Abstract: Traffic signal timing plans are derived from vehicle trajectory or probe data. The probe data is collected and archived in a datastore over a sample time on the order of weeks or longer. Probe data is corrected for clock drift, geo-fence filtered to a selected intersection, and then stop line crossings in the intersection are identified and analyzed along with related data to determine the timing plans and schedule for the intersection. In this way, access to government agency timing plans is obviated so as to save time and expense.

Abstract: Traffic signal timing plans are derived from vehicle trajectory or probe data. The probe data is collected and archived in a datastore over a sample time on the order of weeks or longer. Probe data is corrected for clock drift, geo-fence filtered to a selected intersection, and then stop line crossings in the intersection are identified and analyzed along with related data to determine the timing plans and schedule for the intersection. In this way, access to government agency timing plans is obviated so as to save time and expense.

Abstract: Devices, systems, and methods are disclosed for connecting traffic signal control infrastructure, in-service transit vehicles, and back-end computing and service systems, and providing an adaptable user interface, remotely effecting a change on a Portable Electronic Device (PED), verifying location of transit vehicles and tailoring information to the behavior of a transit operator. System determines an “optimal window” for a transit vehicle to travel through a maximum number of consecutive traffic signals during the green vehicular phase. The system determines and sends a recommended speed to traverse the optimal window. In a case where an optimal window is not possible under current circumstances, the system determines and then advises the driver to remain at the current station for a specified dwell time.

Abstract: Traffic signal timing plans are derived from vehicle trajectory or probe data. The probe data is collected and archived in a datastore over a sample time on the order of weeks or longer. Probe data is corrected for clock drift, geo-fence filtered to a selected intersection, and then stop line crossings in the intersection are identified and analyzed along with related data to determine the timing plans and schedule for the intersection. In this way, access to government agency timing plans is obviated so as to save time and expense.

Abstract: At a roadway intersection controlled by an electronic traffic signal controller system, a potentially dangerous “dilemma zone” problem arises where a driver must quickly decide whether to stop or continue through the intersection. The problem is mitigated by leveraging data provided by an approaching vehicle itself as the source of detection. Based on the vehicle data itself, an “artificial detection” message is sent to the traffic signal controller to attempt to extend the green time, and thus permit a subject vehicle to safely pass through the intersection.

Abstract: Methods and systems to improve the accuracy of traffic signal state change predictions are disclosed. Predictions can be broadcast to vehicle drivers or autonomous systems to improve safety, fuel efficiency and reduce delays. Predictions for fixed-time signals are generated based on their scheduled timing plan and the current clock/time, but these predictions are subject variations, for example, due to traffic signal controller clock drift. Real-time actual, not predicted, data is collected and utilized to correct for these variations. Further, real-time probe data is collected and used to validate correctness of the generated predictions in real time. In one embodiment, GPS data from travelers' devices is utilized to assess validity of the generated predictions, looking particularly at signal stop line crossings relative to predicted green time window. If crossings observed in real time contradict the predicted signal state, the data service providing predictions to users may be suspended.

Abstract: Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. User (for example, driver) requests for a signal change may be implemented in traffic control systems, with all due care. User requests are validated and compared to traffic signal state change predictions. Only when appropriate conditions are met, the user request is used to generate a “synthetic call” to the applicable traffic signal controller (TSC). The new synthetic call substitutes for the usual call signal which arises from a fixed physical hardware detection system such as an inductive loop in the pavement.

Abstract: At a roadway intersection controlled by an electronic traffic signal controller system, a potentially dangerous “dilemma zone” problem arises where a driver must quickly decide whether to stop or continue through the intersection. The problem is mitigated by leveraging data provided by an approaching vehicle itself as the source of detection. Based on the vehicle data itself, an “artificial detection” message is sent to the traffic signal controller to attempt to extend the green time, and thus permit a subject vehicle to safely pass through the intersection.

