4.1 Calculating crash rate at intersections as a first measure of safety level

In the light of the research goals set out in Section 1 and shown in Figure 1, a procedure developed in 1995 by the Italian National Research Council [12] was used to assess the safety level of traffic conditions at each ith intersection investigated, as shown in the flowchart in Figure 3.

Before computing the crash safety level, LoS and total crash cost, a technique for filtering anomalous crash rates was adopted using the 3σ method. The method is based on the calculation of the standard deviation (σ) and mean values (μ) for crash rate distribution to check the homogeneity of scattering around the average and the

maximum deviation at 3σ. Figure 4 shows an example of the control chart of the crash rates for non-circular intersections throughout the study period. It can be observed how 92% of the measurements fall within the range [0; μ + σ] = [0; 1.24], 97% fall within the range [0; μ + 2σ] = [0; 1.94], and all the values fall within the range [0; μ + 3σ] = [0; 2.64]. CRlower limit is equal to 0.36 crashes per year per 10<sup>6</sup> vehicles crossing the ith intersection, and CRupper limit is equal to 0.52 crashes per

Analytical Assessment of Effective Maintenance Operations on At-Grade Unsignalized…

The overall results show that 63% of the total number of intersections indicate a low crash level (a total of 51 non-circular intersections and 7 single-lane roundabouts); 33% show a high crash level (a total of 34 non-circular intersections), and the remaining 4% represents a medium crash level (four non-circular

The next step in the study focused on assessing LoS and crash costs for the four intersections where a high crash level and medium-high crash cost were observed. Neither the non-circular intersections respecting the Italian Road Design Standard nor the roundabouts are included among the "black" rankings. Figure 5 shows an excerpt of the current geometric design of four "black" ranking intersections. Table 2 shows the main features of the investigated intersections mentioned above: the number of legs, AADTmaj, AADTmin, and CRi, as well as the total number of crashes, the total number of injuries, and the total number of vehicles damaged during

) for the

4.2 Calculating level of service as a second measure of safety level

the collision. Table 3 shows the distribution of the hourly traffic flow (qj

tiveness used to set LoS at TWSC intersections as perceived by users.

equivalent passenger cars in the different travel directions as illustrated in Figure 5. The geometrical configuration of the four study intersections in Figure 5 is very simple, and no additional geometric modules exist to promote safe maneuvering, according to the specifications in Section 2. This is the opposite of what happens at intersections where a "low crash level" was observed, where additional modules exist, and where geometric features respect the Italian Road Design Standard requirements in full. LoS was assessed for the entire intersection by evaluating control delay dj for each maneuver jth. The HCM2016 [13] defines control delay as the measure of effec-

year per 10<sup>6</sup> vehicles crossing the ith intersection.

Control charts of the crash rate values for typical intersections.

DOI: http://dx.doi.org/10.5772/intechopen.86435

intersections).

169

Figure 4.

#### Figure 3.

Assessment of the crash safety level of each ith study intersection.

Analytical Assessment of Effective Maintenance Operations on At-Grade Unsignalized… DOI: http://dx.doi.org/10.5772/intechopen.86435

Figure 4. Control charts of the crash rate values for typical intersections.

maximum deviation at 3σ. Figure 4 shows an example of the control chart of the crash rates for non-circular intersections throughout the study period. It can be observed how 92% of the measurements fall within the range [0; μ + σ] = [0; 1.24], 97% fall within the range [0; μ + 2σ] = [0; 1.94], and all the values fall within the range [0; μ + 3σ] = [0; 2.64]. CRlower limit is equal to 0.36 crashes per year per 10<sup>6</sup> vehicles crossing the ith intersection, and CRupper limit is equal to 0.52 crashes per year per 10<sup>6</sup> vehicles crossing the ith intersection.

The overall results show that 63% of the total number of intersections indicate a low crash level (a total of 51 non-circular intersections and 7 single-lane roundabouts); 33% show a high crash level (a total of 34 non-circular intersections), and the remaining 4% represents a medium crash level (four non-circular intersections).

