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Publication Number: FHWA-HRT-12-054
Date: December 2012

 

Methodologies to Measure and Quantify Transportation Management Center Benefits: Final Synthesis Report

5. Methodologies for Developing Measures

This section describes the methodologies used to select and obtain many of these measures. In many cases, the data structures described in this section are employed. (Note that table 6 identifies the measures examined in this study.)

5.1 Delay and Travel Time Measures

5.1.1 Freeway Delay and Travel Time

Many FMSs are equipped with point-based and, in some cases, probe-based traffic detectors to perform normal traffic management functions. Since these detectors provide a basis for automatic data collection for performance evaluation purposes, the manual effort to obtain measures based on speed and travel time is minimal.

Many of the measures in table 6 involve the computation of travel time and delay. System delay is defined as is the sum of freeway mainline delay, freeway ramp delay, and intersection delay for all vehicles. System travel time has a similar relationship. Vehicle travel time and delay consider these quantities on an individual trip basis.

The relationships provided below describe the requirements for obtaining freeway mainline data.

5.1.1.1 Mainline Delay and Travel Time Evaluation for Point Detectors

Figure 6. Equation. Domain system travel time. TT open parenthesis DO and N5 closed parenthesis equals T5 times V open parenthesis DO and N5 closed parenthesis times LE open parenthesis DO closed parenthesis divided by SD open parenthesis DO and N5 closed parenthesis.

Figure 6. Equation. Domain system travel time.

Where:

TT = System mainline travel time (vehicles per hour).
DO = Domain ID.
N5 = 5-min evaluation period index number.
T5 = 5-min period for mainline and ramps.
V = Roadway volume (vehicles per hour).
LE = Length of link, domain, or probe sensing region (mi).
SD = Domain speed (mi/h).

In some systems, SD represents weighted speed.(9) Since speed and volume varies in different lanes, weighted speed is the product of lane volume and lane speed divided by the total volume.

Figure 7. Equation. Domain system delay. If open parenthesis TT open parenthesis DO and N5 closed parenthesis minus T5 times V open parenthesis DO and N5 closed parenthesis times the fraction LE open parenthesis DO closed parenthesis divided by SR open parenthesis DO closed parenthesis closed parenthesis is greater than zero, then D open parenthesis DO and N5 closed parenthesis equals open parenthesis TT open parenthesis DO and N5 closed parenthesis minus T5 times V open parenthesis DO and N5 closed parenthesis times the fraction LE open parenthesis DO closed parenthesis divided by SR open parenthesis DO close parenthesis closed parenthesis. Else D open parenthesis DO and N5 closed parenthesis equals 0.

Figure 7. Equation. Domain system delay.

Figure 8. Equation. Link system travel time. TT open parenthesis L and N5 closed parenthesis equals the sum of TT open parenthesis DO and N5 closed parenthesis from DO equals a to b.

Figure 8. Equation. Link system travel time.

Where:

L = Link ID.

Figure 9. Equation. Link system travel time for 15-min periods. TT open parenthesis L and P closed parenthesis equals the sum of TT open parenthesis L and N5 closed parenthesis from NF equals N5 to NF plus 3.

Figure 9. Equation. Link system travel time for 15-min periods.

Where:

P = 15-min period index.
NF = 5-min index at the beginning of the 15-min period.

Figure 10. Equation. Link system delay. D open parenthesis L and N5 closed parenthesis equals the sum of D open parenthesis DO and N5 closed parenthesis from DO equals a to b.

Figure 10. Equation. Link system delay.

Where:

D = System mainline delay for measurement interval (vehicle hours).

Figure 11. Equation. Link system delay for 15-min periods. D open parenthesis L and P closed parenthesis equals the sum of D open parenthesis L and N5 closed parenthesis from NF equals 5 to NF plus 3.

Figure 11. Equation. Link system delay for 15-min periods.

Figure 12. Equation. Domain vehicle travel time. VT open parenthesis DO and N5 closed parenthesis equals T5 times LE open parenthesis DO closed parenthesis divided by SD open parenthesis DO and N5 closed parenthesis.

Figure 12. Equation. Domain vehicle travel time.

Where:

VT = Vehicle travel time (hours).

Figure 13. Equation. Domain vehicle delay. If open parenthesis VT open parenthesis DO and N5 closed parenthesis minus T5 times LE open parenthesis DO closed parenthesis divided by SR open parenthesis DO closed parenthesis is greater than zero closed parenthesis, then VD open parenthesis DO and N5 closed parenthesis equals open parenthesis VT open parenthesis DO and N5 closed parenthesis minus T5 times LE open parenthesis DO closed parenthesis divided by SR open parenthesis DO closed parenthesis closed parenthesis. Else VD open parenthesis DO and N5 closed parenthesis equals 0.

Figure 13. Equation. Domain vehicle delay.

Where:

VD = Vehicle delay (hours).
SR = Reference speed for delay (mi/h).

VT open parenthesis L and N5 closed parenthesis equals the sum of VT open parenthesis DO and N5 closed parenthesis from DO equals a to b.

Figure 14. Equation. Link vehicle travel time.

VT open parenthesis L and P closed parenthesis equals the sum of VT open parenthesis L and N5 closed parenthesis from NF equals N5 to NF plus 3.

Figure 15. Equation. Link vehicle travel time for each 15-min period.

VD open parenthesis L and NF closed parenthesis equals the sum of VD open parenthesis DO and N5 closed parenthesis from DO equals a to b.

Figure 16. Equation. Link vehicle delay.

VD open parenthesis L and P closed parenthesis equals the sum of VD open parenthesis L and N5 closed parenthesis from NF equals N5 to NF plus 3.

Figure 17. Equation. Link vehicle delay for each 15-min period.

5.1.1.2 Mainline Delay and Travel Time Evaluation for Probe Detectors

Probe detectors provide the basis for developing link delay and link travel time. Because the boundaries of probe sensing regions may not directly correspond to link boundaries, a domain structure (see figure 4) or an equivalent relationship is required. The basic concept requires determining the speed in the set of domains included in the probe sensing region by dividing the region's length by the travel time measured by the probe vehicles, as shown in figure 18 and figure 19. SP represents the speed for all domains encompassed by the probe-sensing region and is used to compute domain and link vehicle travel time and delay in figure 12 through figure 17 at the 5-min level. It is also used for probe detection in place of SD in figure 6 and figure 12

TP open parenthesis PR and T5 closed parenthesis equals 1 divided by x times the sum of TP open parenthesis i closed parenthesis from i equals 1 to x..

Figure 18. Equation. Travel time as sensed by probe PR.

SP open parenthesis PR closed parenthesis equals LE open parenthesis PR closed parenthesis divided by TP open parenthesis PR and T5 closed parenthesis.

Figure 19. Equation. Probe-sensing region speed for region PR.

Where:

TP = Travel time as sensed by probe vehicles (hours).
PR = Probe sensing region ID.
x = Number of vehicles in 5- or 15-min probe vehicle sample.
SP = Probe sensing region speed (mi/h).
RRT = Reference ramp travel time.

Probe detection technologies are discussed in section 6 of this report.

