Enhancing Pedestrian Volume Estimation and Developing HCM Pedestrian Methodologies for Safe and Sustainable Communities (2022)

Below is the uncorrected machine-read text of this chapter, intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text of each book. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

248 Appendix C: Research Approach Attachments Attachment C1: Intercept Survey Instrument Intercept Surveys  Will not be surveying in the rain  Estimates: 2 hours of surveying per site  Examples of approaches “Hi there! Do you have a minute to take a survey on crossing the street here?” “Hey there! Do you have some time to answer questions about this crosswalk?” Pedestrian Crossing Survey Researchers from the UNC’s are conducting a study about the experience of walking in the Chapel Hill/Carrboro area. This study is a part of the National Cooperative Highway Research Program (NCHRP) Project 17-87 “Enhancing Pedestrian Volume Estimation and Developing HCM Pedestrian Methodologies for Safe and Sustainable Communities.” Being in a research study is completely voluntary. You can choose not to be in this research study. You can also say yes now and change your mind later. If you agree to take part in this research, you will be asked to complete this 5-minute survey about your experience crossing this street. We expect that 200 people will take part in this research study. The possible risks to you in taking part in this research are:  feeling uncomfortable being asked about your feelings, and  having someone else find out that you were in a research study. The possible benefits to you for taking part in this research are:  gaining insight into how you felt while crossing the street. To protect your identity as a research subject, we do not ask for your name, and, the research team will store your survey responses on a password-protected computer. In any publication about this research, personal information will not be used. By clicking below and completing this online survey, you acknowledge that you:  are at least 18 years of age, and  agree to participate in the study If you have any questions about this research, please contact Investigator, Seth LaJeunesse by calling 919-962-4236 or emailing lajeune@hsrc.unc.edu. If you have questions or concerns about your rights as a research subject, you may contact the UNC Institutional Review Board at 919-966-3113 or by email to IRB_subjects@unc.edu. 1. How would you rate your crossing experience?

249 a. Very satisfied b. Satisfied c. Dissatisfied d. Very dissatisfied 2. Are you walking? a. To public transportation b. From public transportation c. Neither 3. What is the purpose of your trip? a. Going to work/school/the University b. Going home c. Visiting friends/family d. Exercising e. Running errands f. Other: _______ 4. How long is your walking trip? a. <5 min b. 5-10 min c. 10-15 min d. >15 min 5. How often do you use this crosswalk? a. First time b. Less than one day a month c. 1-3 days a month d. 1-3 days a week e. 4 or more days a week 6. Please indicate your level of agreement with the following statements Participants responded with strongly disagree, disagree, agree, and strongly agree a. “I felt like I had to wait a long time to cross.” b. “I felt like I might get hit by a car when crossing here.” c. “I had enough time to cross this street.” d. “I went out of my way to cross here.” e. “I felt delayed trying to cross this street.” f. “I felt safe crossing here.” g. “I felt rushed trying to cross this street.” h. “Crossing here was the most direct route to get to where I was going.” 7. Do you consider yourself…? a. Hispanic, Latino, or Spanish origin b. American Indian or Alaska native c. Asian d. Black or African American e. White f. Prefer not to say

250 g. Other: _______ 8. What is your age? a. 18-25 b. 26-39 c. 40-65 d. 66-75 e. 76+  “Quick Version - Pedestrian Crossing Survey” o How would you rate your crossing experience? Post-Survey Video Coding Surveyors then filled out the remainder of the survey: 1. Was the button pressed? a. Yes b. No c. Flashing already d. Indeterminate e. N/A (Surveyors entered N/A if crosswalk had no button.) 2. What site? a. Surveyors listed the site name 3. Behaviors (check all that apply) a. Looked at traffic before crossing b. Did not look at traffic before crossing c. Waved to drivers d. Singing or whistling e. Negative gesture/words to drivers 4. Distractions (check all that apply) a. Talking with others crossing b. Talking on cell phone c. Texting/looking at cell phone/device/other d. Wearing headphones/earbuds e. Not engaged with device/others 5. Gender a. Male b. Female c. Indeterminate 6. Group type a. Individual b. All adults

251 c. Adults with kids d. Other e. Can’t tell 7. Notes  One camera per site for RRFB, marked crossings, unmarked crossings, median crossings o Target/goal criteria:  Full length of crosswalk  Sharks teeth on both approaches  Approaches  Push buttons on both sides  Helpful to see RRFB lights if applicable  2 cameras per site for LPIs and control sites o Target/goal criteria:  Traffic lights parallel to crosswalk  Walkman signal parallel to crosswalk  Full length of crosswalk  Approaches  It helps to keep the surveyors in view so that coders can identify who took the survey.  Camera directions: o Strap to pole/existing infrastructure available o Extend 15-20 feet up, avoid powerlines o Camera capture  Angle downwards to get criteria for RRFB Criteria  Angle slightly upwards to capture LPI criteria  Upload survey responses after each outing when you connect to Wi-Fi  Update Google Doc on what site(s)/time(s) were done that day Intercept Survey Video Reduction  Upload video with site/time by USB and SD card to Google Drive and label  Export survey responses from Qualtrics  Locate pedestrian by using End Date (Column B) to see the time that the pedestrian filled out the survey, then rewind to see behavior For Unsignalized Sites: 1. Signal compliance a. Yielded and pushed the button b. Crossed when someone else pressed the button c. Did not push the button d. Crossed with group that did not push the button e. Indeterminate f. N/A

252 2. Pedestrian delay (check all that apply) a. Delayed due to motorist behavior b. Delayed due to signal timing or lights not flashing c. Delayed when pedestrian motioned driver through d. Not delayed crossing the street 3. Did the pedestrian look at traffic before crossing? (Y/N/Can’t tell) 4. Pedestrian eye/gaze a. Looking down b. Looking ahead c. Looking for traffic d. Looking at companions/other people 5. Pedestrian speed a. Slow, unhurried b. Average speed c. Running (but not on a run or a jog) d. Started walking, then ran 6. Crosswalk compliance a. Stayed in crosswalk b. Veered out 7. Interaction with motorist or cyclist (check all that apply) a. Interaction = When a pedestrian and a motorist or cyclist make any kind of avoidance maneuver (change of trajectory or slowing) b. Pedestrian space any area beyond the stop lines or sharks teeth. Therefore it does not apply to unmarked crosswalks. For marked crosswalks with no sharks teeth and no stop bar, it refers to the area with the crosswalk markings. c. Pedestrian dodged right or left to avoid. d. Pedestrian sped up to avoid. e. Pedestrian stopped or slowed to avoid. f. Motorist stopped or slowed before/at the stop/yield line OR at unmarked crossing. g. Motorist encroached on pedestrian space. h. Motorist did not yield. i. Bicyclist stopped or slowed to avoid. j. Bicyclist did not yield. k. No interaction. 8. Group size (#) that the pedestrian is walking with, not all people that cross at that time 9. Group type a. Individual b. All adults c. Adults with children d. Indeterminate

