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In this work, the functional development of motion planning and control for SAE level-4 autonomous urban pilot is presented, including its architecture design, algorithm development, software implementation and hardware prototype. First, a completely AVL in-house designed, modular and generic Advanced Driver Assist System (ADAS) and Automated Driving (AD) application architecture is deployed, such that the motion planning and control modules can communicate with decision making, environment modeling and localization modules. Second, A road-navigation-oriented, sampling-and-searching-based iterative spatial-temporal motion planning algorithm is developed and integrated with classical motion control algorithms, via a ©MATLAB/Simulink implementation platform. Finally, the integrated motion planning and control subsystem is prototyped in ©Speedgoat hardware, via a real-time multi-core multi-thread deployment methodology.

Regarding safety, obstacle avoidance has been considered as one of the most important features among ADAS systems for ground vehicles. However, the implementation of obstacle avoidance functions to commercial vehicles are still under progress. In this paper, we demonstrate a complete process of obstacle avoidance strategy for unmanned ground vehicle and implement the strategy on the self-developed Arduino based RC Car. In this process, the sensor LIDAR was used to detect the obstacles on the fore-path. Based on the measured LIDAR data, an optimized path is automatically generated with accommodation of current car position, obstacle locations, car operation capability and global environmental restrictions. The path planning is updated in real time while new or changing obstacles being detected. This algorithm is validated by the simulation results with the RC car. The comparison will be discussed at the end of this paper.

ADAS features development involves multidisciplinary technical fields, as well as extensive variety of different sensors and actuators, therefore the early design process requires much more resources and time to collaborate and implement. This paper will demonstrate an alternative way of developing prototype ADAS concept features by using remote control car with low cost hobby type of controllers, such as Arduino Due and Raspberry Pi. Camera and a one-beam type Lidar are implemented together with Raspberry Pi. OpenCV free open source software is also used for developing lane detection and object recognition. In this paper, we demonstrate that low cost frame work can be used for the high level concept algorithm architecture, development, and potential operation, as well as high level base testing of various features and functionalities. The developed RC vehicle can be used as a prototype of the early design phase as well as a functional safety testing bench.

In this paper, a sensor fusion approach is introduced to estimate lane departure. The proposed algorithm combines the camera, inertial navigation sensor, and GPS data with the vehicle dynamics to estimate the vehicle path and the lane departure time. The lane path and vehicle path are estimated by using Kalman filters. This algorithm can be used to provide early warning for lane departure in order to increase driving safety. By integrating inertial navigation sensor and GPS data, the inertial sensor biases can be estimated and the vehicle path can be estimated where the GPS data is not available or is poor. Additionally, the algorithm can be used to reduce the latency of information embedded in the controls, so that the vehicle lateral control performance can be significantly improved during lane keeping in Advanced Driver Assistance Systems (ADAS) or autonomous vehicles. Furthermore, it improves lane detection reliability in situations when camera fails to detect lanes.

There has been a rapid increase in popularity of multipurpose All-terrain vehicles (ATV) across the globe over the past few years. SAE BAJA event gives student-community an opportunity to delve deeper into the nitty-gritty of designing a single seat, four-wheeled off road vehicle. The design and development methodology presented in this paper is useful in conceptualization of an ATV for SAE BAJA event. The vehicle is divided into various subsystems including chassis, suspension, drive train, steering, and braking system. Further these subsystems are designed and comprehensively analyzed in software like SolidWorks, ANSYS, WINGEO and MS-Excel. The 3-D model of roll cage is designed in SolidWorks and analyzed in ANSYS 9.0 for front, rear and side impact along with front and side roll-over conditions. Special case of wheel bump is also analyzed. Weight, wall thickness and bending strength of tubing used for roll cage are comprehensively studied.