2009 travel time study update

2009 Travel Time Study Update

A statewide travel time study was conducted in 2000 to determine the relationship between actual travel speeds and

roadway class/posted speed limit. In 2003, this study was updated to stratify the sample draw by posted speed limit

which had since become available as an attribute in the state system roadway information database. In August 2009,

the study was updated again to revise the travel speeds on 65 MPH freeways. This is being done because in July

2009, differential truck speed limits on 65 MPH freeways were removed and it is expected that this will increase

overall drive speeds on these roads. The study was conducted using floating car methodology following all of the

procedures of the previous study to which the reader is referred for details.

For this study, all segments from the previous studies with 65 MPH posted speed were resurveyed, including those

without a speed limit change (non-interstates). The same segments were rerun so that just the changes in speeds

over time could be investigated without clouding the issue with sampling noise. Figure 1 and Table 1 shows the

sample segments as both a map and a table respectively.

Figure 1.Speed Study Segments

SampleID Road Name Start Road End Road Sch. Date Sch. Time

101 I-75 Bluelick Rd. Lincoln Hwy. 18-Aug 11:00

102 I-75 SR 67 CR 208 18-Aug 10:30

103 I-675 SR 4 SR 444 17-Aug 16:30

104 I-71 US 35 SR 41 17-Aug 8:00

105 I-70 SR 83 SR 723 20-Aug 11:00

106 I-75 SR 103 SR 235 18-Aug 12:00

107 I-80/I-90 Fulton/Lucas Co. Line Airport Hwy Exit 3A 18-Aug 14:00

108 I-76 SR 534 N. Bailey Rd. 19-Aug 13:30

109 I-71 SR 61 SR 95 19-Aug 7:30

110 I-77 SR 313 SR 209 20-Aug 10:30

111 I-70 US 127 SR 503 17-Aug 13:30

112 I-75 SR 47 Sidney-Wapakoneta Rd. 17-Aug 15:00

113 I-77 US 36 SR 751 20-Aug 9:30

114 I-71 SR 301 SR 539 19-Aug 9:30

142 SR-129 JCT SR-747 Maud-Hughes Rd; TR-138 17-Aug 11:00

143 US-33 TR-55 CR-10 18-Aug 8:30

144 US-33 Scotts Lawn Rd US-42 18-Aug 7:30

202 US 33 CR 33A I-75 18-Aug 10:00

214 US 23 SR 199 SR 294 18-Aug 16:00

1101 I-75 C-20 Tylersville Rd SR-63 Hamilton-Lebanon Rd 17-Aug 11:30

1102 I-275 SR 125 SR 32 17-Aug 9:30

1105 I-71 Stringtown Rd (Grove City) SR-104 Frank Rd 20-Aug 14:30

1106 I-270 Georgesville Rd US-62 Harrisburg Pike 20-Aug 15:00

1107 I-75 US 68 US 224 18-Aug 12:30

1109 I-70 SR 310 SR 158 20-Aug 13:00

1110 SR 2 N. Lake St. Leavitt Rd. (SR 58) 19-Aug 11:00

1111 I-90 SR 611 SR 83 19-Aug 11:30

1112 I-80 SR 48 I-680 19-Aug 14:00

2106 I-71 SR-104 Frank Rd Greenlawn Ave 20-Aug 14:00

2108 I-670 I-70 Grandview Ave 20-Aug 15:30

2110 SR 16 O' Bannon Rd Marne Rd 20-Aug 8:00

Table 1. Speed Study Segments

After collecting the data, it was entered into a spreadsheet and edited/cleaned. During this process several segments

were dropped from the study. Sample segment 1101 was dropped in its entirety since the section was in a

construction zone with reduced speed limits. For the same reason, part of segment 214 was removed as well as the

off ramp at the end of segment 101 (note, ramp speed updates were not part of this update, however, to be consistent

with the previous runs, sample segments including ramp sections were run the same way in this update). A small

amount of segment 1112 was removed in the IR 80/680/SR 11 interchange area as being inconsistent with the

previous segment definition.

Following the data checking/editing, the segments were grouped as in the previous study to produce a single speed

estimate per study segment. These segment specific speeds were then compared to the speeds on the same segments

from the previous study; these comparisons are shown in the graph of Figure 2. As the figure shows, generally the

speeds were higher in the new study.

Figure 2. Comparison of Speeds from the Original and Updated Studies

Following this comparison the averages by speed table cell were calculated and compared to the old speed table

values as shown in Table 2. In this table a posted speed of 58 means 60 for cars, 55 for trucks, while 63 means 65

for cars and 55 for trucks. The one segment with PS 58 in the CBD class drops from the study. Indeed, removal of

this segment is the main reason for the speed increase on CBD routes (there are very few CBD 65 MPH freeways

and only 4 segments in the study). Partly for this reason and also because the 65 MPH speed shown for this class

was rounded up from 64.6, a speed of 64 MPH was used for this group in the final speed table. For urban routes,

there are only 8 segments in the current study versus the original 9 due to the removal of segment 1101 as previously

mentioned. Seven of the segments are Interstates with 65 MPH for all vehicles while only one has the differential

speed limit. The table shows a marked difference between the two, however, 1 sample segment isn’t enough to

draw conclusions. Since the 67 MPH speed shown was actually rounded up, the class average of 66 MPH was used

for this class in the final speed table. For rural segments, 19 segments were run with 14 being interstates and 5 not.

This is one more segment than existed in this class originally because segment 105 was not run previously due to

construction at that time. While the 65 MPH routes are slightly faster than the 63 MPH, the difference is less than 1

MPH. Interestingly, when the study was done originally, the non-interstate routes were faster because of their lower

percent trucks. With the increased truck speed limit, the interstates are now faster but not by much. The revised

speed for all routes of this class will be 68 MPH.

50

55

60

65

70

75

Run Time Speed Comparison

rspd

rspd_old

Running Speed

Posted Speed

Class 58 63 65 Old

Rural (1) 68.0 68.6 66

Urban (11) 60.7 67.1 65

CBD (21) 59.4 64.6 61

Total 59.4 66.8 67.7

Number of Segments

Posted Speed

Class 58 63 65 Old

Rural (1) 5 14 18

Urban (11) 1 7 9

CBD (21) 1 3 4

Total 1 6 24 Table 2. Running Speeds and Number of Segments

Based upon the previous discussion, the speed tables were updated by modifying 3 cells in both the total and run

time speed tables (rural, urban and CBD 65 MPH routes). The other 65 MPH cells for arterial streets (which hold

dummy values derived from these 3 cells in the original study) were not changed as they generally do not exist and

there is no data one way or the other to support the values in these cells. Table 3 compares the old and new run time

speed tables, total time speed was modified similarly.

NEW

New Code Definition 25 30 35 40 45 50 55 60 65

1 rural freeway -27 -32 -38 -44 48 55 57 62 68

2 rural arterial 25 30 36 41 46 51 55 -62 -66

3 rural 4+ lane collector 25 30 36 40 45 51 56 -62 -66

4 rural 2 lane collector, flat 25 30 36 40 46 50 54 -62 -66

5 rural 2 lane collector, hilly 25 30 36 39 41 45 48 -62 -66

6 rural local, flat 25 30 36 39 43 47 52 -62 -66

7 rural local, hilly 25 30 34 36 39 40 41 -62 -66

8 rural local, township, flat 25 30 36 37 40 44 48 -62 -66

9 rural local, township, hilly 25 30 30 30 30 30 31 -62 -66

11 urban freeway -27 -32 -38 -44 46 56 59 60 66

12 urban arterial 27 31 35 39 43 49 53 -60 -65

13 urban collector 27 31 35 39 43 49 53 -60 -65

16 urban local 27 31 35 39 43 49 53 -60 -65

21 cbd freeway -26 -31 -37 -41 45 50 54 60 64

22 cbd arterial 26 29 32 37 42 46 50 -60 -60

23 cbd collector 26 29 32 37 42 46 50 -60 -60

26 cbd local 22 24 27 30 34 37 40 -60 -60

40 rural ramp 49 49 49 49 49 49 49 49 49

50 urban ramp 43 43 43 43 43 43 43 43 43

OLD

New Code Definition 25 30 35 40 45 50 55 60 65

1 rural freeway -27 -32 -38 -44 48 55 57 62 66

2 rural arterial 25 30 36 41 46 51 55 -62 -66

3 rural 4+ lane collector 25 30 36 40 45 51 56 -62 -66

4 rural 2 lane collector, flat 25 30 36 40 46 50 54 -62 -66

5 rural 2 lane collector, hilly 25 30 36 39 41 45 48 -62 -66

6 rural local, flat 25 30 36 39 43 47 52 -62 -66

7 rural local, hilly 25 30 34 36 39 40 41 -62 -66

8 rural local, township, flat 25 30 36 37 40 44 48 -62 -66

9 rural local, township, hilly 25 30 30 30 30 30 31 -62 -66

11 urban freeway -27 -32 -38 -44 46 56 59 60 65

12 urban arterial 27 31 35 39 43 49 53 -60 -65

13 urban collector 27 31 35 39 43 49 53 -60 -65

16 urban local 27 31 35 39 43 49 53 -60 -65

21 cbd freeway -26 -31 -37 -41 45 50 54 60 62

22 cbd arterial 26 29 32 37 42 46 50 -60 -60

23 cbd collector 26 29 32 37 42 46 50 -60 -60

26 cbd local 22 24 27 30 34 37 40 -60 -60

40 rural ramp 49 49 49 49 49 49 49 49 49

50 urban ramp 43 43 43 43 43 43 43 43 43Table 3. Comparison of Revised and Old Run Time Speed Tables

2003 Speed Study Update

December 2003

The following technical memorandum briefly describes the 2003 update to the statewide speed study. This report is

not all inclusive and should be considered an addendum to the 2000 speed study report.

The 2000 speed study was a stratified random sample drawn from the road inventory database. The stratification

was based on various facility and area types. No stratification was done on posted speed since this did not exist in

the database at the time even though this was anticipated as the most important explanatory variable. The intent was

to simply do linear regressions across posted speed in each category. The problem that arose, however, was that

posted speeds were heavily clustered at only a few values in each category which left large parts of the resulting

speed table based on limited or nonexistent data. The 2003 update targeted specific combinations of posted speed

within the original categories using the statewide model network to draw the sample. This network contains all

collectors and better but does not contain all local streets. However, to maximize the impact of the limited

resources, local street categories were not updated in 2003 so this posed no problem.

Figure 1 shows the distribution of the study. Black segments are the 2000 sample, blue is the 2003 and red are

additional adjacent segments run with the 2003 (these additional segments existed in the 2000 sample as well but are

not shown). The add on segments are simply adjacent segments with the same characteristics of the sample segment

which are added to produce sample segments of from 1 to 2 miles in length.

The data was collected in August/September 2003. Unlike the 2000 study, only off-peak runs were made since the

intention is to update the free flow speed tables. Beyond that, the same procedures were used as in the 2000 study.

