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ADAS and AV technologies are going to disrupt the entire transportation industry, as we know it, with a profound impact on human life. They promise to enhance human lives by providing a safer and much more accessible transportation ecosystem to all of society. However, to deliver on all of its promises, they need to be at least as good as a ‘good’ human driver. Therefore, they need to be very safe and robust, with the ability to perform in a variety of driving scenarios, and be very secure, being immune from any external cyberattacks. Hence, such technologies need to be tested very extensively. However, from various studies, it has been found that, to declare a full AV as good as a human driver, the AV will be required to drive more than a billion miles on real roads, taking tens and sometimes hundreds of years to drive those miles, considering even the most aggressive testing assumptions.

Autonomous vehicles perform various functions with their own control strategies. Functions like Lane Departure Warning (LDW), Lane Keeping system (LKS) and Forward Collision Warning System (FCWS) requires special test tracks for their verification and validation. These test track requirements change with region to region according to available infrastructure. This paper deals with the design and development of test tracks for different ADAS functions verification and validation of Indian specific scenarios and its simulation in IPG CarMaker. The test track conceptualization has been done through the understanding and study of different international standards and geometry of test tracks for Indian conditions have been developed. IPG CarMaker software tool is used for creation of test track, and same track is used for simulation of above ADAS functions in IPG CarMaker.

An excellent physical and mechanical property makes Aluminium (Al) alloy suitable alternative lightweight materials against steel and cast iron in automotive components. ICME is a computational tool, which integrates the materials information to engineering product performance analysis. MatCalc is ICME tool, which follows the chain rule of process, microstructure, property and performance relationship in materials development. This paper reports the development of Al 6061-T6 propeller shaft through forging process and the materials and process model of the Al yoke is simulated using MatCalc simulation software. Finite element analysis method is used for designing of Al 6061-T6 propeller shaft. The forged Al yoke is solutionized at temperature 550°C for 1 hr followed by artificial ageing at temperature 180°C for 16 hrs to improve the hardness and strength of the yoke.

This paper introduces xEV Simulator- A MATLAB based simulator platform capable of analyzing EV/HEV powertrain system in both backward and forward modelling. xEV Simulator employs Forward Simulation for drive-cycle performance evaluations and Backward simulation for powertrain component sizing and support xEV powertrain design. The powertrain subsystems are modelled in Simulink. This enables the model based system simulation and further controller prototyping and HiL testing. xEV Offline Simulator GUI enables user to simulate standard EV/HEV configurations with standard drive-cycles. The model parameters of different component subsystems can be configured. The Backward modelling and simulation support the estimation of subsystem values like Propulsion motor, Energy storage, etc., to perform as per the drive-cycle requirement.

Now-a-days, Advanced driver-assistance systems (ADAS) is equipping cars and drivers with advance information and technology to make them become aware of the environment and handle potential situations in better way semi-autonomously. High-quality training and test data is essential in the development and validation of ADAS systems which lay the foundation for autonomous driving technology. ADAS uses the technology like radar, vision and combinations of various sensors including LIDAR to automatize dynamic driving tasks like steering, braking, and acceleration of vehicle for controlled and safe driving. And to integrate these advance technologies, the ADAS needs labeled data to train the algorithm to detect the various objects and moments of driver. Image annotation is one the well-known service to create such training data for computer vision. There are number of open source annotated datasets available viz. COCO, KITTI etc.

BS-VI or equivalent development calls for tremendous efforts in concept investigation and calibration for engine out, after treatment, diagnostic checks, off-cycle emissions, field performance, component safety etc. Achieving calibration quality for all these tasks is very challenging considering development time and cost with conventional physical testing approach. Present article focuses on assessment of testing and calibration using virtual approach. To prove and validate this approach, a six-cylinder heavy duty diesel engine is selected and configured in HiL environment. The engine plant model is built offline and validated with base engine data at steady state and transient operations and RT model is integrated with ECU hardware. Data for plant model corrections is generated with short measurement campaign. Refined real time plant model is prepared for evaluating different calibration strategies on virtual test bed environment.