253 10. Gender a. Male b. Female c. Indeterminate 11. Notes For Signalized Sites: 1. Is the pedestrian two-stage crossing? (Y/N) a. Did the pedestrian continue on to cross the minor road before or after they crossed the major road? If so, record Y and continue to code the pedestrian as normal b. We are NOT recording which crosswalks they use. And we are NOT including pedestrians who do not use the study crosswalk, but do make a two-stage diagonal crossing at the study intersection on other crosswalks 2. Did pedestrian activate the push-button? a. Yes b. No c. Someone else activated d. N/A (if no button present) e. Indeterminate 3. Signal compliance a. Jumped walk man: Pedestrian began crossing with stop hand but walk signal turned on before he/she reached the second lane. b. Crossed with walk man. c. Crossed with flashing hand. d. Crossed with stop hand. i. Pedestrian crossing with stop hand (on red parallel traffic light) will not be coded. In some scenarios the pedestrian signal will not change (from stop hand to walk man), but the parallel street will be green. These pedestrians should be coded. 4. Crossed with LPI? (Y/N/Can’t tell) a. Started to cross with walk man, but parallel traffic light is red 5. Traffic signal compliance: looking at traffic light of parallel street when the pedestrian arrives to the curb and leaves the curb a. Jumped green i. Control - ped begins crossing on red, the traffic light turns green before he/she reaches the second lane. ii. For LPI: ped steps off curb 4 seconds or less before start of walk. b. Arrive red, wait for green i. In the case of LPI, code this behavior when ped arrives on red and waits for walk signal e. Arrive and exit green f. Arrive green, exit red

254 g. Ran light 6. Pedestrian delay (Select all that apply) a. Delayed due to motorist behavior b. Delayed due to signal timing or lights not flashing i. Includes when pedestrian is waiting for walk man c. Delayed when pedestrian motioned driver through d. Not delayed crossing the street e. Can’t tell 7. Did the pedestrian look at traffic before crossing? (Y/N/Can’t tell) 8. Pedestrian eye/gaze a. Looking down b. Looking ahead c. Looking for traffic d. Looking at companions/other people 9. Pedestrian speed a. Slow, unhurried b. Average speed c. Running (but not on a run or a jog) d. Started walking, then ran 10. Crosswalk compliance a. Stayed in crosswalk b. Veered out i. If a ped does not enter the crosswalk but crosses within 5 ft of it, select veered out and record this behavior in the notes section 11. Motor vehicle volume: volume of cars will be counted between the time the walk signal turns on and when the parallel traffic light turns from green to red a. Volume: right turn from major - count the number of cars turning right from major street to minor street b. Volume: right from minor - count the number of cars turning right from the minor street to major street c. Thru volume from minor - count the number of cars crossing the intersection from minor street i. Lane closest to crosswalk only d. Volume: left from minor - count the number of cars turning left from minor to major street

255 Figure C1-1. Turning Movement Diagram for Counting Motorists. 12. Interaction with motorist or cyclist (check all that apply) a. Interaction = When a pedestrian and a motorist or cyclist make any kind of avoidance maneuver (change of trajectory or slowing) b. Pedestrian space for signalized intersections is defined as the crosswalk area (ignore the stop bar) c. Mark a “1” in the corresponding column for all of the 4 motor vehicle (MV) crossings combined (can mark multiple columns) a. Pedestrian dodged right or left to avoid b. Pedestrian sped up to avoid c. Pedestrian stopped or slowed to avoid d. Motorist stopped or slowed before/at the stop/yield line e. Motorist encroached on pedestrian space f. Motorist did not yield g. Bicyclist stopped or slowed to avoid h. Bicyclist did not yield i. No interaction 13. Group size (#): Number of people the pedestrian is walking with, not all of the people crossing at the same time 14. Group type

256 a. All adults b. Adults with children c. Indeterminate 15. Gender a. Male b. Female c. Indeterminate 16. Notes Table C1-1. Chapel Hill Surveyors. Sarah Brown, Sarah Bland, Sophie Currin, Ellen Emeric, Katie Heuser, Heyne Kim, Walker Harrison Site # Site Date Time Surveyor 1 Surveyor 2 1 RRFB on Franklin 3/20/2019 12-2 PM S. Brown S. Currin 2 Franklin Control (Roberson) 3/5/2019 12-2 PM K. Heuser S. Brown 3 RRFB Pittsboro 3/5/2019 4-6 PM K. Heuser S. Brown 4 Pittsboro Control 3/19/2019 4-6 PM K. Heuser E. Emeric 5 RRFB on MLK 3/19/2019 12 -2 PM S. Brown K. Heuser 6 Control on MLK 3/26/2019 4-6 PM K. Heuser S. Currin 7 South Rd Marked (Student Stores) 4/16/2019 4-6 PM K. Heuser S. Currin 8 Control South Rd Unmarked (Stadium Drive) 4/18/2019 + 5/7/2019 4 -6 PM S. Currin + W. Harrison W. Harrison + E. Emeric 9 Weaver Dairy 4/9/2019 4-6 PM K. Heuser S. Currin 10 RRFB Willow Dr 4/25/2019 4-6 PM K. Heuser S. Currin 11 Willow Control 4/23/2019 4-6 PM S. Currin E. Emeric 12 LPI Columbia and Rosemary 4/30/2019 4-6 PM K. Heuser S. Currin 13 Control Franklin and Raleigh 5/2/2019 4-6 PM K. Heuser S. Bland 14 LPI Franklin and Church 5/24/2019 12-2 PM K. Heuser S. Currin 15 Control Franklin and Graham 6/17/2019 12-2 PM K. Heuser S. Currin 16 LPI Manning and Ridge 5/1/2019 12-2 PM S. Currin E. Emeric 17 Control Manning and Hibbard 5/9/2019 12-2 PM W. Harrison H. Kim 18 LPI Raleigh and Hamilton 5/30/2019 4-6 PM K. Heuser S. Currin 19 Control Raleigh and Finley Golf Course 5/28/2019 4-6 PM K. Heuser S. Currin 20 RRFB on Seawell School Rd 6/3/2019 4:30-6:30 PM K. Heuser S. Currin 21 Control on Estes Dr Ext 6/10/2019 4:30-6:30 PM K. Heuser S. Currin 22 Columbia and Purefoy 5/22/2019 12-2 PM K. Heuser S. Currin 23 Control Columbia (Merritt's Grill) 6/15/2019 12-2 PM K. Heuser H. Kim 24 Control 54 by Kingswood Apts 6/4/2019 4-6 PM K. Heuser S. Currin

257 Table C1-2. Portland Surveyors. Frank Appiah, Jared Islas, Katherine Riffle, Huijun Tan, Zoe Davis Site # Site Date Time Surveyor 1 Surveyor 2 182 SE Hawthorne Blvd. and SE 43rd Ave. 6/18/2019 4-6 PM Jared Katherine 191 SE Hawthorne Blvd. and SE 46th Ave. 6/19/2019 4-6 PM Frank Katherine 196 SE Powell Blvd. and SE 34th Ave. 6/20/2019 4-6 PM Jared Frank 197 SE Powell Blvd. and SE 36th Ave 6/25/2019 4-6 PM Jared Frank 183 E Burnside St. and NE 22nd Ave. 6/26/2019 4-6 PM Jared Frank 153 NE MLK Jr Blvd. at NE Jarret St. 7/2/2019 4-6 PM Jared Katherine 176 NE MLK Jr Blvd. at NE Graham St. 7/2/2019 4-6 PM Frank Zoe 43 NE Glisan St. and NE 78th Ave. 7/10/2019 4-6 PM Jared Zoe + Katherine 156 NE Glisan St. and NE 80th Ave. 7/10/2019 4-6 PM Frank Huijun 207 NE 60th Ave. and NE Halsey St. 7/11/2019 4-6 PM Frank Zoe 165 W Burnside St. and SW 8th Ave. 7/16/2019 12-2 PM Jared Huijun + Zoe 166 W Burnside St. and SW Park Ave. 7/16/2019 12-2 PM Frank Katherine L19 SE Cesar Chavez Blvd. and SE Main St. 7/17/2019 4-6 PM Jared Huijun 189 E Burnside St. and SE 26th Ave 7/17/2019 4-6 PM Frank Katherine 6 SE 122nd Ave. and SE Morrison St. 7/18/2019 4-6 PM Huijun Zoe 163 SE Stark St. and SE 86th Ave 7/23/2019 4-6 PM Jared Zoe 167 SE Stark St. and SE 80th Ave 7/23/2019 4-6 PM Huijun Katherine 177 SW Vermont St. and SW Idaho Dr. 7/24/2019 4-6 PM Frank Huijun 179 SW Vermont St. and SW 37th Ave. 7/24/2019 4-6 PM Zoe Katherine 150 SE Powell Blvd. and SE 54th Ave. 7/25/2019 4-6 PM Jared Frank L22 SE Hawthorne Blvd. and SE 50th Ave. 7/25/2019 4-6 PM Zoe Huijun

