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Evaluating Strategies for Work Zone Transportation Management Plans (2020)

Chapter: 5.0 Field Evaluation of Truck Lane Restrictions

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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
×
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Suggested Citation:"5.0 Field Evaluation of Truck Lane Restrictions." National Academies of Sciences, Engineering, and Medicine. 2020. Evaluating Strategies for Work Zone Transportation Management Plans. Washington, DC: The National Academies Press. doi: 10.17226/25930.
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21 5.0 Field Evaluation of Truck Lane Restrictions A large volume of trucks can degrade the speed, comfort, and convenience of passenger car drivers sharing the road. This problem is exacerbated in work zones that may operate at a reduced capacity or reduced operating speeds resulting from lane closures, lane-width reductions, geometrics, etc. One common approach is to impose certain restrictions on truck movements as a means of improving safety and mobility to reducing the effects of truck traffic on freeways. This is typically achieved through the use of standalone static signs (TRUCKS USE LEFT/RIGHT LANE) or in combination with PCMS. The few studies that have attempted to determine the effects of truck restrictions on highway operations and safety have shown inconclusive results. Truck lane restrictions have not been evaluated in work zones. The goal of this study is to evaluate the operational and safety effectiveness of restricting trucks in work zones to a particular lane(s). 5.1. Site Selection and Characteristics Through outreach efforts to state transportation agencies, the team identified the following three locations in Michigan as test sites for evaluation: • SB I-75 from Dixie Highway to Swan Creek Road, Monroe County. • SB US-23 Flex Route project between M-14 and Silver Lake Road, Washtenaw and Livingston Counties. • NB US-23 Flex Route project between M-14 and Silver Lake Road, Washtenaw and Livingston Counties. 5.1.1 I-75, Monroe County, Michigan This project included reconstruction of 5.6 mi of Interstate-75 from Dixie Highway to I-275 along with the rehabilitation of three bridges, replacement of another three bridges, and reconstruction of 10 ramps. I-75 runs north-south with three lanes in each direction. Construction took place during two summer seasons—2015 (for the northbound roadbed) and 2016 (for the southbound roadbed). Truck lane restrictions were in place during the reconstruction of the southbound bed (April 1–September 30, 2016) to prevent trucks traveling on the patched shoulders and existing drain grates. Trucks were restricted to the left lane. When truck lane restrictions were in place, SB I-75 had two 11-ft-wide lanes. The work zone speed limit was 60 mph. Trucks made up 30% of the traffic composition. Truck lane restrictions were enforced through the use of static signs and a PCMS. The PCMS was placed in the median approximately 3 miles before the beginning of the taper. The first

22 static sign was placed ½-mi upstream from the beginning of the taper, second static sign was placed 2 mi downstream of the taper, and the last static sign was placed a further 2 mi downstream of the second static sign. The message on the static signs and the PCMS was the same (TRUCKS USE LEFT LANE) (Figure 2). Figure 2. Work zone truck lane restriction. 5.1.2 US-23, Washtenaw and Livingston Counties, Michigan The project corridor is a 10-mi section of US-23 within Livingston and Washtenaw Counties. US-23 freeway is a major north-south arterial that traverses through the cities of Ann Arbor and Brighton. Every day, 60,000 to 65,000 vehicles on average travel US-23 between the US-23/M-14 interchange and Silver Lake Road. Congestion and delays are common, especially in the southbound direction during the morning peak period and in the northbound direction during the evening peak period. To lessen the effects of heavy directional commuter travel patterns and to promote safety, Michigan Department of Transportation (MDOT) had made several improvements to the corridor—replacing and repairing bridges, upgrading acceleration and deceleration ramps, upgrading pavement and medians, and installing a Flex Route system to manage peak hour traffic congestion. The Flex Route system is a lane-control system that uses cameras and electronic message boards to let drivers know when additional lanes are available for use during morning and afternoon peak travel periods. US-23 had two 11-ft-wide lanes in each direction. The work zone speed limit was 60 mph. Construction started in November 2016 and lasted until July 2018. In spring 2017, when traffic was shifted to the outside (right) shoulder, the shoulder began to fail. MDOT repaired the areas that failed initially and started using static signs and PCMS to enforce truck lane restrictions to the left lane and keep trucks off the shoulders that were not repaired. Trucks were restricted to using the left lane in both the northbound and southbound directions. The project was not set up originally for trucks to use only the left lane.

23 5.2. Study Methodology 5.2.1 Data Collection Duration I-75, Monroe County, Michigan. The agency conducted the before data collection March 29–30, 2016. The truck restriction was implemented March 31, 2016, and the after data were collected May 16–18, 2016. US-23, Washtenaw and Livingston Counties, Michigan. The Agency collected data with the truck lane restrictions May 22–26, 2017, and without the truck lane restrictions from May 1-3, 2018. The truck lane restrictions were in place in both the northbound and southbound directions. Data were collected and evaluated for both directions. 5.2.2 Data Collection Procedures Vehicular data were collected using Hi-Metrics Nu-Star in-pavement sensors. These nonintrusive sensors use vehicle magnetic-imaging technology to record vehicle data, thus reducing the possibility of drivers adjusting their speeds because of visible equipment and human observers. The dimensions of the sensors are 6.5 in. by 5.5 in. with a thickness of 0.625 in. Each sensor is placed in the center of the travel lane and as a vehicle passes over it, the sensor captures changes in the magnetic field. All vehicular data were collected by direction and by lane. The sensors measured the volume, speed, vehicle classification, headway, and gap data per lane. The agency also screened all raw data to exclude missing data values and outliers, such as vehicles traveling at very low or very high speeds. Data were analyzed separately for passenger cars and commercial vehicles. 5.2.3 Measures of Effectiveness The following operational MOEs were evaluated: • Compliance with truck restriction signing (measured as percentage of truck occupancy by lane). This is a measure of compliance with the restriction and shows whether the restrictions created a tangible reduction in the number of trucks in the left lane. • Mean speeds in the restricted and non-restricted lanes. The expectation is that the redistribution of trucks into specific lanes will increase the speed in the restricted lane(s) and decrease the speed in the non-restricted lane(s) where trucks are forced to move and become more concentrated. Because the restrictions were intended to reduce the number of slow-moving trucks in the right lane, the right lane should exhibit increases in average speed.

