A collision mitigation strategy for intelligent vehicles to compensate for human factors affecting manually driven vehicles

Human factors include human errors and human weaknesses such as long reaction time, limited visibility, limited jerk sustainability, etc. Such human factors account for a

large portion of vehicular accidents involving manually driven vehicles (MDVs). Future Intelligent Vehicles (IVs) are expected to have higher perception ranges, faster reactions and coordinated mobility capability. At early market penetration, IVs will share road with MDVs and will adjust its driving dynamics according to the dynamics of other neighboring vehicles. In such a scenario, we investigate how IVs can compensate for human factors impacting MDVs and accordingly improve traffic safety in mixed traffic conditions. We model a centralized Model Predictive Control (MPC) based controller and integrate constraints derived from human factors. We show that IVs may not only reduce collisions, but also increase traffic density without negatively impacting traffic safety. We finally assess the impact of a gradual penetration of IVs in a mixed vehicle scenario.