**2.1 Vehicle to vehicle (V2V) /to infrastructure communication (V2I): the driving assistance**

The vehicle to vehicle communication is based on the idea that vehicles may exchange information about position, speed and location. In general, most relevant enhancements in the research field of the driving assistance refer to the cooperative awareness aiming to support the active road safety and the traffic efficiency to guarantee the speed management and the road navigation. A more detailed description is provided in the following.

Firstly, the Hazardous Location Notifications (HLN) category may be identified; this kind of services aims to provide road' users about hazardous situations in particular in terms of location, type, expected duration, etc. These services may be further classified in terms of Emergency electronic Brake Light (EBL) for warning drivers of hard braking by vehicles ahead; Emergency Vehicle Approaching (EVA) for providing an early warning of approaching emergency vehicles; Slow or Stationary Vehicle (SSV) for warning drivers about slow or stationary/broken down vehicles ahead; Traffic Jam ahead Warning (TJW) able to provide an alert to the driver that in traffic jam conditions reaches the end of the queue tail; Road Works Warning (RWW) aiming to inform drivers about works on the roads; Intersection movement assist (IMA) that warms drivers of vehicles approaching from a lateral position to the junction.

Further services within HLN category concern the collision risk minimisation (i.e. Cooperative Collision Risk Warning, CCRW) and the drivers of motorcycles warning (i.e. Motor Cycle Approaching indication, MCA).

Other kinds of applications refer to the vehicle to infrastructure communications and in particular to the signage; as the in-Vehicle SiGNage (VSGN) aiming at providing users' with road signs advanced information in the vehicle surroundings (this may facilitate drivers' gap at the signalised junctions), the in-Vehicle SPeeD limits (VSPD), aiming to provide users' with speed limits as well the ShockWave Damping (SWD) service able to recommend drivers about the optimal speed to be adopted by displaying the information in the vehicle. More in general there are the vulnerable road user (VRU) applications aiming at targeting crashes in case of vulnerable situations (for instance work areas, pedestrian detections, presence of emergency vehicles).

Other enhanced applications in case of urban contexts are Green Light Optimal Speed Advisory (GLOSA), Signal Violation/Intersection safety (SigV), Traffic Signal Priority etc.

Concerning the Green Light Optimal Speed Advisory (GLOSA) this is able to provide drivers with speed advice when they are approaching the traffic lights in order to uniformly mitigate the driving conditions by reducing the impact of acceleration/braking. With reference to the Signal Violation/Intersection safety (SigV) and the Traffic Signal Priority (TSP) these are respectively a safety-critical task focusing on the reduction of the number and severity of collisions at signalised intersections and a service able to guarantee the priority at signalised junctions of specific vehicles as emergency vehicles, public transport, etc.

Finally, other services are also referred to the in vehicle - infotainment applications that may be adopted in order to provide drivers with different kinds of information not only in terms of routes but also in terms of available services as parking or charging stations.

An overview of the main V2V and V2I applications is provided in the following table (see **Table 1**).

In general, it may be argued that in general vehicles are already connected devices; the development of an integrated framework combining the above


**Table 1.** *V2V & V2I applications.*

described services in which the vehicles will be able to interact each other and with the road infrastructures, is defined within the domain of Cooperative Intelligent Transport Systems (C-ITS). The C – ITS will be able to guarantee the road network management by synchronising all services and all shared information.

In conclusion in terms of driver guidance this research focuses on the implementation of GLOSA algorithm aiming to improve the traffic efficiency. The algorithm firstly calculates the distance and the travel time to the front traffic signal, then estimate the target speed constrained to the rules that were predefined considering different signal phases at the estimated arrival time.

#### **2.2 V2I – intersection applications: the urban traffic control**

The first criterion of classification of proposed methods in literature refers to the level of aggregation of input variables suitable for consideration in the optimisation procedure; in general two different kinds of variables may be adopted: the aggregate *flow* variables or the disaggregate *arrival* variables; therefore methods based on aggregate variables are also called flow based whereas methods based on disaggregate variables are also called arrival based methods.

Within *flow based methods* a further categorisation may be introduced in terms of junctions interaction; in particular the methods may be divided under single junction and networks depending on the degree of interaction between successive junctions that is isolated junction and interacting junctions [1]; then in case of interacting junctions the urban networks methods have to be applied whilst in case of isolated junction the single junction methods have to be considered. On the methodological point of view in case of interacting junctions the delay of the downstream approaches is influenced by delay of upstream furthermore the set of decision variables needed is also composed not only by stage durations and cycle time but also by an additional variable represented by the offset. Indeed, the offsets are introduced to describe the leg between the green stage at upstream and the green stage at downstream on the same flow direction. In this paper the interacting junctions' approaches are considered. It must be clarified that in case of urban traffic control the interaction between successive junctions may not be neglected therefore methods referring to the interacting junctions are needed in case of urban traffic control.

Alternatively, the *arrival based methods* may be considered in which starting from the number of arriving vehicles collected through loop detectors, the timing plans may be dynamically adapted to the traffic changes by allocating different green timings durations (extend/shorten) and by optimising the cycle length.

