Guidelines for Quantifying Benefits of Traffic Incident Management Strategies (2022)

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43   Table A1 summarizes common rules of thumb related to TIM. Tables A2 to A5 summarize rules 1 to 4 from Table A1 to clarify the research conducted to validate the rule, strengths, limitations, and overall assessment of usability. A P P E N D I X A Common TIM Rules of Thumb

44 Guidelines for Quantifying Benefits of Traffic Incident Management Strategies Common Rule of Thumb Application Source 1. Every minute a freeway lane is blocked due to a traffic incident results in 4 minutes of added travel delay. See Table A2. Simple translation from reduction in ICT to delay. Specific research and validation, source, considerations for wording, caveats, strengths, and limitations are presented in greater detail in the following pages. 2. One blocked lane out of three will reduce traffic flow by 50%; two blocked lanes out of three will reduce traffic flow by 80%. See Table A3. Simple capacity loss parameter for use in estimating delay with and without TIM. 3. Highway incidents cause about 25% of the total congestion (delay). See Table A4. Parameter to use in sketch estimate of delay savings presented in Appendix B. 4. Approximately 20% of all incidents are secondary incidents. See Table A5. Parameter to estimate the number of secondary incidents based on total incident count. 5. TIM reduces total delay by 15%. With a value for delay in a non-TIM environment, multiply by 0.85 to estimate delay with TIM. A Benefit-Cost Model for Traffic Incident Management (Moss 2012). 6. TIM reduces secondary incidents by 5%. Multiply secondary incident count prior to TIM by 0.05 to estimate reduction in secondary incidents with TIM. Evaluation of Freeway Motorist Assist Program (Sun et al., 2010). 7. For every minute that the primary incident is a hazard, the risk of a secondary crash increases 2.8%. 15-minute incident reduction by 2.8% equals a 42% reduction in risk of a secondary crash. ITS Impacts on Safety and Traffic Management: An Investigation of Secondary Crash Causes (Karlaftis et al., 1999). 8. About 10% of secondary crashes are associated with “rubbernecking” incidents in the opposite direction. Method for estimating secondary incidents in opposing traffic based on frequency of secondary crashes in the same direction. An Analysis on the Impact of Rubbernecking on Urban Freeway Traffic (Masinik and Teng, 2004). Table A1. Common rules of thumb related to TIM.

Common TIM Rules of Thumb 45   Research and Validation Discussion • A good discussion of this topic is contained in a memorandum prepared by Oregon DOT. 1 • VISSIM simulation study explored this issue at different levels of demand and incident severity (Saka et al., 2008). 2 • Recovery time is uniform with incident duration until traffic volumes approach capacity (v/c ratio of 0.7 or higher). Recovery time increases faster as traffic volumes approach capacity (e.g., v/c ratio range from 0.75 to 0.9). Considerations for Wording/ Caveats Add one of these qualifiers to the rule of thumb: • During peak periods or congested periods. • Under high volume–capacity ratios (>0.8 or higher). “Every minute a freeway lane is blocked due to a traffic incident during congested periods results in 4 minutes of added travel delay.” Strengths • Relatively easy concept to understand and intuitive. • Stresses the importance of reducing the time it takes to clear incidents. • Long-standing rule of thumb that has been widely used. • Has been validated in general terms by modeling studies. Limitations • Very imprecise and rough estimate. • Every freeway network situation is dynamic and different; it is difficult to generalize with a nice and neat formula (due to traffic demand patterns, number of lanes, availability of exit points/alternate routes, incident severity and type, etc.). • Rule of thumb for delay has not been systematically or rigorously validated with field data. • Only valid at high levels of congestion and in situations with limited exit points upstream of the incident. Overall Assessment • Use with caution, adding caveats and context. Table A2. TIM rule of thumb: every minute a freeway lane is blocked due to a traffic incident results in 4 minutes of added travel delay. [Variations: 4–6 minutes of delay]. 1 Traffic Delay Recovery Time, Robert Maestre and Richard Munford, Planning and Economic Analysis Unit, Oregon Department of Transportation memo. (http://www.oregon.gov/odot/td/tp/reports/trafficdelayrecoverytime.pdf). 2 Estimation of Traffic Recovery Time for Different Flow Regimes on Freeways, Anthony A. Saka et al., Maryland Department of Transportation, State Highway Administration, July 2008. (http://roads.maryland.gov/OPR_Research/MD-09-SP708B4L_ Estimation-of-Traffic-Recovery-Time-for-Non-Recurrent-Incident-Report.pdf).

