**1. Introduction**

The ultimate goal of automating the driving process is to improve safety by reducing accidents caused by human errors. If all vehicles in a network are human– driven, the efficiency of traffic networks can be improved by the control of traffic signal lights and the routes that drivers can choose. Studying the literature on freeway traffic control for HDVs demonstrate that the integration of traffic control strategies such as ramp metering (RM) and route guidance (RG) improve the network performance in regards to travel time, travel distance, throughput and emissions.

Moreover, it seems unrealistic that all the HDVs will suddenly be replaced by the AVs in the near future. Rather, what seems more plausible is that the AVs will be introduced onto the roads in the presence of the HDVs. Therefore, there is a need to consider cases where it becomes necessary to model the interactions between AVs and HDVs. Delays caused at on-ramps and off-ramps are some of the major contributors to overall system efficiency degradation. In addition to the increase of congestion in the merge lane and outer freeway lanes, merging lanes can have an overflow effect which causes the entire freeway to become congested. However, with the advent of CAVs, a lot more information has been made available for improving this overall process.

the notations are borrowed from [5]. The CTM is characterised by the following

*Models and Methods for Intelligent Highway Routing of Human-Driven and Connected…*

*L* Φ<sup>þ</sup>

*<sup>i</sup>* ð Þ� *k* Φ�

*li*ð Þ¼ *k* þ 1 *li*ð Þþ *k T d*ð Þ *<sup>i</sup>*ð Þ� *k ri*ð Þ*k :* (5)

(6)

*<sup>i</sup>* ð Þ¼ *k ϕi*ð Þþ *k ri*ð Þ*k* (2)

*<sup>i</sup>* ð Þ¼ *k ϕi*þ1ð Þþ *k si*ð Þ*k* (3)

<sup>1</sup> � *<sup>β</sup>i*ð Þ*<sup>k</sup> <sup>ϕ</sup>i*þ1ð Þ*<sup>k</sup>* (4)

*<sup>i</sup>* � *<sup>ρ</sup>i*ð Þ� *<sup>k</sup> ri*ð Þ*<sup>k</sup>* , *<sup>q</sup>max*

*i*

*<sup>i</sup>* ð Þ*<sup>k</sup>* (1)

*<sup>ρ</sup>i*ð Þ¼ *<sup>k</sup>* <sup>þ</sup> <sup>1</sup> *<sup>ρ</sup>i*ð Þþ *<sup>k</sup> <sup>T</sup>*

Φ<sup>þ</sup>

Φ�

The dynamic equation of the on-ramp queue length is:

The mainline flows and on-ramp flows are:

*DOI: http://dx.doi.org/10.5772/intechopen.94332*

*<sup>ϕ</sup>i*ð Þ¼ *<sup>k</sup>* min 1ð Þ � *<sup>β</sup><sup>i</sup>*�<sup>1</sup>ð Þ*<sup>k</sup> vi*�<sup>1</sup>ð Þ *<sup>ρ</sup><sup>i</sup>*�<sup>1</sup>ð Þþ *<sup>k</sup> ri*�<sup>1</sup>ð Þ*<sup>k</sup>* , *wi <sup>ρ</sup>max*

*si*ð Þ¼ *<sup>k</sup> <sup>β</sup>i*ð Þ*<sup>k</sup>*

**Symbol Description Unit/Range**

*i* Cell index *i* ¼ f g 1, … , *N*

*k* Time index *k* ¼ f g 0, … ,*K* � 1

*T* Sampling time ½ � *h N* Number of cells int

*K* Time horizon int

*L* Length of each cell ½ � *km vi* Free-flow speed ½ � *km=h ω<sup>i</sup>* Congestion wave speed ½ � *km=h*

*<sup>i</sup>* Cell capacity (Maximum flow rate) ½ � *veh=h*

*<sup>i</sup>* Jam density ½ � *veh=km*

*<sup>i</sup>* Critical density ½ � *veh=km*

*<sup>i</sup>* Maximum on-ramp queue length ½ � *veh*

*<sup>i</sup>* Maximum ramp metering rate ½ � *veh=h ρi*ð Þ*k* Traffic density ½ � *veh=km*

*<sup>i</sup>* ð Þ*k* Total flow entering cell *i* ½ � *veh=h*

*<sup>i</sup>* ð Þ*k* Total flow exiting cell *i* ½ � *veh=h ϕi*ð Þ *k* Mainstream flow entering cell *i* from cell *i* � 1 ½ � *veh=h ri*ð Þ*k* Flow entering cell *i* from its on-ramp ½ � *veh=h si*ð Þ *k* Flow exiting cell *i* through its off-ramp ½ � *veh=h βi*ð Þ *k* Split ratio ∈½ � 0, 1 *li*ð Þ *k* Queue length in the on-ramp ½ � *veh di*ð Þ*k* Flow accessing the on-ramp ½ � *veh=h*

*<sup>i</sup>* ð Þ*k* Ramp metering control variable ½ � *veh=h*

*CTM model variables and parameters of cell i during interval [kT,(k+1)T).*

equations:

*qmax*

*ρmax*

*ρcr*

*l max*

*r C*, *max*

Θ<sup>þ</sup>

Θ�

*rC*

**Table 1.**

**121**

Moving on to mixed–autonomy highway networks, as a specific example of the interaction between HDVs and CAVs, the overtaking behavior performed by a CAV is chosen as the target driving behavior for the last section of this chapter. The reason for this choice is that it is one of the more challenging driving behaviors when compared to car following and lane changing as it encompasses the combination of these behaviors.

This chapter is organized as follows: Section 2 reviews the integration of RM and RG, that have shown significant improvements on different control measures for highway networks with HDVs. Section 3 addresses the specific problem of improving freeway on-ramp merging efficiency by optimally coordinating CAVs. Finally, Section 4 explores the overtaking behavior accomplished by a CAV in the presence of HDVs.
