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Federal Highway Administration Research and Technology
Coordinating, Developing, and Delivering Highway Transportation Innovations

Report
This report is an archived publication and may contain dated technical, contact, and link information
Publication Number: FHWA-HRT-04-147
Date: December 2005

Enhanced Night Visibility Series, Volume XVI: Phase III—Characterization of Experimental Objects

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Figure 1. Diagram. Bird’s-eye view of HID 1 beam pattern. The isocandela diagram shows the lighting footprint of the HID 1 headlamps from an overhead vantage point; the footprint is overlaid on a graph marked off in feet. One foot equals 0.305 meter. The X-axis marks the forward lighting range in feet, and the Y-axis marks the side-to-side lighting range in feet. The peak range of the forward lighting pattern is at X equals about 165 feet (at Y equals 10 feet to the right of the vehicle’s center axis). The maximum illumination distance to the left side of the vehicle is just over Y equals 20 feet (at a forward distance from X equals around 20 to 60 feet). The maximum illumination distance to the right side of the vehicle is also just over Y equals 20 (at a forward distance from X equals around 20 to 60 feet). The illumination levels increase evenly in roughly concentric areas of intensity from the maximum illumination distance back to the light source. Back to Figure 1.

Figure 2. Diagram. Forward beam pattern of HID 1. The isocandela diagram shows the forward lighting footprint of the HID 1 headlamps from the vantage point of the driver; the footprint is overlaid on a graph marked off in degrees. The X-axis marks the side-to-side lighting range in degrees (negative values to the left of the vehicle’s center axis), and the Y-axis marks the vertical lighting range in degrees (negative values at levels below headlamp level). The maximum illumination distance to the left side of the vehicle is at around X equals negative 28 degrees (which occurs at Y equals negative 5 degrees, below the headlamp level). The maximum illumination distance to the right side of the vehicle is at around X equals 31 degrees (which occurs at around Y equals negative 2 degrees, below the headlamp level). The approximate vertical illumination range is from Y equals 0 degrees (at headlamp level) to Y equals negative 9 degrees (below headlamp level). This maximum range occurs at the midpoint of the vehicle (at X equals 0 degrees). The illumination levels increase evenly in roughly concentric areas of intensity from the maximum illumination distance back to the light source. Back to Figure 2.

Figure 3. Diagram. Bird’s-eye view of HID 2 beam pattern. The isocandela diagram shows the lighting footprint of the HID 2 headlamps from an overhead vantage point; the footprint is overlaid on a graph marked off in feet. The X-axis marks the forward lighting range (starting at around 19 feet), and the Y-axis marks the side-to-side lighting range in feet. The peak range of the forward lighting pattern is around X equals 148 feet (at Y equals 5 feet to the right of the vehicle center axis). The maximum illumination distance to the left side of the vehicle is at around Y equals 25 feet (at a forward distance from X equals around 60 to 75 feet). The maximum illumination distance to the right side of the vehicle is at around Y equals 34 feet (at a forward distance from X equals around 65 to 80 feet). The illumination levels increase evenly in roughly concentric areas of intensity from the maximum illumination distance back to the light source. Back to Figure 3.

Figure 4. Diagram. Forward beam pattern of HID 2. The isocandela diagram shows the forward lighting footprint of the HID 2 headlamps from the vantage point of the driver; the footprint is overlaid on a graph marked off in degrees. The X-axis marks the side-to-side lighting range in degrees (negative values to the left of the vehicle’s center axis), and the Y-axis marks the vertical lighting range in degrees (negative values at levels below headlamp level). The maximum illumination angles to the left and right side of the vehicle are both greater than 45 degrees. (The graph’s negative and positive X-value limits are 45 degrees.) The vertical illumination range is from about Y equals positive 2 degrees (above headlamp level) to lower than Y equals negative 10 degrees (below headlamp level), which is the negative limit of the Y-values on the graph. The maximum vertical value Y equals positive 2 degrees occurs at about 6 to 13 degrees to the right of the vehicle’s center axis. In general, the maximum vertical value occurs close to the vehicle’s center axis and falls steadily to below negative 10 degrees, both for the right and left sides of the graph. The illumination levels increase evenly in roughly concentric areas of intensity from the maximum illumination distance back to the light source. Back to Figure 4.

