Abstract: Techniques are disclosed for reducing false positives for generating warnings to avoid potential collisions between a vehicle and vulnerable road users (VRUs). This is accomplished via an onboard vehicle safety system that uses crowd-sourced map data to determine whether a vehicle is capable of performing a maneuver that results in a lateral shift of the vehicle (which may include a lane-shifting or turning maneuver) within a predetermined threshold time period. The ability for the vehicle to make the turning maneuver, among other driving scenarios, may be used to by the safety system to intelligently determine whether a warning or other action is needed to avoid a potential collision with a VRU. In this way, the occurrence and number of false warnings/interventions are minimized or at least reduced, leading to more attentive drivers and thereby improving VRU safety.

Abstract: Techniques are disclosed for an unsafe hot spot detection and reporting system to identify unsafe “hotspot” zones. The system functions to identify hotspot zones that are associated with an increased number of detected warnings regarding unsafe conditions, vehicle collisions, near misses, or other hazardous events. The hotspots are determined based upon historical data that may include safety-based warnings issued from vehicle with respect to in-vehicle monitoring data or other data sources. The system leverages the hotspot location information to identify a safety data model (SDM) rule and automatically adjust one or more safety data model (SDM) parameters of the SDM rule such as follow distance, speed settings, etc., and/or to route the vehicle to an alternate course to avoid an identified unsafe hotspot zone.

Abstract: Systems and methods are provided for predicting blind spot incursions for a host vehicle. In one implementation, a navigation system for a host vehicle may comprise a processor. The processor may be programmed to receive, from an image capture device located on a rear of the host vehicle, at least one image representative of an environment of the host vehicle. The processor may be programmed to analyze the at least one image to identify an object in the environment of the host vehicle and to determine kinematic information associated with the object. The processor may further be programmed to predict, based on the kinematic information, that the object will travel in a region outside of a field of view of the image capture device and perform a control action based on the prediction.