In order to develop system delay and system travel time measures, the volume variable required by figure 6 and figure 7 must be obtained. A source of link volume data, such as a point detector station, is required.

5.1.1.3 Entry Ramp Travel Time

Unlike the mainline, most ITSs do not provide an automatically based sensing methodology for obtaining entry ramp time and delay. Ramp data, if employed, are most conveniently accumulated on a 15-min basis when considering the ramp as a link.

5.1.1.4 Freeway System Travel Time and Delay

Freeway travel time and delay are the sum of mainline travel times and (optionally) ramp travel times and delays. Computation on a 15-min basis is convenient for further measure development.

FT open parenthesis L and P closed parenthesis equals TT open parenthesis L and P closed parenthesis plus T15 times V open parenthesis R closed parenthesis times the sum of RT open parenthesis R and P closed parenthesis from R equals 1 to RN.

Figure 20. Equation. Freeway system travel time.

FD open parenthesis L and P closed parenthesis equals FT open parenthesis L and P closed parenthesis minus T15 times LE open parenthesis L closed parenthesis divided by SR open parenthesis L closed parenthesis minus V open parenthesis R closed parenthesis times the sum of RRT open parenthesis R and P closed parenthesis from R equals 1 to RN.

Figure 21. Equation. Freeway system delay.

Where:

FT = Freeway system travel time.
RT = Entry ramp travel time (hours).
R = Ramp index.
RN = Total number of ramps.
FD = Freeway system delay.

5.1.1.5 Private Vehicle Occupant System Delay

The basic measure is computed on a 15-min basis and link basis and aggregated annually on a system-wide basis, as shown in figure 22.

LPP open parenthesis L and P closed parenthesis equals K subscript 1 times FP open parenthesis L and P closed parenthesis times FD open parenthesis L and P closed parenthesis.

Figure 22. Equation. Private vehicle occupant system delay.

Where:

K1 = Average number of travelers in a private passenger vehicle.
FP = Private passenger vehicle fraction of traffic volume.
LPP = Traveler system delay in private passenger vehicles (person hours).

5.1.1.6 Commercial Vehicle Occupant System Delay

The basic measure is computed on a 15-min basis and link basis and aggregated annually on a system-wide basis, as shown in figure 23.

LPT open parenthesis L and P closed parenthesis equals K subscript 2 times FC open parenthesis L and P closed parenthesis times FD open parenthesis L and P closed parenthesis.

Figure 23. Equation. Commercial vehicle occupant system delay.

Where:

K2 = Average number of occupants in commercial vehicle.
FC = Commercial vehicle fraction of traffic volume.
LPT = Occupant delay in commercial vehicles (person hours).

5.1.1.7 Goods Inventory Delay

The basic measure is computed on a 15-min basis and link basis and aggregated annually on a system-wide basis, as shown in figure 24.

LPG open parenthesis L and P closed parenthesis equals K subscript 3 times FR open parenthesis L and P closed parenthesis times FD open parenthesis L and P closed parenthesis.

Figure 24. Equation. Goods inventory delay.

Where:

K3 = Average weight of load in trucks carrying goods (tons).
FR = Traffic volume fraction of trucks carrying loads, excluding deadheading trucks.
LPG = Goods delay (ton hours).

5.1.2 Route Travel Time and Reliability of Route Travel Time

5.1.2.1 Route Travel Time

Route travel time is commonly provided to the motorist by DMS on the freeway mainline as well as through Web sites. Designated routes are often provided for this purpose, and these routes are convenient to use for evaluation.(17)

Route travel time is the sum of route link travel times and may be computed as follows:

RTT equals the sum of VT open parenthesis L and N5 closed parenthesis from L equals RI to RO.

Figure 25. Equation. Route travel time.

Where:

RTT = Route travel time (hours).
RI = Link on start of selected route.
RO = Link on end of selected route.
VT = Route link travel time (hours).

If a trip starts at 7 a.m., the travel time for the first link on the route (designated as RI) becomes VT. N5 for the first link in this case is 73 (12 5-min periods for the period from midnight until 7 a.m. plus the current evaluation period). It is designated as NSTART.

Recognizing that the links on the route might be covered during different time periods and consequently at different speeds, a laddered concept for computing route travel times was studied.(17) Route travel time is the sum of route link travel times and is computed for the appropriate time period for that link. The concept is described below.

If VT for a link is less than 5 min, then the travel time for the next link uses the same 5-min time period. If VT is greater than or equal to 5 min, then the travel time for the next link uses the subsequent 5-min time period. Higatani et al. indicate that this approach is more accurate than the summation of link travel times computed for a single time period.(18)

Figure 26 provides a flow chart that implements this concept.

This figure shows a flowchart of route travel times. The chart starts as follows: L equals 1 flows to RTT equals zero, which flows to N5 equals NSTART. This flows into the equation, is LE open parenthesis L closed parenthesis divided by VT open parenthesis L, N5 closed parenthesis greater than 0.0833 times open parenthesis 1 plus open parenthesis N5 minus NSTART close parenthesis. If yes, N5 equals NSTART plus 1, and the flow returns to the question. If no, the diagram flows to RTT equals RTT plus VT open parenthesis L, N5 closed parenthesis. The diagram then flows to the question, is L equal to RO? If no, L equals L plus 1, and the flow returns to the first equation. If yes, the user has reached "Exit." A notes section of the figure includes the following information: (1) the route shown starts with L equals 1 and terminates with L equals LR, (2) 0.0833 represents a 5-min period in hours, (3) NSTART is the index for the 5-min time period that represents the start of the route, and (4) when congestion is present, the process selects a 5-min time period for the successive link appropriate for passage from the current link.

Figure 26. Flowchart. Route travel times.

Similarly, freeway route delay (ROD) may be computed as follows:

 ROD equals RRT minus the sum of LE open parenthesis L closed parenthesis divided by SR open parenthesis L closed parenthesis from L equals RI to RO.

Figure 27. Equation. Freeway route delay.

For evaluation purposes, route delay is most meaningful when used as an average value for a peak hour or peak period. To be statistically meaningful, a sufficiently large data sample (number of days for data collection) is required. For a peak hour evaluation, 12 data samples are generated per day. It may be expected during the course of 1 month that data will be available for a minimum of 15 days after eliminating weekends, holidays, and other days that may not be typical because of weather problems, special events, etc. Based on these values, the standard estimate of the mean value of route delay is approximately 7.5 percent.(19)

5.1.2.2 Route Travel Time Reliability

Travel time reliability measures the extent of this unexpected delay. A formal definition for travel time reliability is the consistency or dependability in travel times, as measured day-to-day and/or across different times of the day (20)

Travel time variability may be measured by comparing travel times for a specified route for a given time period (e.g., for a peak hour starting at 7 a.m). Shaw recommends a minimum data collection period of 4 weeks at 15-min intervals.(10) Coupling this criterion with the previous discussion of route travel time, if a "trip" is considered to be a calculation of three 5-min travel times for each 15-min period in a weekday peak hour, eliminating holidays and other non-representative days, a 1 month data collection cycle is a sufficiently representative time period.