#### 4.2 Calculating level of service as a second measure of safety level

The next step in the study focused on assessing LoS and crash costs for the four intersections where a high crash level and medium-high crash cost were observed. Neither the non-circular intersections respecting the Italian Road Design Standard nor the roundabouts are included among the "black" rankings. Figure 5 shows an excerpt of the current geometric design of four "black" ranking intersections.

Table 2 shows the main features of the investigated intersections mentioned above: the number of legs, AADTmaj, AADTmin, and CRi, as well as the total number of crashes, the total number of injuries, and the total number of vehicles damaged during the collision. Table 3 shows the distribution of the hourly traffic flow (qj ) for the equivalent passenger cars in the different travel directions as illustrated in Figure 5.

The geometrical configuration of the four study intersections in Figure 5 is very simple, and no additional geometric modules exist to promote safe maneuvering, according to the specifications in Section 2. This is the opposite of what happens at intersections where a "low crash level" was observed, where additional modules exist, and where geometric features respect the Italian Road Design Standard requirements in full. LoS was assessed for the entire intersection by evaluating control delay dj for each maneuver jth. The HCM2016 [13] defines control delay as the measure of effectiveness used to set LoS at TWSC intersections as perceived by users.

injury crash frequencies per year increase when the total crash frequency per year increases and the mean width of the approaching and departing lanes of the regular intersections decreases. Figure 2b shows how crash frequencies per year increase when the AADT crossing the intersection increases and when the mean width of the

approaching lane to an intersection or departing lane from the intersection

4. Data analysis: evaluating measures reflecting crash risk exposure

4.1 Calculating crash rate at intersections as a first measure of safety level

In the light of the research goals set out in Section 1 and shown in Figure 1, a procedure developed in 1995 by the Italian National Research Council [12] was used to assess the safety level of traffic conditions at each ith intersection investigated, as

Before computing the crash safety level, LoS and total crash cost, a technique for filtering anomalous crash rates was adopted using the 3σ method. The method is based on the calculation of the standard deviation (σ) and mean values (μ) for crash rate distribution to check the homogeneity of scattering around the average and the

decreases.

Figure 3.

168

Assessment of the crash safety level of each ith study intersection.

shown in the flowchart in Figure 3.

Transportation Systems Analysis and Assessment

where qj is the flow in the subject lane for maneuver j, in vph; Ce,j is the effective capacity of the subject lane for maneuver j, in vph; T is the time period, in hours (T = 1 for a 1-h analysis, T = 0.25 for a 15 min analysis); and 5 is the waste time during the deceleration and acceleration phases compared with free flow speed,

Site Traffic volume, vph Site Traffic volume, vph Intersection A Direction X Y Z Intersection B Direction X Y Z W

Analytical Assessment of Effective Maintenance Operations on At-Grade Unsignalized…

DOI: http://dx.doi.org/10.5772/intechopen.86435

Intersection C Direction X Y Z Intersection D Direction X Y Z W

X — 226 13 X — 150 60 60 Y 170 — 68 Y 100 — 70 100 Z 70 11 — Z 70 90 — 80

X — 374 42 X — 150 60 80 Y 274 — 190 Y 180 — 70 80 Z 142 90 — Z 70 40 — 60

W 100 30 110 —

W 30 50 80 —

Eq. (7) was adjusted for the real context working on one of the main variables:

The evaluation of tc,j critical gaps is not immediate and can appear difficult to estimate from a field measurements sample; results of empirical studies have shown that different combinations of configuration and situational influences may lead to diverse profiles of compliance and proactive safety behavior among drivers [21]. In the literature, several techniques exist to calculate gap acceptance data assuming the consistency of road drivers, for example, the Raff and Hart method

As a result, the tc,j value for each driver entering an intersection from a minor road in Figure 5 was calculated using the Drew-Dawson method, based on the median time value. Figure 6 shows an example of critical gaps (tc,j) for drivers crossing intersection A (see Figure 5) turning from leg Y to leg Z (left turn from minor to major road) and from leg Z to leg Y (right turn from minor to major road) during time period T. Table 4 shows an overall view of the observed values of the

The control delay for an entire intersection dentire\_intersection (see Eq. (8)) is calculated by computing a weighted average of the control delay for each maneuver dj,

dentire intersection <sup>¼</sup> <sup>∑</sup>djqj

According to the thresholds defined in HCM2016 [13], the LoS was defined for

each maneuver by also associating qualitative measures from A (control delay between 0 and 10 s/veh) to F (control delay more than 50 s/veh) as provided in