258 Site # Site Date Time Surveyor 1 Surveyor 2 25 NE 33rd Ave. and NE Emerson St. 7/30/2019 4-6 PM Jared Zoe L8 NE 82nd Ave. and NE Wasco St. 7/31/2019 4-6 PM Katherine Huijun 193 NE 82nd Ave. and NE Tillamook St. 7/31/2019 4-6 PM Zoe Jared L21 NE Broadway St. and NE 14th Ave. 8/1/2019 4-6 PM Katherine Frank 192 NE Broadway St. and NE 9th Ave. 8/1/2019 4-6 PM Zoe Huijun L14 NE Broadway St. and NE 32nd Ave. 8/6/2019 4-6 PM Frank Katherine 194 NE Broadway St. and NE 28th Ave. 8/6/2019 4-6 PM Zoe Huijun L4 E Burnside St. and SE 20th Ave. 8/7/2019 4-6 PM Huijun Frank 181 E Burnside St. and SE 28th Ave. 8/7/2019 4-6 PM Zoe Jared 208 NE Alberta St. and NE 33rd Ave. 8/8/2019 4-6 PM Katherine Huijun 207 NE 60th Ave. and NE Halsey St. 8/8/2019 4-6 PM Frank Jared 159 NE Sandy Blvd. and NE 36th Ave. 8/13/2019 4-6 PM Jared Katherine 210 NE Sandy Blvd. and NE 17th Ave. 8/13/2019 4-6 PM Zoe Huijun 131 NE MLK Jr Blvd. at NE Cook St. 8/14/2019 4-6 PM Frank Jared 209 NE MLK Jr Blvd. and NE Sumner St. 8/14/2019 4-6 PM Zoe Katherine 206 NE 33rd Ave. and NE. Shaver St. 8/15/2019 4-6 PM Huijun Frank Attachment C2: Video Data Collection Video Coding Instrument Quality Counts Camera Set Up Most Chapel Hill sites used SD video settings. Portland sites used HD video settings. Standard Definition Sites Video Settings Signal format: NTSC standard Recording/Playback: MPEG-2 Recording in Economy mode (all variable bit rate): 352x240, 1.5 Mbps (megabits bits per second)

259 HD Sites Video Specifications Pickup: 1/4” (2,800,000 pixels) progressive CMOS Lens: F1.9 to 3.2, 2.9 mm to 58 mm, 20:1 power zoom lens Filter diameter: 30.5 mm HD Sites Video Settings Signal format: 1080i/60 Recording/Playback: MPEG-4 AVC/H.264 Recording in “EP” mode (all variable bit rate): 1920x1080, 5 Mbps Video Coding Procedure Quality Counts Video Reduction Unsignalized Sites ● Download videos from Quality Counts ● Code 2hrs from QC for 2 days from 40 sites o 12-2 PM for weekend days, 4-6 PM for weekdays ▪ If weather or other special circumstances encroach on time frame, use best judgement of other peak 2hr periods that day ● Can get pedestrian counts from other questions about group size and sum responses ● Times should be recorded to the millisecond ● Only code what you see – if you can’t see in the video, don’t guess

260 To begin to code Quality Counts videos: ● Determine if the site has a median island. Two-way left-turn lanes do not count as medians. (median) (not a median) Sources: Courtesy of NACTO (left), HSRC/Katie Heuser (right) 1. Site name 2. Date 3. Observation ID - Sequential ID for each observation of a pedestrian. If more than one ped is crossing (e.g., group) one ID for the group a) ID is a combination of three elements: Control/Treated/LPI, Site #, and Ped # b) For example: T50001 for the RRFB at MLK i. The RRFB at MLK is a treated (T) crosswalk, and the site # is 5. This observation ID would be for the first pedestrian you code 4. Is the person on a run/jogging/cycling? If so, record Y but do not code anything else a) We want to count the person but not code their behavior. 5. Size of group (integer) 6. Group type (all adults/adults with kids/other/can’t tell) 7. Gender (M/F/indeterminate) 8. Did the pedestrian activate the push button? (Y/N) a) if a person in a group did not push the button, but another party in that group did, then put Y 9. Direction of crossing – Mark the direction of the crossing ped (southbound, northbound, etc.) 10. If there is a median – see Table C2-1 a) Coders used a stopwatch app on their phone b) PT1 Time when he/she pressed the button (for a group, choose one person and be consistent - always choose first person in group or always choose last person or always choose person in middle if speeds are different, divide group into individuals or separate groups) i. If ped did not press the button, record the time they arrived at the curb & became prepared to cross c) PT2 Time when he/she stepped off the curb into the roadway (may be same as above) i. Record time when first foot steps off d) PT3 Time when he/she arrived at the median i. Ped arrives when first foot crosses the first line of the median e) PT4 Time when he/she arrived stepped off the median f) PT5 Time when he/she finishes crossing (steps onto the curb of the opposing lane) 11. If there is no median – see Table C2-2 a) PT1 Time when he/she pressed the button (for a group, choose one person and be consistent like always choose first person in group or always choose last person or always choose person in middle if speeds are different, divide group into individuals or separate groups) i. If ped did not press the button, record the time they arrived at the curb & became prepared to cross

261 b) PT2 Time when he/she stepped off the curb into the roadway (may be same as above) c) PT5 Time when he/she finishes crossing (steps onto the curb of the opposing lane) 12. One minute volume near side - For one minute prior to when the ped reached the crossing/pressed the button (PT1), count the volume of cars on the near side. a) Cars that are less than halfway through the crosswalk at either starting or stopping point should be counted b) Near and far are relative to the pedestrian direction: near side are the lanes closest to the pedestrian. 13. One minute volume far side - For one minute prior to when the ped reached the crossing/pressed the button (PT1), count the volume of cars on the far side. a) Cars that are less than halfway through the crosswalk at either starting or stopping point should be counted b) Near and far are relative to the pedestrian direction: near side are the lanes farthest from the pedestrian. 14. Pedestrian delay – Did the pedestrian have to wait on the sidewalk for an extended period? a) Select all that apply by marking a “1” in the corresponding column ● Delayed due to motorist behavior ● Delayed due to signal timing or lights not flashing ● Delayed when ped motioned driver through ● Not delayed ● Can’t tell 15. Crosswalk compliance ● Stayed in crosswalk ● Veered out o Strayed from crosswalk 16. Eye/gaze I – select all that apply (for a group, choose all that apply to anyone in the group) a) Select all that apply by marking a “1” in the corresponding column ● Looked at traffic before crossing ● Did NOT look at traffic before crossing 17. Eye/gaze II – select all that apply (for a group, choose all that apply to anyone in the group) a) Select all that apply by marking a “1” in the corresponding column ● Looking down ● Looking for traffic ● Looking ahead ● Looking at companions/other people ● Can’t tell ● We are no longer coding gaze; all applicable columns should have a “n” for NOT CODED 18. Distractions (for a group, choose all that apply to anyone in the group) a) Select all that apply by marking a “1” in the corresponding column ● Talking with others crossing ● Talking on cell phone ● Looking at cell phone/device/other ● Wearing headphones/earbuds o We are no longer coding wearing headphones/earbuds; the column should have a “n” for NOT CODED ● Not engaged with device/others 19. Behaviors – select all that apply (for a group, choose all that apply to anyone in the group) a) Select all that apply by marking a “1” in the corresponding column ● Talking to others present ● Waved to drivers