Figure 5. Photo. Object: pedestrian, black clothing, left. This photo shows a pedestrian wearing black scrubs standing on the left side of the road taken from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just outside the far lane boundary on a straight segment of roadway. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 5.

Figure 6. Photo. Object: pedestrian, black clothing, right. This photo shows a pedestrian wearing black scrubs standing on the right side of the road taken from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just to the right of the participant’s right-hand lane boundary on a straight segment of roadway. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 6.

Figure 7. Photo. Object: pedestrian, denim clothing, left. This photo shows a pedestrian wearing blue denim scrubs standing on the left side of the road taken from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just outside the far lane boundary on a straight segment of roadway. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 7.

Figure 8. Photo. Object: pedestrian, denim clothing, right. This photo shows a pedestrian wearing blue denim scrubs standing on the right side of the road as viewed from the participant vehicle in daylight. The pedestrian is standing just to the right of the participant’s right-hand lane boundary on a straight segment of roadway. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 8.

Figure 9. Photo. Object: pedestrian in left turn, left side. This photo shows a pedestrian wearing blue denim scrubs standing in a left-hand curve on the left side of the road from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just outside the far lane boundary. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 9.

Figure 10. Photo. Object: pedestrian in left turn, right side. This photo shows a pedestrian wearing blue denim scrubs standing in a left-hand curve on the right side of the road as viewed from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just to the right of the participant’s right-hand lane boundary. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 10.

Figure 11. Photo. Object: pedestrian in right turn, left side. This photo shows a pedestrian wearing blue denim scrubs standing in a right-hand curve and on the left side of the road as viewed from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just outside the far lane boundary. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 11.

Figure 12. Photo. Object: pedestrian in right turn, right side. This photo shows a pedestrian wearing blue denim scrubs standing in a right-hand curve and on the right side of the road as viewed from the perspective of the participant’s vehicle in daylight. The pedestrian is standing just to the right of the participant’s right-hand lane boundary. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 12.

Figure 13. Photo. Object: far off axis, left. This photo shows a pedestrian wearing blue denim scrubs standing on the outside edge of the left shoulder of the road as viewed from the perspective of the participant’s vehicle in daylight. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 13.

Figure 14. Photo. Object: far off axis, right. This photo shows a pedestrian wearing blue denim scrubs standing past the outside of the right shoulder as viewed from the perspective of the participant’s vehicle in daylight. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 14.

Figure 15. Photo. Object: bloom object, left. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows a vehicle parked in the oncoming lane. The parked vehicle has its headlamps on. A pedestrian wearing blue denim scrubs is standing on the left side of the road just outside the far lane boundary and in line with the rear wheels of the parked vehicle. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 15.

Figure 16. Photo. Object: bloom object, right. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows a vehicle parked in the oncoming lane. The vehicle has its headlamps on. A pedestrian wearing blue denim scrubs is standing on the right side of the road just to the right of the participant’s right-hand lane boundary and in line with the rear wheels of the parked vehicle. The pedestrian is standing with arms down to the side and facing the oncoming test vehicle. Back to Figure 16.

Figure 17. Photo. Object: dog. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows a dog mockup placed on the centerline that divides the two lanes; the dog’s head is facing the participant’s lane of travel. Back to Figure 17.

Figure 18. Photo. Object: pavement marking turn arrow. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows a left turn arrow made of retroreflective pavement tape placed in the center of the participant’s lane of travel. Back to Figure 18.

Figure 19. Photo. Object: Raised retroreflective pavement markers. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows two raised retroreflective pavement markers placed on the road, one before and one after a skip mark. The raised retroreflective pavement markers are placed with the white, reflective side facing the oncoming test vehicle. Back to Figure 19.

