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In today’s scenario, the emission norms are getting stringent day by day due to an increased level of pollution. The world is shifting towards low carbon footprint which made it necessary to adopt efficient technologies with fewer emissions. The hybridization of vehicles has resulted in improved efficiency with lower emissions which can fulfil the near future emission norms. Retrofitting of hybrid components into a conventional IC engine vehicle is so far the best way to achieve better performance both economically and technologically. This research is primarily focused on the design and development of a novel retrofit solution of P3x architecture for the light commercial vehicle. This retrofit solution is different from other hybrid solutions in terms of powertrain. It contains an innovative add-on powertrain along with the existing powertrain. This additional powertrain consists of a pair of helical gears followed by a chain and sprocket as a coupler for traction motor.

Advanced Driver Assistance Systems (ADAS) play a crucial role in enhancing road safety by providing intelligent assistance to drivers. To ensure the reliability and effectiveness of ADAS functions, rigorous verification and validation processes are necessary. One critical aspect of this process is scenario generation, which involves creating diverse and representative driving scenarios for testing and evaluating ADAS functions. This paper proposes a novel approach for synthetic scenario generation specifically tailored for Indian road conditions. The approach leverages real-time road data collected from various sources, including camera sensors, Lidar sensor, GPS devices, and traffic monitoring systems. The collected data is processed and analyzed to extract relevant information, such as road geometries, traffic patterns, and environmental conditions.

One of the primary reasons for road accidents is driving while distracted or drowsy. Often, long and monotonous road journeys lead to distracted or drowsy driving. Therefore, there is a need for a system which alerts a distracted or drowsy driver. Moreover, as the levels of autonomy move beyond SAE Level 2, the system assumes a larger share of the dynamic driving task. Under challenging circumstances, the system might ask the driver to take back vehicle control. To guarantee safety, it’s crucial to monitor the driver’s condition in order to assess their readiness to regain control of the vehicle. An advanced safety feature known as a driver monitoring system (DMS), sometimes referred to as a driver state sensing (DSS) system, is designed to monitor a driver’s attentiveness and alertness, providing warnings or alerts to refocus their attention on driving when drowsiness or distraction is detected.