∑qj

(2)

Ce,j was calculated by adopting real measurements of tc,j (critical gap per maneuver j-th) and tf,j (follow-up time per maneuver j-th) values at the four study intersections shown in Figure 5 instead of adopting the HCM2016 equation based

[22], the Drew-Dawson method [23–25], and the stepped line model.

weighted by the volume of each flow for the maneuver investigated.

tc,j and tf,j variables for the maneuvers at intersection A.

Distribution of the hourly traffic volume in the subject lane per maneuver.

expressed in seconds (5 s).

on studies across the United States.

effective capacity Ce,j.

Table 3.

171

Figure 5.

The geometric design of the currently non-circular intersections studied.


#### Table 2.

Overview of the crash and traffic features of four typical intersections investigated.

The analytical model (Eq. (7)) adopted to estimate average control delay dj per maneuver jth refers to Eqs. (17)–(38) of HCM2016 [13] and assumes that there is no residual queue at the start of the analysis period. In most cases, the recommended analysis period is 15 min.

$$d\_{j} = \frac{3600}{C\_{\epsilon,j}} + 900 \cdot T \left[ \frac{q\_{j}}{C\_{\epsilon,j}} - 1 + \sqrt{\left(\frac{q\_{j}}{C\_{\epsilon,j}} - 1\right)^{2} + \frac{\frac{3600}{C\_{\epsilon,j}} \cdot \frac{q\_{j}}{C\_{\epsilon,j}}}{450T}} \right] + 5 \tag{1}$$

Analytical Assessment of Effective Maintenance Operations on At-Grade Unsignalized… DOI: http://dx.doi.org/10.5772/intechopen.86435


#### Table 3.

Distribution of the hourly traffic volume in the subject lane per maneuver.

where qj is the flow in the subject lane for maneuver j, in vph; Ce,j is the effective capacity of the subject lane for maneuver j, in vph; T is the time period, in hours (T = 1 for a 1-h analysis, T = 0.25 for a 15 min analysis); and 5 is the waste time during the deceleration and acceleration phases compared with free flow speed, expressed in seconds (5 s).

Eq. (7) was adjusted for the real context working on one of the main variables: effective capacity Ce,j.

Ce,j was calculated by adopting real measurements of tc,j (critical gap per maneuver j-th) and tf,j (follow-up time per maneuver j-th) values at the four study intersections shown in Figure 5 instead of adopting the HCM2016 equation based on studies across the United States.

The evaluation of tc,j critical gaps is not immediate and can appear difficult to estimate from a field measurements sample; results of empirical studies have shown that different combinations of configuration and situational influences may lead to diverse profiles of compliance and proactive safety behavior among drivers [21].

In the literature, several techniques exist to calculate gap acceptance data assuming the consistency of road drivers, for example, the Raff and Hart method [22], the Drew-Dawson method [23–25], and the stepped line model.

As a result, the tc,j value for each driver entering an intersection from a minor road in Figure 5 was calculated using the Drew-Dawson method, based on the median time value. Figure 6 shows an example of critical gaps (tc,j) for drivers crossing intersection A (see Figure 5) turning from leg Y to leg Z (left turn from minor to major road) and from leg Z to leg Y (right turn from minor to major road) during time period T. Table 4 shows an overall view of the observed values of the tc,j and tf,j variables for the maneuvers at intersection A.

The control delay for an entire intersection dentire\_intersection (see Eq. (8)) is calculated by computing a weighted average of the control delay for each maneuver dj, weighted by the volume of each flow for the maneuver investigated.

$$d\_{\text{active interaction}} = \frac{\sum d\_j q\_j}{\sum q\_j} \tag{2}$$

According to the thresholds defined in HCM2016 [13], the LoS was defined for each maneuver by also associating qualitative measures from A (control delay between 0 and 10 s/veh) to F (control delay more than 50 s/veh) as provided in

The analytical model (Eq. (7)) adopted to estimate average control delay dj per maneuver jth refers to Eqs. (17)–(38) of HCM2016 [13] and assumes that there is no residual queue at the start of the analysis period. In most cases, the recommended

> qj Ce,j � 1 � �<sup>2</sup>

vuut

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi

AADTmaj, AADTmin, CRi Number of Total number of

vpd vpd 5-year study period

þ

3600 Ce,j � qj Ce,j 450T

3 7

Crashes Injuries Vehicles damaged

during collision

<sup>5</sup> <sup>þ</sup> 5 (1)

analysis period is 15 min.