The basis for travel time variability and the measures that are used to express it is the standard deviation of the travel time measurements. This is given by Martin and Wu as follows:(7)

s squared equals the sum of open parenthesis T subscript j minus M closed parenthesis squared divided by n minus 1.

Figure 28. Equation. Standard deviation of travel time measurements.

Where:

s = Estimate of travel time standard deviation.
Tj = Travel time of the ith trip on a specific route.
M = Mean travel time of a set of sample trips for the period (e.g., 15 min).
n = Number of sample trips.

Commonly used measures of route travel time reliability are the completion of 90 or 95 percent of the trips within a given time. Statistical tables indicate that the relationship between the sample of travel times and the mean are as follows:

Measures that are commonly used include the following:(20)

Buffer time equals 1.64 times s.

Figure 29. Equation. Buffer time.

Planning time equals route travel times plus buffer time.

Figure 30. Equation. Planning time.

The relationship among these measures is shown in figure 31.(20)

This graph shows the relationship between travel time and planning time indices for Los Angeles, CA, in 2003. The index values are on the y-axis from 1.00 to 2.20, and the time of day (weekdays, non-holidays only) is shown on the x-axis starting from 12 a.m. and increases hourly for 24 h to 12 a.m. Two curves are shown on the graph: a solid line shows the average travel time index and a dashed line shows the planning time index. The travel time curve has two humps that show the morning and evening rush hours. The index value rises from 1.00 around 5:30 a.m. to about 1.30 just before 8:00 a.m. and then drops back down to about 1.10 by 11:00 a.m. The index holds at around 1.10 until the start of the evening rush at 1:30 p.m. and then rises to a peek value of around 1.45 near 6:00 p.m. After 6:00 p.m., the index value drops back at almost a constant rate to 1.00 at about 8:30 p.m. The planning time index mimics the travel time curve except that it is offset above the travel time curve. Starting at 5:30 a.m., the planning time index curve leaves the travel time index curve and increases to just over 1.80 by 8:00 a.m. It then stays above the travel time curve and drops down to just over 1.20 around noon. During the evening rush, the planning time index rises to just over 2.00 before returning to 1.00 between 9:00 and 9:30 p.m. A double arrowed line is drawn between the two evening peeks, and a label defines this line as the "buffer" between expected average and 95th percentile travel times.

Figure 31. Graph. Relationship of travel time reliability indices.

The basis for all of the reliability measures is route or point-to-point travel times. The following lists shows the four basic ways in which these travel times can be developed:(20)

  1. Directly calculated from continuous probe vehicle data.
  2. Estimated from continuous point-based detector data.
  3. Collected in periodic special studies (e.g., floating car runs).
  4. Estimated using computer simulation, sketch planning, or demand forecasting models.

5.1.3 Throughput

Throughput may be evaluated as VMT for a link for the peak hour. For the evaluation process, for each 5 min of the peak hour, the lowest volume for each domain in the link (LV) is identified. Peak hour throughput (PHT) is provided in figure 32.

PHT open parenthesis L closed parenthesis equals the sum of T5 times LE open parenthesis L closed parenthesis times LV open parenthesis L and N5 closed parenthesis from N5 equals 5-min period identifier for peak hour start to N5 plus 12.

Figure 32 . Equation. Peek hour throughput.

Throughput may be considered a measure of system efficiency for a freeway link, particularly during the peak period. Gordon et al. suggest that plots of traveler miles versus traveler hours for various conditions may be useful for evaluating the general performance of ITS improvements.(21) This concept is shown in figure 33, where the solid curve represents improved system operation for all traffic conditions relative to the dashed curve. The slope of the line from the origin to a point on the curve represents speed for the link.

This line graph shows two rounded curves. One plotted with a solid line represents improved system operations for all traffic conditions relative to the dashed curve, which is slightly below it. The y-axis is labeled vehicle miles per hour, and the x-axis is labeled vehicle hours per hour. No values are provided on either axis.

Figure 33. Graph. Link throughput.

The throughput measures originally shown in table 6 include the following:

5.1.4 Surface Street Delay and Travel Time

Signalized surface streets experience discontinuous flow. As a result, speeds measured by point detectors (where available) do not provide information that may directly be used to develop link speeds and travel times. While technologies that make greater use of automatic data are emerging, current evaluations often feature a strong manual component. Section 6 of this report provides more information on these technologies.

The total delay experienced by a road user can be defined as the difference between the travel time actually experienced and the reference travel time that would result in the absence of traffic control, changes in speed due to geometric conditions, any incidents, and the interaction with any other road users. Control delay is defined as the portion of delay that is attributable to the control device (i.e., the signal, its assignment of right-of-way, and the timing used to transition right-of-way in a safe manner) plus the time decelerating to a queue, waiting in queue, and accelerating from a queue. For typical through movements at a signalized intersection, total delay and control delay are the same in the absence of any incidents.(22) Figure 34 shows control delay in a time-space context.(4)

The figure shows the control delay in a time-space diagram. Time is shown on the x-axis, and distance is shown on the y-axis. A horizontal line is labeled "Stop line." The path of the vehicle is show as a dark curve on the graph and consists of four different segments. The first segment is labeled "Running speed" and is followed by a short deceleration curve before reaching the stop line. The deceleration curve is followed by a segment labeled "Stopped delay" and is a horizontal line a short distance below the stop line. The stopped delay segment is followed by a short curve labeled "Acceleration" until the vehicle again reaches the running speed. The point where the vehicle curve intersects the stop line is labeled "T subscript 2." A second thin straight line starts at the same point the as the vehicle curve and intersects the stop line at T subscript 0 and is labeled "Target speed." Another short thin line is projected from the start of the deceleration line along the slope of the running speed and is labeled "T subscript 1" where it intersects the stop line. Additionally, a short thin line (also paralleling the slope of the running speed line) projects from the beginning of the stopped delay line to an intersection with the stop line. This intersection is not labeled; however, the time measured between this intersection and T subscript 2 is labeled "Queue delay." The time measured between T subscript 1 and T subscript 2 is labeled "Control delay," and the time measured between T subscript 0 and T subscript 2 is labeled "Segment delay."

Figure 34. Graph. Control delay.

Control delay for a lane group may be obtained by observations at the intersection or by measuring the time it takes for a vehicle to traverse a path. The relationship between travel time and control delay for a lane group is given by figure 35 as follows:(4)

LCD open parenthesis LI and LG closed parenthesis equals RLTT open parenthesis LI and LG closed parenthesis minus RET open parenthesis LI and LG closed parenthesis.

Figure 35. Equation. The relationship between travel time and control delay.

Where:

LCD = Control delay for the intersection lane group associated with a travel link for a 15-min time period.
RET(LI, LG) = Reference vehicle travel time for the lane group for the travel link.
RLTT(LI, LG) = Vehicle travel time for the lane group for the travel link.

Evaluation methodologies generally include either measuring control delay and computing vehicle travel time using the equation in figure 35 or measuring the link travel time and identifying the control delay using that equation.

