In the foreseeable future, connected vehicles (CVs) will coexist with traditional vehicles (TVs) resulting in a complex mixed traffic environment and the success of CVs will depend on the characteristics of this mixed traffic. Therefore, before the large scale deployment of CVs, it is important to examine how CVs will influence the characteristics of the resultant mixed traffic. To achieve this aim, this study models the mixed traffic of TVs and CVs, and examines the traffic flow disturbance, efficiency, and safety. Intelligent Driver Model (IDM) with estimation errors is utilised to model TVs since it incorporates human factors such as estimation errors. Whereas, connected vehicle driving strategy integrated with IDM is utilised to model CVs because it incorporates driver compliance, a critical human factor for the success of CVs. Moreover, two classes of drivers based on their compliance levels are considered, namely the high-compliance drivers and the low-compliance drivers, to comprehensively investigate the impact of driver compliance on the mixed traffic of CVs and TVs. Two simulation experiments are performed in this study. The first experiment is used to measure traffic flow disturbance and safety while the second is used to measure the traffic flow efficiency. Furthermore, a total of 7 mixed traffic environments are generated in each experiment via different combinations of TVs, CVs with low compliance drivers, and CVs with high compliance drivers. Another important point considered in the simulation is the spatially distribution of CVs in the platoon. As such, three platoon policies are investigated. In the first policy i.e., the best case, the CVs are spatially arranged with a motive to maximise benefits from CVs whereas in the second policy i.e., the worst case, the CVs are spatially arranged with a motive to minimise benefits from CVs. Finally, in the third platoon policy i.e., the random case, the CVs are distributed randomly in the platoon. This study demonstrates the importance of the spatial arrangement of CVs in a platoon at a given penetration rate and its impact on traffic flow disturbance, efficiency, and safety. Moreover, findings from this study underscores that CVs can supress the traffic flow disturbance, and enhance traffic flow efficiency, and safety; however, traffic engineers and policy makers have to be cautious regarding how CVs are distributed in a traffic stream when deploying these vehicles in the real world traffic environment.