Figure 20. Photo. Object: sign. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows yield and speed limit signs placed to the right of the participant’s right-hand lane boundary. Signs are placed with the planes of the signs perpendicular to the lane of travel. Back to Figure 20.

Figure 21. Photo. Object: tire tread. This photo is taken in daylight from the perspective of the participant’s vehicle. It shows a tire tread centered on the right boundary line of the participant’s lane of travel.
Back to Figure 21.

Figure 22. Photo. Measurement regions for pedestrians. The image is a grayscale output of the CCD photometer. The image is a view of the roadway. A pedestrian is visible outside of the right edge line. A red outline traces the pedestrian’s body. The full outline is reproduced to the pedestrian’s immediate left and right; the upper quarter of the outline is reproduced immediately above the pedestrian, and the lower quarter is reproduced below the pedestrian. Back to Figure 22.

Figure 23. Photo. Measurement regions for the tire tread. The image is a grayscale output of the CCD photometer. The image is a view of the roadway. A tire tread is visible on the right edge line. A red outline traces the rectangular area just around the tire tread. The outline is reproduced immediately above, below, to the left, and to the right of the tire tread. Back to Figure 23.

Figure 24. Photo. CCD photometer in experimental vehicle, side view. The photo shows the front seat of the experimental vehicle from outside the opened driver’s-side door. The CCD photometer is aimed forward out the front windshield, and it is mounted on a tripod that rests on the driver’s seat. Back to Figure 24.

Figure 25. Photo. CCD photometer in experimental vehicle, front view. The photo shows the front windshield from the hood of the experimental vehicle. The CCD photometer is in the driver’s seat, and it is aimed forward out the windshield. Back to Figure 25.

Figure 26. Photo. Headlamp testing rack. This photo shows a testing rack with experimental headlamps attached to the front of a sport utility vehicle. Back to Figure 26.

Figure 27. Diagram. Locations of objects in experiment. The diagram shows the entire roadway course of the Smart Road, where participants drove during the IR Clear study. The road is depicted as being fairly straight with one gradual curve toward the top. There is a turnaround loop at each end of the road and two turnarounds in the middle, labeled Turn 2 and Turn 3. The top turnaround is in the upper left corner of the diagram and the bottom turnaround is in the lower right corner, indicating that there is a grade. There are eleven arrows along the side of the road indicating the eleven locations where objects were presented, all on the same side of the road. From the top to the bottom of the road, there are two locations at the top turnaround, four locations following turnaround 2, three locations around turnaround 3, and two locations near the bottom turnaround of the road. Back to Figure 27.

Figure 28. Equation. Contrast calculation. C equals uppercase L subscript Object minus uppercase L subscript Background, that difference divided by uppercase L subscript Background. Back to Figure 28.

Figure 29. Equation. Basic delta uppercase L subscript threshold calculation. Luminance difference subscript lowercase th equals lowercase k times the following sum squared: the quotient of phi to the one-half power divided by alpha, that quotient plus uppercase L to the one-half power. Back to Figure 29.

Figure 30. Equation. Time factor calculation. Uppercase TF equals the quotient of the following: the sum of function lowercase a of alpha and uppercase L subscript uppercase B, that function plus lowercase t, that sum divided by lowercase t. Back to Figure 30.

Figure 31. Equation. Age factor calculation. Uppercase AF equals the following: Age minus lowercase a, that difference squared, that product divided by lowercase b, that quotient plus lowercase c.
Back to Figure 31.

Figure 32. Equation. Complete delta uppercase L subscript threshold model calculation. Luminance difference subscript lowercase th equals lowercase k multiplied by the following sum squared: the quotient of phi to the one-half power divided by alpha, that quotient plus uppercase L to the one-half power. That sum squared multiplied by lowercase k, uppercase TF, uppercase F subscript uppercase CP, and uppercase AF.
Back to Figure 32.

Figure 33. Equation. Visibility level calculation. Uppercase VL equals the quotient of delta uppercase L subscript Actual divided by delta uppercase L subscript Threshold, which is equal to the quotient of the difference of uppercase L subscript Object minus uppercase L subscript Background, that difference divided by delta uppercase L subscript Threshold, which is equal to the quotient of uppercase C subscript Actual divided by uppercase C subscript Threshold. Back to Figure 33.