Current evaluation methodologies primarily use intersection observations and/or measurements using floating vehicles to obtain the variables. Recent technology developments, as described in section 6 of this report, have resulted in a more efficient use of the manual labor required as well as automated techniques to obtain these data.

Chapter 31 of the Highway Capacity Manual provides worksheets to assist in recording manual queue observations and computing control delay from these observations.(4)

Table 10 provides an estimate of the number of runs required to achieve a 95 percent level of confidence.(23)

Table 10. Sample size requirements.

Average Range in Running Speed
(mi/h) × R
Minimum Number of Runs for Specified Permitted Error
+1.0 mi/h +2.0 mi/h +3.0 mi/h +4.0 mi/h +5.0 mi/h
2.5 4 22 2 2 2
5.0 8 4 3 2 2
10.0 21 8 5 4 3
15.0 38 14 8 6 5
20.0 59 221 12 8 6

* Interpolation should be used when R is a value other than those shown in column 1.

Figure 36 provides the basis for evaluating individual vehicle travel time and control delay for a lane group at a signalized intersection approach as well as the measures derived from them.

5.1.4.1 Surface Street System Delay

Intersection delay for a 15-min period is provided in figure 36 as follows:

LCD open parenthesis LI closed parenthesis equals the sum of LCD open parenthesis LI and LG closed parenthesis times V open parenthesis LI and LG closed parenthesis times T15 from LG equals 1 to intersection lane groups.

Figure 36. Equation. Intersection delay.

Where:

LI = Intersection ID.
LG = Traffic signal lane group.
T15 = 15 min for intersection signals and surface streets.

System delay (SSSD) for a 15-min period is provided in figure 37 as follows:

SSSD equals the sum of LCD open parenthesis LI closed parenthesis from LI equals 1 to system intersections.

Figure 37. Equation. System delay.

5.1.4.2 Surface Street Route Delay

Surface street route delay (SSRD) is provided in figure 38 as follows:

SSRD equals the sum of LCD open parenthesis LI and lane group on route closed parenthesis from LI equals first link on route to last link on route.

Figure 38. Equation. Surface street route delay.

5.1.4.3 Surface Street Route Travel Time

Surface street route travel time (RTT) is provided in figure 39 as follows:

RTT equals the sum of RLTT open parenthesis LI and lane group on route closed parenthesis from LI equals first link on route to last link on route.

Figure 39. Equation. Surface street route travel time.

5.1.4.4 Other Surface Street Delay Measures

By substituting SSSD for FD, figure 22 through figure 24 may be used to compute system delay for private vehicle occupants, commercial vehicle occupants, and goods inventory.

5.2 Safety Measures

5.2.1 General Crash Measures

Agencies typically collect and classify crash data based on crash reports to identify trends and areas requiring improvement. Depending on the type of data collected, the database management systems used by these agencies have a great deal of flexibility in providing data at required locations for various functions.

Table 11 shows an example of statewide statistics for Washington State, and table 12 shows an example of a Washington State summary report of crashes by type.(24)

The methodologies developed under this study focus on developing the data for the safety measures identified in table 6 by location. The measures required for the benefit-cost evaluation approach described in this report are as follows:

Table 11. 2009 average collision rates by functional class in Washington-Northwest region (State routes only).

Type of Area

Principal Arterial

Minor Arterial

Collector

Interstate

All Highways

Rural Areas

VMT (millions)

554.74

455.55

216.70

940.03

2,167.02

Miles of highway

133.41

255.98

158.96

57.61

605.96

Total collisions

587

518

394

494

1,993

Collision rate*

1.06

1.14

1.82

0.53

0.92

PDO collisions

378

292

249

347

1,266

PDO collision rate*

0.68

0.64

1.15

0.37

0.58

Injury collisions

205

219

143

145

712

Injury collision rate*

0.37

0.48

0.66

0.15

0.33

Fatal collisions

4

7

2

2

15

Fatal collision rate**

0.72

1.54

0.92

0.21

0.69

Urban Areas

VMT (millions)

4,124.91

503.58

0.00

6,827.04

11,455.53

Miles of highway

333.18

98.04

0.00

141.43

572.65

Total collisions

9,032

1,501

0

9,266

19,799

Collision rate*

2.19

2.98

0.00

1.36

1.73

PDO collisions

5,981

943

0

6,351

13,275

PDO collision rate*

1.45

1.87

0.00

0.93

1.16

Injury collisions

3,034

551

0

2,898

6,483

Injury collision rate*

0.74

1.09

0.00

0.42

0.57

Fatal collisions

17

7

0

17

41

Fatal collision rate**

0.41

1.39

0.00

0.25

0.36

All Areas

VMT (millions)

4,679.65

959.13

216.70

7,767.07

13,622.55

Miles of highway

466.59

354.02

158.96

199.04

1,178.61

Total collisions

9,619

2,019

394

9,760

21,792

Collision rate*

2.06

2.11

1.82

1.26

1.60

PDO collisions

6,359

1,235

249

6,698

14,541

PDO collision rate*

1.36

1.29

1.15

0.86

1.07

Injury collisions

3,239

770

143

3,043

7,195

Injury collision rate*

0.69

0.80

0.66

0.39

0.53

Fatal collisions

21

14

2

19

56

Fatal collision rate**

0.45

1.46

0.92

0.24

0.41

* Indicates per 1 million VMT.
** Indicates per 100 million VMT.

Table 12. 2009 leading collision type for all collisions in Washington (State routes only).

First Collision Type Eastern Region North Central Region Northwest Region Olympic Region South Central Region Southwest Region
Number Percent Number Percent Number Percent Number Percent Number Percent Number Percent
Rear-end (all types) 748 24 408 22 10,457 48 4,254 44 736 23 914 28
Hit fixed object 691 22 485 26 3,276 15 1,824 19 898 28 969 29
Side-swipe (opposite or same direction) 181 6 85 5 2,856 13 963 10 245 8 293 9
Entering at angle 417 13 194 11 1,715 8 1,055 11 231 7 289 9
All other-same direction 145 5 81 4 951 4 401 4 187 6 144 4
Overturn 268 9 162 9 416 2 276 3 386 12 153 5
All other-opposite direction 173 6 98 5 1,180 5 408 4 128 4 135 4
Vehicle strikes deer 287 9 145 8 171 1 186 2 139 4 154 5
All other-non-collision 31 1 44 2 133 1 79 1 91 3 47 1
Vehicle-pedestrian 43 1 10 1 193 1 80 1 9 0 19 1
One parked one moving 18 1 25 1 118 1 76 1 47 1 63 2
Hit non-fixed object 14 0 31 2 57 0 32 0 43 1 40 1
Vehicle-pedalcyclist 22 1 8 0 106 0 43 0 4 0 25 1
Head-on 20 1 14 1 67 0 39 0 17 1 16 0
Vehicle strikes elk 3 0 8 0 18 0 13 0 41 1 29 1
Domestic animal 15 0 19 1 15 0 15 0 24 1 12 0
Parked position (one car entering/leaving) 10 0 4 0 22 0 18 0 2 0 3 0

Alternatively, the components of the general category of crashes may be used for the benefit-cost analysis. These components include the following:

An example of data from the New York State Department of Transportation (NYSDOT) crash record database that was used for a benefit-cost analysis is shown in table 13 and table 14.(25) The tables show the data sorted by the specific freeway links required for the study.