After cleaning and editing the data, segment specific distance, total time, run time and average stops were

calculated. Run times subtracted out control point stop time. Two departures from the 2000 analysis were made at

this point, first the mid block stops were not removed when calculating run time since this delay won’t be accounted

for in intersection modeling. Second, the acceleration/deceleration delay were no removed on a segment by segment

basis since many segments are too short to fully handle this delay. This delay was later accounted for after grouping

the segments as discussed below. The 2000 data was reanalyzed to use this same method. While doing this, a

number of corrections were made to the 2000 data and a couple of samples were dropped as unusable.

It was discovered while developing the 2003 sample that 12 of the 14 samples in category 2 were actually freeways

belonging in category 1. Thus category 2 (rural 4 lane arterials) was dropped. When reanalyzing the 2000 data

these 12 samples were moved to category 1 while the remaining 2 (samples 205 and 210) were added to category 3

(rural 2 lane arterials) to create a generic rural arterial category.

Pivot tables were then used to consolidate the 2000 data into facility type/posted speed categories by sample

segment. Thus unlike the 2000 analysis where every segment of every sample was analyzed individually, all

segments with the same posted speed on a given sample were combined and analyzed as a unit for this analysis.

This method is the statistically correct one given the way the sample was drawn since to analyze all segments

individually biases the results to samples with more control points.

This same process was followed for the 2003 data. One difference, however, was that segments were flagged based

on the posted speed category they were drawn for. Because a posted speed stratification was used for this sample,

segments falling outside the intended posted speed were removed since to include them would bias the other posted

speed categories they fell in. For this purpose, posted speeds on the even 10’s were included if matching the next

highest category (thus if a segment was drawn for 45 MPH, it was retained if it had a posted speed of 40 MPH or 45

MPH). The reason is that even 10 categories are rare so when the posted speed stratification was made, no samples

were drawn from independently from these categories, rather they were lumped for sample selection purposes. This

process resulted in 374 out of 930 miles of studied roadway (40%) being excluded from the study including 57 of

the 276 sample segments being disregarded entirely because the sampled posted speed didn’t actually exist

anywhere on the sample.

After the segments were consolidated, acceleration/deceleration delay was then added on these longer pieces. A

check was made to insure all segments were long enough to handle the distance necessary to fully develop this

acceleration/deceleration (which they were for all but 2 cases which were addressed by placing an upper bound on

the running speed). The precise details of these various computations won’t be addressed here, for the most part the

formulas etc. can be seen in the spreadsheet data2003.xls. Two exceptions are the computation of segment distances

and the intermediate pivot tables used to develop the consolidated segments. The computation for distance involved

comparing with adjacent records and the formula was replaced with values so the data could be resorted afterwards.

To pivot tables necessary to consolidate the data had to be done separately for each variable and then the values

copied and combined (the reason being that Excels pivot tables place multiple variables row-wise but they were

needed column-wise because the segment ID’s had to be row-wise since Excel doesn’t allow enough columns to do

them column-wise).

Figure 2 shows the number of segments in each facility type/area type/posted speed category from the 2000 sample

and the combined 2000/2003 sample. This clearly illustrates the areas that were targeted in 2003 (namely, lower

speed rural arterials and collectors and higher speed urban arterials and collectors.) Figure 3 shows the revised total

and run time free flow speed tables developed from this study. Note that these values have been smoothed to

provide for logical, consistent values. In performing this smoothing, cells that had over 10 sample segments were

fixed, those between 3 and 9 samples were semi-fixed (i.e., they could be changed but reluctantly) while values in

cells with 2 or less samples were modified as necessary to produce the desired consistency. Figure 4 shows the total

time speeds graphically.

FIGURE 1.

2000 Speed Study Number of Segments

POSTED SPED

SPDCLASS 20 25 30 35 40 45 50 55 60 65 Total

1 1 2 2 5 3 15 28

2 2 2 15 19

3 1 2 1 1 14 19

4 2 1 1 3 19 26

5 2 5 1 4 16 28

6 1 1 13 15

7 1 1 1 12 15

8 1 13 14

9 2 2 11 15

11 1 4 2 9 16

12 2 18 6 4 3 2 35

13 1 7 1 19 2 4 2 1 37

16 12 2 1 15

21 1 5 5 4 15

22 14 19 3 36

23 16 1 13 1 31

26 14 14

40 13 1 1 2 17

50 14 1 12 1 28

2000/2003 Combined Study Number of Segments

POSTED SPED

SPDCLASS 20 25 30 35 40 45 50 55 60 65 Total

1 4 1 5 2 13 3 18 46

2 8 12 1 13 18 52

3 1 2 1 1 14 19

4 13 12 2 11 21 59

5 12 14 1 9 20 56

6 1 1 13 15

7 1 1 1 12 15

8 1 13 14

9 2 2 11 15

11 2 3 1 13 2 9 30

12 12 24 9 12 6 12 5 80

13 2 18 1 24 5 16 4 10 80

16 12 2 1 15

21 1 1 5 5 4 16

22 14 19 7 40

23 16 1 13 1 31

26 14 14

40 13 1 1 2 17

50 14 1 12 1 28

10 or more sample segments, best values

3-9 sample segments, use with caution

FIGURE 2.

Revised Speed Tables

Total Travel Time Speed

POSTED SPED

SPDCLASS 25 30 35 40 45 50 55 60 65

1 rural fwy 24 29 34 39 44 55 56 62 66

2 rural art 21 27 34 39 44 49 55 62 66

3 rural 4 coll 21 27 33 38 43 49 56 62 66

4 rural 2 col flat21 27 33 38 44 47 51 62 66

5 rural 2 col hill21 27 33 37 40 44 47 62 66

6 rural loc flat 21 27 33 37 41 43 46 62 66

7 rural loc hill 21 27 31 33 37 38 39 62 66

8 rural twp flat 21 27 33 35 37 40 42 62 66

9 rural twp hill 21 27 27 27 28 28 29 62 66

11 urban fwy 26 31 36 41 46 56 58 60 65

12 urban art 21 25 28 32 39 42 51 60 65

13 urban col 21 25 28 32 39 42 51 60 65

16 urban loc 21 25 27 31 38 40 46 60 65

21 cbd fwy 19 25 31 36 42 47 52 60 60

22 cbd art 18 22 26 30 35 38 41 60 60

23 cbd col 18 20 23 27 30 33 36 60 60

26 cbd loc 15 17 20 24 27 30 33 60 60

40 rural ramp 35 35 35 35 35 35 35 35 35

50 urban ramp 35 35 35 35 35 35 35 35 35

Running Time Speed

POSTED SPED

SPDCLASS 25 30 35 40 45 50 55 60 65

1 rural fwy 27 32 38 44 48 55 57 62 66

2 rural art 25 30 36 41 46 51 55 62 66

3 rural 4 coll 25 30 36 40 45 51 56 62 66

4 rural 2 col flat25 30 36 40 46 50 54 62 66

5 rural 2 col hill25 30 36 39 41 45 48 62 66

6 rural loc flat 25 30 36 39 43 47 52 62 66

7 rural loc hill 25 30 34 36 39 40 41 62 66

8 rural twp flat 25 30 36 37 40 44 48 62 66

9 rural twp hill 25 30 30 30 30 30 31 62 66

11 urban fwy 27 32 38 44 46 56 59 60 65

12 urban art 27 31 35 39 43 49 53 60 65

13 urban col 27 31 35 39 43 49 53 60 65

16 urban loc 27 31 35 39 43 49 53 60 65

21 cbd fwy 26 31 37 41 45 50 54 60 62

22 cbd art 26 29 32 37 42 46 50 60 60

23 cbd col 26 29 32 37 42 46 50 60 60

26 cbd loc 22 24 27 30 34 37 40 60 60

40 rural ramp 49 49 49 49 49 49 49 49 49

50 urban ramp 43 43 43 43 43 43 43 43 43 FIGURE 3.

FIGURE 4.

Statewide Travel Time Study

By

Gregory T. Giaimo

Ohio Department of Transportation

Division of Planning

Office of Technical Services

May 2001

Contents

Acknowledgements 2

Introduction 3

Study Description 4

Study Results 13

Conclusion 25

Appendix A Excerpt From (1) on How to Conduct Speed-Delay Studies 26

Appendix B List of Sample Segments for Travel Time Study 28

Appendix C Average Speed Calculated Directly From Database 33

Appendix D Regression Equation Derived Speeds 35

(1) "Model Specification and Data Collection Program For Small MPO Study Areas in Ohio"

Figures

Figure 1. Roadway Classification Scheme 4

Figure 2. CBD Area Definitions Map 5

Figure 3. Rural Area Sample Selection for Statewide Travel Time Study 6

Figure 4. Sample Segments Map 7

Figure 5. Travel Time Data Collection Form 8

Figure 6. Sample of Raw Data From Travel Time Study Database 9

Figure 7. Method of Determining Speed Table Values 11

Figure 8. Final Total Travel Time Based Speed Table 13

Figure 9. Final Running Speed Table 14

Figure 10. Average Speed versus Posted Speed on Rural Roads 15

Figure 11. Off Peak Average Speed versus Posted Speed on Urban Roads 16

Figure 12. Average Speed versus Posted Speed for Peak & Off Peak on Urban Freeways & Arterials 17

Figure 13. Average Speed versus Posted Speed for Peak & Off Peak on Urban Collectors & Locals 18

Figure 14. Average & Running Speed versus Posted Speed on Rural Roads 19

Figure 15. Average & Running Speed versus Posted Speed on Urban Roads 20

Figure 16. Average Speed versus Posted Speed for Rural & Urban Freeways 21

Figure 17. Average Speed versus Posted Speed for Rural & Urban Arterials 22

Figure 18. Average Speed versus Posted Speed for Rural & Urban Collectors 23

Acknowledgements

Project Manager Greg Giaimo, P.E.

Data Collection Alvin Whyte

Rena Puckett

Matt Hill

Gail Hershey

John Wirtz

Data Analysis Sam Granato

Introduction

A statewide travel time study was conducted in the summer of 2000. This study was conducted primarily to gather

data to be used in the statewide travel demand forecasting model being developed by ODOT and its consultants.

The study was conducted on over 300 1 to 2 mile long segments of roadway throughout the state. These segments

were randomly selected within certain categories and travel time was measured as documented in the next section.

Travel time was measured using the floating car method and therefore represent the travel speeds of cars, not trucks.

The results of the study are presented in the final section of this report.

Study Description

The travel time study was conducted following guidelines set forth in the "Travel Time Data Collection Handbook"

(FHWA-PL-98-035) and as further elaborated in ODOT's "Model Specification and Data Collection Program For

Small MPO Study Areas in Ohio" (see excerpt in Appendix A).

For this study, the roadways in Ohio were stratified into the following categories:

Figure 1. Roadway Classification Scheme

For each category (except ramps which are measure as part of their connecting freeway segment) 14 segments were

selected for study. This number was based on the computations shown in the Appendix (note that the small universe

correction factor was not needed due to the relatively large number of segments on a statewide basis). These

segments were selected using the Road Inventory database.

