Various embodiments are described herein for systems and methods of traffic management in a road network including pathways and at least one intersection. In at least one embodiment, the method comprises receiving data signals from corresponding one or more connected vehicles and generating an intersection model for each approach of each intersection at a first time, where the intersection model comprises estimated arrival times for incoming vehicles at each approach. The method further comprises generating at the first time, for each intersection, candidate traffic timing data signals based at least on the intersection model corresponding to all approaches at the intersection, and generating, at the first time, for each intersection, an optimized traffic timing data signal, which is configured to control the operation of one or more traffic signals at the intersection, and is generated based on the candidate traffic timing data signals and a predetermined optimization variable.

A vehicle driving assistance device includes a driving assistance controller and an acquisition portion. The driving assistance controller includes a signal information acquisition part, a remaining distance calculator, and a driving assistance information output portion. The acquisition portion acquires information on (i) a vehicular speed and remaining distance to the intersection of an intersecting-side vehicle travelling on an intersecting road that joins a main road at the intersection, (ii) an arrival time when the intersecting-side vehicle arrives at the intersection, or (iii) lighting period information of an intersecting-side traffic signal. The driving assistance controller updates lighting period information of a main-side traffic signal based on information acquired from a road-to-vehicle communication transceiver, and outputs driving assistance information based on the updated lighting period information.

A vehicle driving assistance device includes a driving assistance controller and an acquisition portion. The driving assistance controller includes a signal information acquisition part, a remaining distance calculator, and a driving assistance information output portion. The acquisition portion acquires information on (i) a vehicular speed and remaining distance to the intersection of an intersecting-side vehicle travelling on an intersecting road that joins a main road at the intersection, (ii) an arrival time when the intersecting-side vehicle arrives at the intersection, or (iii) lighting period information of an intersecting-side traffic signal. The driving assistance controller updates lighting period information of a main-side traffic signal based on information acquired from a road-to-vehicle communication transceiver, and outputs driving assistance information based on the updated lighting period information.

Several implementations of an access point, an application server, and instances of an application operating upon a cell phone are disclosed. These implementations support the cell phone and its application traveling on a vehicle, which wirelessly communicates through a wireless router, such as a Bluetooth router with an access point situated in a cabinet to direct a traffic controller driving a traffic light. The wireless router responds to a cell phone initiated by the app, by reporting the location and speed of the vehicle, often further including the vehicle type, such as a bicycle or heavy truck. The traffic controller may lengthen a green light in response to a heavy truck, to reduce wear on roadways. The access point may respond to a bicycle, by confirming its presence to the bicycle driver as well as adjust the traffic controller.

Several implementations of an access point, an application server, and instances of an application operating upon a cell phone are disclosed. These implementations support the cell phone and its application traveling on a vehicle, which wirelessly communicates through a wireless router, such as a Bluetooth router with an access point situated in a cabinet to direct a traffic controller driving a traffic light. The wireless router responds to a cell phone initiated by the app, by reporting the location and speed of the vehicle, often further including the vehicle type, such as a bicycle or heavy truck. The traffic controller may lengthen a green light in response to a heavy truck, to reduce wear on roadways. The access point may respond to a bicycle, by confirming its presence to the bicycle driver as well as adjust the traffic controller.

A method is provided for traffic light signal phase and timing control (SPaT) status and notification message delivery. The method includes collecting traffic flow, incident, and emergency vehicle information on a predetermined portion of a road geometry network. The method dynamically adjusts the SPaT information for a traffic light signal in the predetermined portion of the road geometry network based on the information collected, and delivers a normal or abnormal SPaT status change with the adjusted SPaT information.

A method is provided for traffic light signal phase and timing control (SPaT) status and notification message delivery. The method includes collecting traffic flow, incident, and emergency vehicle information on a predetermined portion of a road geometry network. The method dynamically adjusts the SPaT information for a traffic light signal in the predetermined portion of the road geometry network based on the information collected, and delivers a normal or abnormal SPaT status change with the adjusted SPaT information.

A method to schedule intelligent traffic lights in real time based on digital infochemicals (DIs) is disclosed. The method takes advantage of DIs as medium to both predicate traffic flow and smooth the green/Cycle (g/C) ratio. First collect DIs, then update DIs by three actions including aggregation, evaporation, and propagation. After that, adjust the g/C ratio of the traffic light. DIs have the function of prediction due to the propagation that allows DIs reach the traffic earlier than the real traffic flow. On the other hand, DIs have the function of memory due to the evaporation that remembers the information of the historical traffic flow. The prediction and memory of DIs, as the reason why DIs are superior to the pure traffic flow, give the DI-based intelligent traffic light compelling advantages over the pure traffic based intelligent traffic light.

A method to schedule intelligent traffic lights in real time based on digital infochemicals (DIs) is disclosed. The method takes advantage of DIs as medium to both predicate traffic flow and smooth the green/Cycle (g/C) ratio. First collect DIs, then update DIs by three actions including aggregation, evaporation, and propagation. After that, adjust the g/C ratio of the traffic light. DIs have the function of prediction due to the propagation that allows DIs reach the traffic earlier than the real traffic flow. On the other hand, DIs have the function of memory due to the evaporation that remembers the information of the historical traffic flow. The prediction and memory of DIs, as the reason why DIs are superior to the pure traffic flow, give the DI-based intelligent traffic light compelling advantages over the pure traffic based intelligent traffic light.

In this disclosure, collaborative multi-agent-based TST is presented with dedicated intersection controllers that include software agents which read local and remote detection systems and then collaboratively optimize signal timing phases by considering the feedback of all controller agents that may be affected by a change. The disclosure also presents an augmented system which considers network input from handheld remote devices to update certain traffic light phase information and adapt to emerging emergency situations.