Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter.
Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.
Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.
OCR for page 59
59
30
Speed (m/s)
25
20
15
-10 -5 0 5
30
Speed (m/s)
25
20
15
-10 -5 0 5
Tim e (s)
Figure 7.5. Speed profile: (top graph) with missing data; (bottom
graph) after performing linear interpolation.
(i.e., using range values in the "VORAD1_Range_1" range environmental, traffic, and weather data. Valid and accurate
calculations), erroneous variable computations would result, time and location variables should be available for researchers
as shown in Figure 7.6. After applying the algorithm, correct to complete the linkage. As described in earlier reports, most
target variables are identified. studies had GPS data recorded in their data sets. In Project 6,
A critical postprocessing data issue that one must address however, the local computer clocks without synchronization
is the linking of the in-vehicle data with other data, including were used instead of GPS time, resulting in time errors. These
errors deem synchronization infeasible.
Table 7.1. Rain Gauge Measurements
Rain Gauge Measurements Rain Gauge Measurements Video Data
(invalid values), mm (invalid values removed), mm
During the extensive naturalistic driving data collection
8.382 8.382 period, it was not unusual to have technical difficulties in
196.088 8.382 cameras, including disconnection of cables and malfunction
196.088 8.382
of cameras. Special supervision is needed to ensure smoother
data collection and reduction.
196.088 8.382
Each study set up videos with varied views for its particu-
196.088 8.382 lar research goal. VTTI studies usually have four cameras cap-
8.382 8.382 turing the front view, side views (left and right), and driver's
8.382 8.382
Table 7.3. Example Illustration of Radar
Target Tracking
Table 7.2. GPS Imported Data (Null Values)
VORAD_ID VORAD1_Range (Ft)
GPS Date Time Time
(with null values) GPS Date Time (corrected) Step (s) 1 2 3 1 2 3
`2007-06-22 06:30:39.617' `2007-06-22 06:30:39.617' -0.6 231 248 247 50.1 370.1 212.2
`2007-06-22 06:30:39.617' `2007-06-22 06:30:39.617' -0.5 231 248 247 49.5 363.4 205.8
Null `2007-06-22 06:30:39.617' -0.4 248 231 247 354.5 49.6 193.1
`2007-06-22 06:30:39.617' `2007-06-22 06:30:39.617' -0.3 247 231 248 186.7 49.6 344.5
`2007-06-22 06:30:39.617' `2007-06-22 06:30:39.617' -0.2 247 248 231 173.9 331.8 49.5
`2007-06-22 06:30:39.903' `2007-06-22 06:30:39.903' -0.1 247 231 248 165 49.3 321.8