# Service-Oriented Cooperation Policies for Intelligent Ground Vehicles Approaching Intersections
## 4 Design of Cooperation Policies and Algorithms
### Enhanced Policies with Parallel Characteristics  
Single vehicle scheduling policies are so simple to realize, but the disadvantages of such policies are also very obvious. The \"one-by-one\" authorization mechanism will cause the stuttering of vehicular acceleration and traffic flows, and further, heavily affect the traffic efficiency at an intersection. So, besides these aforementioned policies, we further devote to explore some new methods to improve traffic efficiencies through enhancing the parallelism of these policies as far as possible. (1) Platoon-based Authorization Policy: PAP  
The first way is to minimize the stuttering of vehicular acceleration by authorizing a group of vehicles each time, rather than a single one that is the main reason causing the stuttering of vehicular behavior. It can be easily imagined that when one vehicular platoon on a lane is authorized every time, the velocity profiles of these vehicles will probably get smoother than that when authorizing vehicles individually. Many studies has shown that this is an important manner for improving traffic efficiencies. Based on the traditional platoon method, a Platoon-Authorization Policy (PAP) is designed in this paper to improve the performance of those aforementioned policies. Concretely, for a length setting \(N\), the value of every \(\gamma.\tau\) with this policy can be maximally \(N\), which is equal to the amount of vehicles authorized with this token. In addition, only when the value of \(\gamma.\tau\) is zero, \(\gamma.\tau\) is usable and it can be authorized to another vehicular platoon. The main mechanism with this policy is described in Algorithm 3. ```
Input:\(\gamma_{m}.\tau\); \(Q_{\ell_{k}}\); \(N\) (The length of Platoon). Output: Vehicles to be authorized. Set all \(\gamma_{m}.\tau\) to be 0; whileTRUEdo if(There exists at least one \(Q_{\ell_{k}}\) that is not empty);then  Choose one lane queue \(Q_{\ell_{k}}\) with to one previous policy, such as FAFP, HQEP, and HWFP; if(There exists at least one vehicle(H) in \(Q_{\ell_{k}}\));then if(The last vehicle(H) in \(Q_{\ell_{k}}\) is covered in the first \(N\) vehicles of this queue);then  Choose at most \(N\) vehicles in \(Q_{\ell_{k}}\) to form a platoon; else  Choose vehicles from the first to the last vehicle(H) in \(Q_{\ell_{k}}\) to form a platoon; //The real authorization amount will be greater than \(N\);  end if else  Choose at most \(N\) vehicles in \(Q_{\ell_{k}}\) to form a platoon;  end if if(The first several \(\gamma^{\prime}.\tau\) are available) and (No deadlock);then  Authorize these tokens to this platoon;  The value of every \(\gamma^{\prime}.\tau\) equals to the amount of vehicles it was authorized to;  end if  end if
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**ALGORITHM 3**Authorization Mechanism with PAP  
It needs to be emphasized that when merging PAP with above policies, new compound policies will be formed. These new policies will also exhibit different characteristics. Please note that, with the \"PAP+HEQP\" policy, the real length of one authorized platoon in the Algorithm 3 is possible greater than \(N\). This is because we introduced a new consideration that, if the first vehicle (H) will bestill blocked after the platoon ahead it on the same lane has been scheduled, the platoon should be lengthened to cover this vehicle (H). Which is meaningful to warrant the QoS of this vehicle (H). So, we can regard it as a variant of PAP in a sense. (2) Multi-Lane Authorization Policy: MLAP  
Authorizing one intersection as a whole to one vehicle or one vehicular platoon every time is obviously a very convenient way to manage approaching vehicles. However, we can easily prove that there still exists some opportunity to optimize these policies, in particular, when only a part of \(\xi_{\gamma}^{\mathbb{I}}\) is occupied by one vehicle or platoon the left S-CSs are maybe usable for vehicles on other lanes. In reality, such scenes are very normal.