Abstract: A method, computer system, and a computer program product for implementing a plurality of actions associated with an impaired driver to prevent vehicle accidents is provided. The present invention may include collecting, from a plurality of existing vehicle sensors and a plurality of existing portable user device sensors, a plurality of data. The present invention may also include analyzing the collected plurality of data. The present invention may then include determining an impairment state associated with the driver. The present invention may further include implementing the plurality of actions to prohibit the driver from operating the vehicle. The present invention may then include storing the implemented plurality of actions, the analyzed plurality of data, and the determined impairment state associated with the driver in a historical database.

Abstract: A self-learning cycle timer is disclosed. A wait time is measured between a first indication, associated with a stop, and a second indication, associated with movement following the stop, each indication received from a smart device. A geolocation is received from the smart device and a traffic signal identified at the geolocation. The traffic signal's area of influence is determined. The wait time is determined to have occurred inside the area of influence. An average cycle time and a reference time associated with the traffic signal are retrieved from a database. A cycle time associated with the traffic signal is calculated according to the wait time and the reference time. The average cycle time is updated according to the calculated cycle time.

Abstract: A self-learning cycle timer is disclosed. A wait time is measured between a first indication, associated with a stop, and a second indication, associated with movement following the stop, each indication received from a smart device. A geolocation is received from the smart device and a traffic signal identified at the geolocation. The traffic signal's area of influence is determined. The wait time is determined to have occurred inside the area of influence. An average cycle time and a reference time associated with the traffic signal are retrieved from a database. A cycle time associated with the traffic signal is calculated according to the wait time and the reference time. The average cycle time is updated according to the calculated cycle time.

Abstract: A self-learning cycle timer is disclosed. A wait time is measured between a first indication, associated with a stop, and a second indication, associated with movement following the stop, each indication received from a smart device. A geolocation is received from the smart device and a traffic signal identified at the geolocation. The traffic signal's area of influence is determined. The wait time is determined to have occurred inside the area of influence. An average cycle time and a reference time associated with the traffic signal are retrieved from a database. A cycle time associated with the traffic signal is calculated according to the wait time and the reference time. The average cycle time is updated according to the calculated cycle time.

Abstract: A self-learning cycle timer is disclosed. A wait time is measured between a first indication, associated with a stop, and a second indication, associated with movement following the stop, each indication received from a smart device. A geolocation is received from the smart device and a traffic signal identified at the geolocation. The traffic signal's area of influence is determined. The wait time is determined to have occurred inside the area of influence. An average cycle time and a reference time associated with the traffic signal are retrieved from a database. A cycle time associated with the traffic signal is calculated according to the wait time and the reference time. The average cycle time is updated according to the calculated cycle time.

Abstract: A method, computer system, and a computer program product for implementing a plurality of actions associated with an impaired driver to prevent vehicle accidents is provided. The present invention may include collecting, from a plurality of existing vehicle sensors and a plurality of existing portable user device sensors, a plurality of data. The present invention may also include analyzing the collected plurality of data. The present invention may then include determining an impairment state associated with the driver. The present invention may further include implementing the plurality of actions to prohibit the driver from operating the vehicle. The present invention may then include storing the implemented plurality of actions, the analyzed plurality of data, and the determined impairment state associated with the driver in a historical database.

Abstract: A self-learning cycle timer is disclosed. A wait time is measured between a first indication, associated with a stop, and a second indication, associated with movement following the stop, each indication received from a smart device. A geolocation is received from the smart device and a traffic signal identified at the geolocation. The traffic signal's area of influence is determined. The wait time is determined to have occurred inside the area of influence. An average cycle time and a reference time associated with the traffic signal are retrieved from a database. A cycle time associated with the traffic signal is calculated according to the wait time and the reference time. The average cycle time is updated according to the calculated cycle time.