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44 Why 85th or 50th Percentile Speed? Currently, the predominant method for setting speed limits is with the use of the 85th per- centile speed. It was viewed as being representative of a safe speed that would minimize crashes, and the 1964 Solomon study (45) is frequently quoted as being the source to justify the use of the 85th percentile speed. The use of the 85th percentile speed has been supported because it: â¢ Represents a safe speed that minimizes crashes. â¢ Promotes uniform traffic flow along a corridor. â¢ Is a fair way to set the speed limit based on the driving behavior of most of the drivers (i.e., 85Â percent). â¢ Represents reasonable and prudent drivers since the fastest 15Â percent of drivers are excluded. â¢ Is enforceable in that it is fair to ticket the small percentage (15Â percent) of drivers that exceed the posted speed limit. Criticisms of the 85th percentile speed method have included the following: â¢ Setting the posted speed limit based on existing driver behavior may create unsafe road condi- tions because drivers may not see or be aware of all the conditions present within the corridor. â¢ Setting the posted speed limit on existing driver behavior rather than the roadway context may not adequately consider vulnerable roadway users such as pedestrians and bicyclists. â¢ Drivers are not always reasonable and prudent, or they only consider what is reasonable and prudent for themselves and not for all users of the system. â¢ Using measured operating speeds could cause operating speeds to increase over time (i.e., speed creep). Drivers frequently select speeds a certain increment above the posted speed limit, anticipating that they will not receive a ticket if they are not above that assumed enforce- ment speed tolerance. If this occurs, the resulting operating speed would be above the posted speed limit. Using the 85th percentile speed approach in this situation would result in rec- ommending a posted speed limit that is higher than the existing posted speed limit. Posting that higher speed limit would set up the cycle that the next spot speed study may again find a higher operating speed because of drivers using the assumed speed enforcement tolerance to select their speed. â¢ Most of the early research justifying the use of the 85th percentile speed was conducted on rural roads; therefore, it may not be appropriate for urban roads. The NCHRP Project 17-76 research team focused Phase II on collecting data for suburban and urban roads to investigate the relationships among crashes, roadway characteristics, and posted speed limit to fill the known research gap for city streets. The team found that crashes were lowest when the operating speed was within 5Â mph of the average operating speed (see AppendixÂ D of NCHRP Web-Only Document 291). Therefore, the research team recommended that the 50thÂ percentile speed also be a consideration within the SLS-Procedure. S E C T I O N 8 Other Considerations When Setting Posted Speed Limits
Other Considerations When Setting Posted Speed Limits 45Â Â For the SLS-Procedure, the research team suggested the consideration of measured operating speed as the starting point for selecting a posted speed limit, but that the measured operating speed be adjusted based on roadway conditions and the crash experience on the segment. Identifying the Segment Limits Roadway segments are defined based on roadway characteristics and roadway context and type. In general, segments should be homogeneous; that is, the key variables listed in TableÂ 22 should be reasonably uniform throughout the length of the segment. Whenever a significant change in a variable occurs, a new segment should be defined. In particular, a new segment should be defined if the number of lanes, roadway context, or roadway type changes. New seg- ments may also be defined at logical break points based on traffic operations, such as at a major intersection with high turning volumes or a large freeway system interchange. Consider the following rules of thumb in defining break points between segments: â¢ Roadway context: any change. â¢ Roadway type: any change. â¢ AADT or directional design-hour volume: a change of 10Â percent or more. â¢ Number of lanes: any change. â¢ Median type: any change. â¢ LW: change of 1Â ft or more (length-weighted average for the overall segment). â¢ Outside or ISW: change of 2Â ft or more (length-weighted average for the overall segment). â¢ Number of interchanges, traffic signals, or access points: the number per mile changes by 50Â percent or more. â¢ Pedestrian or bicyclist activity: any change. â¢ Sidewalk presence/width: any change. â¢ Sidewalk buffer presence: any change. â¢ On-street parking activity, parallel parking presence, or angle parking presence: any change. Some of these rules of thumb are based on the principles described for the segmentation pro- cess in SectionÂ 18.5.2 of the HSM but with somewhat higher tolerances permitted for segmenta- tion in speed limit calculation than for safety prediction model application. TableÂ 24 provides minimum segment lengths based on the speed limit. If segments are defined with shorter lengths than the minimums, the roadway may have too many speed limit changes Speed Limit (mph) Minimum Length (miles) 20 0.30 25 0.30 30 0.30 35 0.35 40 0.40 45 0.45 50 0.50 55 0.55 60 1.20 65 3.00 70 6.20 75 6.20 80 6.20 85 6.20 Source: FHWA, USLIMITS 2, Table 2, page 34 (44). TableÂ 24. Minimum segment length for a particular speed limit.
