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| Challenges | Proposed solutions |
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| Lack of structured data in all studied routes to identify pedestrians at different times of the day with different light intensities during the day and different weather conditions | Installation of devices in the desired routes to monitor the passage of pedestrians and bicycles around the clock and the use of various data mining techniques and deep learning to create patterns to identify cyclists and pedestrians in different weather conditions and different light intensities |
| Absence of any known standard for selecting appropriate and essential features from the features collected for pedestrian identification or limited features used to model pedestrian behaviors and the need to apply metaheuristic algorithms to solve complex intelligent computing problems | Using more advanced sensors in different directions or applying sensors in the car body, creating a centralized database to consolidate data collected from sources and sensors used in different places |
| Existence of noise in various images and data collected, poor quality or very low quality of some images collected by cameras installed on the road, especially in cloudy, rainy and icy weather or dark at night | Creating high-precision and high-quality sensors and cameras, installing high-quality cameras on sensitive routes, proposing new techniques for preprocessing data and images, and accurately detecting noise images |
| Lack of access to clear and uninterrupted data and images for research due to privacy | Establish protocols and standards for collecting data on public places, establish agreements and laws to protect the privacy of the public while collecting 24-hour data from all road routes |
| The complexity of the environment around the pedestrian can overshadow the operations and methods of identifying the pedestrian and her movement, and as a result, make it difficult to accurately identify the pedestrian | Develop methods to identify different perspectives on pedestrian detection and operations performed by his/her |
| Pedestrian coverage can be very effective in the process of identifying him. If the images are taken from one perspective, it can affect the accuracy of pedestrian identification and reduce the accuracy of identification | Proposing new methods by researchers to prepare multidimensional images and their simultaneous study and aggregation of the results for early identification of pedestrians, especially in cars |
| Real-time and accurate detection of objects (such as pedestrians) is an important challenge for car companies to create and develop self-driving cars | Propose methods to increase the accuracy of pedestrian detection and speed up the process of immediate response to avoid accidents when detecting obstacles and pedestrians |
| Lack of specific data to diagnose cyclists | Collect data on cyclists on different routes with different light intensities and create patterns to identify cyclists |
| The quality of the cameras, the amount of pedestrian distance from the camera can affect the performance of the proposed method and the accuracy of the method detection, which has not been considered in many studies | Define a standard for the best image quality and detection accuracy with different measurements and different shots or videos |
| The cost of performing real-time calculations to identify pedestrians using this proposed method is relatively high | It is necessary to adopt methods to reduce these costs |
| Working with unstructured data with existing traditional methods faces several challenges (including the challenges of preprocessing, analysis, and grouping) | It is necessary to adopt methods or algorithms to optimize the performance of existing methods for analyzing that data and identifying pedestrians through the results of those analyzes. It is also necessary to adopt strategies to improve the performance of algorithms and methods used to classify data and semantic information in occlusion conditions |
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