262 ● Negative gesture to drivers ● Used wheelchair/walker ● Used scooter ● None of the above 20. Interaction with cyclist (for a group, choose all that apply to anyone in the group) ● Pedestrian dodged right or left to avoid ● Pedestrian sped up to avoid ● Pedestrian stopped or slowed to avoid ● Bicyclist stopped or slowed to avoid ● Bicyclist did not yield to pedestrian in crosswalk (same or approaching lane) ● No interaction ● Other 21. Interaction with motorist (for a group, choose all that apply to anyone in the group) An interaction can be defined as: When a pedestrian and a motorist or cyclist make any kind of avoidance maneuver (change of trajectory or slowing) Interactions must be coded for each motorist approaching the crosswalk during a ped crossing. The interaction in lane 1 is whatever lane closest to the ped when they begin to cross. If the crosswalk has only two lanes, ignore lanes 3 & 4. Interactions can be hard to see if the camera view does not capture the shark’s teeth/a good amount of distance upstream. Make up of both camera angles to see the whole picture. It can be easier to pull up the supplementary video in Windows Media Viewer to not disrupt the VLC viewing. ● Pedestrian dodged right or left to avoid: ped moves right to avoid usually a bike or motorcycle, but could be a car ● Ped sped up to avoid: rare, but happens when increase in speed is caused by car action ● Pedestrian stopped or slowed to avoid ● Motorist stopped or slowed to avoid behind the sharks teeth or stop bar OR stopped at an unmarked crosswalk o At an unmarked crosswalk, stopping ● Motorist encroached on pedestrian space o The pedestrian space is any area beyond the stop lines or sharks teeth. Therefore this does not apply to unmarked crosswalks. o Each lane should be treated separately; if a car encroaches on the crosswalk after the pedestrian leaves that lane, the encroaching is not applicable. ● Motorist ‘did not yield’ to pedestrian in crosswalk (same or approaching lane) o A vehicle is considered to yield if the driver slows down or stops for the purpose of allowing the pedestrian to cross. ● Motorist direction (near side, far side) ● No interaction: neither car not ped change speed or trajectory ● Other 22. Notes: Record anything that you observed that may have affected the pedestrian’s crossing Time can be recorded on your phone or with this application, as long as it has milliseconds

263 Table C2-1. Timing for Unsignalized Crosswalks with Medians. Column Purpose Action Format J PT1 Time when he/she arrived at the curb OR pressed button Record time with milliseconds from VLC Time K PT2 Time when he/she stepped off the curb into the road Record time with milliseconds from VLC Hit START on stopwatch Time L Assesses if time in column J is before time in column K =IF(J4<=K4,"OK", "ERROR") M Stopwatch time when ped reaches median Lap 1 In seconds + milliseconds N Stopwatch time when ped leaves the median Lap 2 In seconds + milliseconds O Stopwatch time when ped finishes crossing Hit STOP on stopwatch Lap 3 In seconds + milliseconds P Total stopwatch time for crossing =SUM(K3:M3) In seconds + milliseconds Q PT3 Time when he/she arrived at the median =J3+K3 Time R PT4 Time when he/she arrived stepped off the median =O3+L3 Time S PT5 Time when he/she finishes crossing (steps onto the curb of the opposing lane) =M3+P3 Time

264 Table C2-2. Timing for Unsignalized Crosswalks with No Median. Column Purpose Action Format J PT1 Time when he/she arrived at the curb Record time with milliseconds from VLC Time K PT2 Time when he/she stepped off the curb into the road Record time with milliseconds from VLC Time L Assesses if time in column J is before time in column K =IF(J4<=K4,"OK", "ERROR") M Total stopwatch time for crossing =N3-K3 In seconds + milliseconds N Time ped finishes crossing =J3+K3 Time *To edit the format of time: right click on cell -> format cells -> custom -> type in h:mm:ss.00 *To edit the format of stopwatch time: right click on cell -> format cells -> custom -> type in s.00 Signalized Sites Download videos from Quality Counts ● Code 2hrs from QC for 2 days from 20 sites o 12-2 PM for weekend days, 4-6 PM for weekdays unless we feel it is a morning peak site ▪ If weather or other special circumstances encroach on time frame, use best judgement of other peak 2hr periods that day ● Can get ped counts from other questions about group size and sum responses ● Times should be recorded to the millisecond To begin to begin to code LPI Quality Count videos: ● Open a new Excel spreadsheet and copy the first page of the “QC Video Coding Template_LPI” called “LPI”, as well as the second sheet called “drop down menu” onto your spreadsheet. 1. Site name 2. Date 3. Observation ID - Sequential ID for each observation of a pedestrian. If more than one ped is crossing (e.g., group) one ID for the group a. ID is a combination of three elements: Control/Treated/LPI, Site #, and Ped # b. For example: L120001 for the LPI at Columbia and Rosemary i. The intersection at Columbia and Rosemary is an LPI (L), and the site number is 12. This observation ID would be for the first pedestrian you code. 4. Direction of Crossing - Mark the direction of the crossing ped (southbound, northbound, etc.) 5. Gender (M/F/Indeterminate) 6. Is the person running/jogging? If so, record Y but DO NOT CODE ANYTHING ELSE. a. We want to code the person but not their behavior. 7. Is the person cycling across the crosswalk? If so, record Y but DO NOT CODE ANYTHING ELSE. 8. Did the person cross on a red light? If so, record Y but DO NOT CODE ANYTHING ELSE. a. A pedestrian is considered to have crossed on red if the traffic light of the parallel street remains red after they have reached the second lane. b. If the traffic light of the parallel street changes to green before the pedestrian has reached the second lane, continue coding (this behavior will be noted in the signal compliance section, #15).

265 9. Did the pedestrian cross the intersection in a two-stage diagonal crossing maneuver? Did the person continue on to cross the minor road after or before they crossed the major road? If so, record Y and continue to code the pedestrian as normal. a. We are NOT recording which crosswalks they use. And we are NOT including pedestrians who do not use the study crosswalk, but do make a two-stage diagonal crossing at the study intersection on other crosswalks 10. Size of group (integer) 11. Group type (all adults/adults with kids/other/can’t tell) 12. Did the pedestrian activate the push button? (Y/N/can’t tell) a. if a person in a group did not push the button, but another party in that group did, then put Y 13. Time (refer to Table 2 above) a. PT1 Time when he/she pressed the button (for a group, choose one person and be consistent - always choose first person in group or always choose last person or always choose person in middle. If speeds are different, divide group into individuals or separate groups) i. If ped did not press the button, record the time they arrived at the curb and became prepared to cross. b. PT2 Time walk signal turns on c. PT3 Time when he/she stepped off the curb into the roadway (may be same as above) d. PT5 Time when he/she finishes crossing (steps onto the curb of the opposing lane) 14. Volume of cars will be counted between the time the walk signal turns on and when the parallel traffic light turns from green to red. a. Volume: right turn from major - count the number of cars turning right from major street to minor street b. Volume: right from minor - count the number of cars turning right from the minor street to major street c. Thru volume from minor - count the number of cars crossing the intersection from minor street i. Lane closest to crosswalk only d. Volume: left from minor - count the number of cars turning left from minor to major street. 15. Signal compliance a. Pedestrian signal compliance (when begin crossing) i. Jumped walkman - ped began crossing with stop hand but walk signal turned on before he/she reached the second lane. ii. Crossed with walkman iii. Crossed with flashing hand iv. Crossed with stop hand 1. Pedestrian crossing with stop hand (on red parallel traffic light) will not be coded. In some scenarios the pedestrian signal will not change (from stop hand to walkman), but the parallel street will be green. These pedestrians should be coded. b. Crossed with LPI? - started to cross with walkman, but parallel traffic light is red (Y/N/N/A) c. Traffic signal compliance (looking at traffic light of parallel street) i. Arrive and exit green ii. Arrive green, exit red iii. Arrive red, wait for green

