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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.

Occupant motion in a vehicle rollover accident is a function of many factors. Some important ones are vehicle kinematics, position of the occupant in the vehicle, occupant size, ground topology and restraint usage. The far side belted occupants are more vulnerable than the near side occupants in a rollover accident as they have more energy as a result of their trailing and higher side of the vehicle. This outcome is attributable to the inadequate safety performance of the conventional single loop; B-pillar mounted D-ring restraints. Roof crush tends to displace the vehicle's B-pillar, resulting in D-Ring displacement which causes slack in the lap portion of the restraint. This slack enables centrifugal loads to move the far side occupant further away from the vehicle's instantaneous point of rotation. In this scenario, the presence of any ejection portal can result in an occupant becoming partially or fully ejected.

This paper presents a methodology for predicting thermal comfort inside Midibus cabin with an objective to modify the Heating, Ventilation and Air Conditioning (HVAC) duct design and parametric optimization in order to have improved thermal comfort of occupant. For this purpose the bus cavity is extracted from baseline CAD model including fully seated manikins with various seating positions. Solar Load has been considered in the computational model and passenger heat load is considered as per BSR/ASHRAE 55-1992R standard. CFD simulation predicted the air temperature and velocity distribution inside passenger cabin of the baseline model. The experimental measurements have been carried out as per the guidelines set in APTA-BT-RP-003-07 standard. The results obtained from CFD and Experimental test were analysed as per EVS EN ISO7730 standard and calculated occupant comfort in terms of thermal comfort parameters like Predicted Mean Vote (PMV) and Predicted Percentage Dissatisfied (PPD).

Active control mainly comprises of three parts; sensor-detects the input disturbance, actuator -provide counter measures and control logic -processing of input disturbances and converting it into logical output. Lot of methods for active vibration control are available but this paper deals with active control of steering wheel vibrations of an LCV. A steering wheel is, one such component that directly transfers vibration to the driver. Active technique described here is implemented using accelerometer sensor, IMA (Inertial Mass Actuator) and feed forward Fx-LMS (Filtered reference Least Mean Square) control algorithm. IMA is a single-degree-of-freedom oscillator. To enable a control, IMA needs to be coupled to the structure at a single point, acting as an add-on to the passive system. Fx-LMS is a type of adaptive algorithm which is computationally simple and it also includes compensation for secondary path effects by using an estimate of the secondary path.

In year 2015, 17 people were killed every hour by road accidents in India [1]. The occurrence of road accidents is observed to be higher during night, when visibility is at its lowest. The two factors which affect visibility are insufficient illumination and glare caused by the oncoming traffic. The Adaptive Front Lighting System [AFS] is an active safety feature which addresses these problems by employing specific lighting modes for Town, Country, Expressway conditions and automatic switching between Driving Beam and Passing Beam whenever required. Matrix of LEDs or a Projector with an actuator or a combination of both is employed in achieving different Lighting modes. The projector based AFS module is preferred for implementing the AFS control logic for passing beam owing to its economic cost.

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.

The paper talks about Quantification of Alertness for vision based Driver Drowsiness and Alertness Warning System (DDAWS). The quantification of alertness, as per Karolinska Sleepiness Scale (KSS), reads the basic input of facial features & behaviour recognition of driver in a standard manner. Although quantification of alertness is inconclusive with respect to the true value, the paper emphasised on systematic validation process of the system covering various scenarios in order to evaluate the system’s functionality very close to the reality. The methodology depends on definition of threshold values of blink and head pose. The facial features are defined by number of blinks with classification of heavy blink and light blink and head pose in (x, y, z) directions. The Human Machine Interface (HMI) warnings are selected in the form of visual and acoustic signals. Frequency, Amplitude and Illumination of HMI alerts are specified.

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.