Vehicle localization and position determination is a major factor for the operation of Autonomous Vehicle. Errors or unavailability of resources to determine this, poses a serious threat not only to the vehicle but also the environment around it. Global Positioning System (GPS) is one of the most common resources to determine position about the reference geographic coordinate system. But this resource has several drawbacks of its own viz. clock errors, multi-path errors and also uncertainty of good signal strength due to weather conditions or physical barriers. Also an additional drawback of a low-update rate makes it unreliable for the Autonomous Localization algorithm to operate on this. Thus a system is required which has no external environment dependencies to determine the position of the vehicle. Inertial Measurement Unit is a coupled system comprising of a 3-axis accelerometer and 3-axis gyroscope which records body force accelerations and the yaw rate.

Autonomous Emergency Braking (AEB) systems play a critical role in ensuring vehicle safety by detecting potential rear-end collisions and automatically applying brakes to mitigate or prevent accidents. This paper focuses on establishing a framework for the Verification & Validation (V&V) of Advanced Driver Assistance Systems (ADAS) by testing & verifying the functionality of a RADAR-based AEB ECU. A comprehensive V&V approach was adopted, incorporating both virtual and physical testing. For virtual testing, closed-loop Hardware-in-Loop (HIL) simulation technique was employed. The AEB ECU was interfaced with the real-time hardware via CAN. Data for the relevant target such as the target position, velocity etc. was calculated using an ideal RADAR sensor model running on the real-time hardware. The methodology involved conducting a series of test scenarios, including various driving speeds, obstacle types, and braking distances.

Electric Power Assist Steering (EPAS) is a safety critical system because it affects vehicle stability and dynamics. In EPAS, electric motor takes the power from the battery and delivers this power to rack and pinion only on demand. Since EPAS contains electrical component such as Motor and electronic component such as Electronic Control Unit (ECU), reliability of these components is very important. To ensure safety and reliability, ISO 26262 standards are adapted which are derived from IEC 61508. This standard regulates the product development on system, hardware and software level and manages functional safety for electrical and electronic components. This paper discusses the applicability of the ISO 26262 standard to the development of EPAS ECU with respect to its hardware and software design. Hazard analysis and risk assessment of the basic EPAS architecture is performed and architecture is improved to achieve safety goal as per the standard.

Autonomous driving is looked upon as solution for future of automotive vehicles. The technology has tremendous possibilities to improve safety, fuel economy, comfort, cost of ownership etc. The project to develop an autonomous controller from scratch was undertaken, with objective to drive under selected test scenarios. The car, modified to drive using this autonomous controller, is able to handle these scenarios. The key scenarios include ability to successfully drive on tracks with well-marked lanes, Follow the route as per selected trip plan file, recognize and follow all traffic road signs, traffic signals en-route, identify other vehicles on the road or pedestrians in the lane and take the appropriate action. The development was carried out using frugal engineering approach. As the Autonomous Vehicle technology is still under development, the standard proven published approaches are not available.

Control algorithm development for typical Engine Management System is a challenging task. To develop a reliable control algorithm, proper closed loop testing environment is required. In such development activity, it is of prime importance to validate the algorithm on a standalone target engine. This can be achieved in engine test cell where the actual engine will be controlled by prototype ECU. But this process has drawbacks like higher testing cost, time consuming, non-reusability of test bed etc. Simulation based engine plant model development for closed loop ECU testing is an effective technique for such application. Various generic engine models are available for such application.to suit a particular target engine these model need to be parameterized with precise engine data. The vehicle parameters used for parameterization are typically obtained from actual test and engine design data.

In order to travel in a chaotic and dynamic environment, an autonomous vehicle requires a motion plan. This motion plan ensures collision free, optimum travel without violating any traffic rules. The optimum solution for path planning problem exists in higher dimensions, however, with the help of useful heuristics the problem can be solved in real time, which is required for real time operation of an autonomous vehicle. There are different well established techniques available to plan a collision free kinematically traversable path. One of such techniques is called conformal Lattice planner. However, the legacy version of conformal lattice planner is not optimized and also is prone to fail under specific dynamic environment conditions. Moreover, the legacy version of conformal lattice planner is also not road aware. Due to this reason it is a semi optimized way to solve the motion planning problem.