266 1. In the case of LPI, code this behavior when ped arrives on red and waits for walk signal iv. Jumped green 1. Control - ped begins crossing on red, the traffic light turns green before he/she reaches the second lane. 2. For LPI: ped steps off curb 4 seconds or less before start of walk 16. Crosswalk Compliance i. Stayed in crosswalk ii. Veered out: We've been using "veer off" to describe if a pedestrian has moved away from or moved into the crosswalk. We've been coding people if they do not enter the crosswalk but cross within 5 feet of it; otherwise, they aren't taking advantage of the infrastructure provided. 17. Eye/gaze (for group, code the behavior of the ped who pressed the button/chosen ped) a. Did ped look at traffic before crossing? (Y/N/Can’t tell) 18. Distractions (for a group, choose all that apply to anyone in the group) a. Select all that apply by marking a “1” in the corresponding column i. Talking with others crossing ii. Talking on phone iii. Looking at phone/book iv. Not engaged with device/others v. Can’t tell 19. Behaviors (for a group, choose all that apply to anyone in the group) a. Select all that apply by marking a “1” in the corresponding column i. Waved to drivers ii. Negative gesture to drivers iii. Used wheelchair/walker iv. Used roller skates/skateboard v. Used scooter vi. N/A 20. Interaction with cyclist (for a group, choose all that apply to anyone in the group) a. Mark a “1” in the corresponding column i. Pedestrian dodged right or left to avoid ii. Pedestrian sped up to avoid iii. Pedestrian stopped or slowed to avoid iv. Cyclist stopped or slowed to avoid v. Cyclist did not yield to pedestrian in the crosswalk vi. No interaction 21. Interaction with Right-turn-on-red from Major to Minor*(for a group, choose all that apply to anyone in the group) a. Mark a “1” in the corresponding column i. Ped dodged right or left to avoid ii. Ped sped up to avoid iii. Ped stopped or slowed to avoid iv. MV stopped/slowed outside of crosswalk v. MV stopped/slowed but encroached on crosswalk vi. Motorist did not yield vii. Motorist ran red light viii. No interaction 22. Interaction with Thru and Left Lanes* a. Did MV encroach on crosswalk? (Y/N)

267 23. Interaction with Right turn from Minor to Major* (for a group, choose all that apply to anyone in the group) a. Mark a “1” in the corresponding column i. Ped dodged right or left to avoid ii. Ped sped up to avoid iii. Ped stopped or slowed to avoid iv. MV stopped/slowed outside of crosswalk v. MV stopped/slowed but encroached on crosswalk vi. Motorist did not yield vii. Motorist ran red light viii. No interaction 24. Notes: Record anything you observed that may have affected the pedestrians crossing *Interaction with motorist - an interaction can be defined as: When a pedestrian and a motorist make any kind of avoidance maneuver (change of trajectory of slowing) - Interactions can be hard to see if the camera view does not capture the shark’s teeth/a good amount of distance upstream. Make up of both camera angles to see the whole picture. It can be easier to pull up the supplementary video in Windows Media Viewer to not disrupt the VLC viewing. Interrater Reliability Test Introduction To test the consistency of video coding for the video analysis portion of the data collection, interrater reliability tests were performed, first for UNC coders and later for PSU coders. A separate interrater reliability test was conducted for each university because video was collected first in Chapel Hill and later in Portland. The ideal time for maximizing walking in Chapel Hill was during the spring to minimize the impact of hot summer temperatures which could discourage walking and to maximize pedestrians who might be walking to attend the University. In Portland, the ideal time for walking as considered to be summer, when the weather is expected to be drier and sunnier. For this reason, coders in Chapel Hill were trained first and their interrater reliability had to be assessed before those of the Portland coders who were trained in the summer. After practicing, each coding team was tested to assess the degree of agreement amongst coders. The UNC team was tested twice because the coding procedure was altered slightly after the first test to improve accuracy. The first test was on the video of the RRFB on MLK Jr. Blvd. in Chapel Hill from 5:00 to 6:00 p.m. The second test was on the video of the RRFB on Franklin St. in Chapel Hill from 5:00 to 5:15 p.m. The interrater reliability tests can be used to assess the most accurate elements of the video reduction. Results from the first and second UNC-coder tests were also used to clarify the coding procedure. To test the consistency of the video coding at both universities, the second test described above was repeated for both UNC and PSU coders using statistical tests to compare coding of the same pedestrians between coders. All the coders at both universities coded the same 15-minute video segment (5:00 p.m. to 5:15 p.m.), in which 43 pedestrians crossed at a crosswalk equipped with an RRFB on West Franklin Street in Chapel Hill. Two types of statistical tests were employed: mean absolute percent difference (MAPE) for comparing continuous data (e.g., MV volume, pedestrian delay, crossing time) and intraclass correlation coefficient (kappa statistic) for comparing categorical variables, such as group type and type of interaction with vehicles (Fleiss 1981). For this analysis, a kappa value greater than 0.75 was considered good agreement, between 0.4 and 0.75 was considered fair agreement, and less than 0.4 was considered poor agreement.

268 The results of the analysis revealed that, in general. MV traffic volumes and pedestrian crossing time were coded with acceptable consistency because both were less than 15% average absolute percent difference (MAPE) between average and individual values. Pedestrian delay had higher variability due to the smaller numeric values involved (2 seconds was the average pedestrian delay). There is a limit to how precise any one human video observer can be in recording the exact second when a pedestrian arrived at the curb and/or pushed the button and when that pedestrian stepped off the curb. There is some judgement involved, especially for determining the precise second when a pedestrian arrives at the curb, as pedestrians may not come to a full and complete stop. For this reason, although the MAPE is high, the result is still considered acceptable. For categorical variables, some variables saw high agreement between coders. Categorical variables that had near perfect agreement included:  Direction,  Size of group, and  Type of group. Categorical variables with reasonable agreement (fair to good, kappa>0.4) included:  Gender.  Reason for pedestrian delay.  Crosswalk compliance had good agreement among Chapel Hill coders, but Portland coders did not use the “veered out of crosswalk” code very often.  Behaviors had fair agreement among Chapel Hill coders, but Portland coders did not code behaviors.  Interactions between motorists and pedestrians had good agreement among Chapel Hill coders. Other variables had poor-to-good agreement:  Pedestrian activating the push button had fair-to-poor (kappa < 0.75) agreement.  Observation of eye gaze had poor agreement due to the difficulty in seeing pedestrian head movements in the low-quality video.  Distractions had poor-to-good agreement among Chapel Hill coders, but poor agreement among Portland coders.  Interactions between motorists and pedestrians had poor-to-good agreement among Portland coders. Poor agreement for pedestrian behaviors, distractions, and interactions is in part due to the quality of the video used for the test, which made it hard to observe pedestrian head movements and other activities. Chapel Hill video was collected using lower-quality cameras than those used in Portland. This decision was deliberate, due to UNC’s Internal Review Board (IRB) concerns about pedestrian privacy. Lower-quality video makes it very difficult to see faces and identify individuals, and thus improves privacy. PSU’s IRB did not have this concern; therefore, higher-quality video could be used. (Note that the Chapel Hill intercept survey video was higher quality but taken from an angle sufficiently high that faces were not likely to be identified.) Because the PSU coders were trained and tested weeks after the UNC coders had already coded most of the Chapel Hill video, it was not possible to make changes in the basic coding procedures at that time to make improvements in the PSU interrater reliability results for the distraction and interaction variables. However, because the Portland video is much better quality than the Chapel Hill video and PSU coders mostly only coded Portland video, the actual agreement between coders is expected to be higher than that reported here.