46 Posted Speed Limit Setting Procedure and Tool: User Guide along its length, and record keeping for the roadway will be more complex. If the roadway has a large number of short segments, it may be necessary to combine adjacent segments that are reasonably similar or apply speed limits from adjacent segments to the segment of interest, if appropriate. However, at locations where a significant change in roadway context occurs, it may be desirable to include short sections where the speed limit transitions from a high value to a low value. For example, if a rural principal arterial approaches a rural town, several short segments may be used to reduce speeds to a value consistent with rural town traffic. Roadway segments may have individual concerns, such as a sharp horizontal curve, that require lower speeds. These concerns should be addressed with treatments that consider the specific location, such as posting an advisory speed, rather than by lowering the regulatory speed limit for the entire segment. Gathering Operating Speed In a general sense, the term operating speed relates to the speed at which drivers operate their vehicles along a section of roadway. Typically, for speed limit setting purposes, operating speeds are collected for a representative sample of free-flowing vehicles traveling along a road segment. Free-flowing vehicles are those that are unimpeded by other vehicles or TCDs. Speed data are typically collected at a specific location (or spot) to represent the operating speed along an entire homogeneous segment. The speed data should be collected outside the influence area of a traffic control signal, which is generally considered to be approximately 0.5Â miles. If the signal spac- ing is less than 1Â mile, the speed study should be at approximately the middle of the segment. Attention should also be given to collect data away from other potential traffic interruptions, including stops signs, driveways, and bus stops. Further, data should only be collected during dry conditions and during off-peak daytime periods. Various types of equipment may be used to collect spot speed data, including equipment placed on the road surface (e.g., road tubes, piezoelectric sensors, tape switches, etc.) or hand- held from the roadside (e.g., radar or LIDAR). While each of these devices is appropriate for purposes of setting speed limits, it is important to understand how the data are collected such that only free-flowing vehicles are used in the speed study. For road tubes and other on-road equipment, speeds are collected for all vehicles traveling over the roadway during the duration of the study. These data must be filtered to only include free-flowing vehicles that are unimpeded by other vehicles. Similarly, when using radar or LIDAR, the data collection technician must ensure that free-flowing vehicles are selected at random. Gathering Crash Data Crash data should be collected from a query of crash records for the jurisdiction of interest. At least 3Â years of crash data should be used, but the SLS-Tool can accommodate crash counts for times as short as 1Â year. Two crash counts need to be computed for the segment: all crashes (KABCO), and fatal and injury crashes (KABC). The SLS-Tool compares the crash counts to the computed average and critical crash rates for similar segments. The user may enter average crash rates (computed from similar segments in the state or region) or leave the average crash rate input cells blank. If the cells are left blank, the SLS-Tool computes average crash rates based on HSIS data. In addition to setting speed limits, the crash data query can also be used to identify sites that could benefit from implementing engineering or enforcement treatments to manage speed.
