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In computer vision, cast shadows in an image frequently lead to misdetections. Preprocessing the image to remove these shadows is a common procedure that additionally loads the CPU. Consequently, the frame rate can drop under what is considered acceptable for real time detections. The study presented in this paper determines the variations of temperature in an asphalted road due to wind turbines' dynamic cast shadows and the conditions that lead to them. If the difference of temperature in the road surface between a shaded area and an irradiated one is relatively small, it will not be detected in the infrared spectrum. In these cases, the road detection will be entirely based on the infrared (thermal) spectrum, saving both the preprocessing time that would be needed to remove the shadows in the visible spectrum, and the problems in later processing as consequence of improper shadow elimination.

Thermal vision in the field of autonomous driving is frequently related to pedestrian detection [2]. The fusion of thermal and visible spectrum is well studied and implemented in satellite or aerial imagery. In [3] the infrared information is used to enhance airborne thematic mapper (ATM) data in cloud-shadowed areas. We have not found any other study in the literature that applies thermal vision to avoid the shadow-removal step.

The approach proposed in this paper neither uses supplementary tools nor relies on the uniformity of the road to perform an extrapolation. It applies an Ant Colony Optimization to detect the road using information of the margins [9]. Due to degraded road boundaries, noise in the image and occlusion, among others, variable quality in the initial segmentation of the road can be achieved. Mapping the road detection problem as an optimization one allows the algorithm to perform well under different initial segmentation conditions and for different types of roads (Figure 1). Broggi and Cattani have also used the ACO methodology to detect roads [10]. In this paper, the initial segmentation process is different from the one they propose and the motion rule of the agents has been simplified, not implementing the backtracking process. Moreover, in the algorithm presented in this paper the offline pheromone contribution is influenced by a parameter proportional to the distance between the last pixel of the solution and the attraction point. The method has been generalized to indistinctly work with infrared and visible input images.

Cast shadows on the road cool the surface. If the shadow is static enough, the temperature of the shaded area starts to decrease, so a gradient of temperature between this area and a contiguous one that is irradiated by the sun appears. When this gradient surpasses certain value, the shadow is detected by both the visible and the thermal-based vision system as an obstacle. On the other hand, if the shadow is dynamic (as the ones cast by the wind turbines) there is less time for the asphalt to cool, so the gradient of temperature remains small.

In their periodic movement, the shadows of the wind turbine blades cool the surface of the asphalt in the whole area A (m2) of the projection of the circle described by them. Let us call this the projection area. Given a direct insolation measurement Id(wm2), the amount of direct insolation that effectively reaches A is given by equation 4:

As mentioned earlier, when a wind turbine spins, the reduction of irradiation distributes homogenously in the projection area. Two different situations must be taken into account in order to study the temperature gradients. On the one hand, when the wind turbine blades spinning speed is above a certain threshold, the individual cast shadows of the blades do not generate a temperature gradient detectable by the thermal camera, but they go on contributing to the cooling of the projection area. In Section 5, some results concerning the study of the gradient of temperature that appears between the projection area and the contiguous one is carried out. On the other hand, when the spinning speed is low, individual blades cast shadows generating a temperature gradient that is detected by the thermal camera because there is more time for the asphalt to cool. In Section 5 a spinning speed threshold for which a detectable gradient appears is established.

The time needed for the shaded asphalt to cool 1 C is T1c (sec). Given a blade shadow width l (m), there is a spinning speed w1c(radsec) for which the shadows remain in the same place of the road the necessary time to cool it beneath a temperature which can be detected by the thermal camera. If r is the blade length, then the perimeter of the wind turbine is:

Due to the windy nature of the environment where the prototype is going to navigate, it is frequent for dust to partially cover the road, making it highly difficult to achieve a proper road detection. If the asphalt under the dust is warm enough, the temperature of the road will be considerably higher than the temperature of the margins. In these cases, the road can be detected by its temperature rather than by its visible borders. In certain illumination conditions, for example when facing the sun during dawn, the video sensor saturates, making it very difficult to achieve a proper road detection. In these situations the thermal vision may be used to complement the poor detection achieved when using the visible spectrum. Of course, this is valid when the temperature of the road is different than the temperature of the margins, in Figure 8 it is shown an example of the contrary case. This implies that the thermal images based detection will perform much better on sunny, warm days and, of course, during daytime. What is more, there are road stretches where the temperature measurements are very heterogeneous due to patches of different materials. In these zones it is easier to achieve a good detection via the visible spectrum.

where z represents the range of temperature in a scene, in other words, the difference between the highest and the lowest temperatures detected. This range can be approximated by the difference between the irradiated asphalt temperature and the ambient one. d is the gradient of temperature between a shaded area and a non shaded one. When the ratio is big, the temperature gradient will be more probably detected and vice versa.

Because z is variable, an absolute threshold for d can not be defined. Instead of that, it can be designed as a percentage of z. If the variation of temperature between shaded and non shaded areas is a 5.5% or greater of the maximum variation in the scene, it will be detected in the thermal image preprocessing step. The obtained threshold can not be applied to the study as it is, though. In real road scenes, heat transfer occurs between shaded and non shaded areas in proximity. From the thermal vision point of view, given an Euclidean distance in pixels between two points in the image, the camera assigns a color gradient that depends on its detectability, as previously seen. However, the same temperature gradient on the road may reflect on different pixels sets on the image depending on the perspective in which the scene is captured, thus appearing sharper or smoother color gradients. That means that for a low range of detectability values, there is an uncertainty of the gradient being effectively detected. With this in mind, some tests were performed. On these tests, shaded and non-shaded patches of asphalt in proximity were recorded by the thermal camera. Empirical results show that, for relatively long road patches, it is needed a difference of at least 15% of the maximum temperature variation in the scene for being detected, as shown in Figure 11. ff782bc1db