Data from both the state and local files was used. The class codes listed above were added as an attribute to this

data using the functional class and number of lanes fields (for non-state system routes the width field was used, any

width less than 39 feet was assumed to be a 2 lane road). While functional class could provide the distinction

between rural and urban roads, there is no field in the road inventory that distinguishes CBD areas. This distinction

was deemed necessary for travel modeling purposes so roadways in CBD areas were determined by selecting road

inventory segments that fell within the CBD polygons shown in Figure 2. These polygons were created using the

MPO area travel demand forecasting model network area types.

Once classified, the data was then dynamically segmented using this new attribute. Within each class the number of

miles of roadway was computed. This value was divided by 14 to obtain the sampling interval. The milage at

which the first segment was selected was determined randomly, additional segments were selected at the sampling

interval beginning at this first segment. The table below shows the sampling results for the rural area. Similar

tables result from sampling the urban and cbd areas.

This table shows for example that for class 2 (rural 4+ lane arterials) that there are 3.59 miles on the county system,

1135.71 miles on the state system and 0 miles on the township system. There are a total of 1139.3 miles statewide.

Dividing this by 14 gives a sampling interval of 81.38 miles. The first location was selected after accumulating

21.16 miles, the second at 102.54 etc. The segments were in no particular order in the database.

code definition code definition

1 rural freeway 21 cbd freeway

2 rural 4+lane arterial 22 cbd 4+lane arterial

3 rural 2 lane arterial 23 cbd 2 lane arterial

4 rural 4+lane collector, flat 24 cbd 4+lane collector

5 rural 2 lane collector, flat 25 cbd 2 lane collector

6 rural local, flat 26 cbd local

7 rural 4+lane collector, hilly 31 rural local, township, flat

8 rural 2 lane collector, hilly 32 rural local, township, hilly

9 rural local, hilly 41 rural ramp, off

11 urban freeway 42 rural ramp, on

12 urban 4+lane arterial 43 rural ramp, freeway-freeway

13 urban 2 lane arterial 51 urban ramp, off

14 urban 4+lane collector 52 urban ramp, on

15 urban 2 lane collector 53 urban ramp, freeway-freeway

16 urban local

hilly = ODOT districts 5, 9 10, 11

ramps not sampled separately, ramp segments will be picked up with freeway segments

Figure 2.

After selection, the selected locations were assigned a 4 digit ID (the first 2 digits being the class code, the second 2

being the unique location (1-14) within the class) and compiled in a database. From there the locations were plotted

with their ID labels using GIS. Street maps were referenced into this plot and using the plotted locations, street

names and from/to cross streets resulting in approximately 1 (urban) or 2 mile (rural) sections were determined and

entered into the database. Using the plotted locations, data collection schedules were then developed to minimize

the travel time between segments. Figure 4 shows the segments selected for analysis in the travel time study. Note

that the segments shown are the road inventory segments as dynamically segmented by the categories in Figure 1.

The actual length of road run was a 1 to 2 mile segment regardless of the length of the road inventory segment.

The data was collected using a DMI equipped vehicle. Checkpoints were established along the subject route at all

intersections involving traffic control on the route as well as rail crossings and changes in speed limit, number of

lanes or directional status (oneway versus twoway street). The travel time and distance between each checkpoint

was recorded using the DMI. The form used to collect this data is shown in Figure 5.

Each segment was run 4 times in rural areas and 6 times in urban areas. For two way streets half the runs were made

in each direction. Multiple runs were needed on each segment to obtain a statistically significant measure of the

travel time on the route. The number needed was calculated as shown in the Appendix. Generally routes with

greater variance in travel time require more runs. Since the actual variance is unknown, the roadway type can be

used to approximate this variance. The roadway type is in terms of signal density (higher density gives greater

variance), however since this also is unknown in general, the area type was used as a surrogate (cbd=high density,

urban=medium, rural=low. Using the generalized variances given in the Handbook and rounding yields 4 runs on

rural, 6 on urban and 8 on cbd, freeways always received 4 runs due to their lower variance. All urban and cbd

segments were run in both the off-peak and PM peak periods (thus an urban segment would have a total of 12 runs).

Rural segments were run off-peak only. In order to keep the number of peak and off-peak runs required in balance

with the number of peak-off peak hours available each day, the number of cbd runs was reduced from 8 to 6.

Figure 3. Rural Area Sample Selection for Statewide Travel Time Study

Jurisdiction Milage Random

Class Data County State Township Total Interval Start Mile

1 Milage 829.68 829.68 59.26 57.71

Segments 81 81

2 Milage 3.59 1135.71 1139.30 81.38 21.16

Segments 5 343 348

3 Milage 17.12 4113.87 0.30 4131.29 295.09 144.38

Segments 11 592 1 604

4 Milage 26.17 96.47 0.34 122.98 8.78 7.75

Segments 57 164 3 224

5 Milage 5272.91 5665.69 399.7 11338.30 809.88 360.51

Segments 1305 787 219 2311

6 Milage 12052.47 7.09 12059.56 861.40 192.66

Segments 4072 6 4078

7 Milage 4.15 44.03 0.14 48.32 3.45 0.83

Segments 20 55 1 76

8 Milage 3432.14 3762.46 95.55 7290.15 520.72 198.14

Segments 801 459 92 1352

9 Milage 7108.77 18.38 7127.15 509.08 41.30

Segments 2437 10 2447

31 Milage 19960.57 19960.57 1425.76 1025.21

Segments 16473 16473

32 Milage 16786.70 16786.70 1199.05 1149.07

Segments 17429 17429

Figure 4.

Travel Time

Study Location: Segment ID___________ Street______________ County_____________ Driver____________________

From______________To________________ Direction_____To_____ Date_________ Recorder__________________

Control

Points Cum.

Distance

or Odom.

No.

Lanes

Posted

Speed

Run 1

Run

Time

Int.

Lanes

Park

(Y,N)

Int.

Ctl

.

Point

No. CP Stops

Start/End

Other Stops

Reason Start/End

Note1: Intersection Stop Delay Due to a Control Point Intersection Is to Be Included with the Previous Segment, Delay at the First Check Point is not Included

Note2: Place Control Points at the Following: Signals, Stop Signs (on subject route), Rail Road Crossing, Changes In: Speed Limit/Number of Lanes/Directional Status

Intersection Control Codes: S=Signal, F=Flashing Signal, 4=4 Way Stop, 2=2 Way Stop, Y=Yield, N=None, NA=Not Applicable (for control points not at intersections)

Other Stop Reason Codes: A=Accident/Stalled Vehicle, B=Bus Loading/Unloading, C=Construction, D=Debris in Road, L=Left Turning Vehicle, P=Parking Vehicle,

T=Traffic Congestion, W=Pedestrian

Figure 5.

Int.

Lanes

(Svy) (Opp)

Run 2

Run

Time CP Stops

Start/End

Other Stops

Reason Start/End

Run 3

Run

Time CP Stops

Start/End

Other Stops

Reason Start/End

Once collected the data was brought back to the office and entered into a database. Figure 6. shows sample

raw data for a surveyed segment.

Figure 6. Sample of Raw Data From Travel Time Study Database

Each segment was run in both directions of travel. The runs for opposite directions were stored in separate

database records as shown above. Records were marked with a C (Cardinal) or N (Noncardinal) depending

on the direction the run was made (Cardinal is always south to north, west to east per the road inventory log

ID 1310 1310 1310 1310 1310 1310 1310 1310 1310 1310

Roadname SR-2 SR-2 SR-2 SR-2 SR-2 SR-2 SR-2 SR-2 SR-2 SR-2

Chkpoint # 1 2 3 4 5 5 4 3 2 1

Direction C C C C C N N N N N

Chkpoint Name Elmdale RR Bronx KenmoreUS-24 US-24 KenmoreBronx RR Elmdale

Cum. Dist 0 0.281 0.706 0.948 1.414

No. Lanes 2 2 2 2 2 2 2 2

Posted Spd 40 40 35 35 35 35 35 40

Parking N N N N Y Y Y N

Oneway

Int Lanes (Svy) N/A 1 1 L/TR 1 1 N/A 1

Int. Control N N/A F S S S S F N/A N

Run1 Time 11:16 AM 26 108 149 257 11:10 AM 51 119 205 233

Run1 CP Start 133 249

Run1 CP End 146 253

Run1 Stop Reason

Run1 Stop Time

Run2 Time 11:27 AM 29 113 148 309 11:22 AM 55 121 214 243

Run2 CP Start 242

Run2 CP End 305

Run2 Stop Reason

Run2 Stop Time

Run3 Time 11:35 AM 34 119 142 238 11:30 AM 49 113 155 223

Run3 CP Start

Run3 CP End

Run3 Stop Reason

Run3 Stop Time

Run4 Time 4:30 PM 26 112 151 252 4:33 PM 118 144 231 300


Run4 CP End 247 107

Run4 Stop Reason

Run4 Stop Time

Run5 Time 4:36 PM 26 107 155 328 4:41 PM 49 119 208 238

Run5 CP Start 245

Run5 CP End 326

Run5 Stop Reason L

Run5 Stop Time 10

Run6 Time 4:46 PM 33 123 220 320 4:50 PM 117 144 223 252


Run6 CP End 202 107

Run6 Stop Reason

Run6 Stop Time

point numbering). Distances are in miles and represent the distance from the beginning of the segment.

Further data processing will populate the distance between checkpoints later. No distances are given in the

noncardinal direction because they can be calculated from the cardinal distances. Times are stored in

minutes/seconds from the beginning of the run. All stop time was kept track of separately to allow it to be

segregated from run time. Most stops occur at the checkpoints (usually intersections) so this time was kept

track of by simply noting the elapsed seconds when the vehicle stopped and when it resumed. Occasionally

stops occur at other locations, these are indicated with a reason code and the total seconds stopped.

The data processing began with some clean up of the data and conversion of raw recorded cumulative times

and distances to segment values. As roughly one-quarter of the road segments used did not have a posted

speed limit recorded, such limits were estimated based on prima facie speed guidance from the Ohio

MUTCD. Additionally, because only stopped delay was recorded in the field, added time for vehicle

acceleration and deceleration from stop to posted/estimated speed was used, using estimates of 3.5

mph/second for vehicle acceleration and 5.0 mph/second for deceleration. Street segment numbers and

distances were not field recorded in the non-cardinal direction and were added. Data entry locations for

some streets were sometimes moved depending on where PM peak hour data was recorded. On and off-

ramps were initially entered with the corresponding freeway road codes, these were manually reassigned to

ramp codes based on checkpoint descriptions. Speeds were calculated for each run of each roadway

segment to identify errors in the database. Any road segments with clearly illogical speeds for which

coding errors could not be easily identified and corrected were not used in the analysis.

After processing and cleaning the data, tables of total and running speed by posted speed were created.

These were created in 2 ways, by averaging for all roadways of a certain class and posted speed and by

developing regression equations within each roadway class with posted speed as the independent variable.