24 • Frequency of headway. Vehicle headway is a measure of the temporal space between two vehicles, and is defined as the elapsed time between the arrival of the leading vehicle and the following vehicle at a designated test point. It is usually measured in seconds. Since the average of vehicle headways is the reciprocal of flow rate, vehicle headways represent microscopic measures of flows passing a point. To some extent, the minimum acceptable mean headway determines the roadway capacity. The agency used the K-S test, a goodness-of-fit test, to test whether there is a meaningful difference between the measured frequency distribution between the before-and-after conditions. This is a surrogate measure for safety. • Headway led by truck. This MOE examines the number of instances where a vehicle leads a platoon of traffic. A platoon is defined as a vehicle traveling with a headway greater than 3 seconds, followed by one or more vehicles with a headway less than 3 seconds. As noted above, this MOE is also a surrogate measure for safety. 5.2.4 Method for a Statistical Test for the Lane Distribution of Trucks To determine the proportion of vehicles complying with the truck lane restrictions between any of the data collection periods, a z-test for independent samples was computed. The null and alternative hypotheses for the test are: • Null Hypothesis (H0): There is no difference between the two-sample proportions, or H0: P1 – P2 = 0 • Alternative Hypothesis (Ha): There is a difference between the two-sample proportions, H0: P1 – P2 ≠ 0. Equation 1 shows the Z-statistic used to compute the statistical difference between the two proportions, where PSB and PSA are the sample proportions, n1 and n2 are sample sizes for the corresponding proportions being considered, and P is the combined proportion in both samples. Equation 1. Z-statistic to determine the lane compliance between the before-after periods.       +− − = 21 11)1( nn PP PP Z SASB

25 Equation 2. Combined proportion of vehicles during the before-after data collection periods. P is calculated using Equation 2. Where: xB, xA = percentage of trucks for the before-and-after periods; nB, nA = sample size in before-and-after periods. The critical value when α = 0.05 for a one-tail test is 1.96. The null hypothesis is rejected when the computed z-test exceeds the critical value, thus concluding that the difference in lane distribution of trucks being compared differ between the two collection periods being considered. 5.2.5 Method for a Statistical Test for the Truck Speeds The comparison of the differences between truck speeds before and after the restriction was based on the t-test for independent samples. The t-statistic is commonly used to test the hypothesis of differences in population parameters. In this study, the null and alternative hypotheses for testing the differences in two population mean speed measures, μ1 and μ2, were: • Null Hypothesis (H0): There has not been a change in mean speeds as a result of truck lane restrictions, or H0: μ1 – μ2 = 0. • Alternative Hypothesis (Ha): There has been a decrease in mean speeds as a result of truck lane restrictions, or Ha: μ1 – μ2 > 0. The agency calculated a t-statistic at each study site for each sensor location and between data collection periods. Independent two-sample t-statistics were applied to test for the difference between two sample means at each study site. Equation 3 shows the t-statistic for calculating large samples with known variables. Equation 3. t-statistic to test for the difference between two sample means. Where: AB XX , = mean speed for the before-and-after periods; sB, sA = standard deviation of speed for the before-and-after periods; nB, nA = sample size in before-and-after periods. AB AB nn xxP + + = A A B B AB n s n s XXt 22 )( + −=

26 The degrees of freedom (df) for the independent samples t-statistic is nA + nB - 2. The critical value when α = 0.05 for a one-tail test is 1.645. The null hypothesis is rejected when the computed t-test exceeds the critical value, thus concluding that the mean speeds compared differ between the two collection periods being considered. An alternative method to determine the statistical significance of truck lane restrictions on mean speed is the p-value associated with the t-statistic. A low p-value (i.e., less than or equal to 0.05) indicates a high probability that implementing the truck lane restrictions influenced mean speeds between two data collection periods. The team computed t-statistic and p-values at each study site. It was anticipated that the difference in mean speeds at the control sites would not be statistically significant. However, if there is a statistically significant difference in mean speeds, the magnitude of this difference would need to be accounted for. In this case, the team added or subtracted, depending on whether it was positive or negative, to the numerator in Equation 1. As such, the mean speed difference computed at the treatment sites was adjusted to account for statistically significant mean speed differences at the treatment sites. 5.2.6 Method for a Statistical Test for Frequency of Headways The comparison of the differences between vehicle headways with and without the ramp metering was based on the K-S test for independent samples. The K-S test is commonly used to obtain a probability of similarity between two distributions to determine whether two datasets differ significantly. The K-S test is nonparametric and assumption-free, meaning that it has the advantage of making no assumption about the distribution of data. The purpose of this test is to obtain the cumulative distribution function of the two distributions that need to be compared. The K-S distance is a measure defined as the maximum value of the absolute difference between two cumulative distribution functions; it measures the largest absolute difference between two distribution functions for varying time. The K-S distance is defined by: The supremum is the least upper bound of a set. Given a sample of observations x = (x1;…., xn), the empirical distribution function Fn is given by the following expression Where #{…..} denotes the number of elements contained in the set {…..} and Fn defines a discrete probability distribution function on the real line. For large values of n, the empirical distribution converges to the theoretical one.

27 A smaller K-S statistic value indicates a better goodness-of-fit, and in a two-sample K-S test, the decision to reject the null hypothesis is based on comparing the p-value with the significance level α. 5.3. Comparison of Results for Truck Lane Distribution The primary interest in evaluating the effectiveness of truck lane restrictions is the percentage changes of the lane distribution of trucks at the test sites. The without and with percentages of lane distribution of trucks are to be compared. 5.3.1 SB I-75 Location Table 3 and Figures 3 through 5 show the lane distributions of trucks in percentages without and with the truck lane restrictions. Once the truck lane restrictions were implemented, the percentage of trucks in the left lane increased for all time periods. The percentage of trucks in the left lane increased by 67.7% in the morning peak period (6–9 a.m.), by 84.2% in the mid-day period (10 a.m.–1 p.m.) and by 89.7% in the evening peak period (3–6 p.m.). When the truck lane restrictions were implemented, the percentage of trucks in the right lane decreased for all time periods. The percentage of trucks in the left lane decreased by 74 percent in the morning peak period (6–9 a.m.), by 68.1 percent in the mid-day period (10 a.m.–1 p.m.) and by 73.9 percent in the evening peak period (3–6 p.m.). Table 3. SB I-75 Differences in lane distribution without and with truck lane restrictions. Time Lane Percentage of Trucks Without Truck Restrictions With Truck Restrictions Percent Change (%) Significant Change Morning Peak Period (6–9 a.m.) Left Lane 16.1 27.0 +67.7 Significant Right Lane 41.2 10.7 -74.0 Significant Mid-day Period (10 a.m.–1 p.m.) Left Lane 20.2 37.2 +84.2 Significant Right Lane 53.0 16.9 -68.1 Significant Evening Peak Period (3–6 p.m.) Left Lane 12.6 23.9 +89.7 Significant Right Lane 36.4 9.5 -73.9 Significant The statistical test shows that the percentage of trucks in the left lane significantly increased during all time periods (a = 0.05).

