54%. Table 3.39: Gender by Time of Day (Weekday) Male Female Early AM 63% 37% AM Peak 46% 54% Mid-day 50% 50% PM Peak 54% 46% Evening 59% 41% Total 52% 48% 33

34 People 65 and over make up only 2% of the passengers in the Early AM and AM Peak periods. During the mid-day, that number increase to 11%. The AM Peak and Evening time periods see higher proportions of passengers under the age of 18. Passengers in the middle age ranges (19-64) make up 93% of the riders in the Early AM time period. Table 3.40: Age by Time of Day (Weekday) or over Early AM 4% 51% 42% 2% AM Peak 10% 49% 38% 2% Mid-day 3% 45% 42% 11% PM Peak 9% 44% 39% 7% Evening 11% 47% 40% 2% Total 7% 46% 40% 7% Hispanics travel less in the Evening than any other time period, and virtually no Asians ride in the Early AM time period. Asian Table 3.41: Ethnicity by Time of Day (Weekday) Black/ African American Hispanic Native American White Other Early AM 0% 3% 9% 4% 76% 9% AM Peak 3% 2% 7% 4% 77% 7% Mid-day 2% 4% 9% 4% 78% 3% PM Peak 0% 3% 8% 5% 79% 6% Evening 3% 4% 6% 4% 78% 6% Total 2% 3% 8% 4% 78% 5% 34

35 The Early AM period serves a significantly higher percentage of workers. 85% of transit users in this period are either full-time or part-time workers. AM peak is the next highest in percentage workers, followed by the Evening Time period. The highest percentages of students are served during the AM Peak (17%) and Evening (16%) periods. Table 3.42: Employment Status by Time of Day (Weekday) Full-time worker Part-time worker Homemaker Unemployed University/ other student Retired Early AM 60% 25% 0% 6% 5% 4% AM Peak 40% 26% 3% 6% 17% 8% Mid-day 22% 24% 4% 18% 14% 18% PM Peak 29% 28% 3% 17% 11% 13% Evening 36% 24% 1% 15% 16% 8% Total 31% 25% 3% 15% 13% 13% Transit users in the Mid-day period are less likely to have a car belonging to their household (68% have zero cars). Passengers in the Early AM were the most likely to own at least one car. Table 3.43: Household Vehicles by Time of Day (Weekday) None or more Early AM 50% 32% 9% 9% AM Peak 56% 27% 15% 2% Mid-day 68% 20% 9% 3% PM Peak 57% 27% 7% 9% Evening 56% 26% 13% 5% Total 61% 24% 10% 5% 35

36 With 55% earning less than $10K/year, transit users in the Mid-day tend to have the lowest household income. 87% percent of the Mid-day users have household income below the $25K/year mark. Transit users in the evening tend to have the highest household incomes of all the time periods. Less than $10,000 Table 3.44: Household Income by Time of Day (Weekday) $10,000- $14,999 $15,000- $24,999 $25,000- $49,999 $50,000- $74,999 $75,000 or more Early AM 35% 21% 30% 12% 1% 0% AM Peak 38% 17% 25% 12% 5% 3% Mid-day 55% 21% 11% 9% 2% 2% PM Peak 46% 18% 17% 11% 7% 1% Evening 38% 21% 21% 14% 5% 1% Total 47% 20% 17% 11% 4% 2% The majority of trips were coming from home and going to work (10.6%) and then going back home from work (24%). Table 3.45 shows the distribution of Origin Purpose by Destination Purpose. Table 3.45: Distribution of Origin Purpose by Destination Purpose (Weekday) Home University/ School Shopping Recreat -ional Work Medical Services Social Services Other Home 5.3% 5.4% 3.0% 1.8% 10.6% 2.5% 0.8% 4.3% University/School 9.8% 0.3% 0.1% 0.0% 0.2% 0.2% 0.0% 0.3% Shopping 6.3% 0.2% 1.1% 0.3% 0.5% 0.2% 0.0% 0.3% Recreational 2.1% 0.0% 0.0% 0.2% 0.0% 0.0% 0.0% 0.3% Work 24% 0.3% 0.1% 0.3% 1.4% 0.2% 0.0% 0.8% Medical Services 5.1% 0.3% 0.1% 0.0% 0.2% 0.9% 0.1% 0.5% Social Services 1.6% 0.1% 0.1% 0.0% 0.2% 0.0% 0.2% 0.3% Other 5.3% 0.3% 0.6% 0.1% 0.4% 0.1% 0.0% 1.2% 36