Site Number

of legs

Transportation Systems Analysis and Assessment

Figure 5.

Table 2.

170

dj <sup>¼</sup> <sup>3600</sup> Ce,j

<sup>þ</sup> <sup>900</sup> � <sup>T</sup> qj

The geometric design of the currently non-circular intersections studied.

Ce,j

Overview of the crash and traffic features of four typical intersections investigated.

2 6 4

� 1 þ

Intersection A 3 3163 2120 2.22 4 3 4 Intersection B 4 3518 3153 1.32 11 4 9 Intersection C 3 6193 3097 1.72 12 8 7 Intersection D 4 4112 3102 2.09 14 4 6

#### Figure 6.

Example of tc,j assessment using the Drew-Dawson method for two maneuvers at intersection A.


included in the TCC prediction model are significant with a 95% level of confidence

Std. error t-value p-value Lower confidence limit Upper confidence limit 1457.90 12.19 0.001189 13130.97 22410.36

Analytical Assessment of Effective Maintenance Operations on At-Grade Unsignalized…

4.3 Treatment to manage and reduce the crash level by carrying out strategies

The next step in the research was to design different geometric solutions (Figure 8) for intersection D (Figure 5), which has a high crash rate, medium-high crash cost, low-medium LoS (Table 5) and to estimate, on the one hand, the expected LoS and, conversely, the expected reduction of the annual crash frequency of the configurations hypothesized. The solution shown in Figure 8a is an adaptation of intersection D to the requirements of the Italian Road Design Standard on the geometric design of road intersections [14]. The solution shown in Figure 8b

Before redesigning the geometric configuration of the area of intersection to include a roundabout, for which the investigated database showed that the mean crash rate over 5 years was lower than at non-circular intersections, it was decided to adjust the current non-circular intersection in line with the requirements of the

a.Phase I: adjusting the radius of the edges of the entry and exit legs of the

intersection, the width of the traffic lanes, the removal of obstacles in the areas within the so-called sight triangles, and the addition of median-refuge islands on the major and minor roads, as recommended by the Italian Road Design

) of the model is 83%.

TCC ¼ 17:771dentire intersection (3)

(Table 6). The adjusted coefficient of determination (R<sup>2</sup>

Statistical parameters of the regression model.

Total crash cost versus average control delay of the entire intersection.

DOI: http://dx.doi.org/10.5772/intechopen.86435

able to improve the expected LoS and safety levels

refers to transforming the shape into a compact roundabout.

4.3.1 Control delay: comparing before and after solutions

Italian Standard in force in two phases:

Standard [14];

173

Figure 7.

Table 6.

#### Table 4.

Observed tc,j and tf,j values for all maneuvers at intersection A.


#### Table 5.

Overview of control delay and crash costs at non-circular intersections with the old configuration.

Exhibit 17-2 of the HCM2016 [13]. Table 5 shows the dj values for the intersections investigated as listed in Tables 2 and 3 and the corresponding crash costs from the cost of an injured person approximately equals to 73,631 Euro, fatality equals to 1,394,434 Euro, and damaged vehicles almost of 7686 Euro.

Table 5 shows that the total crash cost (TCC) increases when the control delay of the entire intersection dentire intersection investigated increases: when the mean dj of the vehicles leaving the intersection area increases, this indicates that drivers do not feel safe to make the maneuver. This circumstance is mainly due to the poor geometric configuration of the intersection and, as confirmed by the preliminary results of this study, can amplify the frequency and severity of crashes.

Figure 7 shows a positive linear relationship using the ordinary least square method to predict the total crash cost in euros by varying the average control delay at the entire intersection, which is a measure of LoS (Eq. (9)). The parameters