28 Figure 3 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the morning peak period (6–9 a.m.) at the SB I-75 test site. During this period, the percentage of trucks using the left lane increased from 16.1 percent without truck lane restrictions to 27 percent with the truck lane restrictions, an increase of 67.7 percent. During the same time period, the percentage of trucks using the right lane decreased from 41.2 percent without truck lane restrictions to 10.7 percent with the truck lane restrictions, a decrease of 74 percent. Figure 3. SB I-75 Comparison of truck lane distribution during morning peak period (6–9 a.m.). Figure 4 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the mid-day period (10 a.m.–1 p.m.) at the SB I-75 test site. During this period, the percentage of trucks using the left lane increased from 20.2 percent without truck lane restrictions to 37.2 percent with the truck lane restrictions, an increase of 84.2 percent. During the same time period, the percentage of trucks using the right lane decreased from 53 percent without truck lane restrictions to 16.9 percent with the truck lane restrictions, a decrease of 68.1 percent. 0.0 10.0 20.0 30.0 40.0 50.0 Left Lane Right Lane Without Truck Restrictions 16.0 41.2 With Truck Restrictions 27.0 10.7 Pe rc en ta ge o f T ru ck s SB I-75 Comparison of Truck Lane Distribution During Morning Peak Period (6-9 a.m.)

29 Figure 4. SB I-75 Comparison of truck lane distribution during mid-day period (10 a.m.–1 p.m.). Figure 5 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the evening peak period (3–6 p.m.) at the SB I-75 test site During this period, the percentage of trucks using the left lane increased from 12.6 percent without truck lane restrictions to 23.9 percent with the truck lane restrictions, an increase of 89.7 percent. During the same time period, the percentage of trucks using the right lane decreased from 36.4 percent without truck lane restrictions to 9.5 percent with the truck lane restrictions, a decrease of 73.9 percent. Figure 5. SB I-75 Comparison of truck lane distribution during evening peak period (3–6 p.m.). 0.0 10.0 20.0 30.0 40.0 50.0 60.0 Left Lane Right Lane Without Truck Restrictions 20.2 53.0 With Truck Restrictions 37.2 16.9 Pe rc en ta ge o f T ru ck s SB I-75 Comparison of Truck Lane Distribution During Mid Day Period (10 a.m.-1 p.m.) 0.0 5.0 10.0 15.0 20.0 25.0 30.0 35.0 40.0 Left Lane Right Lane Without Truck Restrictions 12.6 36.4 With Truck Restrictions 23.9 9.5 Pe rc en ta ge o f T ru ck s SB I-75 Comparison of Truck Lane Distribution During Evening Peak Period (3-6 p.m.)

30 5.3.2 SB US-23 Location Table 4 and Figures 6 through 8 show the lane distributions of trucks in percentages without and with the truck lane restrictions. When the truck lane restrictions were implemented, the percentage of trucks in the left lane increased for all time periods. The percentage of trucks in the left lane increased by 446.7% in the morning peak period (6–9 a.m.), by 465.6% in the mid-day period (10 a.m.–1 p.m.) and by 370.8% in the evening peak period (3–6 p.m.). When the truck lane restrictions were implemented, the percentage of trucks in the right lane decreased for all time periods. The percentage of trucks in the right lane decreased by 41.6% in the morning peak period (6–9 a.m.), by 45.5% in the mid-day period (10 a.m.–1 p.m.) and by 51% in the evening peak period (3–6 p.m.). The statistical test shows that the percentage of trucks in the left lane was significantly increased (a = 0.05) during the mid-day and evening peak periods. Table 4. SB US-23 Differences in lane distribution without and with truck lane restrictions. Time Lane Percentage of Trucks Without Truck Restrictions With Truck Restrictions Percent Change (%) Significant Difference? Morning Peak Period (6–9 a.m.) Left Lane 1.5 8.2 +446.7 Not Significant Right Lane 13.7 8.0 -41.6 Significant Mid-Day Period (10 a.m.–1 p.m.) Left Lane 3.2 18.1 +465.6 Significant Right Lane 21.1 11.5 -45.5 Significant Evening Peak Period (3–6 p.m.) Left Lane 2.4 11.3 +370.8 Significant Right Lane 15.1 7.4 -51.0 Significant Figure 6 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the morning peak period (6–9 a.m.) at the SB US-23 test site. During this period, the percentage of trucks using the left lane increased from 1.5 percent without truck lane restrictions to 8.2 percent with the truck lane restrictions, an increase of 446.7 percent. During the same time period, the percentage of trucks using the right lane decreased from 13.7 percent without truck lane restrictions to 8 percent with the truck lane restrictions, a decrease of 41.6 percent.

31 Figure 6. SB US-23 comparison of truck lane distribution during morning peak period (6–9 a.m.). Figure 7 shows the differences in the percentage of trucks using the right and the left lanes in the without and with conditions during the mid-day period (10 a.m.–1 p.m.) at the SB US-23 test site. During this period, the percentage of trucks using the left lane increased from 3.2 percent without truck lane restrictions to 18.1 percent with the truck lane restrictions, an increase of 465.6 percent. During the same time period, the percentage of trucks using the right lane decreased from 21.1 percent without truck lane restrictions to 11.5 percent with the truck lane restrictions, a decrease of 45.5 percent. Figure 7. SB US-23 Comparison of truck lane distribution during mid-day period (10 a.m.–1 p.m.). 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Left Lane Right Lane Without Truck Restrictions 1.5 13.7 With Truck Restrictions 8.2 8.0 Pe rc en ta ge o f T ru ck s SB US-23 Comparison of Truck Lane Distribution During Morning Peak Period (6-9 a.m.) 0.0 5.0 10.0 15.0 20.0 25.0 Left Lane Right Lane Without Truck Restrictions 3.2 21.1 With Truck Restrictions 18.1 11.5 Pe rc en ta ge o f T ru ck s SB US-23 Comparison of Truck Lane Distribution During Mid Day Period (10 a.m.-1 p.m.)