Depending on the TMC's hours of operation and the crash classifications provided by FMS, TMC-generated data may be used to supplement crash record data.

Table 13. Crash rates for selected links in Rochester, NY, during the accident period from March 1, 2000, to February 28, 2002.

Roadway Link Link Description Total Accidents Average AADT Link Length (mi) Accident Rate Statewide Average Rate
NYS Route 104 Goodman Street interchange 120 68,200 0.80 2.68* 2.26
Culver Road interchange 72 73,000 0.80 1.50 2.26
Route 590 interchange 71 70,000 0.80 1.54 1.94
Route 590 to Bay Road 46 68,000 1.60 0.55 1.78
Bay Road interchange 32 62,000 0.80 0.79 2.26
Bay Road to Five Mile Line Road 12 57,000 1.25 0.21 1.09
Five Mile Line Road to Route 250 88 45,000 2.86 0.91 1.47
Phillips Road to Salt Road 16 42,000 0.90 0.52 1.47
Salt Road interchange 8 33,000 0.40 0.66 1.47
Route 104 Total 465 64,257 10.21 0.96 1.94
Interstate 490 Route 390 interchange 141 90,000 1.46 1.38 1.94
Mount Read interchange 60 100,000 0.47 1.44 2.26
Mount Read Boulevard to inner loop area 229 92,000 1.46 2.19 2.26
Inner loop area 330 107,000 1.59 2.50* 1.94
Goodman Street interchange 80 92,000 0.50 1.99 2.26
Route 490 Total 840 105,770 5.48 1.95* 1.94
NYS Route 590 Browncroft Boulevard interchange 29 90,000 0.40 0.88 2.26
Browncroft Boulevard to Empire Boulevard 31 101,000 0.67 0.55 1.78
Empire Boulevard interchange 113 101,000 0.58 2.25 2.26
Empire Boulevard to Route 104 55 98,000 0.85 0.81 1.78
Route 104 interchange 27 76,000 0.60 0.70 1.47
Ridge Road interchange 18 22,000 0.60 1.60* 1.47
Route 590 Total 273 50,725 3.70 1.94 1.94

*Average accident rate is higher than the statewide average rate for similar facility types.

Table 14. Crash classification by link in Rochester, NY, during accident period from March 1, 2000, to February 28, 2002.

Roadway Link Link Description Severity Total Accidents
Fatality Injury PDO
Total Percent Total Percent Total Percent
NYS Route 104 Goodman Street interchange 0 0.00 31 25.83 89 74.17 120
Culver Road interchange 0 0.00 17 23.61 55 76.39 72
Route 590 interchange 0 0.00 11 15.49 60 84.51 71
Route 590 to Bay Road 0 0.00 13 28.26 33 71.74 46
Bay Road interchange 0 0.00 14 43.75 18 56.25 32
Bay Road to Five Mile Line Road 0 0.00 5 41.67 7 58.33 12
Five Mile Line, Hard, Holt, and Route 250 interchanges 0 1.14 26 29.55 61 69.32 88
Phillips Road to Salt Road 0 0.00 4 25.00 12 75.00 16
Salt Road interchange 0 0.00 4 50.00 4 50.00 6
Route 104 total accidents and severity distribution 1 0.22 125 26.88 339 72.90 465
NYSDOT average severity distribution N/A 0.35 N/A 33.12 N/A 66.53 N/A
Interstate 490 Route 390 interchange 0 0.00 38 25.95 103 73.05 141
Mount Read interchange 0 0.00 18 30.00 42 70.00 60
Mount Read Boulevard to inner loop area 0 0.00 58 25.33 171 74.67 229
Inner loop area 0 0.30 84 25.45 245 74.24 330
Goodman Street interchange 0 0.00 19 23.75 61 76.25 80
Route 490 total accidents and severity distribution 1 0.12 217 25.83 622 74.05 840
NYSDOT average severity distribution N/A 1.35 N/A 33.12 N/A 66.53 N/A
NYS Route 590 Browncroft Boulevard interchange 0 0.00 5 17.24 24 82.76 29
Browncroft Boulevard to Empire Boulevard 0 0.00 9 29.03 22 70.97 31
Empire Boulevard interchange 0 0.00 29 25.66 84 74.34 113
Empire Boulevard to Route 104 0 0.00 18 32.73 37 67.27 55
Route 104 interchange 0 0.00 2 7.41 25 92.59 27
Ridge Road interchange 1 5.56 1 5.56 16 88.89 18
Route 590 total accidents and severity distribution 1 0.37 64 23.44 208 76.19 273
NYSDOT average severity distribution N/A 0.35 N/A 33.12 N/A 66.53 N/A

N/A = Not applicable.

While freeway crash data are generally best organized by links for benefit-cost analyses and when trying to identify locations requiring increased attention, crash data on surface streets are most often classified by intersection location. Crash record databases may be used to organize and analyze data in particular systems for comparison to agency averages. One measure that is useful in making these comparisons is crashes per 1 million vehicles entering the intersection or freeway ramp. Table 15 is an example of average values provided by NYSDOT.(26)

Table 15. Average intersection accident rates for State highways by intersection type based on accident data from January 1, 2007, to December 31, 2008.

Intersection Type All Types ACC/MEV Wet Road ACC/MEV Left Turn ACC/MEV Rear End ACC/MEV Over- Taking ACC/MEV Right Angle ACC/MEV Right Turn ACC/MEV Head On ACC/MEV Side-Swipe ACC/MEV
Three-Legged Intersections
Signal all lanes 0.22 0.04 0.02 0.06 0.01 0.03 0.01 0.01 0.01
Sign all lanes 0.15 0.03 0.01 0.03 0 0.01 0 0 0
No control all lanes 0.09 0.01 0.01 0.01 0 0.01 0 0 0
Four-Legged Intersections
Signal all lanes 0.50 0.09 0.06 0.11 0.02 0.11 0.02 0.01 0.01
Sign all lanes 0.31 0.06 0.02 0.04 0.01 0.08 0.01 0 0
No control all lanes 0.12 0.02 0 0.01 0.01 0.02 0 0 0.01
On Ramp (All Control)
Merge with one lane 0.07 0 - - - - - - -
Merge with two+ lanes 0.04 0.01 - - - - - - -
Off Ramp (All Control)
Merge with one lane 0.08 0.08 - - - - - - -
Merge with two+ lanes 0.04 0.01 - - - - - - -

ACC/MEV = Accidents per million vehicles entering the intersection.

- Indicates accident information was not collected.

Note: NYSDOT stopped processing most non-reportable accidents beginning with 2002 accident data. Therefore, the rates are based primarily on just reportable accidents from NYSDOT.

Kar and Datta describe a complex weighting of PDO, injury, and fatality crash costs, as well as crash frequency to develop a safety performance index (SPI).(27) Their findings indicate that SPI may be used for planning resource allocations to reduce crashes.

