Steering intervention strategy for side lane collision Avoidance

Advance Driver Assistance Systems (ADAS) have successfully been integrated in many vehicles; however, the research on its improvement is still on-going. Some of the features of ADAS include Lane Departure warning System, Blind Spot detection, Lane Change Assistance and etc. However, with such systems available, accidents still occurred due to the driver's lack of awareness and negligence towards the given indication and warning, especially situation related to side lane collision. Thus, this paper aims to propose a simple steering intervention control. If the driver still proceed for the lane change when there are other object appearing in the blind spot area, the proposed solution will automatically trigger vehicle evasion mode to avoid side lane collision. The system does not take into account comfort in order to warn the driver. The system was tested and validated using a test vehicle. The results show that the steering intervention provides good vehicle evasion results and hypothetically it may act as the final warning towards the person behind the wheel

Threat assessment algorithm for Active Blind Spot Assist system using short range radar sensor

Road safety has become more concern due to the number of accidents that keeps increasing every year. The safety systems include from simple installation such as seat belt, airbag, and rear camera to more complicated and intelligent systems such as braking assist, lane change assist, steering control and blind spot monitoring. This paper proposes another intelligent safety system to be implemented in passenger vehicle by monitoring the blind-spot region by using automotive short range radar as sensor to assess its surrounding. This system is called Active Blind-Spot Assist (ABSA) system and this system will collaborate with a Steering Intervention system for autonomous steering maneuvers. The objective of ABSA system is to deploy safety interventions by giving warning to the driver whenever other vehicle is detected within the blind-spot region. Furthermore, this active system also triggers autonomous steering control when the potential of collision with the detected vehicle increases greatly. Consequently, a threat assessment algorithm is developed to evaluate the right moment to give safety interventions to the driver and the conditions for autonomous steering maneuvers. The process of developing the threat assessment algorithm explained in this paper

I-Drive: Modular system architecture and hardware configuration for an intelligent Vehicle research platform

There are many researches in the field of autonomous and Intelligent Vehicle in Malaysia, but most of them never have the chance to be tested in actual environment due to constraints in terms of hardware and its configuration. Thus, this paper aims to share with other researchers in the field of Autonomous and Intelligent Vehicle with our independent modular-based system and hardware configuration of an Autonomous and Intelligent Vehicle research platform at our university. Each of the research projects are represented by a module and they are linked by a communication layer. The modules utilised the communication layers to transmit and received data as a part of system communication network, and finally this configuration build up the whole system. Through this approach, it is hoped that the contribution from each research project leads to fully autonomous vehicle and intelligent vehicle. The proposed modular system and hardware configuration have been successfully verified via our platform through lane-keeping research. The proposed platform is demonstrated via I-DRIVE (Intelligent Drive Vehicle) on the standard testing track and Malaysia highway road

I-Drive: Modular system architecture and hardware configuration for an intelligent Vehicle research platform

There are many researches in the field of autonomous and Intelligent Vehicle in Malaysia, but most of them never have the chance to be tested in actual environment due to constraints in terms of hardware and its configuration. Thus, this paper aims to share with other researchers in the field of Autonomous and Intelligent Vehicle with our independent modular-based system and hardware configuration of an Autonomous and Intelligent Vehicle research platform at our university. Each of the research projects are represented by a module and they are linked by a communication layer. The modules utilised the communication layers to transmit and received data as a part of system communication network, and finally this configuration build up the whole system. Through this approach, it is hoped that the contribution from each research project leads to fully autonomous vehicle and intelligent vehicle. The proposed modular system and hardware configuration have been successfully verified via our platform through lane-keeping research. The proposed platform is demonstrated via I-DRIVE (Intelligent Drive Vehicle) on the standard testing track and Malaysia highway road

A new technique for 3D measurment using 3D producer

The paper describes a study using video captured by 3D producer. An off-the-shelf NuView 3D adapter and a Cannon camcorder were used to capture 3D-video footage. The NuView allows two distinct views (left and right view) to enter the single lens camcorder. A simple single convergence control in the NuView allows the user to obtain 3D view of near and far objects. The research involves the calibration of the system for 3D measurement. A stereo-digitizing photogrammetric workstation was used to determine the accuracy of the system. The results show that system can achieve a depth accuracy of 45 mm and 60 mm at object distances of 3 and 5 m respectively. The horizontal accuracy is approximately two times more accurate than the depth

TERRAIN EXTRACTION BY INTEGRATING TERRESTRIAL LASER SCANNER DATA AND SPECTRAL INFORMATION

The extraction of true terrain points from unstructured laser point cloud data is an important process in order to produce an accurate digital terrain model (DTM). However, most of these spatial filtering methods just utilizing the geometrical data to discriminate the terrain points from nonterrain points. The point cloud filtering method also can be improved by using the spectral information available with some scanners. Therefore, the objective of this study is to investigate the effectiveness of using the three-channel (red, green and blue) of the colour image captured from built-in digital camera which is available in some Terrestrial Laser Scanner (TLS) for terrain extraction. In this study, the data acquisition was conducted at a mini replica landscape in Universiti Teknologi Malaysia (UTM), Skudai campus using Leica ScanStation C10. The spectral information of the coloured point clouds from selected sample classes are extracted for spectral analysis. The coloured point clouds which within the corresponding preset spectral threshold are identified as that specific feature point from the dataset. This process of terrain extraction is done through using developed Matlab coding. Result demonstrates that a higher spectral resolution passive image is required in order to improve the output. This is because low quality of the colour images captured by the sensor contributes to the low separability in spectral reflectance. In conclusion, this study shows that, spectral information is capable to be used as a parameter for terrain extraction