32 Figure 8 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the evening peak period (3–6 p.m.) at the SB US-23 test site. During this period, the percentage of trucks using the left lane increased from 2.4 percent without truck lane restrictions to 11.3 percent with the truck lane restrictions, an increase of 370.8 percent. During the same time period, the percentage of trucks using the right lane decreased from 15.1 percent without truck lane restrictions to 7.4 percent with the truck lane restrictions, a decrease of 51 percent. Figure 8. SB US-23 Comparison of truck lane distribution during evening peak period (3–6 p.m.). 5.3.3 NB US-23 Location Table 5 and Figures 9 through 11 show the lane distributions of trucks in percentages without and with the truck lane restrictions. When the truck lane restrictions were implemented, the percentage of trucks in the left lane increased for all time periods. The percentage of trucks in the left lane increased by 928% in the morning peak period (6–9 a.m.), by 726.9% in the mid-day period (10 a.m.–1 a.m.) and by 415.2% in the evening peak period (3–6 p.m.). When the truck lane restrictions were implemented, the percentage of trucks in the right lane decreased for all time periods. The percentage of trucks in the right lane decreased by 59.9% in the morning peak period (6–9 a.m.), by 52.3% in the mid-day period (10 a.m.–1 p.m.) and by 54.7% in the evening peak period (3–6 p.m.). The statistical test shows that the percentage of trucks in the left lane was significantly increased (a = 0.05) for all time periods. 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 Left Lane Right Lane Without Truck Restrictions 2.4 15.1 With Truck Restrictions 11.3 7.4 Pe rc en ta ge o f T ru ck s SB US-23 Comparison of Truck Lane Distribution During Evening Peak Period (3-6 p.m.)

33 Table 5. NB US-23 Differences in lane distribution without and with truck lane restrictions. Time Lane Percentage of Trucks Without Truck Restrictions With Truck Restrictions Percent Change (%) Significant Difference? Morning Peak Period (6–9 a.m.) Left Lane 2.5 25.7 +928.0 Significant Right Lane 20.7 8.3 -59.9 Significant Mid-day Period (10 a.m.–1 p.m.) Left Lane 2.6 21.5 +726.9 Significant Right Lane 19.5 9.3 -52.3 Significant Evening Peak Period (3–6 p.m.) Left Lane 2.1 10.9 +415.2 Significant Right Lane 13.2 6.0 -54.7 Significant Figure 9 shows the differences in the percentage of trucks using the right and the left lane in the ‘without’ and ‘with’ conditions during the morning peak period (6-9 a.m.) at the NB US-23 test site. During this period, the percentage of trucks using the left lane increased from 2.5 percent without truck lane restrictions to 25.7 percent with the truck lane restrictions, an increase of 928 percent. During the same time period, the percentage of trucks using the right lane decreased from 20.7 percent without truck lane restrictions to 8.3 percent with the truck lane restrictions, a decrease of 59.9 percent. Figure 9. NB US-23 Comparison of truck lane distribution during morning peak period (6–9 a.m.). Figure 10 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the mid-day period (10 a.m.–1 p.m.) at the NB US-23 test site. During this period, the percentage of trucks using the left lane increased from 2.6 percent 0.0 5.0 10.0 15.0 20.0 25.0 30.0 Left Lane Right Lane Without Truck Restrictions 2.5 20.7 With Truck Restrictions 25.7 8.3 Pe rc en ta ge o f T ru ck s NB US-23 Comparison of Truck Lane Distribution During Morning Peak Period (6-9 a.m.)

34 without truck lane restrictions to 21.5 percent with the truck lane restrictions, an increase of 726.9 percent. During the same time period, the percentage of trucks using the right lane decreased from 19.5 percent without truck lane restrictions to 9.3 percent with the truck lane restrictions, a decrease of 52.3 percent. Figure 10. NB US-23 Comparison of truck lane distribution during mid-day period (10 a.m.–1 p.m.). Figure 11 shows the differences in the percentage of trucks using the right and the left lane in the without and with conditions during the evening peak period (3–6 p.m.) at the NB US-23 test site. During this period, the percentage of trucks using the left lane increased from 2.1 percent without truck lane restrictions to 10.9 percent with the truck lane restrictions, an increase of 415.2 percent. During the same time period, the percentage of trucks using the right lane decreased from 13.2 percent without truck lane restrictions to 6 percent with the truck lane restrictions, a decrease of 54.7 percent. 0.0 5.0 10.0 15.0 20.0 25.0 Left Lane Right Lane Without Truck Restrictions 2.6 19.5 With Truck Restrictions 21.5 9.3 Pe rc en ta ge o f T ru ck s NB US-23 Comparison of Truck Lane Distribution During Mid Day Period (10 a.m.-1 p.m.)

35 Figure 11. NB US-23 Comparison of truck lane distribution during evening peak period (3–6 p.m.). 5.3.4 Combined For All Sites Table 6 shows the changes in lane distribution for all three sites for all time periods. At all three sites trucks were restricted to using the left lane and the data clearly show that the truck lane restrictions were effective in creating a tangible increase in the number of trucks using the left lane. When the truck restrictions were in place, the percentage change in trucks using the left lane, for all time periods, increased by 84.76% for SB I-75, 502.64% for SB US-23, and 669.04% for NB US- 23. For all sites combined, the percentage change in trucks using the left lane, for all time periods, increased by 234.96%. When the truck restrictions were in place, the percentage change in trucks using the right lane, for all time periods, decreased by 71.74% for SB I-75, 48.31% for SB US-23, and 51.32 percent for NB US-23. For all sites combined, the percentage change in trucks using the right lane, for all time periods, decreased by 59.36%. 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 Left Lane Right Lane Without Truck Restrictions 2.1 13.2 With Truck Restrictions 10.9 6.0 Pe rc en ta ge o f T ru ck s NB US-23 Comparison of Truck Lane Distribution During Evening Peak Period (3-6 p.m.)

36 Table 6. Lane distribution differences without and with truck lane restrictions for all sites. Lane Location Without Truck Restrictions With Truck Restrictions Percent Change (%) Car Volumes Truck Volumes % of Trucks Car Volumes Truck Volumes % of Trucks Left Lane SB I-75 22,232 4746 17.59 21,201 10209 32.50 84.76 SB US-23 35,987 834 2.27 20,943 3318 13.68 502.64 NB US-23 28,507 697 2.39 18,189 4096 18.38 669.04 Totals 86,726 6,277 6.75 60,333 17623 22.61 234.96 Right Lane SB I-75 9,465 7,691 44.83 18,128 2630 12.67 -71.74 SB US-23 23,333 4,749 16.91 24,696 2366 8.74 -48.31 NB US-23 2,1031 4436 17.42 26,899 2493 8.48 -51.32 Totals 53,829 16,876 23.87 69,723 7489 9.70 -59.36 • SB I-75: Data were collected for 40 hours in the without condition and for 46 hours in the with condition. • SB US-23 and NB US-23: Data were collected for 48 hours in the without condition and for 46 hours in the with condition.