The regression method has the advantage of producing speed values across a range of posted speeds even if

their were no observations for certain posted speeds. The drawback is that the regression curves may not

be applicable for ranges of posted speed where no or few observations exist. The use of regression analysis

to develop speed values over a range of posted speeds was necessitated by the fact that the sample was not

stratified by posted speed. The reason was that posted speed was only partly populated in the road

inventory state system file and not at all in the local file.

For many roadway classifications nearly all the sampled segments have the same or only a few posted

speeds. Therefore, the final speed table was developed using a combination of the regression results and

the average speeds by posted speed. Figure 7 below describes how the final speed table values were

determined for each roadway classification/posted speed combination. Note that for the rural

classifications, almost all observations had a posted speed of 55, thus while the regression results were used

to populate the speed table, values for posted speeds other than 55 should be regarded with some caution.

In addition, it should be noted that a number of roadway classes were compressed upon examining the data.

This was done when there was no significant difference in the speed results for related classes, particularly

when the slight differences that did exist were illogical.

For those roadway classifications where regression equations are recommended for use, the correlation

between actual and posted speeds was quite poor. It is slightly higher for running time than for overall

travel time. Average r-square values in the PM peak are .16 for overall travel time and .25 for running time

without intersection delay, while for the off-peak period the average r-square value is .24 for overall travel

time and .28 for running time. In addition, for roadway segments used in the analysis, the standard

deviation of the running time was less than half that of overall travel time with intersection delay (with

coefficient of variation being 13% for running time compared to 24% for overall time). This indicates the

explicit modeling of intersections within travel forecasting would provide better assignment results when

using speed table lookups rather than link specific speeds.

The class 4 and 7 roadways (4+ lane rural collectors in flat and hilly areas) were compressed thus

indicating that hilly terrain does not impact speeds on multi-lane roads. It should be remembered however,

that all speed data presented herein was derived for cars, not trucks. Had a heavy truck been used, some

degradation in speed in hilly terrain would be expected. Classes 2 and 3 (2 and 4+ lane rural arterials were

compressed for the same reason, the data shows that for equal posted speed the travel speed on these types

of roads is independent of the number of lanes. The key difference between the 2 lane and 4+ lane roads is

that the posted speed tends to be higher on the 4+ lane arterials. The urban and cbd roadway classes were

combined in the same way , for these roads other factors such as intersection delay are far more important

than number of lanes in determining travel speeds. In fact, the raw data shows that for equal posted speed,

the 2 lane urban roads had higher running speeds than the 4 lane, this is probably an indication of the access

density that tends to exist along urban 4+ lane roads compared to 2 lane roads. Roadway classes that have

very restricted ranges of posted speed such as urban local roads (25 MPH), rural local roads (55 MPH) and

ramps were typically given a single average value of speed rather than producing separate values by posted

speed. This has the potential to create incorrect speeds for unusual circumstances where for example a

rural local road has a posted speed of 25 MPH in which case its speed value from the speed tables herein

would be too high.

Figure 7. Method of Determining Speed Table Values

Posted Num. Length Length

Code Speed Segments (off peak) (peak) Method1 any 29 100.94 1 group avg incl class 43

2/3 35 7 4.426 combined regression results for classes 2-3 (note 5)

2/3 40 combined regression results for classes 2-3 (note 5)




4/7 25 26 4.16 combined regression result for classes 4 and 7 (note 3)

4/7 30 0 combined regression result for classes 4 and 7 (note 3)






5 25 0 regression

5 30 0 regression

5 35 2 2.32 regression

5 40 0 regression


5 50 0 regression



6 30 0 regression

6 35 0 regression


6 45 0 regression

6 50 0 regression



8 30 0 regression


8 40 0 regression


8 50 0 regression


Posted Num. Length Length

Code Speed Segments (off peak) (peak) Method9 25 0 regression

9 30 0 regression




9 50 0 regression


11 any 34 57.62 49.39 1 group avg incl class 53

12/13/14/15 25 43 12.303 12.303 combined regression results for classes 12-15 (note 5)

12/13/14/15 30 2 0.988 0 combined regression results for classes 12-15 (note 5)






16 any 40 15.144 15.144 1 group avg (note 6)

21 55 44 22.08 22.08 regression (note 2)

21 60 10 12.42 12.42 regression (note 2)

21 65 13 8.70 8.70 regression (note 2)

22/23 25 158 22.12 22.12 combined regression from 22-23 (note 7)

22/23 30 0 0 0 combined regression from 22-23 (note 7)









26 25 26 2.04 2.04 1 group avg (note 4)

31 any 44 53.74 1 group avg (note 4)

32 any 35 56.28 1 group avg



51 any 22 6.18 5.21 1 group avg (note 1)

52 any 21 7.24 6.27 1 group avg

Note 1 Ignore 1 segment with posted 65 mph

Note 2 Reduce range to 55-65 because only 1 obs w/ ps 35 mph outside this range

Note 3 No difference in result between classes 4 and 7 indicating hills do no impact 4 lane roads

Note 4 Only 1 posted speed present in data

Note 5 No statisitcal difference in results and some illogical relations

Note 6 Class 16 kept separate from 12-15 since posted speed distribution was so small (mostly 25 with a few 35)

thus regression results above 25 would not apply to this class

Note 7 For posted speed of 25-30 the regression results were averaged with classes 24-25

Note 8 For posted speed of 25-30 the regression results were averaged with classes 22-23

Study Results

Figures 8 and 9 presents the final speed table derived from the present study. Figure 8 reflects the speeds

based upon total travel time and Figure 9 the running time speeds (intersection delay removed). Boxed

values in these tables are speeds which should be used with extreme caution or not at all since they

represent conditions which were not present in the survey data set. These boxed values were derived by

simply extending the last valid entry into the boxed region rather than applying the regression results which

were meaningless in these ranges.

Figure 8. Final Total Travel Time Based Speed Table

Off Peak Travel Time Speed Posted Speed

Old Code New CodeDefinition 25 30 35 40 45 50 55 60 65

1 1 rural freeway 64 64 64 64 64 64 64 64 64

2/3 2 rural arterial 42 42 42 45 48 51 54

4/7 3 rural 4+ lane collector23 28 33 38 43 48 53

5 4 rural 2 lane collector, flat38 39 41 43 45 46 48

8 5 rural 2 lane collector, hilly32 34 36 39 41 44 46

6 6 rural local, flat 28 32 35 38 41 44 47

9 7 rural local, hilly 34 35 35 36 36 37 37

31 8 rural local, township, flat40 40 40 40 40 40 40

32 9 rural local, township, hilly30 30 30 30 30 30 30

11 11 urban freeway 63 63 63 63 63 63 63 63 63

12/13 12 urban arterial 20 24 28 32 36 40 44

14/15 13 urban collector 20 24 28 32 36 40 44

16 16 urban local 25 25 25 25 25 25 25

21 21 cbd freeway 47 47 47 47 47 47 47 53 60

22/23 22 cbd arterial 19 22 26 29 33 33 33

24/25 23 cbd collector 19 21 22 24 25 25 25

26 26 cbd local 12 12 12 12 12 12 12

41 41 rural ramp, off 36 36 36 36 36 36 36

42 42 rural ramp, on 44 44 44 44 44 44 44

51 51 urban ramp, off 32 32 32 32 32 32 32

52 52 urban ramp, on 46 46 46 46 46 46 46

PM Peak Travel Time Speed Posted Speed


11 11 urban freeway 59 59 59 59 59 59 59 59 59

12/13 12 urban arterial 21 24 28 31 35 39 42

14/15 13 urban collector 21 24 28 31 35 39 42

16 16 urban local 24 24 24 24 24 24 24

21 21 cbd freeway 46 46 46 46 46 46 46 50 54

22/23 22 cbd arterial 19 22 25 28 31 31 31

24/25 23 cbd collector 19 21 23 25 26 26 26

26 26 cbd local 12 12 12 12 12 12 12

51 51 urban ramp, off 24 24 24 24 24 24 24

52 52 urban ramp, on 37 37 37 37 37 37 37

Figure 9. Final Running Speed Table

Off Peak Run Time Speed Posted Speed


1 1 rural freeway 64 64 64 64 64 64 64 64 64

2/3 2 rural arterial 46 46 46 48 51 53 55

4/7 3 rural 4+ lane collector 28 33 37 42 46 51 55

5 4 rural 2 lane collector, flat 36 39 42 44 47 49 52

8 5 rural 2 lane collector, hilly33 35 38 41 43 46 49

6 6 rural local, flat 33 36 40 43 47 50 53

9 7 rural local, hilly 43 43 42 42 42 42 42

31 8 rural local, township, flat 44 44 44 44 44 44 44

32 9 rural local, township, hilly 32 32 32 32 32 32 32

11 11 urban freeway 63 63 63 63 63 63 63 63 63

12/13 12 urban arterial 26 31 35 39 43 47 51

14/15 13 urban collector 26 31 35 39 43 47 51

16 16 urban local 30 30 30 30 30 30 30

21 21 cbd freeway 50 50 50 50 50 50 50 55 61

22/23 22 cbd arterial 26 29 32 35 39 39 39

24/25 23 cbd collector 26 29 32 35 37 37 37

26 26 cbd local 25 25 25 25 25 25 25

41 41 rural ramp, off 57 57 57 57 57 57 57

42 42 rural ramp, on 44 44 44 44 44 44 44

51 51 urban ramp, off 46 46 46 46 46 46 46

52 52 urban ramp, on 46 46 46 46 46 46 46

PM Peak Run Time Speed Posted Speed


11 11 urban freeway 59 59 59 59 59 59 59 59 59

12/13 12 urban arterial 28 31 35 38 41 44 48

14/15 13 urban collector 28 31 35 38 41 44 48

16 16 urban local 31 31 31 31 31 31 31

21 21 cbd freeway 50 50 50 50 50 50 50 53 57

22/23 22 cbd arterial 26 29 32 36 40 40 40

24/25 23 cbd collector 26 29 32 34 36 36 36

26 26 cbd local 24 24 24 24 24 24 24

51 51 urban ramp, off 38 38 38 38 38 38 38

52 52 urban ramp, on 37 37 37 37 37 37 37

Figures 10-18 show various combinations of the speed data plotted for comparison purposes. Each chart

shows the speed table travel speed versus the posted speed limit. Figure 10 shows values of the travel time

speed for all of the rural classifications while Figure 11 shows the same data for the PM peak period on the

urban classes. Note that in general, higher functionally classed roadways have higher speeds than lower

classes. One notable exception is on 4+ lane collectors. The regression equation for these roadways has a

steep slope giving speeds lower than lower functional classes for low values of posted speed and higher

values for higher posted speeds. The reason is that when rural collectors go to 4+ lanes with low posted

speeds they tend to be in small village which gave urban characteristics which give lower speeds than 2

lane rural roads with low posted speed which tend to be in residential areas. At higher posted speeds the 4+

lane collectors have higher speeds than comparable 2 lane roads as expected.