5.2.1.1 Crash Causality

Some agencies maintain extensive databases for classification of crashes by causality factors.
For example, WSDOT maintains a database that reports on the details of a number of factors, including the following:(24)

Because ITS has different impacts on these factors and agencies collect and report crash causality data using different formats with varying levels of detail and different importance scales, researchers in this project have generally not developed specific measures to deal with these items. However, it is recognized that work zone crashes are important to most agencies, and TMC operations often significantly include management assistance for this issue. Therefore, measures are included in table 6 and table 7 for work zone crashes.

Table 16. WSDOT crash data for contributing circumstances.(24)

Driver Contributing Circumstances Fata Collisions Serious Injury Collisions Minor Injury Collisions PDO Collisions All Collisions
Exceeding reasonable safe speed 107 462 7,317 13,808 21,694
Did not grant right of way to vehicle 24 255 5,754 14,311 20,344
Follow too close 4 118 6,323 10,548 16,993
Other 56 281 2,818 11,359 14,514
Inattention 25 167 3,347 6,240 9,779
Under influence of alcohol 184 386 2,464 3,459 6,493
Disregard stop and go light 8 70 1,408 1,935 3,421
Improper turn 2 16 560 2,662 3,240
Driver distractions outside vehicle 2 35 961 1,645 2,643
Exceeding stated speed limit 80 216 932 1,346 2,574
Operating defective equipment 12 56 668 1,639 2,375
Improper backing 0 6 127 2,159 2,292
Disregard stop sign-flashing red 20 60 854 1,301 2,235
Over center line 54 154 679 884 1,771
Apparently asleep 10 70 665 907 1,652
Did not grant right of way to pedestrian/pedal cyclist 16 136 1,286 40 1,478
Driver interacting with passengers, animals, or objects in the vehicle 6 26 589 782 1,403
Other driver distractions inside vehicle 1 22 481 717 1,221
Improper passing 22 45 296 847 1,210
Unknown driver distraction 1 8 299 594 902
Driver operating handheld telecommunication device 4 19 313 470 806
Apparently ill 8 43 413 342 806
Under influence of drugs 11 53 332 399 795
Improper U-turn 2 15 205 562 784
Driver adjusting audio or entertainment system 0 6 160 252 418
Driver eating or drinking 4 9 119 225 357
Apparently fatigued 1 8 142 164 315
Improper parking location 0 7 17 188 212
Driver operating other electronic device 1 3 71 107 182
Disregard yield sign-flashing yellow 0 1 51 114 166
Had taken medication 0 5 75 79 159
Failing to signal 0 1 47 111 159
Driver smoking 0 4 47 84 135
Headlight violation 1 4 32 49 86
Driver reading or writing 0 0 32 50 82
Driver operating hands-free wireless telecommunication device 0 1 17 47 65
Improper signal 0 2 11 51 64
Disregard flagger-officer 0 3 20 26 49
Driver grooming 0 0 6 12 18

The Work Zone Safety Performance Measures Guidance Booklet suggests the safety measures shown in table 17.(28)

Table 17. Safety work zone performance measures.

Condition Measure
Site crash rate during construction/site crash rate prior to construction < 1.0 Excellent
Site crash rate during construction/site crash rate prior to construction = 1.0 Good
Site crash rate during construction/site crash rate prior to construction < 1.2 Fair
Site crash rate during construction/site crash rate prior to construction < 1.3 Poor
Site crash rate during construction/site crash rate prior to construction > 1.3 Very poor

This figure is a bar graph showing the five leading contributing circumstances in all collisions. The top circumstance is "exceeding reasonable safe speed," which had 21,694 collisions. The second circumstance is "did not grant right of way to vehicle," which had 20,344 collisions. The third circumstance is "follow too closely," which had 16,993 collisions. The forth circumstance is "other," which had 14,514 collisions. Finally, the fifth circumstance is "inattention," which had 9,779 collisions.

Figure 40. Graph. Five leading contributing circumstances in all collisions.

This figure is a bar graph showing the five leading contributing circumstances in fatal collisions. The top circumstance is "under influence of alcohol," which had 184 collisions. The second circumstance is "exceeding reasonable safe speed," which had 107 collisions. The third circumstance is "exceeding stated speed limit," which had 80 collisions. The forth circumstance is "other," which had 56 collisions. Finally, the fifth circumstance is "over center line," which had 54 collisions.

Figure 41. Graph. Five leading contributing circumstances in fatal collisions.

An overall measure for the TMC is the average of the annual evaluations of the work zones included in the TMC's management region.

5.2.1.2 Secondary Crashes

Secondary crashes result from an existing incident. Many of these crashes occur at the tail of queues that result from the incident. It has been estimated that 14 to 30 percent of crashes are secondary crashes.(29,30)

Secondary crashes are often not identified as such by many of the accident reporting and classification systems. Since the ITS techniques that support more rapid incident clearance and provide advance motorist warning of queues may substantially reduce secondary crashes, secondary crashes are an important measure for ITS performance. These data are best obtained by ensuring that secondary crashes are included as a crash classification parameter in FMS. An overall measure for the TMC is the annual sum of the secondary crashes included in the TMC's management region.

5.3 Fuel Consumption

5.3.1 Freeways

Congestion significantly increases fuel consumption rates per VMT. The fuel consumption rates in table 18 were computed using the Motor Vehicle Emission Simulator (MOVES) model.(31) The model employs a representative vehicle class mix. The speeds listed in the table are average speeds for the driving cycle for which the model is based. The domain speed may be used in conjunction with the table.

Table 18. Fuel consumption rates in gallons per VMT.

Speed Range Year
2011 2016
10 mi/h > s 0.175 0.167
20 mi/h > s ≥ 10 mi/h 0.077 0.073
30 mi/h > s ≥ 20 mi/h 0.059 0.056
40 mi/h > s ≥ 30 mi/h 0.052 0.050
50 mi/h > s ≥ 40 mi/h 0.050 0.048
60 mi/h > s ≥ 50 mi/h 0.048 0.046
s > 60 mi/h 0.049 0.046

Note: s represents the speed range.

Fuel consumption (FUF) in gallons for a domain for a 5-min period is computed as follows:

FUF open parenthesis DO and T5 closed parenthesis equals 0.0833 times G time LE open parenthesis DO closed parenthesis times V open parenthesis DO closed parenthesis.

Figure 42. Equation. Fuel consumption.

Fuel consumption and changes in fuel consumption are often reported on an annual basis.

5.3.2 Surface Streets

Because surface street travel is characterized by several factors at locations upstream of a queue at a controlled intersection and by delays at the intersection and because detailed observations are usually unavailable at locations away from the intersection, an appropriate measure of system performance is the fuel consumption resulting from control delay at traffic signals.

Federal Highway Administration (FHWA) data developed for this project provide the following conservative fuel consumption rates when intersections experience control delay:

Fuel consumption resulting from control delay for each lane group for a 15-min evaluation period is given by the following equation:

FUP open parenthesis LI, LG, and N15 closed parenthesis equals 0.25 times GA times V open parenthesis LI, LG, and N15 closed parenthesis times LCD open parenthesis LI, LG, and N15 closed parenthesis.