269 Due to the poor interrater agreement for some of the variables, results for these variables are either not reported or are noted as less reliable. Methods To test the consistency of video coding, interrater reliability tests were performed using statistical tests to compare the coding of the same pedestrians between coders. All the coders at both universities coded the same 15-minute video segment (5:00 PM to 5:15 PM), in which 43 pedestrians crossed at a RRFB crossing on West Franklin Street in Chapel Hill. Two types of statistical tests were employed: mean absolute percent difference (MAPE) for comparing MV volume, pedestrian delay, and crossing time; and intraclass correlation coefficient (kappa statistic) for comparing categorical variables. MAPE was used for comparing MV traffic volume per minute, pedestrian delay per pedestrian and pedestrian crossing time per pedestrian, where the “ground truth” for a given pedestrian was defined as the average pedestrian delay (or MV volume or pedestrian crossing time, depending on the metric to be evaluated) for that pedestrian averaged across all the coders. For example, if the average of the pedestrian delay observed by six coders for a given pedestrian was 2 seconds, the MAPE was computed as the absolute value of the difference between the pedestrian delay observed by a given coder and the 2-second average divided by the 2 second average. MAPE = 1 𝑝×𝑐 ∑ ∑ |𝑥𝑖𝑗−𝑚𝑖| 𝑚𝑖 𝑝 𝑖=1 𝑐 𝑗=1 where xij = MV traffic volume for the minute prior to pedestrian i stepping off the curb, pedestrian delay for pedestrian i, or pedestrian crossing time for pedestrian i, as observed by coder j; mi = mean MV traffic volume for the minute prior to pedestrian i stepping off the curb, mean pedestrian delay for pedestrian i, or mean pedestrian crossing time for pedestrian i; p = total number of pedestrians; and c = total number of coders. For the categorical variables, the intraclass correlation coefficient (kappa statistic, κ) was used (Fleiss 1981) as presented by Green (1997): 𝜅 = 1 − 𝑛𝑚2 − ∑ ∑ 𝑥𝑖𝑗 2𝑘 𝑗=1 𝑛 𝑖=1 𝑛𝑚(𝑚 − 1)∑ 𝑝𝑗𝑞𝑗 𝑘 𝑗=1 where κ = intraclass correlation coefficient (kappa statistic); k = number of categories (options) with counting variable j; for example, k=3 for gender because three gender categories were coded (male, female, indeterminate); m = number of coders; x = number of ratings coded in a given category; for example, if five of the six coders coded a given pedestrian as male, x=5; n = number of pedestrians with counting variable i; pj = the overall proportion of coding in a category = ∑ 𝑥𝑖 𝑛 𝑖=1 𝑛𝑚 ; and

270 qj = 1 − pj. If coders are in complete agreement, κ = 1. If κ = 0, the agreement between coders is equal to random agreement. If κ < 0, the agreement between coders is even less likely than random agreement (Green 1997). Generally, for this analysis, a value of κ > 0.75 was considered good agreement, between 0.4 and 0.75 was considered fair agreement, and less than 0.4 was considered poor agreement. Coding was compared between coders at each university, for all the observed crossing pedestrians, which were the same between coders. There were four coders at UNC (m=4) and six at PSU (m=6). For UNC, 23 individuals or groups of pedestrians had matching step-off-the-curb times between all four coders (n=23). This result means that 23 of the 27 pedestrian crossing groups matched within three seconds for all four coders. For PSU, ten individual pedestrians (n= 10) had matching step-off-the-curb times between all six coders and fourteen individuals or groups of pedestrians (n=14) had matching step-off-the-curb times between all six coders. That means that 14 of the 27 pedestrian crossing groups matched within three seconds between all six coders. Results Table C2-3 shows results of the comparison of MAPE for the MVs traffic volumes, pedestrian crossing times and pedestrian delay. Generally MV traffic volumes and pedestrian crossing time were coded with acceptable consistency since both are less than 15% average absolute percent difference (MAPE) between average and individual values. Pedestrian delay had higher variability due to the smaller numeric value (2 seconds is the average pedestrian delay). There is a limit to how precise any one human video observer can be in recording the exact second when a pedestrian arrived at the curb or pushed the button and when that pedestrian stepped off the curb. There is some judgement involved especially for determining the precise second when a pedestrian arrives at the curb, as pedestrians may not come to a full and complete stop. For this reason, although the MAPE is high, this result is still considered acceptable. Table C2-3. Comparison of Vehicle Volume and Pedestrian Crossing Time and Delay Metrics. Metric Error (MAPE) Interpretation Average Units MV traffic volume 11% Fair 21 Motor vehicles/minute Pedestrian crossing time 13% Fair 9 Seconds Pedestrian delay 29% Poor 2 Seconds For the categorical variables a separate interrater reliability test was conducted for each University because video was collected first in Chapel Hill and later in Portland. Results of the interrater reliability test for the categorical variables is reported in Table C2-4. Table C2-4. Summary of Interrater Reliability for Categorical Variables. Category Chapel Hill Portland κ Interpreta tion # of Responses κ Interpret ation # of Responses Direction 1.00 Good 69 0.94 Good 70 Size of group 1.00 Good 92 1.00 Good 84 Type of group 0.94 Good 92 1.00 Good 84

271 Category Chapel Hill Portland κ Interpreta tion # of Responses κ Interpret ation # of Responses Gender 0.74 Fair 92 0.53 Fair 60 Did ped activate the push-button? 0.72 Fair 92 0.38 Poor 84 Eye Gaze 1 (looked for traffic before crossing) 0.22 Poor 69 0.08 Poor 60 Eye Gaze 2 (looking up, down, at traffic or others in the group) 0.20 Poor 92 −0.06 Poor 60 Pedestrian Delay 0.54 Fair 69 0.46 Fair 60 Delayed due to motorist behavior 12 12 Delayed due to signal timing or lights not flashing 3 0 Delayed when ped motioned driver through 0 0 Not delayed 53 48 Can't tell 1 0 Crosswalk Compliance 0.87 Good 92 * 60 Distractions 92 60 Talking with others crossing 0.69 Fair 17 no data 0 Talking on phone 0.85 Good 7 0.17 Poor 2 Looking at phone/book 0.37 Poor 5 −0.02 Poor 1 Wearing headphones/earbuds no data N/A 0 no data N/A 0 Not engaged with device/others 0.48 Fair 56 0.03 Poor 51 Can’t tell −0.08 Poor 7 −0.11 Poor 6 Behaviors (for a group, choose all that apply to anyone in the group) 93 60 Talking to others present 0.65 Fair 15 no data N/A N/A Waved to drivers 0.48 Fair 4 −0.02 Poor 1 Negative gesture to drives no data N/A 0 no data N/A 0 Used wheelchair/walker no data N/A 0 no data N/A 0 Used walker no data N/A 0 no data N/A 0 Used scooter no data N/A 0 no data N/A 0 N/A 0.72 Fair 74 -0.02 Poor 59 Interaction in Lane 1 (nearest to ped) 95 0.28 Poor 60 Ped dodged right or left to avoid * N/A 1 * N/A 1 Ped sped up to avoid no data N/A 0 no data N/A 0 Ped stopped or slowed to avoid * N/A 2 no data N/A 0 MV stopped/slowed behind sharks teeth/stop bar * N/A 3 0.08 Poor 9 MV stopped/slowed but encroached on ped space 0.86 Good 21 0.33 Poor 6 Motorist did not yield * N/A 3 * N/A 1 No interaction 0.77 Good 65 0.71 Fair 43 Interaction in Lane 2 95 62 Ped dodged right or left to avoid no data N/A 0 * N/A 1 Ped sped up to avoid no data N/A 0 no data N/A 0 Ped stopped or slowed to avoid no data N/A 0 no data N/A 0 MV stopped/slowed behind sharks teeth/stop bar * N/A 1 −0.02 Poor 9 MV stopped/slowed but encroached on ped space 0.95 Good 67 0.45 Fair 23