Figures 12 and 13 compare the peak and off peak speeds on the urban roads. Figure 12 is for the freeways

and arterials while Figure 13 is for the collectors and locals. In general the data shows slightly lower

speeds during the peak period, however, in general the values are very close indicating the relatively

uncongested nature of the random sample. Obviously, had the sample been targeted to congested areas, a

greater impact would be seen. Additionally, some background level of congestion is present even during

the off peak period as indicated by the lower speeds on urban roads compared to rural. Note that the cbd

area collectors had a slightly higher speed during the peak than the off peak, the values are extremely close

and reflect statistical noise, the values are merely an indication that there is no statistical difference in

speeds on urban collectors between the peak and off-peak periods.

Figures 14 and 15 compare the average travel speed with the running speed. In all cases the running speed

is higher than average speed as it must be since running speed does not account for intersection delay.

Note that the running speed and average travel speed curves are parallel for like road classes indicating a

relatively uniform impact of intersection delay across posted speeds. It should also be noted that the

freeway running time is equal to the average travel time since there is no intersection delay.

Figures 16-18 compare all roadway classes for each of freeways, arterials and collectors respectively.

These figures allow the comparison of the impact of various conditions including rural versus urban area

type on the speed of roads with like functional class. Note that for freeways, rural and urban are closer

together while cbd is much slower. For arterials urban and cbd are close together while rural is much

faster. For collectors there is about an equal amount of speed reduction going from rural to urban as from

urban to cbd.

Conclusion

This report has documented the results of the travel time study conducted by ODOT. Results have been

shown which will be useful for developing speed values for travel demand forecasting model. A key

finding of this report has been that travel speed is insensitive to the number of lanes but does depend on

roadway class and posted speed.

Appendix A Excerpt From "Model Specification and Data Collection Program For Small MPO Study Areas in

Ohio" on How to Conduct Speed-Delay Studies

D. Speed Delay Study

A speed/delay study is necessary to establish area specific network speeds for each MPO area. ODOT will

conduct such a study on a statewide basis and MPO's are free to use the results of this study for their area,

though collection of posted speeds will still be required. MPO's are encouraged to conduct their own

studies to produce area specific values. A side benefit of the speed/delay study is that it provides a

database for congestion management activities and is a valuable resource in of itself outside the travel

model context.

In general this study should follow the guidelines contained in the Travel Time Data Collection Handbook

(5). A test vehicle method should be employed using a floating car/average car driving style. This study is

sufficiently large that it may require use of a consultant, however, a crew of summer interns could complete

the study in a single summer (significantly less time for the smallest areas) for significantly less cost.

All roadways in the study area which are included in the forecasting network should be grouped based on

the following two classifications which are defined by the proposed speed table format discussed in

Chapter 2:

Areatype: CBD (includes Fringe), Urban (includes Residential, Outlying Business District), Rural

Facility Type: Freeway/Expressway (Limited Access)

Arterial (4+ Lanes)

Arterial (2 Lanes)

Collector

Local

Township Roads

Centroid Connectors

Ramps

Each roadway should be broken into approximately 2 mile segments for arterial streets and 3 mile segments

for freeways. These segment breaks should occur at interchanges/intersections. Segments should be

defined such that the entire segment is in the same category. The segment should also not change between

a 1 way and 2 way street. The segment length criteria are rough guidelines only, with the other factors in

this paragraph providing the primary means for defining segments.

A random sample of segments within each category should be selected for speed delay runs based on the

following parameters:

Coefficient of Variation: 0.20

Z Statistic (90% confidence): 1.845

Relative Percent Error: 10%

This yields a sample of 14 segments per category. These values are based on guidance given on page 2-10

of (5). Next the number of segments in each category should be adjusted for the population size using the

correction equation:

n = n'/(1+n'/N)

where

n = sample size

n' = uncorrected sample size (always 14 for this study)

N = population size

Thus if a certain category had 30 segments total, the sample required would be:

n = 14/(1+14/30) = 10 segments

Once the segments to study have been determined, the number of runs to make on each segment should be

determined as follows:

Category Number of Runs

Freeways 4

Rural Nonfreeway 4

Urban Nonfreeway 6

CBD Nonfreeway 8

These values are based on Tables 3-3 and 3-4 of (5) using a 90% confidence level with a 10% relative

error. The freeway categories in these tables have been collapsed since the higher volume categories

generally don't apply to the small MPO's and the arterial categories have been translated from signal

densities to area types. Also, the number of runs required has been rounded down to even numbers so that

the runs can be apportioned equally by direction for 2 way streets.

The indicated number of runs can be conducted at any time of the day for rural categories. For urban and

CBD categories, the indicated number of runs should be repeated in both the peak (6 AM to 8 AM, 4 PM to

6 PM) and off peak periods (thus doubling the number of runs needed on those routes). Only the off peak

(free flow) speeds are strictly necessary for the equilibrium traffic assignment algorithms, however, peak

(congested) speeds should be obtained as well for comparative purposes and to use in all-or-nothing

assignments.

Travel time runs should be made Monday through Thursday and should avoid the day before and after a

holiday weekend.

Conduct of the study can use any of the available test vehicle methods including manual recording, distance

measuring instrument (DMI) or global positioning system (GPS) technology. Checkpoints should be

established throughout each segment to delimit major intersections, changes in roadway characteristics or

other features of note which could affect travel time data. The handbook (5) suggests checkpoint spacing

of about 025 to 0.5 miles, however, this is only a rough guide since the characteristics of the previous

sentence will control. For consistency, segments should be initiated after passing through any intersection

at checkpoint 1, while any delay due to an intersection at the last checkpoint should be included in the

segment.

Run time and stop delay time should be recorded separately in the studies. The reason for any stop delay

should be noted. Speed delay runs will be discarded for routes experiencing major incidents (accidents

construction etc) and will be conducted at another time if possible. Stop delay for minor incidents or those

whose stop delay can be isololated (such as trains) will be removed prior to the computation of average

facility speeds.

When a centroid connector segment is selected, a combination of local streets in the selected zone should

be picked which give approximately the same length as the centroid connector.

Speeds will be calculated as a space mean speed by dividing distance traveled by the travel time required.

In addition to keeping track of travel times and delay, the posted speed limit, number of lanes and direction

status (oneway vs twoway), presence/absence of parking, intersection control at each intersection and turn

lane presence on the intersection approach should all be collected so that their effects on speed can be

studied. It is generally useful to run the route once without collecting speed/time data to record this data as

well as to establish the location of the listed control points (and the distance between points if doing so

manually).

Appendix B

List of Sample Segments for Travel Time Study id JUR CO RTE BEG LEN road name start road end road

101 S ALL 0075R 9.92 13.26 I-75 Bluelick Rd. Lincoln Hwy.

102 S AUG 0075R 5.53 6.34 I-75 SR 67 CR 208

103 S CLA 0675R 0 1.42 I-675 SR 4 SR 444

104 S FAY 0071R 0 14.65 I-71 US 35 SR 41

105 S GUE 0070R 0 7.95 I-70 SR 83 SR 723

106 S HAN 0075R 0 13.83 I-75 SR 103 SR 235

107 S LUC 0080K 0 4.01 I-80/I-90 Fulton/Lucas Co. Line Airport Hwy Exit 3A

108 S MAH 0076R 0 8.65 I-76 SR 534 N. Bailey Rd.

109 S MRW 0071R 0 19.93 I-71 SR 61 SR 95

110 S GUE 0077R 0 23.44 I-77 SR 313 SR 209

111 S PRE 0070R 0 17.67 I-70 US 127 SR 503

112 S SHE 0075R 7.64 12.91 I-75 SR 47 Sidney-Wapakoneta Rd.

113 S TUS 0077R 0 19.8 I-77 US 36 SR 751

114 S WAY 0071R 0 7.1 I-71 SR 301 SR 539

201 S ASD 0030R 0 13.29 US 30 SR 60 SR 89

202 S AUG 0033R 3.46 10.67 US 33 CR 33A I-75

203 S COL 0007R 0 4.24 SR 7 SR 39 SR 45

204 S ERI 0002R 17.39 13.17 SR 2 SR 13 SR 61

205 S GEA 0422R 16.05 3.85 US 422 SR 528 SR 305

206 S JAC 0032R 0 10.06 SR 32 Glade Rd. (CR 24) Cove Rd. (CR 22)

207 S LIC 0016R 14.24 2.54 SR 16 TR 142 SR 37

208 S MED 0018R 16 5.13 SR 18 Windfall Rd. SR 94

209 S PIC 0023R 9.75 13.41 US 23 Hagerty Rd. Upton Rd.

210 S ROS 0023R 0 15.32 US 23 De Bord Rd. (TR 182) Rozelle Creek Rd.

211 S SCI 0023R 2.61 14.1 US 23 CR 55 CR 58

212 S TRU 0082R 19.61 7.96 SR 82 SR 11 SR 193

213 S WAR 0042R 17.94 6.8 US 42 Franklin Rd Cincinnati-Columbus Rd.

214 S WYA 0023R 0 23 US 23 SR 199 SR 294

301 S ASD 0250R 0 12.18 US 250 US 224 TR 448

302 S BRO 0052R 0 20.02 US-52 T-255 Pisgah Hill Rd C-1001 Old US 52

303 S CLE 0131R 5.19 9.95 SR 131 Goshen Rd. Newtonsville Rd.

304 S DEF 0024R 12.45 6.88 US 24 Adams Ridge Rd. Flory Rd.

305 S GEA 0088R 2.73 3.6 Nash Rd. SR 528 CR 6

306 S HEN 0006R 0 10.94 US 6 SR 34 TR 18

307 S JEF 0043R 9.26 12.45 SR 43 TR 472 TR 266

308 S MAH 0014R 0 7.92 SR 14 Beloit Snodes Rd. (CR 25) SR 534

309 S MOE 0007R 0 12.41 SR 7 TR 974 Barnes Run Rd.

310 S OTT 0002R 0 14.88 SR 2 Camp Perry Western Rd. Toussaint East Rd.

311 S PUT 0224R 11.64 8.59 US 224 SR 115 Co.Rd. 15M

312 S STA 0044R 15.14 8.07 SR 44 State St. (CR 31) St. Peter's Church Rd.

313 S VAN 0224R 0 22.22 US 224 SR 49 Dull-Robinson Rd

314 S WIL 0015R 0 11.13 SR 15 Co. Rd. I SR 107

401 S ASD 0039R 9.09 0.13 SR 39 TR 749 SR 3

402 S BUT 0063R 0.13 1.87 SR-63 Hamilton-Lebanon Rd SR-4 Hamilton-Middletown Rd Brittan Ln

403 C CLA 327 1.45 0.54 Upper Valley Pike SR 41 Saint Paris Pike

404 S CLA 0040R 16.87 10.71 US 40 I-70 SR 54

405 S CLA 0334R 0 0.2 SR 334 SR 72 SR 4

406 S ERI 0060R 7.92 0.59 Savannah-Vermilion Rd. Mason Rd. SR 113

407 S LOG 0347R 0.64 2.14 SR 347 US 33 TR 143

408 S MAD 0040R 0 16.11 US 40 SR 29 SR 142

409 S MAD 0040R 0 16.11 US 40 SR 38 US 42

410 C MAH 65 5.2 2.41 N. Bailey Rd. Mahoning Rd. (CR 18) W. Mahoning-Trumbull Co. Line Rd.

411 C MOT 193 0 0.53 Farmersville & West Alexandria Pike - Center St.

Vine St. Elm St.