37 5.4. Comparison of Results for Truck Speeds A comparison of truck speeds was conducted to evaluate the effect of lane-use restriction. Besides the evaluation based on the lane distribution of trucks, a comparison of truck speeds can also determine if lane-use restrictions cause changes in travel characteristics. The truck speeds were compared separately according to the time period; morning peak period (6–9 a.m.), mid-day period (10 a.m.–1 p.m.), and evening peak period (3–6 p.m.) for each site. 5.4.1 SB I-75 Location Table 7 shows the comparison of average speed of trucks without and with the truck lane restrictions. With the truck restrictions in place, the average truck speeds reduced in the right lane during the morning peak period (by 16.39%) and mid-day period (by 16.03%) and evening peak period (by 16.25%). These reductions are expected because if truck lane restrictions are effective, it is assumed that the number of passenger cars in the right lane would increase and trucks would travel at the prevailing speed. With the truck restrictions in place, the average truck speeds increased in the left lane during the morning peak period (by 9.38%), mid-day period (by 7.17%), and evening peak period (by 7.58%). These increases were are expected, as vehicles traveled close to the posted speed limit of 60 mph. The changes in average speeds of trucks are all statistically significant (α = 0.05). Table 7. SB I-75 truck speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 52.27 51.97 51.81 66.16 64.85 64.84 With Truck Restrictions 57.17 55.70 55.74 55.31 54.46 54.30 % Change +9.38 +7.17 +7.58 -16.39 -16.03 -16.25 Significant Change Yes Yes Yes Yes Yes Yes Table 8 shows the comparison of average speed of passenger cars without and with the truck lane restrictions. With the truck restrictions in place, the passenger car average speeds reduced in the right lane during the morning peak period (by 15.04%), mid-day period (by 14.05%), and evening peak period (by 14.13%).

38 With the truck restrictions in place, the passenger car average speeds increased in the left lane during the morning peak period (by 8.82%), mid-day period (by 5.43%), and evening peak period (by 6.07%). The changes in average speeds of passenger cars are all statistically significant (α = 0.05). Table 8. SB I-75 car speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 58.02 56.03 56.97 70.89 68.27 68.60 With Truck Restrictions 63.14 59.07 60.42 60.23 58.68 58.91 % Change +8.82 +5.43 +6.07 -15.04 -14.05 -14.13 Significant Change Yes Yes Yes Yes Yes Yes 5.4.2 SB US-23 Location Table 9 shows the comparison of average speed of trucks without and with the truck lane restrictions. With the truck restrictions in place, the average truck speeds reduced in the right lane during the morning peak period (by 4.19%), mid-day period (by 5.35%), and evening peak period (by 3.14%) as traffic volumes in the right lane increased. With the truck restrictions in place, the average truck speeds increased in the left lane during the morning peak period (by 5.25%), decreased during the mid-day period (by 4.24%), and evening peak period (by 1.82%). It was observed that the truck speeds in the left lane in the with condition were somewhat higher than those in the without condition. The changes in average speeds of trucks were all statistically significant (α = 0.05), with the exception of the left lane during the evening peak period. Table 9. SB US-23 truck speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 60.65 64.46 64.10 57.52 58.83 57.87 With Truck Restrictions 63.83 61.72 62.94 55.11 55.68 56.05 % Change 5.25 -4.24 -1.82 -4.19 -5.35 -3.14 Significant Change Yes Yes No Yes Yes Yes

39 Table 10 shows the comparison of average speed of passenger cars without and with the truck lane restrictions. With the truck restrictions in place, the passenger car average speeds increased slightly in the right lane during the morning peak period (by 1.11%), reduced during the mid-day period (by - 2.66%), and evening peak period (by -1.07%). With the truck restrictions in place, the passenger car average speeds increased slightly in the left lane during the morning peak period (by 1.55%), and decreased during the mid-day period (by 5.98%), and evening peak period (by 2.6%). The changes in average speeds of passenger cars are all statistically significant (α = 0.05). Table 10. SB US-23 car speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 64.10 69.38 68.10 60.32 63.40 62.38 With Truck Restrictions 65.09 65.23 66.33 60.99 61.71 61.71 % Change 1.55 -5.98 -2.60 1.11 -2.66 -1.07 Significant Change Yes Yes Yes Yes Yes Yes 5.4.3 NB US-23 Location Table 11 shows the comparison of average speed of trucks without and with the truck lane restrictions. With the truck restrictions in place, the average truck speeds increased significantly in the right lane during the morning peak period (by 23.53%), mid-day period (by 18.16%), and decreased during the evening peak period (by 16.26%). With the truck restrictions in place, the average truck speeds decreased in the left lane during the morning peak period (by 14.65%), mid-day period (by 16.78%), and evening peak period (by 38.57%). It was observed that the truck speeds in left lane in the without condition were significantly lower than those in the right lane without condition. The changes in average speeds of trucks are all statistically significant (α = 0.05) with the exception of those in the left lane during the evening peak period.

40 Table 11. NB US-23 truck speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 59.36 57.90 56.35 51.84 52.67 50.82 With Truck Restrictions 50.67 48.18 34.62 64.04 62.23 42.56 % Change -14.65 -16.78 -38.57 23.53 18.16 -16.26 Significant Change Yes Yes Yes Yes Yes Yes Table 12 shows the comparison of average speed of passenger cars without and with the truck lane restrictions. With the truck restrictions in place, the passenger car average speeds increased significantly in the right lane during the morning peak period (by 17.7%), mid-day period (by 10.66%), and decreased during the evening peak period (by 33.14%). With the truck restrictions in place, the passenger car average speeds decreased in the left lane during the morning peak period (by 12.85%), mid-day period (by 17.20%), and evening peak period (by 40.26%). The changes in average speeds of passenger cars are all statistically significant (α = 0.05). Table 12. NB US-23 car speeds without and with truck lane restrictions. Left Lane Average Speeds (mph) Right Lane Average Speeds (mph) 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. 6–9 a.m. 10 a.m.–1 p.m. 3–6 p.m. Without Truck Restrictions 60.58 59.79 58.33 56.61 56.29 54.38 With Truck Restrictions 52.80 49.51 34.84 66.63 62.30 36.36 % Change -12.85 -17.20 -40.26 17.70 10.66 -33.14 Significant Change Yes Yes Yes Yes Yes Yes 5.5. Comparison of Headways Results The vehicle headway is defined as the time (in seconds) or gap (in feet), between two successive vehicles as they pass a point on the roadway, measured from the same common feature of both vehicles. Headway is a good measure of congestion and lack of passing opportunities created by the traffic mix; it is also a good surrogate safety measure as lane changing and frequent passing generally lead to conflicts and the likelihood of crashes. In general, a longer headway accepted by a merging vehicle is safer than a shorter headway.