Figure 34. Bar graph. Comparison of object luminance at detection and recognition of pedestrian objects. The graph is titled “Pedestrian Luminance at Detection and Recognition for VIS Systems.” The Y-axis is labeled “Object Luminance (candela per square meter).” The X-axis is labeled “Object and Headlamp,” and it is divided into the 12 pedestrian objects. Each pedestrian object is further divided into the three visible-light vision enhancement systems: HID 1, HID 2, and HLB. Each VES has two bars, one for detection and one for recognition. For the black-clothed, blue-clothed, and bloom pedestrians, standard error bars are present. The graph shows that the object luminance values at detection and recognition are very similar, especially given the large standard errors of black-clothed, blue-clothed, and bloom pedestrians. Back to Figure 34.

Figure 35. Bar graph. Comparison of object luminance at detection and recognition of retroreflective objects. The graph is titled “Retroreflective Object Luminance at Detection and Recognition for VIS Systems.” The Y-axis is labeled “Object Luminance (candela per square meter).” The X-axis is labeled “Object and Headlamp,” and it is divided into the four retroreflective objects: arrow, retroreflective pavement marker, sign 1, and sign 2. Each retroreflective object is further divided into the three visible-light VESs: HID 1, HID 2, and HLB. Each VES has two bars, one for detection and one for recognition. For each bar, a standard error bar is present. The graph shows that the object luminance values at detection and recognition are very similar, with the standard error bars of each pair overlapping. All object luminance values are below 0.6 candela per square meter except for HID 1 and HID 2 for the retroreflective pavement markers, HLB for sign 1, and HLB for sign 2, whose object luminance values range from about 1.1 to 2.2 candela per square meter.
Back to Figure 35.

Figure 36. Bar graph. Comparison of object luminance at detection and recognition of obstacle objects. The graph is titled “Obstacle Object Luminance at Detection and Recognition for VIS Systems.” The Y-axis is labeled “Object Luminance (candela per square meter).” The X-axis is labeled “Object and Headlamp” and is divided into the two obstacle objects: dog and tire. Each obstacle object is further divided into the three visible-light VESs: HID 1, HID 2, and HLB. Each VES has two bars, one for detection and one for recognition. For each bar, a standard error bar is present. The graph shows that the object luminance values at detection and recognition are very similar, with the standard error bars of each pair overlapping. All object luminance values are below 0.5 candela per square meter except for HID 2 for the dog, whose object luminance values are just below 1.5 candela per square meter for detection and about 3.2 candela per square meter for recognition (though their standard errors overlap). Back to Figure 36.

Figure 37. Bar graph. Mean luminance values at pedestrian object detection. The graph is titled “Pedestrian Luminance at Detection for VIS Systems.” The Y-axis is labeled “Luminance (candela per square meter).” The X-axis is labeled “Pedestrian,” and it is divided into the twelve pedestrian objects. Each pedestrian has three bars: HID 1, HID 2, and HLB. For the black-clothed, blue-clothed, and bloom pedestrians, standard error bars are present. The range of object luminance for HID 1 is from 0.025 candela per square meter for the far off axis right pedestrian to just above 0.1 candela per square meter for the bloom left pedestrian. The range of object luminance for HID 2 is from just above 0 candela per square meter with the far off axis left and far off axis right pedestrians to just above 0.15 candela per square meter for the bloom left pedestrian. The range of object luminance for HLB is from 0.02 candela per square meter for the far off axis right pedestrian to 0.14 candela per square meter for the bloom right pedestrian. Standard error varies from very small (bloom left) to very large (black-clothed left). Overall, the two bloom objects required the highest luminance for detection. Back to Figure 37.