Abstract: Methods and systems to improve the accuracy of traffic signal state change predictions are disclosed. Predictions can be broadcast to vehicle drivers or autonomous systems to improve safety, fuel efficiency and reduce delays. Predictions for fixed-time signals are generated based on their scheduled timing plan and the current clock/time, but these predictions are subject variations, for example, due to traffic signal controller clock drift. Real-time actual, not predicted, data is collected and utilized to correct for these variations. Further, real-time probe data is collected and used to validate correctness of the generated predictions in real time. In one embodiment, GPS data from travelers' devices is utilized to assess validity of the generated predictions, looking particularly at signal stop line crossings relative to predicted green time window. If crossings observed in real time contradict the predicted signal state, the data service providing predictions to users may be suspended.

Abstract: A fleet of vehicles (“connected vehicles”) are equipped to wirelessly transmit data in real time, the data including at least an identifier of the vehicle, a GPS location, and a timestamp. Preferably, messages may be sent from the vehicles approximately once per second. This “probe data” from operating vehicles is analyzed to assemble vehicle operation data over a collection period of say, a few weeks. The data is analyzed for a specific signalized intersection. In an embodiment, a preferred process is to leverage the connected vehicle probe data to figure out the traffic volume for a target time period and location, and then optimize the corresponding timing plan for that time period for the subject signal/lane/phase. Target time periods may be on the order of 15 minutes, 30 minutes or an hour, although the exact time period is not critical.

Abstract: Methods and systems are disclosed for generating a timely and reliable warning message before a traffic control signal changes to a red light state. A preferred process leverages traffic signal state data, state change predictions, and signal timing plans. The warning message may be distributed for various uses by downstream users and applications.

Abstract: Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve driver convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. Predictions can be computed with suitable machines installed in a vehicle, in cooperation with a remote back-end server system. The prediction computations in the vehicle may be supported by data communicated to the vehicle computing machinery over various wireless communications, including telecom systems, DSRC, etc.

Abstract: Devices, systems, and methods are disclosed for connecting traffic signal control infrastructure, in-service transit vehicles, and back-end computing and service systems, and providing an adaptable user interface, remotely effecting a change on a Portable Electronic Device (PED), verifying location of transit vehicles and tailoring information to the behavior of a transit operator. System determines an “optimal window” for a transit vehicle to travel through a maximum number of consecutive traffic signals during the green vehicular phase. The system determines and sends a recommended speed to traverse the optimal window. In a case where an optimal window is not possible under current circumstances, the system determines and then advises the driver to remain at the current station for a specified dwell time.

Abstract: Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve driver convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. Predictions can be computed with suitable machines installed in a vehicle, in cooperation with a remote back-end server system. The prediction computations in the vehicle may be supported by data communicated to the vehicle computing machinery over various wireless communications, including telecom systems, DSRC, etc.

Abstract: Methods and systems are disclosed for generating a timely and reliable warning message before a traffic control signal changes to a red light state. A preferred process leverages traffic signal state data, state change predictions, and signal timing plans. The warning message may be distributed for various uses by downstream users and applications.

Abstract: Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve driver convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. Predictions can be computed with suitable machines installed in a vehicle, in cooperation with a remote back-end server system. The prediction computations in the vehicle may be supported by data communicated to the vehicle computing machinery over various wireless communications, including telecom systems, DSRC, etc.

Abstract: Methods and systems are disclosed for generating a timely and reliable warning message before a traffic control signal changes to a red light state. A preferred process leverages traffic signal state data, state change predictions, and signal timing plans. The warning message may be distributed for various uses by downstream users and applications.

Abstract: Methods and systems are disclosed for generating a timely and reliable warning message before a traffic control signal changes to a red light state. A preferred process leverages traffic signal state data, state change predictions, and signal timing plans. The warning message may be distributed for various uses by downstream users and applications.

Abstract: Computer-implemented predictions of upcoming traffic control signal states or state changes can be used to improve driver convenience, safety, and fuel economy. Such information can be used advantageously by a human operator, or by an autonomous or semi-autonomous vehicle control system. Predictions can be computed with suitable machines installed in a vehicle, in cooperation with a remote back-end server system. The prediction computations in the vehicle may be supported by data communicated to the vehicle computing machinery over various wireless communications, including telecom systems, DSRC, etc.