Figure 43. Equation. Fuel consumption due to control delay.

Where:

GA = Fuel consumption rate.
FUP = Fuel consumption for intersections for a 15-min period (gallons).
N15 = 15-min evaluation period index number.

Aggregation of these data to an annual period provides a meaningful measure for improvements to traffic control measures.

5.4 Emissions

Appendix B discusses emissions models and how they apply to performance evaluation.

5.5 Service Quality and User Perceptions

5.5.1 Route Delay

Travel time information is commonly made available to motorists through DMS and other information delivery methods. As a result, motorists are aware of variations in travel time throughout the day as well as day to day. This information is usually provided in terms of the time to reach a freeway exit from a specific DMS or from a prescribed freeway entry location. Route delay is essentially route travel time minus the travel time for a reference speed. For surface streets, it is provided by the equation in figure 38 . Freeway route delay is the sum of link delay for the links comprising the route (see figure 16).

5.5.2 Route Travel Time Reliability

Section 5.1.2.1 describes the methodology to compute freeway route travel time. Some agencies provide information on travel time reliability to motorists, often by means of electronic information delivery techniques. Section 5.1.2.2 discusses the various measures for freeway travel time reliability.

5.5.2.1 LOS

LOS is a commonly used measure for quality of service.(10) The characteristics for freeway LOS are summarized in table 19.(32)

Table 19. Freeway LOS characteristics.

LOS Description
A Free flow with low volumes and high speeds.
B Reasonably free flow, but speeds beginning to be restricted by traffic conditions.
C In stable flow zone, but most drivers are restricted in the freedom to select their own speeds.
D Approaching unstable flow; drivers have little freedom to select their own speeds.
E Unstable flow; may be short stoppages.
F Unacceptable congestion, stop-and-go, and forced flow.

While the American Association of State Highway and Transportation Officials publication, A Policy on Geometric Design of Highway and Streets, suggests a level C LOS for urban and suburban freeways, the decision is based on a number of factors for the local agency to consider.(33) Agencies may also consider the availability of transit alternatives in the selection of a design LOS.(34)

The recommended measure includes LOSs worse than level C as well as a grouping of levels A, B, and C. Table 20 defines LOS in terms of traffic density LOS.(4)

Table 20. LOS criteria for freeway facilities.

LOS Density (passenger cars/mi/lane)
A ≤ 11
B 11-18
C > 18-26
D > 26-35
E > 35-45
F > 45 or any component of demand volume to capacity ratio > 1.00

Density (DD) may be computed from detector measurements as follows:

DD open parenthesis DO and N5 closed parenthesis equals V open parenthesis DO and N5 closed parenthesis divided by SD open parenthesis DO and N5 closed parenthesis.

Figure 44. Equation. Density.

Commonly used LOS measures include the following:

DWL open parenthesis L and N5 closed parenthesis equals the fraction the sum of DD open parenthesis DO closed parenthesis times V open parenthesis DO closed parenthesis times LE open parenthesis DO closed parenthesis from DO equals 1 to domains in link divided by the sum of V open parenthesis DO closed parenthesis times LE open parenthesis DO closed parenthesis from DO equals 1 to domains in link.

Figure 45. Equation. 5-min weighted average link density.

DWLP open parenthesis L and N60 closed parenthesis equals 0.083 times the sum of DWL open parenthesis L and N5 closed parenthesis from N5 equals index for start of peak hour to N5 plus 12.

Figure 46. Equation. Peak hour weighted average link density.

Table 21. LOS for signalized intersections.

LOS

Description

A Control delay ≤ 10 s/vehicle
B 20 s/vehicle ≥ control delay > 10 s
C 35 s/vehicle ≥ control delay > 20 s
D 55 s/vehicle ≥ control delay > 35 s
E 80 s/vehicle ≥ control delay > 55 s
F Control delay > 80 s/vehicle

5.5.2.2 User Satisfaction

Commonly used measures include the following:

5.5.2.3 Equity

While most ITS functions and operations result in improvements in travel time for the entire system as well as for each motorist, there are functions and operations that may result in delay reduction or reduction in crashes for the entire system but may adversely affect some individual highway users. Examples include the following:

Measures for equity include the following:

This graph shows an example of a Lorenz curve for a metered freeway entrance ramp. The y-axis is labeled proportion of delay from zero to 1.2, and the x-axis is labeled proportion of vehicles from zero to 1.2. A blue thin line extends at a 45-degree angle from 0,0 to 1,1 and represents a condition where there is no equity discrepancy (i.e., all vehicles share the same amount of delay). A heavy black, slightly concave curve extends from 0,0 to 1,1 with around a 1.0 gap between the lines near 0.6 on the x-axis. The heavy line is the Lorenz curve and identifies the relationship between the proportion of delay and proportion of vehicles incurring the delay. Area AD is shown on the graph representing the area between the thin blue line and the heavy black line. Area AT is shown on the graph representing the area under the heavy black line.

Figure 47. Graph. Example of Lorenz curve for a metered freeway entrance ramp.

G equals AD divided by open parenthesis AD plus AT closed parenthesis.

Figure 48. Equation. Gini coefficient.

5.5.3 Incident Clearance Time

A major benefit of using ITS to reduce delay is the ability it provides operations managers to reduce incident clearance time. Although this benefit is included in section 5.1, "Delay and Travel Time Measures," its importance to the evaluation of TMC operations may merit special attention.

Gordon describes the following simplistic model for the total system delay from the time an incident occurs until the queue clears:(21)

D subscript T equals open parenthesis q subscript 2 minus q subscript 3 closed parenthesis times T squared divided by 2 plus open parenthesis q subscript 2 minus q subscript 3 closed parenthesis squared times T squared divided by open parenthesis 2 times open parenthesis q subscript 1 minus q subscript 2 closed parenthesis closed parenthesis.

Figure 49. Equation. Total system delay.

Where:

DT = Total system delay from the time an incident occurs until the queue clears.
q1 = Volume at incident clearance (roadway capacity).
q2 = Volume entering incident location (demand volume).
q3 = Volume when incident is present (restricted capacity resulting from incident).
T = Time from start of incident to incident clearance (capacity is restored).

Rewriting figure 49 as figure 50, Gordon shows that the ratio of change in delay as a result of reduced incident clearance time to incident clearance time is given by figure 51.(21)

D subscript T equals K times T squared.

Figure 50. Equation. Rewriting total system delay.

The derivative of D subscript T divided by T equals 2 times K.

Figure 51. Equation. Relationship between change in delay and reduced incident clearance time.

Where:

T = Incident clearance time.
K = Percentage of delay.

From figure 51, it is observed that a small percentage of reduction in the time needed to clear an incident results in twice the percentage of delay reduced.