412 S PAU 0066R 8.49 0.24 SR 66/First Street T-82 Potts T-110 Rhees

413 S SUM 0303R 4.74 0.51 SR 303 Black Rd. Stine Rd.

414 S WOO 0025R 1.14 6.96 South Dixie Hwy. Jerry City Rd. Defiance Pike (SR 281)

501 S AUG 0196R 0 6.21 SR 196 Fairmont Rd. Union-Wayne Rd.

502 C BUT 134 1.4 2.19 C-134 Yankee Rd C-18 Princeton Rd C-136 Linn Rd

503 T CHP 94 0 1.22 Carysville Rd. SR 235 Kiser Lake Rd.

504 S DAR 0047R 0.45 9.99 SR 47 T-22 Hillgrove-Ft. Recovery Rd C-65 Young Rd.

505 C FAY 94 0 2.46 Jeffersonville-W. Lancaster Rd. (TR 94)_

W. Lancaster Rd. (TR 16) SR 734

506 S HAN 0103R 0 21.06 SR 103 TR 60 CR 9

507 C HEN 10 0 6.71 TR 10 CR L TR N

508 S MAH 0014R 7.92 2.08 SR 14 Butcher Rd. Lisbon Rd.

509 C MIA 42 0 3.35 Ginghamsburg-Fredrick Rd. Matrindale Rd. CR 25A

510 S PAU 0114R 0 11.58 SR 114 C-1 State Line Road T-33 Lare Road

511 C RIC 77 0 7.94 Olivesburg-Fitchville Rd. Nelson Rd. SR 96

512 S SEN 0019R 4.17 16.09 SR 19 (Bucyrus-Clyde Rd.) CR 16 TR 106 (Coe Rd.)

513 C UNI 129 0 9.17 Wolford-Maskill Rd. SR 4 Wheeler-Green Rd. (CR 205)

514 S WIL 0034R 0 15.76 SR 34 CR H CR J

601 C AUG 50 0 6.11 Amsterdam Rd. Wilker Rd. Thieman Rd.

602 C CLE 54 0 3 Glancy Corner Marathon Rd. Blue Sky Park SR 286

603 C DAR 128 0 3.21 C-128 Foote Rd C-53 Reed Rd Darke-Shelby Co Line Rd

604 C FRA 106 2.8 6.25 C-106 Wagoner Rd T-207 Kennedy Rd C-95 Clark State Rd

605 C HAN 96 0 6 CR 96 CR 117 TR 123

606 C HUR 240 0 0.31 Jim Esker Rd. Begin. US 20

607 C MAD 132 0 1.67 Arthur-Bradley Rd. SR 38 Taylor-Blair Rd. (CR 14)

608 C MER 31 0 22.42 St. Peter Rd. Philothea Rd. SR 219

609 C MRW 46 0 2.59 Williamsport-Crestline Rd. SR 19 Marion Johnsville Rd.

610 C POR 191 0 1.39 Griffith Rd. SR 225 CR 135

611 C SAN 198 8.29 3.52 CR 198 US 6 TR 211 (Marzke)

612 C TRU 57 0.26 0.88 Stillwagon Rd. Mines Rd. End

613 C WAR 37 0 5.96 Clarksville Rd. US 22 Wilmington Rd

614 C WYA 47 0 20.57 CR 47i CR 128e TR 136a

701 S COL 0030R 24.15 0.41 US 30 Applegate Rd. Stookesberry Rd.

702 S GUE 0022R 0 5.58 US 22 Glenn Hwy. CR 413 (Meadow Rd.) CR 430

703 S GUE 0022R 0 5.58 US 22 Glenn Hwy. Patch Rd (CR 14) CR 413 (Meadow Rd.)

704 S JEF 0150R 6.23 0.1 SR 150 Longrun Rd. (CR 7) Fork Rd. (CR 8)

705 S LIC 0040R 4.14 5.17 US 40 SR 310 CR 39

706 S LIC 0040R 28.58 1.56 US 40 Rankin Rd. CR 8

707 S MUS 0022R 23.33 4.43 US 22 Brook Rd. Snoots Ln.

708 S MUS 0022R 23.33 4.43 US 22 Southern Rd. Brook Rd.

709 S MUS 0040R 0 9.75 US 40 Kimes Rd. I-70

710 S MUS 0040R 0 9.75 US 40 CR 415 Kimes Rd.

711 S MUS 0040R 0 9.75 US 40 Warner Ln. CR 415

712 C PIK 58 0 0.86 Shyville Rd. Begin. TR 601

713 S ROS 0207R 10.76 0.18 SR 207 North St. Browns Chapel Rd.

714 S TUS 0800R 30.79 0.89 SR 800 CR 107 SR 212

801 C BEL 56 29.92 5.81 C-56 Morgan Hill Rd C-10 Maynard-Crescent Road T-451 (Grays Ridge)

802 S BRO 0505R 0 10.43 SR-505 C-18 Eden Rd SR-125

803 T COL 776 4.62 0.56 Pike Rd Osborne Rd. Glasgow Rd.

804 C FAI 13 1.91 6.55 Basil Western Rd. Carrol Northern Rd. Bader Rd.

805 S GAL 0141R 0 22.15 SR 141 CR 138 CR132

806 S HIG 0247R 0 11.74 SR 247 Crooked Rd. (TR 170A) Union Rd. (TR 179A)

807 C HOC 13 0 5.5 Nickel Plate Rd. Skinner Rd. Keller Rd.

808 S KNO 0205R 0 6.94 SR 205, Danville-Jelloway Rd. SR 3 TR 324

809 C LAW 4 0 13.11 Waterloo Rd. Buckeye Rd. SR 141

810 S MOE 0260R 0 5.52 SR 260 SR 565 CR 105

811 C MUS 44 0 1.7 Salt Creek Rd. SR 60 Wilhelm Rd.

812 S PER 0188R 0 4.48 SR 188 High Point Rd. TR 80

813 C SCI 34 0 4.66 Sedan Crabtree Rd. Cramer Rd. Crabtree Cemetary Rd.

814 S VIN 0160R 0 18.5 SR 160 CR 28 TR 18

901 C ATH 75 0 6.61 Coolville Ridge Rd. Long Run Rd. TR 90

902 C CAR 19 7.61 4.81 Autumn Rd. Alamo Rd. SR 9& 43

903 C FAI 26 0 6.87 Revenge Rd. Clear Creek Bridge Beck Rd.

904 C GAL Bladen SR 218 Victory Rd

905 C HIG 8 0 7.39 Panhandle Rd. Horseshoe Rd. Collins Ln.

906 C HOL 330 0 2.34 CR 330 SR 226 SR 754

907 C KNO 47 0 3.75 Ridge Rd. TR 369 (Cooke Rd) TR 366

908 C LIC 42 0 7.15 Watkins Rd. Blacks Rd. Hollow Rd.

909 C MOE 61 0 1.78 Egger Ridge Rd. TR 17 SR 145

910 C MUS 46 0 2.98 Darlington Dr. Moxadarla Rd. Baughman Run Rd.

911 C PER 6 6.37 0.25 TR 6 Flint Ridge Rd. SR 93

912 C ROS 28 3.17 5.45 Potts Hill Rd. Ewing Rd. (TR 34) CR 149 (Spargursville Rd.)

913 C TUS 9 0 1.25 Laurel Creek Rd. Ridge Rd. SR 258

914 C WAS 340 0 1.04 CR 340 SR 60 SR 821

1101 S BUT 0075R 9.59 1.66 I-75 C-20 Tylersville Rd SR-63 Hamilton-Lebanon Rd

1102 S CLE 0275R 6.38 7.5 I-275 SR 125 SR 32

1103 S CUY 0090R 8.31 0.87 I-90 US 20 W 117th St.

1104 S CUY 0271R 3.57 1.78 I-271 I-480 US 422

1105 S FRA 0071R 10.96 0.2 I-71 Stringtown Rd (Grove City) SR-104 Frank Rd

1106 S FRA 0270R 0.42 8.85 I-270 Georgesville Rd US-62 Harrisburg Pike

1107 S HAN 0075R 13.83 5.27 I-75 US 68 US 224

1108 S LAW 0052R 2.51 19.65 US 52 SR 650 SR 93

1109 S LIC 0070R 0 3.66 I-70 SR 310 SR 158

1110 S LOR 0002R 0 11.14 SR 2 N. Lake St. Leavitt Rd. (SR 58)

1111 S LOR 0090R 9.48 13.85 I-90 SR 611 SR 83

1112 S MAH 0080R 4.08 0.35 I-80 SR 48 I-680

1113 C MOT 705 0.17 2.08 Airport Access Rd. I-70 US 40

1114 S STA 0077R 8.39 8.29 I-77 US 30 SR 800

1201 S ATB 0020R 9.93 2.87 US 20 SR 45 Sanborn Rd.

1202 S ATH 0033R 10.7 2.25 US 33 SR 682 SR 550

1203 S ATH 0682R 0.14 0.51 SR 682 SR 56 SR 32

1204 C CUY 12 1.8 0.26 Broadway Macedonia Rd. Richmond Rd.

1205 S CUY 0003R 6.82 0.32 Ridge Rd. Pleasant Valley Rd. Ridgewood Dr.

1206 S CUY 0043R 11.69 1.58 Miles Ave. E 93rd St. E 131st St.

1207 C FRA 8 8.38 1.42 Sunbury Road SR-161 Central College Rd

1208 S FRA 0161R 12.69 1.67 SR-161 Dublin-Granville Rd Karl Rd Cleveland Ave

1209 C HAM 239 0 9.86 Winton Rd W Sharon Rd W Kemper Rd

1210 C LUC 502 2 3.98 Douglas Rd SR 246 Dorr St Kenwood Blvd

1211 S LUC 0020R 12.93 3.78 US 20 Heatherdowns Blvd SR 2 Airport Hwy

1212 C MUS 3 7.12 1.11 Linden Ave. McIntire Ave Sheridan St.

1213 T STA 211 2.25 0.61 Fulton Dr. 11th St. 24th St.

1214 S STA 0687R 3.7 0.18 SR 687 Whipple Ave. 24th St.

1301 C ALL 160 3.2 1.74 Sugar St. Williams St. Bluelick Rd.

1302 S COL 0165R 4.2 2.16 SR 165 Rebecca St. Hadley Rd. (TR 1016)

1303 C CUY 72 0 1.25 Turkey Rd. Rockside Rd. McCracken Rd.

1304 S CUY 0175R 10.95 2.55 SR 175 Anderson Rd. Highland Rd.

1305 S DEL 0042R 4.22 3.08 US-42 London Rd William St Exit

1306 S ERI 0006R 23.66 3.84 Cleveland Sandusky Rd. Frailey Rd. Poorman Rd.

1307 C FRA 125 3.63 3 Clime Rd Demorest Rd US-62 Harrisburg Pike

1308 S GEA 0306R 4.45 6.81 Chillicothe Rd. CR 11 (Bainbridge Rd.) CR 606 (Washington St.)

1309 C HAM 470 4.25 0.52 Reed-Hartman Hwy Cornell Park Dr Fields Ertel Rd

1310 S LUC 0002R 14.64 1.46 SR 2 Elmdale Ave US 24 Detroit Ave