41 Car–truck interactions are viewed as the driving actions of non-truck drivers resulting from psychological discomfort in the vicinity of trucks, primarily due to truck physical/operational characteristics. While interactions can also arise from the truck driver perspective, they tend to be less significant behaviorally as cars are smaller in size and have better operational characteristics. There is a rich body of literature on safety issues involving trucks. These studies mostly focus on the analyses of crash data or on models to understand key causal factors in relation to crashes. However, the existing literature does not address the modeling of traffic flow interactions between trucks and other vehicles arising from a driver behavior perspective, especially those that do not lead to crashes. Such a capability is essential for analyzing strategies to mitigate car–truck interactions, which further influence traffic performance, safety, and the travel experience of non-truck drivers. This study attempted to capture the effect of the car–truck interaction on vehicle headway, vehicle platoons and gap acceptance by different leading and following vehicle types. 5.5.1 Comparison of Results for Frequency of Headway An evaluation of the headways accepted by the following vehicles in each lane was conducted to determine if there were any differences without and with the truck lane restrictions in place. An analysis of vehicle headways was conducted in the morning peak period (6–9 a.m.) and in the evening peak period (3–6 p.m.) to determine the average values and distribution during the without and with the truck lane restrictions. 5.5.1.1 SB I-75 Location An analysis of headways of vehicles in the morning peak period (6–9 a.m.) was conducted to determine the average values and distribution for the with and without conditions. The K-S test was used to judge how faithfully a distribution fits the sample data. The K-S test was adopted to determine the goodness-of-fit in the work zone traffic condition. Tables 13 and 14 summarize the K-S test results of without and with implementation of truck lane restrictions. The following describes the headway analysis comparison for the right lane and left lane. SB I-75 Headway Analysis Results Using K-S Test—Left Lane Figure 12 presents a visual performance comparison of headway distribution through cumulative distribution function in the morning peak period for without vs. with implementation of truck lane restriction on the left lane. The agency observed a slight shift in the headway distribution toward longer headway during the with condition. The with condition had a longer headway for approximately 50% of sample (cumulative percentage 20% to 70%) with a maximum headway difference of 50 ft. The median value of headway was 255 ft during

42 the without condition as opposed to 286 ft during the with condition. With the significance level α of 0.05 and the sample size of 2,254 for the without condition and 2,730 for the with condition, the critical statistic of K-S test for the maximum difference between the cumulative distributions, D, was 0.04. The results of K-S test for the without condition vs. the with condition shows a value of D of 0.061 (greater than the critical value of 0.04), which suggests the differences in the two cumulative distributions are statistically significant. Table 13. SB I-75 Headway analysis results using K-S test—left lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 2,254 2,370 Mean Headway (ft) 396 410 Median Headway (ft) 255 286 Maximum difference (D) 0.061 Significance Yes Figure 12. SB I-75 Cumulative headway distribution plot (left lane)—without vs. with condition (6–9 a.m.). 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 500 1000 1500 2000 2500 3000 3500 4000 Cu m ul at iv e Pe rc en ta ge Headway (Feet) Without Truck Lane Restrictions (Left Lane) 6-9 AM With Truck Lane Restrictions (Left Lane) 6-9 AM

43 SB I-75 Headway Analysis Results Using K-S Test—Right Lane Figure 13 presents a visual performance comparison of headway distribution through a cumulative distribution function in the morning peak period for the without condition vs. the with condition in the right lane. The agency observed a shift in the headway distribution toward longer headways during the without condition. The without condition had a longer headway in approximately 95% of the sample (cumulative percentage 5% to 100%) with a maximum headway difference of 400 ft. The median value of headway was 481 ft during the without condition as opposed to 367 ft during the with condition. With the significance level α of 0.05 and the sample size of 1,481 for the without condition and 1,679 for the with condition, the critical statistic of K-S test for the maximum difference between the cumulative distributions, D, was 0.05. The results of K-S test for the without condition vs. the with condition shows a value of D of 0.127 (greater than the critical value of 0.05), which suggests the differences in the two cumulative distributions are statistically significant. Table 14. SB I-75 Headway analysis results using K-S test—right lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 1,481 1,679 Mean Headway (ft) 732 556 Median Headway (ft) 481 367 Maximum difference (D) 0.127 Significance Yes

44 Figure 13. SB I-75 Cumulative headway distribution plot (right lane)—without vs. with condition (6–9 a.m.). 5.5.1.2 SB US -23 Location Tables 15 and 16 summarize the K-S test results of without and with implementation of truck lane restrictions. The following discusses the headway analysis comparison for the right lane and left lane. SB US-23 Headway Analysis Results Using K-S Test - Left Lane Figure 14 presents a visual performance comparison of headway distribution through a cumulative distribution function in the morning peak period for the without vs. the with implementation periods of truck lane restrictions on the SB left lane. A shift in the headway distribution toward longer headways during the with condition was observed. At the headway of 100 ft, the cumulative percentages are 29.58% and 45.47% during the with condition and the without condition, respectively. The with condition had longer headways in approximately 55% of the sample (cumulative percentage 45% to 100%) with a maximum headway difference of 400 ft. The median value of headway was 104 ft during the without condition as opposed to 167 ft during the with condition. With the significance level α of 0.05 and the sample size of 5,993 during the without” condition and 3,374 during the with condition, the critical statistic of the K-S 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 1000 2000 3000 4000 5000 6000 Cu m ul at iv e Pe rc en ta ge Headway (Feet) Without Truck Lane Restrictions (Right Lane) 6-9 AM With Truck Lane Restrictions (Right Lane) 6-9 AM

45 test for the maximum difference between the cumulative distributions, D, was 0.04. The results of the K-S test for the without condition vs. the with condition shows a value of D of 0.194 (greater than the critical value of 0.04), which suggests the differences in the two cumulative distributions are statistically significant. Table 15. SB US-23 Headway analysis results using K-S test—left lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 5,993 3,374 Mean Headway (ft) 166 277 Median Headway (ft) 104 167 Maximum difference (D) 0.194 Significance Yes Figure 14. SB US-23 Cumulative headway distribution plot (left lane)—without vs. with condition (6–9 a.m.). SB US-23 Headway Analysis Results Using K-S Test—Right Lane 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 500 1000 1500 2000 2500 3000 3500 Cu m ul at iv e Pe rc en ta ge Headway (Feet) (SB) Left Lane without truck lane restrictions 6-9 AM (SB) Left Lane with truck lane restrictions 6-9 AM

46 Figure 15 presents a visual performance comparison of headway distributions through cumulative distribution function in the morning peak period for the without condition vs. the with condition on the SB right lane. A slight shift in the headway distribution toward longer headways during the with condition was observed. The with condition has a longer headway in approximately 25% of the sample (cumulative percentage 75% to 100%) with a maximum headway difference of 100 ft. The median value of headway was 211 ft at the without condition as opposed to 229 ft at the with condition. With the significance level α of 0.05 and the sample size of 3,094 during the without condition and 2,883 during the with condition, the critical statistic of K-S test for the maximum difference between the cumulative distributions, D, is 0.04. The results of K-S test for the without condition vs. the with condition shows a value of D of 0.02 (less than the critical value of 0.04), which suggests the differences in the two cumulative distributions are not statistically significant. Table 16. SB US-23 Headway analysis results using K-S test—right lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 3,094 2,883 Mean Headway (ft) 305 326 Median Headway (ft) 211 229 Maximum difference (D) 0.023 Significance No

