CS-7638 Midterm Practice Exam Newest
2026 Questions and Correct Detailed
Answers Already Graded A+
What is the importance of understanding sensor data in self-driving cars? -
CORRECT ANSWER-It is crucial for making assessments about the environment
and ensuring safe navigation.
What is the preferred Gaussian when tracking another car with a self-driving car?
- CORRECT ANSWER-The third Gaussian, as it is the most certain and
minimizes the chance of an accident.
What are the characteristics of a Gaussian distribution? - CORRECT ANSWER-
Gaussians are unimodal distributions that are symmetrical.
How do you evaluate a Gaussian with μ = 10, σ² = 4, and x = 8? - CORRECT
ANSWER-The approximate answer is 0.12.
What is the formula for the Gaussian function? - CORRECT ANSWER-The
Gaussian function is given by 1/sqrt(2*pi*sigma2) multiplied by the exponential of
-0.5(x-mu)²/sigma2.
,What value of x maximizes the Gaussian function? - CORRECT ANSWER-Setting
x to the same value as mu maximizes the function.
What are the two steps in the Kalman filter process? - CORRECT ANSWER-
Measurement updates and motion updates.
Which operation is used for measurement updates in the Kalman filter? -
CORRECT ANSWER-Products are used for measurement updates.
Which operation is used for motion updates in the Kalman filter? - CORRECT
ANSWER-Convolutions are used for motion updates.
How does Bayes Rule apply in the context of the Kalman filter? - CORRECT
ANSWER-Bayes Rule applies to measurements, while total probability applies to
motions.
What happens to the mean of a Gaussian after receiving a measurement? -
CORRECT ANSWER-The new mean shifts towards the measurement, reflecting
increased certainty.
,What is the effect of combining two Gaussians in terms of certainty? - CORRECT
ANSWER-The resulting Gaussian is more certain than either of the two
component Gaussians.
How is the new mean calculated when multiplying a prior and measurement
Gaussian? - CORRECT ANSWER-The new mean is a weighted sum of the old
means, with weights based on their variances.
What is the formula for calculating the new variance after a measurement
update? - CORRECT ANSWER-The new variance is given by σ²' = 1 / (1/σ² +
1/r²).
What is the primary function of the laser-range finder in a self-driving car? -
CORRECT ANSWER-To take distance scans 10 times a second and collect about
a million data points to spot other cars.
What additional equipment is used in self-driving cars for localization? -
CORRECT ANSWER-A stereo camera system and GPS antennas.
What is the main purpose of tracking in self-driving cars? - CORRECT ANSWER-
To understand the position and speed of other vehicles to avoid collisions.
, How do Kalman filters differ from Monte Carlo localization? - CORRECT
ANSWER-Kalman filters estimate a continuous state, while Monte Carlo
localization uses discrete places.
What type of distribution do Kalman filters produce? - CORRECT ANSWER-A
unimodal distribution.
What is the goal of using a Kalman filter in tracking? - CORRECT ANSWER-To
estimate future locations and velocities based on noisy and uncertain data.
What is a Gaussian in the context of Kalman filters? - CORRECT ANSWER-A
continuous function characterized by a mean (μ) and variance (σ²) that represents
the probability distribution of the state.
What does the area under a Gaussian curve represent? - CORRECT ANSWER-It
sums up to 1, indicating the total probability.
What are the two parameters that characterize a Gaussian? - CORRECT
ANSWER-The mean (μ) and the variance (σ²).
2026 Questions and Correct Detailed
Answers Already Graded A+
What is the importance of understanding sensor data in self-driving cars? -
CORRECT ANSWER-It is crucial for making assessments about the environment
and ensuring safe navigation.
What is the preferred Gaussian when tracking another car with a self-driving car?
- CORRECT ANSWER-The third Gaussian, as it is the most certain and
minimizes the chance of an accident.
What are the characteristics of a Gaussian distribution? - CORRECT ANSWER-
Gaussians are unimodal distributions that are symmetrical.
How do you evaluate a Gaussian with μ = 10, σ² = 4, and x = 8? - CORRECT
ANSWER-The approximate answer is 0.12.
What is the formula for the Gaussian function? - CORRECT ANSWER-The
Gaussian function is given by 1/sqrt(2*pi*sigma2) multiplied by the exponential of
-0.5(x-mu)²/sigma2.
,What value of x maximizes the Gaussian function? - CORRECT ANSWER-Setting
x to the same value as mu maximizes the function.
What are the two steps in the Kalman filter process? - CORRECT ANSWER-
Measurement updates and motion updates.
Which operation is used for measurement updates in the Kalman filter? -
CORRECT ANSWER-Products are used for measurement updates.
Which operation is used for motion updates in the Kalman filter? - CORRECT
ANSWER-Convolutions are used for motion updates.
How does Bayes Rule apply in the context of the Kalman filter? - CORRECT
ANSWER-Bayes Rule applies to measurements, while total probability applies to
motions.
What happens to the mean of a Gaussian after receiving a measurement? -
CORRECT ANSWER-The new mean shifts towards the measurement, reflecting
increased certainty.
,What is the effect of combining two Gaussians in terms of certainty? - CORRECT
ANSWER-The resulting Gaussian is more certain than either of the two
component Gaussians.
How is the new mean calculated when multiplying a prior and measurement
Gaussian? - CORRECT ANSWER-The new mean is a weighted sum of the old
means, with weights based on their variances.
What is the formula for calculating the new variance after a measurement
update? - CORRECT ANSWER-The new variance is given by σ²' = 1 / (1/σ² +
1/r²).
What is the primary function of the laser-range finder in a self-driving car? -
CORRECT ANSWER-To take distance scans 10 times a second and collect about
a million data points to spot other cars.
What additional equipment is used in self-driving cars for localization? -
CORRECT ANSWER-A stereo camera system and GPS antennas.
What is the main purpose of tracking in self-driving cars? - CORRECT ANSWER-
To understand the position and speed of other vehicles to avoid collisions.
, How do Kalman filters differ from Monte Carlo localization? - CORRECT
ANSWER-Kalman filters estimate a continuous state, while Monte Carlo
localization uses discrete places.
What type of distribution do Kalman filters produce? - CORRECT ANSWER-A
unimodal distribution.
What is the goal of using a Kalman filter in tracking? - CORRECT ANSWER-To
estimate future locations and velocities based on noisy and uncertain data.
What is a Gaussian in the context of Kalman filters? - CORRECT ANSWER-A
continuous function characterized by a mean (μ) and variance (σ²) that represents
the probability distribution of the state.
What does the area under a Gaussian curve represent? - CORRECT ANSWER-It
sums up to 1, indicating the total probability.
What are the two parameters that characterize a Gaussian? - CORRECT
ANSWER-The mean (μ) and the variance (σ²).