Figure 38. Bar graph. Mean background luminance values at pedestrian object detection. The graph is titled “Pedestrian Background Luminance at Detection for VIS Systems.” The Y-axis is labeled “Background Luminance (candela per square meter).” The X-axis is labeled “Pedestrian” and is divided into the twelve pedestrian objects. Each pedestrian has three bars: HID 1, HID 2, and HLB. For the black-clothed, blue-clothed, and bloom pedestrians, standard error bars are present. The range of background luminance for HID 1 is from 0.015 candela per square meter for the far off axis right pedestrian to 0.055 candela per square meter for the black-clothed left pedestrian. The range of background luminance for HID 2 is from just above 0 candela per square meter with the far off axis left and far off axis right pedestrians to 0.09 candela per square meter for the bloom right pedestrian. The range of background luminance for HLB is from 0.007 candela per square meter for the far off axis right pedestrian to 0.097 candela per square meter for the bloom right pedestrian. Standard error varies from very small (black-clothed right pedestrian) to very large (bloom right pedestrian). Overall, the two bloom objects had the highest background luminance at detection.
Back to Figure 38.

Figure 39. Bar graph. Mean contrast values at pedestrian object detection. The graph is titled “Pedestrian Contrast at Detection for VIS Systems.” The Y-axis is labeled “Contrast.” The X-axis is labeled “Pedestrian,” and it is divided into the twelve pedestrian objects. Each pedestrian has three bars: HID 1, HID 2, and HLB. For the black-clothed, blue-clothed, and bloom pedestrians, standard error bars are present. The range of contrast for HID 1 is from minus 0.1 for the black-clothed left pedestrian to positive 2.45 for the bloom left pedestrian. The range of contrast for HID 2 is from positive 0.4 with the blue-clothed right pedestrian to positive 2.75 for the bloom left pedestrian. The range of contrast for HLB is from positive 0.8 for the bloom left pedestrian to positive 2.8 for the far off axis right pedestrian. Standard error varies from very small (blue-clothed left pedestrian) to fairly large (bloom left pedestrian). Back to Figure 39.

Figure 40. Bar graph. Older driver mean visibility levels at pedestrian object detection. The graph is titled “Pedestrian Visibility Level at Detection for VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Pedestrian,” and it is divided into the twelve pedestrian objects. Each pedestrian has three bars: HID 1, HID 2, and HLB. For the black-clothed, blue-clothed, and bloom pedestrians, standard error bars are present. The range of visibility level for HID 1 is from just above 0 for the black-clothed left pedestrian to just above 12 for the bloom left pedestrian and right turn, left pedestrian. The range of visibility level for HID 2 is from 1 with the far off axis left pedestrian to 22 for the bloom left pedestrian. The range of visibility level for HLB is from 2.5 for the bloom left pedestrian to 17.5 for the left turn, left pedestrian. Standard error varies from very small (black-clothed left pedestrian) to fairly large (bloom left pedestrian). Back to Figure 40.

Figure 41. Picture. Right turn right pedestrian in HID 2 condition. The image shows a pedestrian standing just to the right of the right-hand road edgeline in a right-hand turn. The pedestrian is facing the camera and standing with arms down to the side. The bottom half of the pedestrian is lit, and the upper half is not lit. Back to Figure 41.

Figure 42. Picture. Right turn right pedestrian in HLB condition. The image shows a pedestrian standing just to the right of the right-hand road edgeline in a right-hand turn. The pedestrian is facing the camera and standing with arms down to the side. The entire pedestrian is lit from top to bottom. Back to Figure 42.

Figure 43. Bar graph. Mean luminance values at obstacle object detection. The graph is titled “Obstacle Object Luminance at Detection for VIS Systems.” The Y-axis is labeled “Luminance (candela per square meter).” The X-axis is labeled “Obstacle Object,” and it is divided into the two obstacle objects: dog and tire. Each obstacle object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. The object luminance values for the dog are: 0.2 for HID 1, just below 1.5 for HID 2, and 0.45 for HLB. The object luminance values for the tire are: 0.1 for HID 1, 0.25 for HID 2, and 0.1 for HLB. Standard error varies from very small (HID 1) to very large (HID 2). Back to Figure 43.