47 Figure 15. SB US-23 Cumulative headway distribution plot (right lane)—without vs. with condition (6–9 a.m.). 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 500 1000 1500 2000 2500 3000 3500 Cu m ul at iv e Pe rc en ta ge Headway (Feet) (SB) Right Lane without truck lane restrictions 6-9 AM (SB) Right Lane with truck lane restrictions 6-9 AM

48 5.5.1.3 NB US -23 Tables 17 and 18 summarize the K-S test results of without and with implementation of truck lane restrictions. A discussion of the headway analysis comparison for the right lane and left lane follows. NB US-23 Headway Analysis Results Using K-S Test—Left Lane Figure 16 presents a visual performance comparison of headway distribution through cumulative distribution function in the morning peak period for without vs. with implementation of truck lane restriction on the NB left lane. The agency observed a slight shift in the headway distribution toward longer headway during the with condition. The with condition had a longer headway in an approximately 15% of sample (cumulative percentage 85% to 100%) with a maximum headway difference of 500 ft. The median value of headway was 167 ft during the without condition as opposed to 141 ft during the with condition. With the significance level α of 0.05 and the sample size of 4,036 during the without condition and 2,359 during the with condition, the critical statistic of K-S test for the maximum difference between the cumulative distributions, D, is 0.04. The results of K-S test for the without condition vs. the with condition shows a value of D of 0.049 (greater than the critical value of 0.04), which suggests the differences in the two cumulative distributions are statistically significant. Table 17. NB US-23 Headway analysis results using K-S test–left lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 4,036 2,359 Mean Headway (ft) 226 270 Median Headway (ft) 167 141 Maximum difference (D) 0.049 Significance Yes

49 Figure 16. NB US-23 Cumulative headway distribution plot (left lane)—without vs. with condition (3–6 p.m.). 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 500 1000 1500 2000 2500 3000 3500 4000 4500 Cu m ul at iv e Pe rc en ta ge Headway (Feet) (NB) Left Lane without truck lane restrictions 3-6 PM (NB) Left Lane with truck lane restrictions 3-6 PM

50 NB US-23 Headway Analysis Results Using K-S Test—Right Lane Figure 17 presents a visual performance comparison of headway distribution through cumulative distribution function in the morning peak period for the without condition vs. the with condition on NB right lane. The agency observed a shift in the headway distribution toward longer headways during the without condition. At the headway of 100 ft, the cumulative percentages are 39.41% and 21.98% during the with condition and the without condition, respectively. The without condition had a longer headway in an approximately 55% of sample (cumulative percentage 40% to 95%) with a maximum headway difference of 300 ft. The median value of headway was 246 ft at the without condition as opposed to 339 ft at the with condition. With the significance level α of 0.05 and the sample size of 2,411 during the without condition and 3,139 during the with condition, the critical statistic of K-S test for the maximum difference between the cumulative distributions, D, is 0.04. The results of K-S test for the without condition vs. the with condition shows a value of D of 0.277 (greater than the critical value of 0.04), which suggests the differences in the two cumulative distributions are statistically significant. Table 18. NB US-23 Headway analysis results using K-S test—right lane. Conditions Without implementation of truck lane restrictions With implementation of truck lane restrictions Volume (Vehicle/3-hr) 2,411 3,139 Mean Headway (ft) 354 339 Median Headway (ft) 246 339 Maximum difference (D) 0.277 Significance Yes

51 Figure 17. NB US-23 Cumulative headway distribution plot (right lane)—without vs. with condition (3–6 p.m.). 5.5.2 Comparison of Results for Platoon Headways and Gap Acceptance The team examined the number of instances where a vehicle leads a platoon of traffic. A platoon is defined as a vehicle traveling with a headway greater than 3 seconds, followed by one or more vehicles with a headway less than 3 seconds. In this analysis, the headway was analyzed for different vehicle leader–follower pairs—car followed by a car or truck (C-C and C-T) and a truck followed by a car or truck (T-C and T-T). Table 19 shows the results of the mean headways and gap acceptance for the different vehicle pairs without and with truck lane restrictions at the SB I-75 test site. It is noted that data were presented for evening peak period (3–6 p.m.) only, which happened to have the highest traffic volumes during the day. The results show that the mean headways in the left lane increased for C-C (by 1.9%), C-T (by 13.2%), and T-T (by 2.3%) pairs, and decreased for T-C pairs (by 0.9%). Correspondingly, the 0.00% 10.00% 20.00% 30.00% 40.00% 50.00% 60.00% 70.00% 80.00% 90.00% 100.00% 0 500 1000 1500 2000 2500 3000 3500 4000 4500 5000 Cu m ul at iv e Pe rc en ta ge Headway (Feet) (NB) Right Lane without truck lane restrictions 3-6 PM (NB) Right Lane with truck lane restrictions 3-6 PM

52 mean gaps in the left lane decreased for C-C (by 4.5%), T-C (by 8%), and T-T (by 8.1%) pairs and increased for T-C pairs (by 5.6%). In the right lane, the mean headways decreased (by 16.1% for C-C, 11.1% for C-T, 6.7% for T-C, and 4.4% for T-T) for all vehicle pairs and the mean gaps increased for all vehicle pairs (by 0.2% for C-C, 5.6% for C-T, 8.8% for T-C, and 24.4% for T-T). The decrease in headways in the right lane was expected as the volume of passenger cars in the right lane increased when the truck restrictions were in place. However, it is noted that, in theory, trucks should not be using the right lane in the after condition, as the restrictions were in place. The presence of trucks in the right lane can be attributed to trucks not complying with the restrictions, as well as trucks making lane change maneuvers to exit. Table 20 shows the results of the mean headways and gap acceptance for the different vehicle pairs without and with truck lane restrictions at the SB US-23 test site. It is noted that data were presented for morning peak period (6–9 a.m.) only, which happened to have the highest traffic volumes during the day. The results show that the mean headways in the left lane increased for C-C (by 14.1%), C-T (by 38.9%), T-C (by 23.6%), and decreased for T-T (by 67.6%). Correspondingly, the mean gaps in the left lane also increased for C-C (by 14.4%), T-C (by 35.9%), and T-C (by 20.8%) pairs, and decreased for T-T pairs (by 66.5%). In the right lane, the mean headways increased for C-C (by 6.1%), C-T (by 7.5%), T-C (by 5.8%), and decreased for T-T (by 7.6%) pairs. The mean gaps also increased for all vehicle pairs (by 5.5% for C-C, 12.3% for C-T, 10.1% for T-C, and 1.9% for T-T). Table 21 shows the results of the mean headways and gap acceptance for the different vehicle pairs without and with truck lane restrictions at the NB US-23 test site. It is noted that data were presented for evening peak period (3–6 p.m.) only, which happened to have the highest traffic volumes during the day. The results show that the mean headways in the left lane decreased for all vehicle pairs (by 26.2% for C-C, 34.4% for C-T, and 7.5% for T-C). Correspondingly, the mean gaps in the left lane also increased for C-C (by 24%), C-T (by 20.5%), and T-C (by 32.2%) pairs. T-T vehicle interactions were not found within the evening peak period (3–6 p.m.). In the right lane, the mean headways decreased for all vehicle pairs (by 43.9% for C-C, 27.6% for C-T, and 19% for T-C, and 4.7% for T-T). The mean gaps also decreased for all vehicle pairs (by 19.1% for C-C, 18.7% for C-T, 7.8% for T-C, and 10.1% for T-T).

