Formas de origen marino

In order to identify the locations that triggered HBIs, the Earth Point program, Excel to KML, was used, which displays Excel files on Google Earth and can be found at (Earth point, 2016). The position data (latitude and longitude coordinates) are imported to Google Earth. An inspection of the locations of these HBIs revealed that the majority occurred on the approaches to roundabouts, Figure 3-7 shows roundabout locations, and Figure 3-8 shows a sample of the selected locations with HBIs clustering around the approaches and circulatory lanes.

Figure 3-8 Samples of the Selected Roundabout Locations with HBIs

After the data were uploaded to Google Earth, because the majority of HBIs were clustered around roundabouts, 70 roundabouts covering 294 approaches with low and high occurrences

of HBIs were selected randomly. Note that of the 294 approaches of the selected roundabouts, for modelling purposes 284 were analysed, as the other ten approaches were located on roads that are not classified and traffic data for these kinds of road are not available. The selected roundabouts comprise nine roundabouts on the M1, ten roundabouts on the M6, six roundabouts on the M5 and nine roundabouts on the M4, with the others located on different motorways and A-class roads. Table 3-4 describes the characteristics of the 70 roundabouts, and Table 3-5 describes the characteristics of the roundabout approaches. The roundabouts have different numbers of arms, but the majority of them have four. In addition, the majority of the selected locations are grade separated.

Table 3-4 Whole Roundabout Characteristics

No. 3- arm 4- arm 5- arm 6- arm Traffic signals No traffic signals Partially signalised 2- lane 3- lane At- grade Grade- separated 70 12 39 12 7 20 28 22 39 31 19 51

Table 3-5 Roundabout Approach Characteristics

No. Traffic signals No traffic signals 2- lane 3- lane At- grade Grade- separated A road M road B road 284 142 142 172 112 73 211 174 94 16

The following is the description of each category used in this study for the roundabout as a whole, within the circulatory lanes, and at approaches:

 A roundabout is considered signalised when it is signalised at approaches and within the circulatory.

 A roundabout is considered un-signalised when it is un-signalised at approaches and within the circulatory.

 A roundabout is considered partially signalised when one or more of the approaches and circulatory lanes are signalised, but not all.

 Entry width for a roundabout taken as a whole is the average approach entry width, while at approaches it is the entry width at each individual approach.

 Traffic volume (AADT and percentage of truck traffic) for each roundabout and for the circulatory is the sum of the traffic volume at the roundabout’s approaches.

 Traffic volume (AADT and percentage of truck traffic) at approaches is the volume at each individual approach.

 When the roundabout has two circulatory lanes, and all approaches or the majority of approaches are two-lanes, this roundabout is as a whole considered to be a two-lane roundabout, and similarly for three-lanes.

 Individual approaches either signalised or un-signalised, and either they are two-lanes or three-lanes.

3.3.2 Harsh Braking Incidents

The truck HBI spreadsheet supplied by Microlise Ltd includes speed, date, time, longitude, and latitude (see Table 3-2). One objective of this study is to characterise HBIs to a number of factors, for this reason this section illustrates the procedures that are undertaken to filter, allocate, and count HBIs at the selected roundabouts, which will help understand the general characteristics of HBIs illustrated in Chapter Six, in addition to obtaining the number of HBIs for modelling purposes that is illustrated in Chapter Seven and Chapter Ten. Following is the procedure:

 As discussed earlier, the coordinates of HBIs (latitude and longitude) were uploaded to Google Earth using Excel to KML program.

 After the data was uploaded, locations were selected; the numbers of HBIs in each selected roundabout approach and within the circulatory lanes for the purpose of analysis were counted manually from Google Earth.

