Abstract: Methods and systems for adapting an advanced driver assistance driving system of a vehicle. One system includes an electronic processor of an advanced driver assistance driving system. The electronic processor is configured to control the vehicle using a control parameter of the advanced driver assistance driving system. The electronic processor is also configured to activate a learning mode for the advanced driver assistance driving system and receive feedback associated with the control of the vehicle. The electronic processor is also configured to adjust the control parameter of the advanced driver assistance driving system based on the feedback and control the vehicle using the adjusted control parameter.

Abstract: A method of operating a vehicle having a driver assistance system includes detecting driving parameters pertaining to the vehicle while the vehicle is being driven on a roadway using a sensor system of the vehicle. Objects including road signs, lane indicators, and other vehicles are detected using the sensor system. The objects include at least road signs, lane indicators, and other vehicles on the roadway. A traffic rule pertaining to the roadway is identified using a traffic violation warning and prevention system of the driver assistance system. A traffic situation pertaining to the traffic rule is detected based on the detected objects and the driving parameters. An alert is generated that warns the driver of a potential traffic violation when the traffic situation is detected. Alternatively, the driver assistance system may be configured to take control of the vehicle to prevent violation of the traffic rule.

Abstract: Methods and systems for adapting an advanced driver assistance driving system of a vehicle. One system includes an electronic processor of an advanced driver assistance driving system. The electronic processor is configured to control the vehicle using a control parameter of the advanced driver assistance driving system. The electronic processor is also configured to activate a learning mode for the advanced driver assistance driving system and receive feedback associated with the control of the vehicle. The electronic processor is also configured to adjust the control parameter of the advanced driver assistance driving system based on the feedback and control the vehicle using the adjusted control parameter.

Abstract: A system for modifying vehicle behavior based on data from a dynamically updated roadway coefficient of friction database. The system includes a roadway coefficient of friction database and an electronic computing device. The electronic computing device includes a first electronic processor that is configured to receive a current coefficient of friction and a location of a vehicle and depending on a criterion, replace, in the roadway coefficient of friction database, a previous coefficient of friction with the current coefficient of friction. The first electronic processor is also configured to receive a request for a coefficient of friction associated with a location and transmit the coefficient of friction associated with the location. Additionally, the system includes a plurality of vehicles each including a second electronic processor. Each second electronic processor is configured to perform a preventative measure based on the coefficient of friction received from the electronic computing device.

Abstract: A system and method for avoiding collisions in a traffic intersection using radar sensors is disclosed. The system detects the location, speed, size, and direction of travel of objects, including vehicles and vulnerable road users, in and approaching a traffic intersection. Using this information, trajectories for all objects are determined, and, if a likelihood of a collision is determined, one or more traffic signal transitions are delayed in an attempt to avoid the collision.

Abstract: A system and method for avoiding collisions in a traffic intersection using radar sensors is disclosed. The system detects the location, speed, size, and direction of travel of objects, including vehicles and vulnerable road users, in and approaching a traffic intersection. Using this information, trajectories for all objects are determined, and, if a likelihood of a collision is determined, one or more traffic signal transitions are delayed in an attempt to avoid the collision.

Abstract: A global positioning signal based learned control event prediction method and apparatus includes a learning auxiliary module connected to a communication bus of a vehicle. The arrangement stores events and event locations using global positioning signals for a vehicle traveling along a path. When the vehicle travels the same path a second time, the detected events and event locations are determined. When the events match at the same event locations, a predictive action is determined for a future occurrence of the vehicle approaching the event location. Thus, as the vehicle approaches the event location, the predictive action, for example pre-filling of the vehicle brakes or pre-tensioning of the seat belts occurs.

Abstract: A global positioning signal based learned control event prediction method and apparatus includes a learning auxiliary module connected to a communication bus of a vehicle. The arrangement stores events and event locations using global positioning signals for a vehicle traveling along a path. When the vehicle travels the same path a second time, the detected events and event locations are determined. When the events match at the same event locations, a predictive action is determined for a future occurrence of the vehicle approaching the event location. Thus, as the vehicle approaches the event location, the predictive action, for example pre-filling of the vehicle brakes or pre-tensioning of the seat belts occurs.