53 Table 19. SB I-75 Platoon headways and gap acceptance (3–6 p.m.). Lane Headway Type % of Trucks Average Speed (mph) Sample Size Mean Headway (ft) Mean Gap (sec) Without With Difference (%) Without With Difference (%) Without With Without With Difference (%) Without With Difference (%) Le ft L an e C-C 12.62 23.87 +89.2 56.3 59.3 +5.3 2,034 1,568 299.1 304.7 1.9 3.55 3.39 -4.5 C-T 82 148 303.4 343.3 13.2 3.78 3.99 5.6 T-C 700 940 287.4 284.7 -0.9 3.74 3.44 -8.0 T-T 128 296 320.9 328.2 2.3 4.34 3.99 -8.1 R ig ht La ne C-C 36.42 9.51 -73.9 67 58 -13.4 748 1790 417.9 350.5 -16.1 4.06 4.07 0.2 C-T 206 58 474.3 421.5 -11.1 4.78 5.05 5.6 T-C 570 266 376.9 351.8 -6.7 3.97 4.32 8.8 T-T 262 26 415.1 433.3 4.4 4.47 5.65 26.4 Table 20. SB US-23 Platoon headways and gap acceptance (6–9 a.m.). Lane Headway Type % of Trucks Average Speed (mph) Sample Size Mean Headway (ft) Mean Gap (sec) Without With Difference (%) Without With Difference (%) Without With Without With Difference (%) Without With Difference (%) Le ft L an e C-C 1.49 8.16 +449.4 64.04 65 +1.5 2,690 2,154 2,90.6 331.6 14.1 2.99 3.42 14.4 C-T 30 116 297.2 412.7 38.9 3.23 4.39 35.9 T-C 104 396 287.2 355.1 23.6 3.17 3.83 20.8 T-T 4 36 NA* 366.2 NA* NA* 4.19 NA* R ig ht La ne C-C 13.74 8.03 -41.6 59.9 60.5 +1.0 2,104 2,258 291.2 308.9 6.1 3.28 3.46 5.5 C-T 94 90 374.7 402.8 7.5 4.13 4.64 12.3 T-C 598 284 306.9 324.8 5.8 3.68 4.05 10.1 T-T 68 28 353.4 326.7 -7.6 4.13 4.21 1.9 * Small data sample

54 Table 21. NB US-23 Platoon headways and gap acceptance (3–6 p.m.). Lane Headway Type % of Trucks Average Speed (mph) Sample Size Mean Headway (ft) Mean Gap (sec) Without With Difference (%) Without With Difference (%) Without With Without With Difference (%) Without With Difference (%) Le ft La ne C-C 2.13 10.95 +415.2 58.2 34.8 -40.2 3,298 1,576 268.9 198.5 -26.2 3.12 3.87 24.0 C-T 44 62 337.9 221.6 -34.4 3.95 4.76 20.5 T-C 120 338 276.1 255.3 -7.5 3.45 4.56 32.2 R ig ht La ne C-C 13.17 5.96 -54.7 53.9 36.7 -31.9 1,660 2,806 301.7 169.3 -43.9 3.76 3.04 -19.1 C-T 90 98 339.4 245.6 -27.6 4.44 3.61 -18.7 T-C 392 290 296.8 240.3 -19.0 4.0 3.69 -7.8 T-T 40 14 324.7 309.4 -4.7 4.45 4 -10.1 No T-T interactions were found within the evening peak period (3–6 p.m.).

55 5.6. Work Zone Crash Modification Factor for Truck Lane Restrictions This section discusses the CMF calculation for deploying truck lanes. Table 22 shows the expected and actual crash results for the deployment of truck lane. The Total Hours column indicates the number of hours of data analyzed. Table 22. Expected and actual crash results for truck lane restriction. Treatment Total Hours Expected Crashes Actual Crashes Percent Change Truck Lane Deployment 5,880 695.3 449 -35 For truck lane deployment condition, there was a 35% decrease from expected to actual crashes. In order to determine the proportional effects of the treatments on the numbers of crashes, an odds ratio analysis was undertaken according to the following equations: Where: CMFD = crash modification factor = proportional effect of a deployment on crashes: TAD = total actual crashes during a deployment (equal to 449 in this case); TED = total expected crashes during a deployment (equal to 695.3 in this case); TAND = total actual crashes when nothing was deployed (equal to 425 in this case); TEND = total expected crashes when nothing was deployed (equal to 614.3 in this case); and SD (CMFD) = standard error. Table 23 shows the results from the CMF calculation. The calculated CMF for the deployment of truck lane is less than 1, indicating that this treatment had only minor effect on reducing the number of crashes, without taking standard error into account.

56 Table 23. CMF results for truck lane restriction. Treatment CMFD SE(CMFD) ADT Truck Lane Deployment (Interstate) 0.928 0.081 Up to 100,000 Vehicles The CMF is limited because of the few test sites. Agencies should use this as a guide, and monitor all work zones and take appropriate action to mitigate any increase in crashes (i.e., severity and number).

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Transportation management plans (TMPs) are a set of coordinated strategies designed to help agencies achieve work zone project goals related to traffic mobility, efficient system operation, motorist and worker safety, and other operational targets.

The TRB National Cooperative Highway Research Program'sNCHRP Web-Only Document 276: Evaluating Strategies for Work Zone Transportation Management Plans focuses on the field evaluations that are part of NCHRP Research Report 945: Strategies for Work Zone Transportation Management Plans.

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