Other Considerations When Setting Posted Speed Limits 47Â Â Design Speed The relationship between design speed and posted speed was addressed in a 2015 memo- randum from FHWA (46). The memo started with quoting Joseph S. Tooleâs foreword to the 2009 FHWAâs Speed Concepts: Informational Guide (47): âdesigners of highways use a desig- nated design speed to establish design features; operators set speed limits deemed safe for the particular type of road; but drivers select their speed based on their individual perception of safety. Quite frequently, these speed measures are not compatible and their values relative to each other can vary.â The 2009 guide (47) introduced the concept of âinferred design speedâ and defined that term as âthe maximum speed for which all critical design-speed-related criteria are met at a particular location.â Stated in another manner, a given set of roadway characteristics can be used to infer the design speed met by that roadway section. The results of a 2003 NCHRP project examining the relationship between design speed, posted speed, and operating speed concluded that âwhile a relationship between operating speed and posted speed limit can be defined, a relationship of design speed to either operating speed or posted speed cannot be defined with the same level of confidenceâ (6). The research also found that design speed appears to have minimal impact on operating speeds unless a tight horizontal radius or a vertical curve with a low K-value is present. Large variance in operating speed was found for a given inferred design speed on rural two-lane highways. The research also concluded that when posted speed exceeds design speed, liability concerns may arise even though drivers can safely exceed the design speed. The FHWA memo (46) stated that the selection of a posted speed is an operational deci- sion for which the owner and operator of the facility is responsible and that inferred design speeds less than the posted speed limit do not necessarily present an unsafe operating con- dition. The memo recommended that âif a state legislature or highway agency establishes a speed limit greater than a roadwayâs inferred design speed, FHWA recommends that a safety analysis be performed to determine the need for appropriate warning or informational signs such as advisory speeds on curves or other mitigation measures prior to posting the speed limitâ (46). Relationships Among Safety, Speed, and Roadway Characteristics, Including Posted Speed Limit The relationships among safety, speed, and roadway characteristics, including posted speed limit, are complex. The association among these variables can vary widely. TableÂ 25 provides a brief and simple overview of the relationship for different variables with operating speed and crash frequencies by rural and urban facility. A short synthesis on key variables follows. Addi- tional details about these relationships are available in the NCHRP Web-Only Document 291, especially in Appendices A and B (2). Traffic Variables For a motor vehicle crash to occur or to measure how fast a driver is moving, a vehicle must be present. The quantity of traffic and the characteristics of that traffic have an obvious relationship with both speed and safety. Traffic variables include: â¢ AADT: Traffic flow measure AADT is considered the most determinant variable for the occurrence of crashes. Many safety performance functions consider only traffic flow and seg- ment length in the model development. The relationship between traffic volume and crashes
48 Posted Speed Limit Setting Procedure and Tool: User Guide can be affected by whether the section is undivided or divided. The effect of this variable on crash frequencies differs based on the facility type. Usually, roadways with higher AADT values are associated with higher operating speeds on both urban and rural roadways. However, Jessen etÂ al. (15) found lower operating speeds to be associated with higher AADT roadways. The researchers commented that motorists may view increases in traffic volume as a motiva- tion to slow down. â¢ Operating speed: The operating speed measures are evaluated to assess the consistency of the adopted design values along the designed road alignment. Operating speeds reflect the speed behavior of drivers who are affected by roadway geometry, surroundings, traffic, and other variables. A study using 179 roadway sections in Israel explored the relationship between operating speeds (obtained from global positioning system devices) and crashes on rural two- lane roadways with 50-mph posted speed limit (48). The main finding of the study was that in both day and night hours, the number of injury crashes increased with an increase in the segment mean speed, while controlling for traffic exposure and road infrastructure condi- tions. Wang etÂ al. (49) reviewed several previous studies to identify factors, especially traffic and road geometry factors, related to crashes. The authors concluded that some studies found increased speed reduces safety, and other studies found the opposite. â¢ Other traffic variables: Other traffic variables include congestion and the percentage of trucks. Several studies showed that congestion increases risk of traffic crashes. The percentage of trucks has a mixed effect on operating speeds. Category Variables Rural Operating Speed Rural Crash Frequency Urban Operating Speed Urban Crash Frequency Traffic AADT Operating speed Congestion Percent truck TCD Posted speed limit Signalized intersection Passing lane/zones Roadway Geometry Horizontal alignment Vertical alignment Presence of median Median width Number of lanes LW SW Bike lanes Intersection angle Intersection lighting Surroundings Access density (driveways and intersections) School Parking Liquor store Sidewalk presence Development (surrounding land and use) Other variables One-way or two-way Note: â§ = increase with increase of the attribute, â© = decrease with increase of the attribute, â©â§ = mixed effect, â = relationship not identified or unknown. TableÂ 25. Effect of variables on operating speeds and crash frequencies.