1311 C MAH 100 2.05 3.38 Shields Rd. Tippecanoe Rd. (CR 117) CR 135

1312 C MAH 500 1.88 1.71 Poland Ave. Dewey Ave. Walton Ave.

1313 C STA 112 2.4 3.39 8th St. Trump Ave. SR 44

1314 C WAR 4 2.07 2.44 Fields-Ertel Rd. Butler-Warren Rd. Mason-Montgomery Rd.

1401 C BUT 508 0 0.41 US-127 Pleasant Ave (Hamilton)

Shneck Ave Pershing Ave

1402 C CUY 19 0 5.94 Fairmount Blvd. Coventry Rd. Eaton Rd.

1403 C CUY 97 0 1.06 Shaaf rd. W. 11th St. SR 17 (Brookpark Rd.)

1404 C CUY 704 1.22 2.71 Big Creek Pkwy. Bagley Rd. W. 130th St.

1405 C FRA 82 0.38 0.46 Schrock Rd Huntley Rd Karl Rd

1406 C HAM 235 2.84 0.92 W Sharon Road SR 747 Congress Ave/Princeton Pike

Chester Rd

1407 C HAM 693 0 0.42 Forest Ave Williams Ave Norwood Ave

1408 C LAW 1 11.64 0.51 Old US 52 (CR 1) Rosslyn Dr. Third St.

1409 C MAH 135 1.96 2.17 Glenwood Ave. US 224 CR 100

1410 C MOT 602 0.16 0.96 First St. Ludlow St. Keowee St.

1411 C MOT 659 0.96 0.15 W. Schantz Ave. Kramer Rd. Sorrento Ave.

1412 C SCI 614 0 0.43 US 52 E Corp Limit, New Boston SR 140

1413 T SHE 135 1.54 2.2 Van Demark Rd. Industrial Dr. Russell Rd. (TR 47)

1414 C TRU 1469 1.91 1.09 Perkins Jones Rd. Dietz East SR 82

1501 C BUT 24 0 1 C-24 Jacksonburg Rd US 127 C-157 Morgan-Thaler Rd

1502 C CUY 69 0.68 2.54 Hilliard Blvd. Dover Center Rd. SR 252

1503 C FAY 140 1.34 0.87 CR 140 SR 753 US 22

1504 C FRA 707 1.17 0.82 Perimeter Loop Rd N/Perimeter Dr

Avery Road/Muirfield Dr Emerald Parkway

1505 C GEA 5 7.48 5.65 Mentor Rd. Hermitage Rd. Auburn Rd.

1506 C HAM 698 0 0.48 Isabella Ave Wasson Ave Madison Ave

1507 C LAW 508 0.67 2.45 Fifth St. Lawrence St. Ellison

1508 C LUC 573 0 1.59 Central Ave US 24 Detroit Ave. La Grange St

1509 C MOT 29 0 2.03 Olive Rd. US 35 Little Richmond Rd.

1510 T MOT 128 0 1.01 Bartley Rd. Brantford Rd. North Dixie Dr.

1511 C RIC 150 0 1.69 Lewis Rd. SR 309 US 30

1512 S SEN 0101R 1.01 0.63 Market St. SR 101 Perry St. CR 13

1513 C SUM 50 0 3.04 South Main St. Mt. Pleasant Rd. West Nimisila Rd.

1514 C WAY 70 21.16 0.64 Doylestown Rd./Collier Dr. Serfass Rd. Portage St.

1601 M ALL Merlin Chipman Spencerville Rd

1602 M CLA Banes Ave Begin. Moorefield Rd

1603 M CUY Oxford Pk. Ln Begin. Fitch Rd.

1604 M FRA Thompson Hamilton Rd US-62

1605 M HAM Glade Ave Beacon Rd Birney Ln

1606 M HAM Nandale Chevoit Rd End

1607 M JEF Springdale Begin. Sunset Blvd

1608 M LIC Aldine Dr. Begin. Heath Rd

1609 M LUC Clark St Begin. Hill Rd.

1610 M MAH Edgehill Ave Elmwood Mahoning Ave

1611 M MOT Calumet Ln. Dayton & Liberty Pk US 35, Third St.

1612 M RIC Kemore Dr. Begin. Home Rd.

1613 M STA 39th Street Market Ave Martindale Rd

1614 M SUM Junior Denaple Rd Albrecht

2101 S CUY 0006R 12.2 1.7 US 6 Lake Ave. US 42

2102 S CUY 0090R 18.28 1.73 I-90 CR 382 E 55th St. CR 318 (Eddy Rd.)

2103 S CUY 0090R 8.65 13.5 I-90 SR 10 (Lorain Rd.) I-490

2104 S CUY 0490R 1.7 0.73 I-490 I-77 E 55th St.

2105 S CUY 0490R 0 0.41 I-490 I-90 I-77

2106 S FRA 0071R 11.05 3.46 I-71 SR-104 Frank Rd Greenlawn Ave

2107 S FRA 0071R 19.54 8.37 I-71 E North Broadway Morse Rd

2108 S FRA 0670P 1.05 1.79 I-670 I-70 Grandview Ave

2109 S FRA 0670R 5.85 0.57 I-670 I-71 Leonard Ave

2110 S LIC 0016R 16.78 7.8 SR 16 O' Bannon Rd Marne Rd

2111 S LUC 0075R 2.61 1.9 I-75 US 24 Detroit Ave. Phillips Ave

2112 S MAH 0680R 4.4 2.19 I-680 West River Crossing East River Crossing

2113 S SUM 0008R 0.46 7.22 SR 8 SR 261 (Talmadge Rd.) SR 59 (Perkins St.)

2114 S SUM 0059J 0 0.74 SR 59 Diagonal Rd. Mill St.

2201 C CLA 338 3.81 0.09 S. Yellow Springs St. W. John St. W. Pleasant St.

2202 C CUY 400 0.71 1.88 E 105th St. Chester Ave. Superior Ave.

2203 S CUY 0010R 12 4.86 Carnegie Ave. W 44th St. W 3rd St.

2204 S CUY 0014R 3.22 2.29 Broadway Warner Rd. Union Ave.

2205 C FRA 93 0 0.18 Hudson St Summit St McGuffy Rd

2206 S FRA 0023D 0 4.46 S High St Whittier St State St

2207 S FRA 0033R 17.59 4.32 Livingston Ave S High St S 18th St

2208 S FRA 0062R 17.66 1.6 US-62 Nelson Rd E Broad St E 5th Ave

2209 S GRE 0035R 7.26 3.72 US 35 (E Main St.) Orange St. S. Columbus St.

2210 C HAM 601 1.66 0.26 7th St Linn St Sycamore St

2211 S HAM 0022R 1.08 2.14 SR-3 Gilbert Ave Eden Park Dr Oak St

2212 C LUC 514 0.26 1.74 Collingwood Blvd Nebraska St Bancroft St

2213 S STA 0172R 6.09 1.65 Lincoln Way Wales Rd. 27th St.

2214 C SUM 605 5.58 1.54 Broad Blvd. State Rd SR 8

2301 S ALL 0081R 16.59 0.05 SR 81 N. Charles St. Jackson St.

2302 S ALL 0081R 17 2.72 SR 81 Neubrecht Rd. N. Dixie Hwy

2303 C BUT 609 0.74 1.15 Central Ave (Middletown) McKinley St Lylburn Rd

2304 C CUY 37 0.96 1.05 CR 37 (Denison Ave.) CR 10 (W. 73rd St.) CR 412 (Fulton Pkwy)

2305 C CUY 390 0 0.87 E 79th St. SR 87 Hough Ave.

2306 C FRA 57 0 0.66 Kenny Rd King Ave Lane Ave

2307 C FRA 548 1.68 0.91 Goodale Blvd Urlin Ave Northwest Blvd

2308 S HAM 0042R 0.65 0.59 Elm St. Central Pkwy. W. 3rd St.

2309 C JEF 603 0 1.51 Fourth St. Slack St. Madison Ave

2310 C POR 148 0.1 0.58 Summit St. Franklin Ave. Loop Rd.

2311 S RIC 0545R 0 1.1 SR 545 (Wayne St.) Orange St. Annadale Dr.

2312 S STA 0153R 6.33 0.72 SR 153 (E Main) Chapel St. Cyprus Ave

2313 C SUM 613 1.05 0.82 2nd St. Francis Ave. Portage Trail

2314 S TRU 0169R 3.33 3.42 SR 169 East Ave. Draper St.

2401 T BUT 179 2.75 0.89 Main St (Middletown) 11th Ave Manchester Ave

2402 C BUT 509 0.09 0.87 2nd St (Hamilton) Hanover St Vine St (Hensel)

2403 C CUY 150 1.93 0.12 Franklin Ave. W. 74th St. W. 29th St.

2404 C CUY 718 0 0.59 W. 9th St. Detroit-Superior Dr. End

2405 C CUY 723 0 3.37 Wade Park Ave. 65th St. 118th St.

2406 C CUY 763 0.73 1.02 W. 3rd St. Jefferson Ave Eagle Ave.

2407 C FRA 583 1.2 0.6 Long St Ohio Ave Nelson Rd

2408 C HAM 720 1 0.84 Gest St. Summer St. Freeman Ave.

2409 C HAM 737 0 0.6 8th St. Mound St. Eggleston Ave.

2410 C LUC 519 0.28 0.63 Main/Cherry St SR 65 Summit St Delaware Ave

2411 C LUC 549 0.7 0.78 Jefferson Ave Collingwood Blvd SR 65 Summit St

2412 C MAH 552 0 1.58 Belmont Ave. SR 193 SR 289

2413 C MOT 604 0 1.16 Second St. Holiday Ln. Meigs St.

2414 C SUM 606 0 0.91 South Main St. Bartges St. Mill St.

2501 C BUT 508 0.32 0.41 3rd St (Hamilton) Pershing/Central Black St

2502 C CUY 340 2.78 1.91 E. 71st St. SR 87 Wade Park Ave.

2503 C CUY 412 2.79 2.44 Fulton Rd. Storer Ave. SR 10

2504 C CUY 730 0 0.66 East Blvd. E. 105th St. Euclid Ave.

2505 C CUY 792 0 1.1 Addison Rd 79 th St Clair

2506 C FRA 529 1.38 1.29 Ohio Ave Frebis Ave Livingston Ave

2507 C FRA 549 1.91 2.31 E 2nd Ave N High St St Clair Rd

2508 C HAM 662 0 1.71 Highland Ave. Milton St. Goodman St.

2509 C JEF 604 0 1.52 Sixth St. Slack St. Madison Ave

2510 C LUC 544 0 0.29 Indiana Ave Hawley St SR 51 Washington St