272 Category Chapel Hill Portland κ Interpreta tion # of Responses κ Interpret ation # of Responses Motorist did not yield * N/A 3 * N/A 1 No interaction 1.00 Good 24 0.87 Good 28 Interaction in Lane 3 Multiple codes per ped 94 Multiple codes per ped 61 Ped dodged right or left to avoid no data N/A 0 no data N/A 2 Ped sped up to avoid no data N/A 0 no data N/A 0 Ped stopped or slowed to avoid * N/A 1 no data N/A 0 MV stopped/slowed behind sharks teeth/stop bar 0.88 Good 9 0.05 Poor 16 MV stopped/slowed but encroached on ped space 0.91 Good 46 0.34 Poor 19 Motorist did not yield * N/A 2 no data N/A 0 No interaction 0.91 Good 36 0.25 Poor 24 Interaction in Lane 4 93 57 Ped dodged right or left to avoid no data N/A 0 no data N/A 0 Ped sped up to avoid no data N/A 0 no data N/A 0 Ped stopped or slowed to avoid no data N/A 0 no data N/A 0 MV stopped/slowed behind sharks teeth/stop bar 0.81 Good 12 0.25 Poor 16 MV stopped/slowed but encroached on ped space 0.95 Good 25 0.54 Fair 8 Motorist did not yield * N/A 3 no data N/A 0 No interaction 0.90 Good 53 0.31 Poor 33 Notes: MV = motor vehicle. *Insufficient data. Pedestrian direction of travel was coded as the exact opposite by one of the UNC coders and as east– west instead of north–south by one of the PSU coders, but disregarding these errors, agreement on direction of pedestrian travel was very good. Generally, agreement between coders on group size and type of group was near perfect. Gender had fair agreement. Coding whether the pedestrian pushed the button or not had fair-to-poor agreement. Observations of direction of pedestrian eye gaze had very poor agreement, largely due to the poor quality of the video making it hard to observe pedestrian head movements. Eye Gaze 2 was only coded by one of the Portland coders, leading to very poor agreement. Pedestrian delay was also coded qualitatively in terms of what caused the delay (e.g., motorist behavior, RRFB not flashing). Agreement for this metric was fair, with most (77 to 80 percent) pedestrians coded as “not delayed.” Crosswalk compliance, which coded whether pedestrians stayed in the crosswalk markings or veered out, had good agreement among the UNC coders, but PSU coders rarely coded pedestrians as veered out. Distractions were challenging to code, because some of the distractions are rare and difficult to observe, such as “wearing headphones/earbuds,” which could not be seen in the Chapel Hill video. Coders were instructed to code all that apply, so coding was compared separately for each type of distraction, some of which were not coded at all by any of the coders. For both coding teams, the not-distracted option (“not engaged with device/others”) was the most common code. The most common distraction coded by the UNC coders was “talking with others while crossing,” but PSU coders did not code this at all. As with distractions, coders were instructed to code all behaviors that apply to anyone in the group of pedestrians, so coding was compared separately for each type of behavior. For Chapel Hill “talking to others present” and “waving to drivers” had fair agreement. For Portland, “waved to drivers” was only coded once,

273 “talking to others present” was not even an option for coders (since it was already coded under distractions) and none of the other behaviors were coded; therefore, comparisons could not be made for pedestrian behavior. Similarly, interactions were coded as all that apply. Interactions were coded for each lane of motor vehicle traffic. For the location in the test video, there were four lanes of traffic that each pedestrian had to cross, two lanes in each direction. The lanes were coded from closest to where the pedestrian started crossing to farthest from the pedestrian. Interactions with bicyclists were also coded, but because there were no such interactions in the test video, and such interactions were rare overall, there were no data to compare raters for bicyclist–pedestrian interaction. The most common interactions were “MV stopped/slowed behind sharks teeth/stop bar” and “MV stopped/slowed but encroached on pedestrian space”. “Motorist did not yield” was also coded in some cases where the motorist had sufficient distance and time to stop but chose not to. Because the video angle did not show enough of the motorist approach (could not see when motorist crossed the stopping distance threshold), motorist ability to stop was coded subjectively. Interaction coding was much more consistent between Chapel Hill coders, with most being coded good, while the Portland coders were less consistent, varying from poor to fair for the interactions coded. This result may have been in part because there were 4 Chapel Hill coders and 23 matching pedestrians between Chapel Hill coders, but more coders (6) and fewer matching pedestrians (10) for the Portland coders. Results for variables with poor interrater agreement were either not reported or were noted as being less reliable.

274 Attachment C3: Naturalistic Walking Study Naturalistic Walking Study Recruitment Flyer Researchers from the UNC’s are conducting a study about the experience of walking in the Chapel Hill– Carrboro area. Being in a research study is completely voluntary. You can choose not to be in this research study. You can also say yes now and change your mind later. If you agree to take part in this research, you will be asked to wear a wristband and carry with you a GPS device. The wristband will collect data about your heartrate and stress responses, and will be stored on a separate, protected server. Your participation in this study will take about one week. Each day, we will ask you for complete a brief 3-min survey. This survey will ask about your walks that day, how long each walk was, how you felt while you walked, and if you were with anyone else while you walked. All participants will receive $200 to compensate for their time. We expect that 20 people will take part in this research study. We are looking for participants who:  Are at least 18 years of age  Have daily access to a smartphone  Are willing and able to wear a biosensing wristband on their wrist and carry a small GPS device with them for one week  Are willing and able to meet members of the research team at the UNC HSRC at 730 Martin Luther King Jr. Blvd, Chapel Hill, NC on two occasions (once before and once after the study)  Walk daily or at least 4 times a week for at least 10 minutes at a time within the circled area below: Source: Map data © 2019 Google If you have any questions about this research, please contact the Study Investigator, Seth LaJeunesse by calling 919-962-4236 or emailing lajeune@hsrc.unc.edu. If you have questions or concerns about your rights as a research subject, you may contact the UNC Institutional Review Board at 919-966-3113 or by email to IRB_subjects@unc.edu.

