The ADAS&ME project (“Adaptive ADAS to support incapacitated drivers & Mitigate Effectively risks through tailor made HMI under automation”) will develop Advanced Driver Assistance Systems that adapts to the driver’s/rider’s state and the situational/environmental context when control is transferred between the vehicle and the driver/rider, ensuring a safer and more efficient road usage. The project in centred on seven use cases involving cars, trucks, buses and motorcycles. Each use case defines several societal benefits. For example, the combination of driver state monitoring and automated functions can effectively manage high risk situations, thereby reducing the number of traffic crashes due to driver error. Functions addressing other specific use cases such as long-haul trucking or bus driving will have a significant impact to emission reduction and more efficient transport. Experimental research will be carried out to develop and evaluate driver state monitoring algorithms, HMI designs and automation transitions. Robust algorithms for detection/prediction of fatigue/sleepiness, stress, inattention, emotions, thermal fatigue, faint and rest will be developed, making use of existing and novel sensing technologies, taking into account traffic and weather conditions via V2X as well as the individual driver’s physiology and driving behaviour. The detection/prediction results, along with the severity of scenarios, are used to design multimodal and adaptive warning and intervention strategies. The final outcome is the successful fusion of the developed elements into an integrated driver/rider state monitoring system, able to both be utilized in and be supported by vehicle automation of Levels 1 to 4. The system will be validated with a wide pool of drivers/riders under simulated and real road conditions and under different driver/rider states; with the use of 2 cars (1 conventional, 1 electric), 1 truck, 2 PTWs and 1 bus demonstrators. The expected impacts of ADAS&ME on mobility, congestion and safety are significant.