In terms of time dependency, it may be argued that flow based methods may be stationary or dynamic over time differently from arrival based methods that are

**149**

*Centralised Traffic Control and Green Light Optimal Speed Advisory Procedure in Mixed…*

intrinsically dynamic; this paper mainly focuses on dynamic approaches in order to

In summary two main dynamic approaches may be distinguished: the *planningbased traffic signal control* within centralised paradigms and the *actuated traffic signal control* within decentralised paradigms. In the first case, optimisation method starting from observed data and a traffic flow prediction model in forward time horizon, the actual input flows are estimated [3]. In general, the approach is oriented to decision variables design every control interval. Concerning the actuated traffic signal control, starting from the number of arriving vehicles collected through loop detectors, the timing plans may be dynamically adapted to the traffic changes by allocating different green timings durations (extend/shorten) and by the

Alternatively, to these methods are approaches are also discussed in literature in

• parts of the urban network through the implementation of gating control at the perimeter of the protected network (e.g. link metering or gating control;

All these methods usually adopted in presence of unequipped vehicles must be extended to the case of connected vehicles. One of the most limiting points in case of centralised traffic control is the traffic flow prediction necessary to guarantee the consistency between traffic flow inputs and decision variables optimisation every control interval. The presence of connected vehicle may be useful in terms of estimation of location and speed of unequipped vehicles supporting the traffic flow prediction robustness. In terms of traffic flow modelling a microscopic approach

• To apply a hybrid implementation of the centralised traffic control method

• To integrate these approaches with a procedure for traffic flow estimations.

In particular, one of the main problems in case of centralised control is the queue spillback and propagation in oversaturation conditions and queue may not be

the queue equidistribution. A multi - objective optimisation procedure has been considered based on the combination of two criteria: the queue length optimisation

To this aim a further refinement of the optimisation criteria is herein introduced:

In conclusion in terms of traffic control the paper aim is twofold:

properly managed with respect to the longitudinal capacity.

More in general two main traffic control paradigms may be related to the traffic flow input variables: the *centralised* and the *decentralised* approaches [2]. Indeed in case of centralised paradigms the traffic measurements are supposed to be received by a single central control agent which is responsible for deriving and implementing all control actions system considered consisting of three components respectively for regulating green splits, offsets, and cycle time; in case of decentralised paradigms the controller does not require information about global network inflow and the controller locally adjusts the traffic signal decision variables. In the last case depending on the adopted method variables adjustment may depend on both upstream and downstream local measurements (e.g. queue length) at each

*DOI: http://dx.doi.org/10.5772/intechopen.95247*

junction.

particular:

cycle length optimisation.

LM; see [8**–**11].

has been considered.

and the link metering approach;

provide a method suitable for on-line traffic management.

• the control of some sensitive links, arterials [4**–**7],

## *Centralised Traffic Control and Green Light Optimal Speed Advisory Procedure in Mixed… DOI: http://dx.doi.org/10.5772/intechopen.95247*

intrinsically dynamic; this paper mainly focuses on dynamic approaches in order to provide a method suitable for on-line traffic management.

More in general two main traffic control paradigms may be related to the traffic flow input variables: the *centralised* and the *decentralised* approaches [2]. Indeed in case of centralised paradigms the traffic measurements are supposed to be received by a single central control agent which is responsible for deriving and implementing all control actions system considered consisting of three components respectively for regulating green splits, offsets, and cycle time; in case of decentralised paradigms the controller does not require information about global network inflow and the controller locally adjusts the traffic signal decision variables. In the last case depending on the adopted method variables adjustment may depend on both upstream and downstream local measurements (e.g. queue length) at each junction.

In summary two main dynamic approaches may be distinguished: the *planningbased traffic signal control* within centralised paradigms and the *actuated traffic signal control* within decentralised paradigms. In the first case, optimisation method starting from observed data and a traffic flow prediction model in forward time horizon, the actual input flows are estimated [3]. In general, the approach is oriented to decision variables design every control interval. Concerning the actuated traffic signal control, starting from the number of arriving vehicles collected through loop detectors, the timing plans may be dynamically adapted to the traffic changes by allocating different green timings durations (extend/shorten) and by the cycle length optimisation.

Alternatively, to these methods are approaches are also discussed in literature in particular:


All these methods usually adopted in presence of unequipped vehicles must be extended to the case of connected vehicles. One of the most limiting points in case of centralised traffic control is the traffic flow prediction necessary to guarantee the consistency between traffic flow inputs and decision variables optimisation every control interval. The presence of connected vehicle may be useful in terms of estimation of location and speed of unequipped vehicles supporting the traffic flow prediction robustness. In terms of traffic flow modelling a microscopic approach has been considered.

In conclusion in terms of traffic control the paper aim is twofold:


In particular, one of the main problems in case of centralised control is the queue spillback and propagation in oversaturation conditions and queue may not be properly managed with respect to the longitudinal capacity.

To this aim a further refinement of the optimisation criteria is herein introduced: the queue equidistribution. A multi - objective optimisation procedure has been considered based on the combination of two criteria: the queue length optimisation

and the queue equidistribution and a proper metaheuristics algorithm has been applied. Regarding the link metering control as further discussed in sub-Section 2, this is based on occupancy as a control variable.