275 Materials used in the Naturalistic Walking Study SpyTec GPS device used in the study Empatica E4 biosensing wristband used in the study

276 Intake Questionnaire Today's date: 1. First name: 2. What is your birthday (mm/dd/yyyy)?: 3. What is your gender?  Female  Male  Self identify: 4. Do you consider yourself to be of Hispanic/Latino origin?  Yes  No 5. Do you consider yourself…(select all that apply)?  Hispanic, Latino, or Spanish origin  American Indian or Alaska native  Asian  Black or African American  White  Prefer not to say  Other: ___________________ 6. What is the zip code of your home address? __ __ __ __ __ 7. What is the highest level of school you have completed?  Less than high school  High school diploma/GED  Some College or Associate’s degree  Bachelor’s degree  Graduate or professional degree 8. For how many years have you walked around Chapel Hill? If less than one year, please write “less than one year.” ________________. 9. At what time of day do you normally start walking outside of the house? ______AM/PM 10. By what time of day are you normally finished with walking outside? ________AM/PM 11. Email address: ___________________________________ 12. Mobile phone: _______________________________ What time of day would you like to receive the daily survey? ________AM/PM

277 Attachment C4: Pedestrian Network LOS The following presents text on pedestrian network LOS. This text is designed to be inserted into the Planning and Preliminary Engineering Applications Guide to the HCM (NCHRP Report 825) prior to the references section in Chapter O. 9. Pedestrian Networks This section presents a method for evaluating the pedestrian connectivity provided by a defined pedestrian network, which could range from a small neighborhood to an entire city. FHWA’s Guidebook for Measuring Multimodal Network Connectivity (Twaddell et al. 2018) defines the following elements of pedestrian connectivity:  Network Quality. How does the network support users or pedestrians of varying levels of experience, ages, abilities, and comfort with walking?  Network Completeness. How much of the network is available to pedestrians?  Network Density. How dense are the available links and nodes of the pedestrian network?  Route Directness. How far out of their way do users have to travel to find a facility they can or want to use?  Access to Destinations. What destinations can be reached using the network? The following method, developed by NCHRP Project 17-87 (Ryus et al. 2020), starts by analyzing the quality of the links and nodes forming the network, and then uses the results to evaluate network completeness, network density, and route directness. Network density can be assessed separately using a measure such as number of 3- and 4-leg intersections per acre or street centerline miles per square mile. The method can be performed by hand for relatively small study areas, but is best performed with the assistance of GIS software for larger study areas. Step 1. Estimate PLTS for Facilities The following simplified version of the PLTS method developed by the ODOT 2019) is used to develop a PLTS for a given sidewalk or path. The required input data are: sidewalk physical and effective width, sidewalk condition, physical buffer type, and posted speed limit. The effective width considers shy distance from the curb (for curb tight sidewalks), as described in the HCM, and can also consider sidewalk obstructions when data are available. There are four PLTS levels as follows:  PLTS 1 – Represents little to no traffic stress and requires little attention to the traffic situation. The facility is a sidewalk or shared-use path with a buffer between the pedestrian and MV facility. Pedestrians feel safe and comfortable on the pedestrian facility and are willing to use this facility.  PLTS 2 – Represents little traffic stress and requires more attention to the traffic situation than of which young children may be capable. This would be suitable for children over 10, teens, and adults. Sidewalk condition should be good with limited areas of fair condition and most users are willing to use this facility.  PLTS 3 – Represents moderate stress and is suitable for adults. An able-bodied adult would feel uncomfortable but safe using this facility. This category includes higher-speed roadways with small buffers, and some users are willing to use this facility.  PLTS 4 – Represents high traffic stress. Only able-bodied adults with limited route choices would use this facility. Traffic speeds are moderate to high with narrow or no pedestrian facilities provided. Facilities include high-speed, multilane roadways with narrow sidewalks, no sidewalks, and buffers. Only the most confident or trip purpose driven users will use this facility.

278 Exhibits 116A and 116B are used to determine a facility’s PLTS. The higher (i.e., worse) of the PLTS scores from the two exhibits determines the PLTS. Exhibit 116A. PLTS for Sidewalk Condition. Actual/Effective Sidewalk Width (ft) Sidewalk Condition Good Fair Poor Very Poor No Sidewalk Actual <4 PLTS 4 PLTS 4 PLTS 4 PLTS 4 PLTS 4 ≥4 to <5 PLTS 3 PLTS 3 PLTS 3 PLTS 4 PLTS 4 ≥5 PLTS 2 PLTS 2 PLTS 3 PLTS 4 PLTS 4 Effective ≥6 PLTS 1 PLTS 1 PLTS 2 PLTS 3 PLTS 4 Source: ODOT 2019. Notes: Can be applied to other facilities such as walkways and shared-use paths. Effective width is available/usable area for the pedestrian. Consider increasing the PLTS one level (max PLTS 4) for segments that do not have illumination. Effective width should be proportional to volume as higher-volume sidewalks should be wider than the base six feet. Use a minimum PLTS 2 for higher-volume sidewalks that are not proportional. Exhibit 116B. PLTS for Physical Buffer Type. Physical Buffer Type Buffer Typea Prevailing or Posted Speed ≤ 25 mph 30 mph 35 mph ≥ 40 mph No buffer (curb tight) PLTS 2 PLTS 3 PLTS 3 PLTS 4 Solid surface PLTS 2b PLTS 2 PLTS 2 PLTS 2 Landscaped PLTS 1 PLTS 2 PLTS 2 PLTS 2 Landscaped with trees PLTS 1 PLTS 1 PLTS 1 PLTS 2 Vertical Source: ODOT 2019. Notes: a Combined buffers: If two or more of the buffer conditions apply, use the most appropriate, typically the lower-stress level. b If street furniture, street trees, lighting, and/or planters are present the PLTS can be lowered to PLTS 1. Step 2. Estimate PLTS for Nodes Determine the PLTS for Crossings As Follows:  Signalized crossings: PLTS 2 for all signalized crossings.  Uncontrolled crossings: Convert the HCM’s LOS for uncontrolled crossings as follows: LOS A–D = PLTS 2, LOS E = PLTS 3, LOS F = PLTS 4, using Exhibit 115A or similar service volume tables, the computational engine on HCM Volume 4, or the HCM method directly. Note that PLTS is never 1 for crossings, because it represents a condition requiring little attention to the traffic situation. In addition, the HCM LOS method was based on the perspective of adults, while a PLTS 1 facility is considered suitable for younger children.

279 Step 3. Evaluate Pedestrian Network Completeness The study area pedestrian network can be mapped using color coding for different link and node PLTS values. Mapping the network with PLTS 3 or better provides a picture of basic network connectivity, while mapping the network with PLTS 2 or better provides a picture of network connectivity for a broader range of users, including older children and elderly pedestrians. “Connectivity islands” can also be mapped using different colors, showing the extent of individual subnetworks connected by links and nodes with a given PLTS or better. [Example figure to be provided in the final draft version.] Finally, the percentage by length of the study area network providing a given PLTS or better can be determined. Step 4. Evaluate Route Directness Optionally, the shortest network distance between selected origins and destinations can be compared to the shortest distance at a given PLTS (or the fact that no such route is available is identified). Step 5. Evaluate Access to Destinations Optionally, for a neighborhood-sized study area, an analysis could determine which selected destinations (e.g., schools, grocery stores) are accessible from the study area at a given PLTS. For a specific destination, an analysis could determine what percentage of the destination’s market or service area is accessible at a given PLTS. References Fleiss, J.L. (1981). The Measurement of Interrater Agreement. In Statistical Methods for Rates and Proportions, Second Edition. John Wiley & Sons, Inc., New York, pp. 212–304. Green, A.M. (1997). Kappa Statistics for Multiple Raters Using Categorical Classifications. Proceedings, Twenty- Second Annual SAS® Users Group International Conference, San Diego, California.