46 Guidelines for Quantifying Benefits of Traffic Incident Management Strategies Research and Validation Discussion • Rules of thumb values based on Goolsby3 (Texas A&M Transportation Institute [TTI]). o Based on a 2-year detailed study of incidents in Houston (1969–1971). o Over 1,150 crashes were analyzed. • For one lane out of three blocked: o Findings from this research showed a reduction in the effective capacity of 45%, since the average available capacity ratio (ACR) is 55%. o 2010 HCM estimates a 51% reduction. o 50% appears to be a slight overestimate of the impact of one lane of three being blocked (50.5% was actual value from Goolsby). • For two lanes out of three blocked: o Task 4 findings showed a reduction in the effective capacity of 76%, since the average ACR is 24%. o 2010 HCM estimates an 83% reduction. o 80% may slightly overestimate the capacity loss but is in between task 4 and HCM estimate (79.3% was actual value from Goolsby). • See NCHRP Web-Only Document 301: Development of Guidelines on Quantifying Benefits of Traffic Incident Management Strategies for further information. Considerations for Wording/ Caveats • Only valid during peak periods or congested periods; reduction in roadway capacity will be far less significant when traffic is not heavy. • Referred to as a reduction (or temporary drop) in (effective) capacity. • Capacity during incidents has been estimated for bottleneck conditions. • May wish to use 45%–50% as a range for one of three lanes being blocked; 75%–80% as a range for two of three lanes being blocked. Strengths • 50% and 80% are round figures to use. • Facilitates an understanding that incidents have a bigger impact than the geographic real estate (proportion of lanes) that they occupy. • Estimates are taken from previous work (based on well-known study). Limitations • Only applicable to freeway facilities with limited access and exits. • Estimates of the impact of incidents appear to be only slightly exaggerated. • A possible explanation is that urban drivers are more aggressive now than during the time period of the TTI study (late 1960s/early 1970s), which would be consistent with the incidents studied as a part of this research effort. • As a part of this effort, researchers estimated based on detailed observation of a small sample size (19 incidents) in urban areas of Dallas and Northern Virginia. Overall Assessment • Good estimate based on sound study and data analysis. Table A3. TIM rule of thumb: one blocked lane out of three will reduce traffic flow by about 50%; two blocked lanes out of three will reduce traffic flow by about 80%. 3 Goolsby, M. Influence of Incidents on Freeway Quality of Service, Highway Research Board, Highway Research Record, No. 349. Washington, D.C., pp. 41–46, 1971.

Common TIM Rules of Thumb 47   Research and Validation Discussion • Rule of thumb value established from source, Traffic Congestion and Reliability: Linking Solutions to Problems (FHWA). 4 • Value-based on merging data sets from several independent studies and is an approximation. Considerations for Wording/ Caveats • Based on national-level data; local conditions can vary widely. • Generally, areas with less recurrent congestion can expect that the percentage of delay caused by highway incidents may be higher than those areas with high levels of recurrent congestion. • May wish to say “highway incidents cause about 25% of the total congestion in congested urban areas.” Previous work has shown that congestion is the result of seven root causes, often interacting with one another. • Physical Bottlenecks (Insufficient "Capacity") [cause an estimated 40% of the total congestion nationally]—Capacity is the maximum amount of traffic capable of being handled by a given highway section. Capacity is determined by a number of factors: the number and width of lanes and shoulders; merge areas at interchanges; and roadway alignment (grades and curves). • Traffic Incidents [cause an estimated 25% of the total congestion nationally]—Events that disrupt the normal flow of traffic, usually by physical impedance in the travel lanes. Events such as vehicular crashes, breakdowns, and debris in travel lanes are the most common forms of incidents. • Work Zones [10%] —Construction activities on the roadway that result in physical changes to the highway environment. These changes may include a reduction in the number or width of travel lanes, lane "shifts," lane diversions, reduction or elimination of shoulders, and even temporary roadway closures. • Weather [15%]—Environmental conditions can lead to changes in driver behavior that affect traffic flow. • Traffic Control Devices [5%]—Intermittent disruption of traffic flow by control devices such as railroad grade crossings and poorly timed signals also contribute to congestion and travel time variability. • Special Events [5%]—A special case of demand fluctuations whereby traffic flow in the vicinity of the event will be radically different from "typical" patterns. Special events occasionally cause "surges" in traffic demand that overwhelm the system. • Fluctuations in Normal Traffic—Day-to-day variability in demand leads to some days with higher traffic volumes than others. Varying demand volumes superimposed on a system with fixed capacity also results in variable (i.e., unreliable) travel times. Table A4. TIM rule of thumb: highway incidents cause about 25% of the total congestion (delay). 4 Cambridge Systematics with TTI, Traffic Congestion and Reliability: Linking Solutions to Problems (FHWA), July 2004.