Figure 44. Bar graph. Mean background luminance values at obstacle object detection. The graph is titled “Obstacle Object Background Luminance at Detection for VIS Systems.” The Y-axis is labeled “Background Luminance (candela per square meter).” The X-axis is labeled “Obstacle Object,” and it is divided into the two obstacle objects: dog and tire. Each obstacle object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. The background luminance values for the dog are: just below 0.1 for HID 1, 6.5 for HID 2, and 0.13 for HLB. The object luminance values for the tire are: 0.13 for HID 1, 0.3 for HID 2, and 0.13 for HLB. Standard error varies from very small (HID 1) to very large (HID 2). Back to Figure 44.

Figure 45. Bar graph. Mean contrast values at obstacle object detection. The graph is titled “Obstacle Object Contrast at Detection for VIS Systems.” The Y-axis is labeled “Contrast.” The X-axis is labeled “Obstacle Object,” and it is divided into the two obstacle objects: dog and tire. Each obstacle object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. The contrast values for the dog are: positive 1.25 for HID 1, positive 1 for HID 2, and positive 2.8 for HLB. The contrast values for the tire are: negative 0.1 for HID 1, negative 0.25 for HID 2, and positive 0.07 for HLB. Standard error varies from very small (HID 1) to fairly large (HLB). Back to Figure 45.

Figure 46. Bar graph. Older driver mean visibility levels at obstacle object detection. The graph is titled “Obstacle Object Visibility Level at Detection for VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Obstacle Object,” and it is divided into the two obstacle objects: dog and tire. Each obstacle object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. The visibility level values for the dog are: 3.2 for HID 1, 2.9 for HID 2, and 8 for HLB. The visibility level values for the tire are: just above 0 for HID 1, 1.5 for HID 2, and 0.3 for HLB. Standard error varies from very small (tire) to fairly large (dog). Back to Figure 46.

Figure 47. Bar graph. Mean luminance values at retroreflective object detection. The graph is titled “Retroreflective Object Luminance at Detection for VIS Systems.” The Y-axis is labeled “Luminance (candela per square meter).” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects: turn arrow, retroreflective pavement markers, sign 1, and sign 2. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Object luminance values for HID 1 range from 0.2 with sign 1 to 1.7 with retroreflective pavement marker. Object luminance values for HID 2 range from 0.1 with sign 1 to 1.1 with retroreflective pavement marker. Object luminance values for HLB range from 0.2 with RRPM to 2.2 with sign 1. Standard error varies from very small (turn arrow) to very large (RRPM). Back to Figure 47.

Figure 48. Bar graph. Mean luminance values at retroreflective object recognition. The graph is titled “Retroreflective Object Luminance at Recognition for VIS Systems.” The Y-axis is labeled “Luminance (candela per square meter).” The X-axis is labeled “Retroreflective Object” and is divided into the four retroreflective objects-turn arrow, retroreflective pavement markers, sign 1, and sign 2-as well as two additional categories: Recognition 30/55 and Recognition stop/yield. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. All object luminance values are below 3 candela per square meter except for HID 1 with Recognition 30/55 (21 candela per square meter), HLB with Recognition 30/55 (93 candela per square meter), and HLB with Recognition stop/yield (9 candela per square meter). Standard errors are all very small with the exception of Recognition 30/55 for HID 1 and HLB. Back to Figure 48.

Figure 49. Bar graph. Mean background luminance values at retroreflective object detection. The graph is titled “Retroreflective Object Background Luminance at Detection for VIS Systems.” The Y-axis is labeled “Background Luminance (candela per square meter).” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects: turn arrow, retroreflective pavement markers, sign 1, and sign 2. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Background luminance values for HID 1 range from about 0.025 candela per square meter with the retroreflective pavement markers, sign 1, and sign 2 to 0.165 candela per square meter with the turn arrow. Background luminance values for HID 2 range from about 0.025 candela per square meter with sign 1 to 0.075 candela per square meter with the turn arrow. Background luminance values for HLB range from 0.035 with retroreflective pavement markers to 0.24 with sign 1. Standard error varies widely. Back to Figure 49.