Measures to consider include the recording of the time needed to clear an incident and the total delay resulting from the incident. A number of evaluation studies employed techniques to estimate delay and the reduction in delay by service patrols; however, these methodologies are not well suited to non-research-related evaluation efforts.(37,38)

Incident clearance time (T) data may be obtained by subtracting the recorded clock time from the time that the incident is detected from the time that it is cleared (moving lanes cleared). An average incident detection period should be added to obtain the value for T. These data, along with the classification of incidents, are usually collected at the TMC by the traffic management system's incident management screens. Prior to obtaining the average value for T over the evaluation period for each incident class, it is recommended that incidents exceeding 6 h are deleted from the average (or are limited to 6 h) because these long periods are often the result of conditions over which the TMC has little control or influence, such as weather, roadway damage, or special hazardous materials situations.

5.5.4 Service Patrol Measures

Motorist service patrols have proved popular with the public.(39,37) Measures for evaluation include the service patrol assists, quality of service, and rating by public, as outlined in the following sections.

5.5.4.1 Service Patrol Assists

Most agencies that operate service patrol agencies maintain and often publish records of the number of assists and the type of service provided for each response.

5.5.4.2 Quality of Service

The following measures may be used to evaluate the quality of service provided:

Service patrol vehicle operators generally fill out a report for each assist, such as that used by WSDOT (see figure 52 ).(37) The detailed information collected is useful for operations improvements.

5.5.4.3 Rating by Public

Feedback from the public is often obtained through surveys completed by motorists at the time service is provided. Figure 53 shows a survey form used by WSDOT. The public's rating on service is shown in figure 54.

This form shows a sample of a Washington State Department of Transportation service patrol assist form. The form provides space for service patrol staff to fill out information about vehicles they assist. The top of the form is information about the service patrol including "Your Name," "Agency/Company," and "Month, Day, Year." The second section is for information about the location of disabled vehicle, with space for the highway, direction, and mile post or street name. This section also contains two check box areas for information about the lane type and the lane number. Lane type selections include mainline, on-ramp, high-occupancy vehicle, exit-ramp, collector distributor, and express lane. The lane number check boxes include right shoulder, lane 1, lane 2, lane 3, lane 4, lane 5, and left shoulder. The third section of the form is labeled "Time logs for your response." This section contains two columns. The first column is labeled "Detection/
Notification" with three check boxes: (1) subject was found by you, (2) information broadcast by Washington State Patrol, and (3) Other. The second column is unlabeled and provides space for the responder to fill out time information for the following four statements: (1) time you detected or being notified, (2) time you arrived at the scene, (3) time road cleared vehicle out of travel lane, and (4) time you departed from the assisted vehicle. The fourth section is labeled "Check all that apply" and has three columns. The first column in this section is labeled "Cause" and lists the following eight check boxes: disabled, accident, injury accident, debris, pedestrian, fire, unable to locate, and other. The second column is labeled "Problem" and contains the following eight check boxes: fuel, tire, mechanical, overheat, electrical, abandoned, blocking, and other. The third column is unlabeled and contains the following check boxes: (1) push (a) off freeway and (b) to shoulder, (2) tow (a) off freeway and (b) to shoulder, (3) assist, (4) clear off, (5) transport, (6) call additional tow service (a) rotation tow and (b) owner requested, (7) photos taken, and (7) other. The fifth and last section of the form is labeled "Description of disabled vehicle." This section provides space for the responder to include information for up to two vehicles on the license number, State, color, and make. There is a blank space for drivers to fill in any other data about the vehicle they feel is relevant.

Figure 52. Illustration. Washington service patrol assist form.

This figure shows a Washington State Department of Transportation (WSDOT) service patrol survey. The survey begins with a note to the motorist saying: "Dear Motorist: Assistance from this WSDOT Service Patrol is provided to you free of charge by the Washington State Department of Transportation. It is designed to reduce traffic congestion during your daily commute. To help us improve the service, please take a moment to answer these survey questions and mail the form back. No postage is necessary. No gratuities or payments will be accepted by WSDOT Service Patrol drivers. In addition, they cannot recommend secondary tow operators." The survey consists of the eight questions. The first is, How did the WSDOT Service Patrol know you needed assistance? The question has the following four check boxes: (1) another driver saw me, (2) used a call box, (3) State Patrol assistance, or (4) other (with space to fill in an answer). Question 2 is, How long did you wait for Service Patrol assistance? The question has the following six check boxes: (1) Less than 5 min, (2) 5 to 10 min, (3) 10 to 20 min, (4) 20 to 30 min, (5) 30 to 40 min, and (6) Longer). Question 3 is, If the Service Patrol moved your car to a safe area, how long did you wait for additional help? the question has the following seven check boxes: (1) Less than 15 min, (2) 15 to 30 min, (3) 30 to 45 min, (4) 45 to 60 min, (5) 60 to 90 min, (6) Longer, (7) No more help is needed. Question 4 is, If you needed a secondary tow, what company did you choose and why? Space is provided for a written response. Question 6 is, Overall, how would you rate the service? The question has the following five check boxes: (1) Excellent, (2) Good, (3) Fair, (4) Poor, and (5) Other. Question 6 is, How did you know about the Service Patrol Program? The question has the following eight check boxes: (1) newspaper, (2) radio, (3) TV, (4) brochure, (5) friend, (6) billboard, (7) other (with space for a written response), and (8) did not know until today. Question 8 is, How would you improve the WSDOT Service Patrol program? There is space for a written response. The survey concludes with the following statement: "For more information regarding the WSDOT Service Patrol, please call: (206) 726-6752."

Figure 53. Illustration. WSDOT service patrol survey.

This figure is a bar chart comparing the public ratings for the five different Washington State Department of Transportation (WSDOT) service patrol programs in the Seattle and Tacoma, WA, regions. The y-axis shows percent from zero to 100. The x-axis shows the five responses offered on the survey: excellent, good, fair, poor, and other. The five service patrol programs rated are Seattle: Washington State Patrol (WSP), Seattle: registered tow truck operators (RTTO), Seattle: WSDOT, Tacoma: WSP, and Tacoma: RTTO. The chart shows 90 percent or more of the ratings in the excellent category for all five programs. All five programs received a few ratings in the good category. Seattle: RTTO and Seattle: WSDOT received 1 to 2 percent in the fair category. None of the programs received a poor rating. Seattle: WSP, Seattle: RTTO, and Seattle: WSDOT received between 2 and 5 percent in the "Other" category.

Figure 54. Graph. Public rating on WSDOT service patrol program.

5.5.5 Response to Weather Situations

ITS may provide motorist information and other information to police and highway maintenance agencies to assist in responding to weather situations that affect travelling conditions. These conditions include snow/ice, fog, high winds, and flooding.

These conditions may be detected by road weather information systems, fog detectors, and reports by service patrols, motorists, and police. A measure for this service is the average time in minutes from receipt of the alert to the time that information is provided to motorists and to other response services.

5.6 Database to Provide Motorist Information

Providing information to motorists is a key function of freeway and corridor TMCs. Information may be provided via the following:

It is important for the information provided by the TMC to be complete and consistent for all information delivery techniques. The following classes of information may be considered:

The capability of the TMC to provide data that may be accessed by the delivery methods described above may be rated on a scale of 0 to 10 for each of the above classes.

 

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FHWA
United States Department of Transportation - Federal Highway Administration