A vehicle driving behavior monitoring and warning system that includes a host vehicle having a communication device that receives operating information of remote vehicles that are located within a predetermined zone of interest, a warning device and an electronic controller. The electronic controller is connected to the communication device and the warning device. The electronic controller evaluates operating information received by the communication device and determine whether or not one of the remote vehicles is operating with questionable driving behavior and determines whether or not the remote vehicle poses a potential threat to the host vehicle. In response to determining that the remote vehicle is operating with questionable driving behavior and poses a potential threat to the host vehicle, the electronic controller operates the warning device warning the operator of the host vehicle of the remote vehicle.

Various embodiments for systems and methods for cooperative driving of connected autonomous vehicles using responsibility-sensitive safety (RSS) rules are disclosed herein. The CAV system integrates proposed RSS rules with CAV's motion planning algorithm to enable cooperative driving of CAVs. The CAV system further integrates a deadlock detection and resolution system for resolving traffic deadlocks between CAVs. The CAV system reduces redundant calculation of dependency graphs.

A vehicular collision avoidance system includes a forward-viewing camera viewing through the windshield at least forward of the equipped vehicle, a rearward-sensing radar sensor sensing at least rearward of the equipped vehicle, and an electronic control unit. The vehicular collision avoidance system detects vehicles present forward and/or rearward of the equipped vehicle. Responsive to data processing of radar data captured by the rearward-sensing radar sensor, the vehicular collision avoidance system detects another vehicle approaching the equipped vehicle from the rear, determines distance between the equipped vehicle and the other vehicle, and determines speed difference between the equipped vehicle and the other vehicle. Based at least in part on the determined distance between the equipped vehicle and the other vehicle and the determined speed difference between the equipped vehicle and the other vehicle, the vehicular collision avoidance system controls the equipped vehicle to mitigate impact by the other vehicle.

The present invention determines whether a vehicle is traveling at a location where preparation is needed for the vehicle to exit to another road branching from a current traveling road, estimates a lane change intention of a driver when it is determined that a lane change is needed for the vehicle to exit the current traveling road, and communicates the lane change to neighboring vehicles by activating a turn signal when the lane change intention is estimated.

A method is disclosed for mitigating the risks associated with operating an autonomous or semi-autonomous vehicle by using calculated route traversal values to select less risky travel routes and/or modify vehicle operation. Various approaches to achieving this risk mitigation are presented. A computing device is configured to generate a database of route traversal values. This device may receive a variety of historical route traversal information, real-time vehicle information, and/or route information from one of more data sources and calculate a route traversal value for the associated driving route. Subsequently, the computing device may provide the associated route traversal value to other devices, such as a vehicle navigation device associated with the autonomous or semi-autonomous vehicle. An insurance company may use this information to help determine insurance premiums for autonomous or semi-autonomous vehicles by analyzing and/or mitigating the risk associated with operating those vehicles.

An electronic device obtains location information and traveling status information of multiple vehicles in platooning, and traffic condition information of a road segment on which the multiple vehicles travel. The electronic device determines whether the multiple vehicles are suitable for continuing the platooning according to the location information and the traveling status information of the multiple vehicles, and the traffic condition information of the road segment on which the multiple vehicles travel. The electronic device transmits a platoon dismissing notification message to the multiple vehicles when it is determined that the multiple vehicles are not suitable for continuing the platooning, to inform the multiple vehicles to cancel the platooning.

An autonomous driving system for an autonomous vehicle includes an automated driving controller wirelessly connected to a towing taxi. The automated driving controller determines the autonomous driving system is non-functional. In response to determining the autonomous driving system is non-functional, the automated driving controller generates a notification indicating the autonomous driving system is non-functional. The automated driving controller receives, from the towing taxi, a current data string including a data point corresponding to a current point in time in combination with a predicted data point for each of one or more predicted points of time in the future. The current data string is compared with a previous data string recorded at a previous point in time. In response to determining the current data string matches the previous data string, the automated driving controller determines one or more driving maneuvers for the autonomous vehicle based on the current data string.

A method of controlling operation of a vehicle includes monitoring one or more features of a road segment, the vehicle configured to communicate with a plurality of objects in a wireless communication network, the vehicle configured to generate a communication based on a reference value of a parameter related to at least one of an environment around the vehicle and a behavior of the vehicle. The method also includes determining, based on the monitoring, a condition of the road segment, the condition including at least a curvature of the road segment, inputting the condition into a machine learning model configured to adjust the reference value based on the condition and output an adjusted reference value, and comparing the adjusted reference value to a current parameter value, and based on the adjusted reference value matching the current parameter value, transmitting an alert to one or more of the plurality of objects.

A method of coordinating one or more maneuvers among automated vehicles is presented. The method comprises: planning (21) a coordinated maneuver sequence that involves an initiating vehicle (HV) and a remote vehicle (RV, RV1, RV2, RV3, RV4); and transmitting (22) a request message (CQM) to the remote vehicle (RV, RV1, RV2, RV3, RV4), the request message (CQM) including information specifying the coordinated maneuver sequence.

The techniques and systems herein enable estimated-acceleration determination for AEB Specifically, for a potential collision, a determination is made as to whether the target of the potential collision is likely to be stopped prior to the potential collision (e.g., due to its own braking). One of a plurality of estimated-acceleration functions is then selected based on whether the target is likely to be stopped prior to the potential collision. Using the selected estimated-acceleration function, an estimated acceleration to avoid the potential collision is calculated. By selecting different estimated-acceleration functions based on whether targets are likely to be stopped prior to potential collisions, more-accurate estimated accelerations may be generated, thus enabling better collision avoidance and/or avoiding unnecessarily strong braking.