48 Guidelines for Quantifying Benefits of Traffic Incident Management Strategies Research and Validation Discussion • Rule of thumb from FHWA. 5 • Recent studies, using advanced research methodologies, have found that secondary crashes occur with frequency lower than 20%. • A study by Chung estimated that the frequencies of secondary crashes in the same and opposite directions were 7.4% and 3.8% of total primary crashes, or 6.7% and 3.4% of all incidents, respectively.6 This means that secondary crashes comprise about 10.1% of all crashes.7 • Study of detailed accident records for a 27-mile stretch of the New Jersey Turnpike by Yang et al. found that the number of secondary crashes was about 8% of total incidents.8 • Application of computation methods to estimate reduction in secondary crashes reveals that the average (for methods other than Raub, which assumes 15%) for secondary crashes for Maryland I-495 corridor is about 16% of total incidents and for the I-75 Dallas corridor is about 9% of total incidents.9 Strengths • Based on analysis of national-level data. • 25% can be considered on the conservative side. Limitations • Value applies better to congested urban areas than it does for small cities and rural areas. • In rural areas, just about any delay that occurs will be event-related rather than caused by bottlenecks (insufficient capacity). In rural areas, estimates suggest that traffic incidents and work zones alone cause 80% to 90% of what delay that does occur. Overall Assessment • Use with caution! Use local data on sources of congestion wherever possible. Table A4. (Continued). Table A5. TIM rule of thumb: approximately 20% of all incidents are secondary incidents. 5 “Traffic Incident Management,” Federal Highway Administration. http://ops.fhwa.dot.gov/aboutus/one_pagers/tim.htm. Accessed March 7, 2016. 6 Chung, Y. Identifying Primary and Secondary Crashes from Spatiotemporal Crash Impact Analysis. Transportation Research Record: Journal of the Transportation Research Board, No. 2229, pp. 8–18, 2011. 7 Zhan, C., A. Gan, and M. Hadi., Identifying Secondary Crashes and Their Contributing Factors. Transportation Research Record: Journal of the Transportation Research Board, No. 2102, pp. 68–75, 2009. 8 Yang, H., B. Bartin, and K. Ozbay. Investigating the Characteristics of Secondary Crashes on Freeways, TRB Paper ID: 13-4866, Transportation Research Board’s 92nd Annual Meeting, Washington, D.C., 2013. 9 Due to its small sample size in terms of number of incidents, Seattle is not included here.

Common TIM Rules of Thumb 49   Limitations • Based on recent findings, including this study, 20% appears to be high. • The relative proportion of secondary crashes compared to all incidents does not reveal the benefits of TIM; however, if one has good before and after data on the total number of incidents, one can estimate the number of secondary crashes reduced by the TIM activities being evaluated. • A better indication of TIM benefits would concentrate on the reduction in frequency and duration of incidents, the risk of secondary crashes down as the incident duration is reduced; in turn, this should reduce the total number of incidents. Data on these parameters are difficult to obtain. (The Chou method was the only method in this study to incorporate incident duration directly in the estimation process.) Overall Assessment • Not recommended for use; use a percentage between 10% and 15%. Considerations for Wording/ Caveats • Estimates from literature do not always use the FHWA definition of secondary accidents, which is “the number of unplanned incidents beginning with the time of detection of the primary incident where an incident occurs as a result of the original incident either within the incident scene or within the queue in either direction.” • Frequently, only the secondary crashes occurring in the same direction of travel as the primary incident are quantified. It is possible that this under- reports the frequency of secondary incidents. • Based on recent results from this study and others, it appears that 20% may be too high; perhaps a range should be provided for the user. • From 8% to 20%; or from 10% to 15% is more in line with previous research. • Point estimate of 10% would be fairly conservative. • Point estimate of 15% would be more aggressive. Strengths • Twenty percent is an easy-to-recall round number and comes from FHWA (and most likely was based on actual data analysis).10 10 The origin of the 20% value was not found by the research team. Table A5. (Continued).