SirenDetect. Jennifer Michelstein Department of Electrical Engineering Adviser: Professor Peter Kindlmann May 1, 2003. Alerting Drivers about Emergency Vehicles. GPS. INSIDE A CAR. BUTTONS. CALENDAR/MINI PC. INSIDE A CAR. RADIO, CD PLAYER, SPEAKERS. PHONE WITH BUTTONS IN STEERING WHEEL.
Department of Electrical Engineering
Adviser: Professor Peter Kindlmann
May 1, 2003
Alerting Drivers about Emergency Vehicles
Added features = Less attention to the road and other vehicles.
Driving has become perilous.
The FFT is an algorithm that “reduces the number of computations from something on the order of N02 to N0 log N0.”*
105 – 180 Hz
370 - 430 Hz
220 – 300 Hz
n - order of the filter
Wn - the two-element vector Wn = [f1, f2] where f1, f2 are the limits of the passband, scaled from 0 to 1
[b,a] - filtering coefficients
By experiment, n1 = n2 = 8; n3 = 6.
2. Construct filters in parallel; pass siren through filters.
3. Obtain peak amplitude of each key region.
4. Repeat steps 2-3 for multiple siren samples; average
amplitudes to obtain typical A1, A2, A3.
5. Run current sound sample through parallel filters; compare
resulting amplitudes to A1, A2, and A3 to determine if sample
is a siren.
Bandpass Region 1
Bandpass Region 2
Bandpass Region 3
Advantages: Simple(st), Fast(est), and Inexpensive Implementation.
Disadvantages: Inaccuracy in presence of noise, disturbances.
2. Respective Magnitude Comparisons.
Advantages: Simple, Fast, and Inexpensive; high accuracy.
Disadvantages: Robustness? Testing necessary.
3. Time Domain.
Advantages: High Accuracy.
Disadvantages: Difficult, more costly implementation.
4. Combination of 2 (Relative Magnitudes) and 3 (Time Domain).
Advantages: Greatest Accuracy.
Disadvantages: Costly and possibly redundant algorithm.
Testing various algorithms proved that comparing respective amplitudes was the ideal implementation. Adjusting thresholds after testing various siren samples made detection more reliable.
if (x13 > ??) & (x13 < ??) true2 = 1;end;if (x23 > ??) & (x23 < ??) true3 = 1;end;if (true1) & (true2) & (true3) its_a_siren=1;end;
x12 = max1 / max2;x13 = max1 / max3;x23 = max2 / max3;true1 = 0;true2 = 0;true3 = 0;its_a_siren=0;if (x12 >??) & (x12 < ??) true1 = 1;end;
Test in Laboratory Setting using microphones oriented in various directions; sirens mixed with street noises, music, etc.
SirenDetect will store a fingerprint for each of the
unique siren sounds emitted by emergency vehicles.
2. Siren Differentiation.
SirenDetect will distinguish between the siren of an
ambulance, fire truck, police car, or other emergency
vehicle. The driver will be notified of the type of car
that is approaching.
3. Directional Capabilities.
Strategic positioning of microphones will allow
SirenDetect to compare amplitudes of signals and
identify the precise location from which the emergency
vehicle is approaching.
4. Robustness Evaluation.
The system must be tested in residential areas, on highways,
in cars traveling the same direction as emergency vehicles, the
opposite direction, and at various angles (30, 45, 60, 90, etc.).
Possible hazards are the Doppler effect and noise interference.
The thresholds employed in the current code may need
slight adjustments to be comprehensive in various driving
conditions, yet should not be all-inclusive (i.e. detecting
too many noises as sirens). Efficiency - Accuracy Trade-Off.
Peter Kindlmann, Project Adviser