 To understand the general characteristics of HBIs, the distance between the point of each HBI and the entry line is identified for each of the selected 284 roundabout approaches; in addition to explore at what speed these braking incidents happened, the relationship between the distance that trucks recorded harsh braking away from the entry line and speed was examined. This process was undertaken to explore general trends of harsh braking, that is, if the distance changes based on the speed data available. From the Microlise data sheet there is no column describing at what distance the HBI was recorded; the only information available

is latitude and longitude, and for all the HBIs the distance between the two points was calculated by the following formula (Lentz, 2008):

ܦ=ܴா× cosିଵ((cos(ܴ(90 −ܮܽݐଵ)) × (cosܴ(90 −ܮܽݐଶ)) + (sin(ܴ(90 −ܮܽݐଵ)) × (sin(ܴ(90 −ܮܽݐଶ)) ×

(cosܴ(ܮ݋݊݃ଵ−ܮ݋݊݃ଶ)))) (3-1)

where:

ܴா=Earth Radius which is6378.135 km D= Distance is in km

ܴ= Radiance

ܮܽݐଵ and ܮܽݐଶ are the latitude of the first point and second point in decimal degrees, respectively.

ܮ݋݊݃ଵ and ܮ݋݊݃ଶ are the longitude of the first point and second point in decimal degrees, respectively.

Note that the latitude and longitude of the HBIs in this study was in decimal degrees (DD), in

case of Degrees° Minutes´ Second˝ (DMS) the_ܮܽݐଵ, ܮܽݐ_ଶ,ܮ݋݊݃_ଵ and ܮ݋݊݃_ଶ shown in Eq. (3-1) should be multiplied by 24 to convert them to DD.

 Since Microlise’s Excel data is for all UK roads and intersections, in order to filter the selected locations, the latitude and longitude from the centre of the roundabout was used as the main distance, and the distance between latitude/longitude from the centre of the roundabouts and all other points (over 195,297 HBIs) on the UK roads and intersections were calculated. Then the IF logical statement test in Excel was used (IF (logical_test, [value_if_true], [value_if_false])) in order to filter the selected roundabouts and copied to a different Excel sheet. The majority of HBIs occurred within 350m of the roundabouts (see Figure 3-9 for a sample of roundabout), so this distance was used as the distance from the roundabout centres to the final point of the HBIs within the roundabout. The same processes were carried out for the other 69 roundabouts using the latitude and longitude of the centre of the roundabouts and the IF logical statement.

Figure 3-9 HBI and Accidents Clustered Around A1/A14 Junction

 After each of the selected locations was filtered from the complete data of the UK roads and intersections, a similar process was carried out for each of the selected locations in order to allocate the HBIs to individual arms. In this case, the latitude and longitude of the entry line of each individual approach was used as a base and the distance was identified, then IF statements were used to filter each approach, with this process repeated for the remaining 293 approaches. Note that after each approach was filtered, the data were uploaded to Google Earth to check if they were located at approaches and not located nearby or in fields (because sometimes there are parking areas or buildings located close to the selected roundabouts as can be seen in Figure 3-9).

 Signalisation was investigated using the online mapping site Google Earth, the approaches that are signalised and located in at-grade roundabouts were all copied and pasted to a different Excel sheet, the same process was repeated for un-signalised approaches that are on at-grade roundabouts, and for signalised and un-signalised approaches that are located on grade-separated roundabouts. Note that the roundabouts were analysed according to grade separation because grade separation was used as an indicator for the later modelling. Then the relationship between driveway distance and speed was examined, in order to explore at what speed and distance away from the entry line the trucks recording HBIs.

 From the HBI spreadsheet (see Table 3-2), there is a column that indicates at what time the HBI occurred, which was used to specify peak and off-peak periods (note that based on DFT,

2015) the morning peak was defined as 7:00am to 9:00am; evening peak 4:00pm and to 6:00pm). This process was undertaken in order to see how congestion influences HBIs, and hence to compare the results with previous studies.

 Note that numbers of HBIs were counted manually from Google Earth, but from the spreadsheet that contains the filtered harsh braking data and distance for each individual approach, the number of HBIs at approaches could be counted automatically in addition to the manual count from Google Earth.