Figure 50. Bar graph. Mean background luminance values at retroreflective object recognition. The graph is titled “Retroreflective Object Background Luminance at Recognition for VIS Systems.” The Y-axis is labeled “Background Luminance (candela per square meter).” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects-turn arrow, retroreflective pavement markers, sign 1, and sign 2-as well as two additional categories: Recognition 30/55 and Recognition stop/yield. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Background luminance values for HID 1 range from about 0.25 candela per square meter with all objects except the turn arrow and Recognition 30/55 to 0.17 candela per square meter with the turn arrow. Background luminance values for HID 2 range from about 0.03 candela per square meter with sign 1 and the retroreflective pavement markers to 0.14 candela per square meter with Recognition stop/yield. Background luminance values for HLB range from 0.03 with sign 1 to 0.52 with Recognition stop/yield. Standard error varies widely. Back to Figure 50.

Figure 51. Bar graph. Mean contrast values at retroreflective object detection. The graph is titled “Retroreflective Object Contrast at Detection for VIS Systems.” The Y-axis is labeled “Contrast.” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects: turn arrow, retroreflective pavement markers, sign 1, and sign 2. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Contrast values for HID 1 range from about 1 with the turn arrow to 51 with the retroreflective pavement markers. Contrast values for HID 2 range from about 1 with the turn arrow to 25 with the retroreflective pavement markers. Contrast values for HLB range from about 1 with the turn arrow to 17 with sign 2. Standard error varies widely. Back to Figure 51.

Figure 52. Bar graph. Mean contrast values at retroreflective object recognition. The graph is titled “Retroreflective Object Contrast at Recognition for VIS Systems.” The Y-axis is labeled “Contrast.” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects-turn arrow, retroreflective pavement markers, sign 1, and sign 2-as well as two additional categories: Recognition 30/55 and Recognition stop/yield. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Contrast values for HID 1 range from about 0 with the turn arrow to about 150 with the Recognition 30/55. Contrast values for HID 2 range from about 0 with the turn arrow to about 45 with the Recognition 30/55. Contrast values for HLB range from about 0 with the turn arrow to about 270 with Recognition 30/55. Standard error varies widely. Back to Figure 52.

Figure 53. Bar graph. Older driver mean visibility levels at retroreflective object detection. The graph is titled “Retroreflective Object Visibility Level at Detection for VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects: turn arrow, retroreflective pavement markers, sign 1, and sign 2. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Visibility level values for HID 1 range from about 1 with the turn arrow and retroreflective pavement markers to 28 with sign 2. Visibility level values for HID 2 range from about 1 with the turn arrow and retroreflective pavement markers to 4 with sign 2. Visibility level values for HLB range from about 1 with the turn arrow and retroreflective pavement markers to 100 with sign 1. Standard error varies widely. Back to Figure 53.

Figure 54. Bar graph. Older driver mean visibility levels at retroreflective object recognition. The graph is titled “Retroreflective Object Visibility Level at Recognition for VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects-turn arrow, retroreflective pavement markers, sign 1, and sign 2-as well as two additional categories: Recognition 30/55 and Recognition stop/yield. Each retroreflective object has three bars: HID 1, HID 2, and HLB. For each bar, standard error bars are present. Visibility level values for HID 1 range from about 1 with the turn arrow and retroreflective pavement markers to 28 with sign 2. Visibility level values for all objects are below 200 except for HID 1 with Recognition 30/55 (just under 2,000) and HLB with Recognition 30/55 (about 4,700). Standard error varies widely. Back to Figure 54.

