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Inside DSP on Automotive Signal Processing: Street Smarts
By , 9/12/2004

Imagine getting on a bus and going for a ride on the highway—with no driver. Or imagine having your car tell you that you’re about to hit a traffic snarl and suggest an alternate route. Pretty cool, right? These applications are possible only with advanced digital signal processing—not only inside the vehicle, but outside as well.

Digital signal processing is already used outside of the car in automotive-related application areas ranging from traffic control to road maintenance. Radar speed detectors, for example, use signal-processing techniques to measure the Doppler shift of reflected signals. Signal processing is also used to measure the structural integrity of bridges through probing and analysis of the structure. And, as Figure 1 shows, automotive repair shops even highlight the “digital signal processor technology” used in some wheel-alignment equipment!
Figure 1 - A poster promoting Hunter Engineering's DSP-based wheel alignment system.
Click to Enlarge

In this article, we present an overview of two key categories of outside-the-car signal processing: intelligent transportation systems and applications based on vehicle location systems.

Intelligent Transportation Systems

Intelligent transportation systems (ITS) are comprised of technologies used in vehicles and roadways to manage and improve traffic flow. A key component of ITS lies in traffic control systems, where signal processing plays a significant role. Signal processing-based systems are used to detect cars as they approach an intersection, thus allowing the traffic control system to change the state of the traffic light as needed.

One of the most common implementations of car detection uses an inductive loop embedded under the road surface. When a car passes overhead, the car’s metallic content alters the loop inductance, and the car is detected. Other methods of car detection include radar, laser, and air-filled tubes laid out onto the road surface. These methods employ varying degrees of signal processing and analysis in order to accurately detect vehicles.

Inductive loop detectors can also form the heart of a photo-enforced traffic light. By using information from two loops that are embedded in the roadway in front of a traffic light, the system can determine when a car has passed over the loops in quick succession—which indicates that the car is not stopping. If the light is red when the car passes, the system can trigger a high-resolution digital camera to take a photo of the offending vehicle.

Researchers and transit authorities have proposed many other uses for vehicle detection technologies. For example, by placing inductive detectors at regular intervals on highways, the current travel time between points on the highway can be computed. This type of information can be distributed to drivers (for example, through the Radio Data System used in Europe or through a telephone hotline) to help reduce congestion. Recently, such traffic information has been integrated into select vehicle navigation systems in the U.S. through Sirius and XM Satellite Radio broadcasts. These systems can show traffic congestion on a map and suggest alternate routes to drivers.


In order for inductive loops to detect traffic congestion, they must be able to detect individual cars as they traverse a stretch of highway. In other words, if the same car can be identified (with high probability) as it passes over each detector, the travel time between points can be computed. Figure 2 shows an example of embedded inductive loops used to detect congestion on a highway. One proposed way to identify individual cars is to more accurately measure the change in inductance as a car passes. Cars have different shapes, lengths, and metallic content, so each car generates a unique signature. If the same inductive signature is detected by two successive loops and the elapsed time is reasonable, it is probably the same car.
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