37 85% of passengers walk from their origin and to their destination. The next highest combination was bicycling to and from origin and destination at 7%, which was up 44% since Table 3.46: Distribution of Access by Egress Modes (Weekday) Walk/WC Bicycled By Car Skateboard Total Walk/WC 85% 1% 2% 0% 89% Bicycled 0% 7% 0% 0% 8% By Car 3% 0% 1% 0% 3% Skateboard 0% 0% 0% 1% 1% Total 88% 7% 4% 1% 100% SATURDAY ANALYSIS Since the 2011 passenger survey, RVTD added Saturday bus service. RVTD s Saturday service features limited service spans (8:00am to 4:00pm) and lower frequencies (60 minutes or higher). Saturday service was oversampled by 20%, resulting in nearly 400 individual responses. Below are summary charts for comparing Saturday transit users to weekday transit users. Ridership by route was consistent with weekday patterns, with somewhat higher percentage of ridership on the route 24 and a somewhat lower percentage on the route 30. Figure 3.47: Distribution of Ridership by Route: Weekday vs. Saturday 60% 50% 40% 30% 20% Weekday Saturday 10% 0%

38 Saturday trip purpose differs significantly from weekdays. As expected, a significantly lower percentage of transit users are using the bus for school. As a percentage of total trips, work trips are slightly lower than weekdays. Still, work remains the most common trip purpose, regardless of the day. Shopping and recreation trips are proportionally higher on Saturdays, while medical and social services are slightly lower. Figure 3.48: Trip Purpose by Route: Weekday vs. Saturday 25% 20% 15% 10% 5% 0% Weekday Saturday Saturday employment status differs slightly from weekdays. A slightly lower percentage of full-time workers ride on Saturday, while a slightly higher percentage of part-time workers ride. Unemployed riders are more common on Saturdays, while students and retired are less common. Figure 3.49: Employment Status: Weekday vs. Saturday 35% 30% 25% 20% 15% 10% Weekday Saturday 5% 0% Full-time worker Part-time worker Homemaker Unemployed University/ other student Retired 38

39 Ethnic distribution between weekday and Saturday transit users was consistent except for a slightly higher percentage of Hispanic transit users on Saturday and slightly fewer white users. Figure 3.50: Ethnic Distribution: Weekday vs. Saturday 90% 80% 70% 60% 50% 40% 30% Weekday Saturday 20% 10% 0% Asian Black/ African American Hispanic Native American White Other Saturday transit users are slightly more likely to use transit less than 4 days/week, but significantly less likely to use the bus over 5 days/week. Figure 3.51: Trip Frequency: Weekday vs. Saturday 50% 45% 40% 35% 30% 25% 20% 15% 10% 5% 0% 1 day a week 2 days a week 3 days a week 4 days a week 5 days a week 6 days a week Weekday Saturday 39

40 Saturday transit users are significantly less likely to drive if transit service weren t available, but were somewhat more likely to ride with someone else, take a taxi, or not make the trip. Figure 3.52: Bus Service not Available: Weekday vs. Saturday 45% 40% 35% 30% 25% 20% 15% Weekday Saturday 10% 5% 0% Walk/ Wheelchair Drive Ride with someone else Taxi Bicycle/ Skateboard Would not make this trip 40

41 SPATIAL ANALYSIS Figure 3.53: Trip Destination distribution by Zone; Origin: Central Medford (All Routes) % Destination of trips Leaving from Central Medford Central Medford 3% 2% 4% 3% 1% 1% 1% North Central Medford Central Ashland White City 4% 5% 40% Central Point 6% 6% 7% 8% 9% Southeast Medford Northeast Medford Talent South Ashland South Medford Commercial 41

42 Figure 3.54: Trip Destination Distribution by Zone; Origin: Route 10, North of Talent % Destination of route 10 trips Leaving from North of Talent Central Medford Central Ashland 3% 6% 3% 7% 1% 37% South Ashland Talent Phoenix 10% 10% 22% South Medford Commercial Southeast Medford South Talent South Phoenix White City 42

43 Figure 3.55: Trip Destination Distribution by Zone; Origin: Route 10, South of Talent % Destination of route 10 trips Leaving from North of Talent Central Medford South Ashland 3% 1% 3% 6% 7% 9% 11% 37% Talent South Medford Commercial Phoenix Southeast Medford South Talent North Central Medford Northeast Medford White City 43

44 Figure 3.56: Trip Destination Distribution by Zone; Origin: Route 10, Talent % Destination of trips Leaving from Central Medford Central Ashland 4% 7% 6% 8% 39% 24% 12% South Ashland South Talent Central Medford Talent Phoenix Southeast Medford South Medford Commercial 44