Figure 55. Bar graph. Comparison of older driver mean visibility levels at pedestrian object detection with the IR system versus the VIS systems. The graph is titled “Pedestrian Visibility Level at Detection for IR and VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Pedestrian,” and it is divided into the 12 pedestrian objects. Each pedestrian has four bars: FIR, NIR 1, NIR 2, and VIS. For each bar, standard error bars are present. Visibility level values for FIR are nearly zero for all pedestrians except the left turn left pedestrian (39), left turn right pedestrian (2), and right turn right pedestrian (1). Visibility levels for NIR 1 range between 0 and 3 for all pedestrians. Visibility levels for NIR 2 are between 0 and 11. Visibility levels for the VIS systems range from 2 to 12. Visibility level values for the IR systems are all lower than the VIS visibility levels except for the left turn left pedestrian. Here, FIR has a visibility level of 39, NIR 1 has a visibility level of 0, NIR 2 has a visibility level of 11, and VIS has a visibility level of 9. Standard error varies widely. Back to Figure 55.

Figure 56. Bar graph. Comparison of older driver mean visibility levels at obstacle object detection with the IR systems versus the VIS systems. The graph is titled “Obstacle Object Visibility Level at Detection for IR and VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Obstacle Object,” and it is divided into the two obstacle objects: dog and tire. Each object has four bars: FIR, NIR 1, NIR 2, and VIS. For each bar, standard error bars are present. Visibility level values for the dog are 1.4 for FIR, 4.3 for NIR 1, 5.7 for NIR 2, and 4.7 for VIS systems. The standard errors for NIR 1, NIR 2, and VIS all overlap, and the standard errors for FIR and NIR 1 overlap. Visibility levels for the tire are 1.6 for FIR, 0.1 for NIR 1, 0.2 for NIR 2, and 0.6 for VISs. All standard errors appear to overlap. Back to Figure 56.

Figure 57. Bar graph. Comparison of older driver mean visibility levels at retroreflective object detection with the IR systems versus the VIS systems. The graph is titled “Retroreflective Object Visibility Level at Detection for IR and VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Retroreflective Object,” and it is divided into the four retroreflective objects: arrow, retroreflective pavement markers, sign 1, and sign 2. Each object has four bars: FIR, NIR 1, NIR 2, and VIS. For each bar, standard error bars are present. Visibility levels for the arrow and retroreflective pavement markers are all below 4. For sign 1, visibility levels are 10 for FIR, 53 for NIR 1, 10 for NIR 2, and 37 for VIS. For sign 2, visibility levels are 15 for FIR, 24 for NIR 1, 9 for NIR 2, and 36 for VIS. Standard errors all either overlap or come close to doing so, except for FIR and VIS as well as NIR 2 and VIS for sign 2. Standard errors for FIR and VIS also for sign 1 also do not overlap. Back to Figure 57.

Figure 58. Bar graph. Comparison of older driver mean visibility levels at sign recognition for the IR systems versus the VIS systems. The graph is titled “Sign Visibility Level at Recognition for IR and VIS Systems.” The Y-axis is labeled “Visibility Level.” The X-axis is labeled “Sign Object,” and it is divided into the two sign recognition tasks: Recognition 30/55 and Recognition Stop/Yield. Each object has four bars: FIR, NIR 1, NIR 2, and VIS. For each bar, standard error bars are present. Visibility levels for the Recognition 30/55 task are 500 for FIR, just over 1,000 for NIR 1, just under 500 for NIR 2, and about 2,250 for VIS. The standard errors of FIR and NIR 2 overlap. Visibility levels for the Recognition Stop/Yield task are about 100 for FIR, NIR 2, and VIS (standard errors overlap) and over 400 for NIR 1. Back to Figure 58.

Figure 59. Line graph. Age comparison for detection of pedestrians. The graph is titled “Age Comparison.” The Y-axis is labeled “Percentage of Young Performance.” The X-axis is labeled “Age Group,” and it is divided into young, middle, and old. There are three data series: model, IR, and VIS. VIS has the highest percentage of young performance, descending from 100 percent to about 94 percent with middle and about 71 percent with older. The IR data series is below the VIS line, going from 100 percent with young to about 81 percent with middle to about 62 percent with older. The model data series is beneath the IR line, going from 100 percent with young to about 72 percent with middle to about 36 percent with older. Back to Figure 59.

 

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