Other Considerations When Setting Posted Speed Limits 49Â Â TCD Variables The type of TCDs present can influence operating speeds and crashes. For example, when traffic signals are timed to optimize progression along a corridor, drivers tend to operate at that speed to avoid having to stop at the next signal. Most signs and markings, however, do not have such a major impact on speeds with the exception of the posted speed limit sign. TCD variables include: â¢ Posted speed limit: Prior studies showed that posted speed limit has a significant effect on operating speed on urban streets. For rural high-speed highways, posted speed limits are typi- cally established with consideration of several factors, including the roadway design speed. Several studies showed that vehicular operating speeds are impacted by the posted speed limit, with vehicular speeds tending to increase as the posted speed limit increases. However, the magnitude of the increase in operating speed is typically only a fraction of the amount of the actual speed limit increase. The research literature generally suggests that the resulting change in operating speeds would likely lead to an increase in the overall crash rate and would also shift the severity distribution toward crashes of greater severity. â¢ Other TCD variables: Other important TCD variables include the presence of intersections and passing lanes. For urban roadways, the presence of an intersection is associated with higher crash frequencies and lower operating speeds. Passing lanes are effective in crash reduction on rural roadways. However, passing lanes are associated with higher intersection- related crash frequencies on rural roadways. Roadway Geometry Variables The design of the roadway can influence either operating speed or crashes in select cases. Roadway geometry variables include: â¢ Horizontal alignment: Horizontal curves have been identified as the geometric variable that is the most influential on driver speed behavior and crash risk. The measures used in the studies varied and included the degree of curve, length of curve, deflection angle, and/or superelevation rate. Horizontal alignment is also associated with negatively affecting safety as shown in the HSM (43). Prior research has shown that crash frequency increases with the length and/or degree of horizontal curvature (43, 50) although there is a value where the influ- ence is no long present. â¢ Vertical alignment: Studies showed that roadways with vertical alignment experience lower operating speeds once the vertical alignment exceeds a certain value. Prior research has showed that steeper vertical alignments could induce higher crash potentials (13). Total crash rates typically increase with the degree of vertical alignments, mainly in the presence of hidden horizontal curves, intersections, or driveways. Safety risks associated with higher speed limits increased on segments with steeper vertical curves. â¢ Median: Median barriers are associated with severe crash rate reduction but have also been found to be associated with more property-damage-only crashes. A Michigan study found that the presence of a TWLTL was associated with a significant increase in total and injury crashes but was also associated with a significant decrease in fatal crashes (50). â¢ SW: Wider shoulder widths are associated with higher operating speeds. The HSM suggests that the width of the paved shoulder along non-freeways has a similar effect on crashes as travel lane widths, and that wider widths are associated with fewer crashes (43). The increased recovery and vehicle storage space and increased separation from roadside hazards are asso- ciated with fewer crashes.
50 Posted Speed Limit Setting Procedure and Tool: User Guide â¢ Other roadway geometry variables: Other roadway geometry variables that may have an effect on speed or crashes include the LW, number of lanes, presence of bike lane, intersection angle, and intersection lighting. Variables Associated with Roadway Surroundings The characteristics of the roadâs surroundings, including the neighboring land use, affect both operating speed and crashes. Variables associated with roadway surroundings include: â¢ Access density (driveways and intersections): Prior studies have demonstrated that as the density of access points (or the number of intersections and/or driveways per mile of high- way) increases, the frequency of traffic crashes also increases. This occurs partially due to driving errors caused by intersections and/or driveways that may result in rear-end and/or sideswipe type crashes. Specifically, NCHRP Report 420 concluded that an increase in crashes occurs due to the higher number of access points (51). Roadways with high access densities usually experience lower operating speeds. â¢ Other variables associated with surroundings: Other variables associated with surround- ings include the presence of schools, presence of liquor stores, presence of sidewalks, and development.