To serve the needs of the future, transportation systems must undergo a radical transformation, from the centralized paradigm to the asynchronous, distributed paradigm that integrates fast computers and high-performance networks through novel computer algorithms. Intelligent Transportation Systems takes the first step towards meeting that challenge. Focusing on highway and railway systems, the authors stress the need for computer modeling and simulation to help design and validate complex, large-scale systems and the design of new performance metrics to estimate the performance of these systems. They present the basic principles related to travel-related decision making, including coordination, control, and routing.

Intelligent Transportation Systems : New Principles and Architectures

Crc mechanical engineering series

Deconstructing an image based upon it parts poses a challenge to image analysis that may be solved using adaptive algorithms. The presence of occlusion or image rotation makes template matching difficult. Image segmentation techniques can be used to discriminate between objects via feature synthesis using deformable templates. This paper describes modifications to existing techniques commonly used to do real-time image segmentation for efficient hardware implementation. Edge detection and edge direction finding techniques may be used within the context of deformable templates for real-time automatic target recognition and tracking.

Configurable hardware for image segmentation

Nowadays the transportation systems show new challenges in management and supervision issues due to amount of vehicles and the variability and extension of the roads. New technologies have been developed to get information about traffic in cities. Nevertheless, new frameworks with different technologies applied to traffic monitoring have not been well defined. In this paper, a new framework with Radio Frequency Identification technology (RFID) applied to road traffic monitoring is exposed. In order to validate the designed framework, an experiment in a university campus was carried out, concluding the effectiveness of the RFID technology for traffic monitoring.

RFID framework for intelligent traffic monitoring

In recent years, image processing technology has been developed rapidly and presented a relatively obvious development trend. Real time image processing has been widely used. A multi-DSP real time image processing system based on Rapid IO Protocol is introduced in this paper, its has many characteristics: big data quantity, rapid data transmission, quick data processing and it can carry out large-scale real time signal processing.

Multi-DSP Real Time Image Processing System Based on Rapid IO Protocol

This paper presents a real-time image processing system for use in intelligent transportation systems. The system, run from a desktop computer, incorporates high-density pixel parallel (HDPP) processor chips into a programmable framework. By utilizing the system in a time-sharing fashion, multiple low-level image processing tasks can be implemented on the HDPP hardware. Examples of applications that have been implemented on the system and executed in real time include optical flow, template matching, and stereo vision.

C.G. Sodini

Papers

Massively parallel image processing system for intelligent transportation system applications