2511 C LUC 546 0.06 1.23 Woodruff Ave Collingwood Blvd SR 120 Cherry St

2512 C MAH 555 0 1.48 Madison Avenue Freeway SR 289 US 62

2513 C RIC 509 0 0.27 W. Second St. Sturger Ave Bushnell St

2514 C SUM 632 0 1.25 North St. N. Valley St. Furnace St.

2601 M ALL High St S. Main S. Union

2602 M CLA Washington Limestone Linden

2603 M CUY Euclid 6 th Street 9th Street

2604 M FRA Cherry St. Wall St. Front St.

2605 M HAM Garfield P Elm Race St.

2606 M HAM E 6th St. Vine RuthLyons

2607 M JEF Market St Fourth St. Lake Erie Ave

2608 M LIC Locust St. 10th 6th

2609 M LUC Madison 14 St. 11 St.

2610 M MAH Federal Vindica St. Hazel St.

2611 M MOT Fourth St. Wilkinson Ludlow

2612 M RIC Glen Ave. 3rd SR 430

2613 M STA Reynolds Marion Mc Kinley

2614 M SUM Buchtell Rd Main St. Broadway

3101 T ALL 571 0 0.32 Michele Lehman Rd. Lehman Rd.

3102 T BUT 57 0 3.99 Oxford Milford Rd. SR 73 Somerville Rd.

3103 T CLI 181 0 1.32 Thorpe Rd. Gordon Rd Co. Line -Orchard Grove Rd.

3104 T DEF 119 0 6.77 Breininger Rd. Scholl Rd. Huber Rd.

3105 T FUL 15-1 0.74 2.88 TR 15-1 US 20 SR 120

3106 T HAR 199 0 4.14 TR 199 TR 146 TR 195

3107 T LOR 30 0 4.44 Quarry Rd. New London Eastern Rd. Bursley Rd.

3108 T MER 124 0 6.02 Pine Rd. Wabash Rd. Durbin Rd.

3109 T PAU 48 0 20.78 C-48 T-48 SR 637 C-165 Wetzel Rd

3110 T PRE 349 0 0.95 Somers Rd. Camden West Elkton Rd. Somers-Gratis Rd.

3111 T SAN 91 0 2 Wendler Rd. US 23 Rollersville Rd.

3112 T STA 161 0 3.98 Bowmont Ave. Westbrook St. Elson St.

3113 T VAN 184 0 1.85 Pollock Rd Lincoln Hwy Dull-Robinson Rd

3114 T WOO 24 0 12.02 Hammansburg Rd. Range Line Rd. Liberty Hi Rd.

3201 T ADA 29 0 6.21 Brush Creek Rd. US 52 Caplinger Rd.

3202 T BEL 187 0 3.89 T-187 T-188 C-100 McMillan Road

3203 T CAR 238 0 5.49 Macaw Rd. Bell FLower Rd. Lunar Rd.

3204 T COS 89 0 3.93 TR 89 TR 236 SR 93

3205 T GAL 636 0 0.49 Ann Dr. CR 94 CR 94

3206 T HAS 324 0 1.46 TR 324 TR 323 TR 269

3207 T HOL 177 0 2.98 TR 177 TR 183 TR 176

3208 T JEF 289 0 8.52 TR 289 TR 290 TR 218

3209 T LIC 18 0 7.97 Concord SR 37 Northridge (C21)

3210 T MEG 355 0 0.94 Kennedy Rd. CR 99 Titus Rd.

3211 T MUS 120 0 3.04 Lentz Rd. Canal Rd. Vickers Hill Rd.

3212 T PER 97 0 0.36 CR 97 (Tecumseh Rd.) SR 93 End

3213 T SCI 132 0 3.3 Hills Rd. CR 32 (Rarden Rd.) Carter Rd. (TR 130)

3214 T VIN 12E 0 17.68 TR 12E SR 327 Hocking Co. TR 176

Appendix C Average Speed Calculated Directly From Database

Posted Number Total Speeds Running Speeds

Code Speed Segments Off-peak PM peak Off-peak PM peak

1 55 1 67 0 67 0

1 65 26 64 0 64 0

2 45 7 45 0 49 0

2 50 6 56 0 56 0

2 55 13 56 0 56 0

2 55 9 54 0 54 0

2 55 14 52 0 55 0

3 35 7 45 0 48 0

3 55 31 54 0 55 0

4 25 20 23 0 27 0

4 35 7 30 0 38 0

4 40 2 38 0 46 0

4 45 4 45 0 45 0

4 50 6 51 0 51 0

4 55 37 53 0 55 0

5 35 2 40 0 40 0

5 45 3 47 0 49 0

5 55 33 48 0 52 0

6 25 2 27 0 34 0

6 40 2 41 0 41 0

6 55 38 47 0 53 0

7 25 6 25 0 27 0

7 35 24 32 0 39 0

7 40 2 36 0 36 0

7 45 2 53 0 53 0

7 50 2 47 0 47 0

7 55 31 53 0 55 0

8 25 2 29 0 32 0

8 35 2 37 0 37 0

8 45 5 45 0 45 0

8 55 25 46 0 48 0

9 35 2 34 0 39 0

9 40 2 33 0 38 0

9 45 4 39 0 48 0

9 55 32 37 0 41 0

11 55 3 66 49 66 49

11 60 4 62 0 62 0

11 65 27 62 61 62 61

12 25 7 22 20 27 26

12 35 64 27 27 33 34

12 40 19 32 31 38 41

12 45 19 36 33 41 40

12 50 12 30 26 41 39

12 55 2 58 60 58 60

Posted Number Total Speeds Running Speeds

Code Speed Segments Off-peak PM peak Off-peak PM peak

13 25 6 26 24 30 30

13 35 60 27 27 34 33

13 40 20 30 28 38 36

13 45 4 41 45 47 45

13 50 2 49 45 49 45

13 55 6 51 44 57 48

14 20 2 23 21 29 28

14 25 26 22 21 28 28

14 35 53 25 25 34 34

14 40 4 31 31 40 41

14 45 24 33 32 39 38

14 50 2 56 56 56 56

14 55 2 59 57 59 57

15 25 4 28 27 31 32

15 30 2 23 0 28 0

15 35 43 29 30 35 35

15 40 2 42 42 42 42

15 45 3 45 44 47 47

15 50 3 41 43 51 46

16 25 36 23 23 29 29

16 35 4 33 33 37 37

21 25 16 20 21 26 30

21 35 1 39 47 39 47

21 55 44 45 41 48 45

21 60 10 59 62 60 64

21 65 13 60 59 60 59

22 25 93 20 20 27 26

22 35 87 26 24 32 32

23 25 65 16 18 23 25

23 35 74 25 25 31 32

23 45 14 37 37 43 44

24 25 91 21 20 27 28

24 30 4 26 32 31 32

24 35 71 22 22 32 32

25 25 105 18 17 28 26

25 30 2 28 29 28 29

25 35 62 23 23 31 31

25 55 6 34 35 45 43

26 25 26 12 12 25 24

31 55 44 40 0 44 0

32 25 4 31 0 32 0

32 35 4 34 0 37 0

32 55 27 29 0 31 0

41 40 26 36 0 57 0

42 40 16 44 0 44 0

43 40 2 42 0 42 0

51 35 22 32 24 46 38

51 65 1 73 72 73 72

52 35 21 46 37 46 37

Appendix D Regression Equation Derived Speeds

Travel Time Speeds

Posted

Speed: 25 30 35 40 45 50 55 60 65

Off-peak:

Class

1 68 67 66 64

2 32 35 39 43 47 51 54 58 62

3 40 43 45 47 50 52 54 57 59

4 23 28 33 38 43 48 53 59 64

5 38 39 41 43 45 46 48 50 51

6 28 32 35 38 41 44 47 51 54

7 23 28 33 38 43 48 54 59 64

8 32 34 36 39 41 44 46 49 51

9 34 35 35 36 36 37 37 38 38

11 66 65 64 62

12 21 25 28 31 34 37 40 43 47

13 18 23 28 33 38 43 48 53 58

14 19 23 27 31 35 38 42 46 50

15 22 26 30 34 39 43 47 51 56

16 23 28 33 38 42 47 52 57 62

21 34 40 47 53 60

22 20 23 26 28 31 34 37 39 42

23 16 21 26 30 35 40 45 50 55

24 21 21 22 23 23 24 24 25 25

25 18 20 23 25 28 30 33 35 38

32 33 32 31 31 30 30 29 29 28

PM peak hour:

11 43 49 55 61

12 22 24 27 29 32 34 36 39 41

13 19 23 27 31 35 39 44 48 52

14 19 23 27 30 34 38 41 45 48

15 23 27 31 35 39 43 48 52 56

16 23 28 33 39 44 50 55 61 66

21 41 46 50 54

22 20 22 24 25 27 29 30 32 33

23 17 22 26 30 34 39 43 47 51

24 20 21 22 23 23 24 25 26 26

25 17 20 23 26 29 32 35 38 41

Running Speeds 5-9-01

Posted

Speed: 25 30 35 40 45 50 55 60 65

Off-peak:

Class

1 68 67 66 64

2 38 41 44 47 50 53 56 59 61

3 45 47 48 50 52 53 55 56 58

4 28 32 37 42 46 51 55 60 65

5 36 39 42 44 47 49 52 54 57

6 33 36 40 43 47 50 53 57 60

7 29 33 38 42 46 51 55 60 64

8 33 35 38 41 43 46 49 51 54

9 43 43 42 42 42 42 42 41 41

11 66 65 64 62

12 27 30 34 37 40 44 47 51 54

13 25 30 35 40 44 49 54 59 64

14 27 31 34 38 41 44 48 51 55

15 27 31 36 40 45 50 54 59 63

16 29 33 37 41 45 50 54 58 62

21 38 44 50 55 61

22 27 29 32 34 37 39 42 44 46

23 23 27 32 36 41 46 50 55 60

24 27 29 32 34 37 40 42 45 47

25 28 30 32 35 37 39 42 44 46

32 34 34 33 33 32 32 32 31 31

PM peak hour:

11 43 49 55 61

12 28 31 34 37 41 44 47 51 54

13 27 30 34 37 40 44 47 50 54

14 28 31 34 38 41 44 47 50 53

15 29 32 36 39 43 47 50 54 57

16 29 33 37 41 45 49 53 58 62

21 46 50 53 57

22 26 29 32 35 38 42 45 48 51

23 24 29 33 37 41 46 50 54 59

24 28 30 32 34 36 38 39 41 43

25 26 29 31 34 37 39 42 45 48

2009 travel time study update

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