## 4 Results
### Impact of Connected Vehicles on Traffic Management in Rural, Urban and Highway Roads  
Organizations were asked for their opinion on the impact of the increasing number of connected vehicles on traffic management in three different regions, namely highways, urban areas and rural areas. The binomial test in Table 8 with a significance value of 0.78 > 0.05 (for rural areas) confirm that respondents believe there would be no significant impact on rural areas traffic management with the induction of connected vehicles. However, the impact on highways and urban areas will be otherwise. Furthermore, the Wilcoxon sign rank test in Table 9 confirms that participating organizations agree on a positive impact of connected vehicles on highways and urban areas. The test results show that connected vehicles would have a positive impact on urban areas when compared to rural areas (Fig. Value 0.00 < 0.05) and it shows similar results for highways when compared to rural areas. However, when compared within the group, highways and urban areas (sig. value 0.310 > 0.05) show that there would be a positive impact on traffic management in both regions. It is expected that CVs would lead to noticeable reduction in congestion and capacity challenges and result in smooth traffic management, especially in these two regions. In rural areas, there would be little to no effect, which means there would be barely any reduction in congestion and capacity challenges compared to the present traffic condition. The possible reason could be that the augmented number of people are moving to urban areas leaving rural areas less populated. Less population means less vehicles and subsequently less impact on traffic management in the future, when compared to the present time. \begin{table}
\begin{tabular}{c c c c c c} \hline \hline  & & **Category** & **N** & **Observed Prop.** & **Test Prop.** & **Exact Sig.** **(2-Tailed)** \\ \hline Toll & Group 1 & \textless{}=3 & 46 & 0.9 & 0.5 & \\ Collection & Group 2 & \textgreater{}3 & 5 & 0.1 & & 0.000 \\ Total & & 51 & 1 & & \\ \hline Highway & Group 1 & \textless{}=3 & 50 & 0.98 & 0.5 & \\ RTC & Group 2 & \textgreater{}3 & 1 & 0.02 & & 0.000 \\ Total & & 51 & 1 & & \\ \hline Traffic & Group 1 & \textless{}=3 & 50 & 0.98 & 0.5 & \\ Management & Group 2 & \textgreater{}3 & 1 & 0.02 & & 0.000 \\ Total & & 51 & 1 & & \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Binomial test (Statistics) for IOT. \begin{table}
\begin{tabular}{c c c c} \hline \hline  & **Toll Collection V/S** & **Toll Collection V/S** & **Highway RTC V/S** \\  & **Highway RTC** & **Traffic Management** & **Traffic Management** \\ \hline Z & \textless{}2.433 a & \textless{}2.922 a & \textless{}1.732 a \\ \hline Asymp. Sig. (2-tailed) & 0.015 & 0.003 & 0.083 \\ \hline \hline \end{tabular} a Based on negative ranks.  
\end{table} 
Table 7: Wilcoxon Signed-rank test (Statistics) for IOT. To understand the impact of autonomous vehicles on highways in terms of road accidents, traffic volumes and toll pricing, research studies created a scenario that until 2030, at least 30% of all vehicles on highways would be fully autonomous and organizations were supposed to answer this question in light of the given scenario. The binomial test results in Table 10 clearly indicate that 30% of autonomous vehicles on highways until 2030 will have no effect on toll pricing (Sig value. 0.392 \(>\) 0.05) and they are most likely to stay as it is. However, this scenario will have a positive impact on road safety and traffic volumes mostly because autonomous vehicles are more intelligent and smarter than human drivers thus resulting in better road safety. These vehicles would be able to make multiple trips as restrictions on driving bans for such cars will be lifted and thus increasing the traffic volume on highways. Autonomous vehicles would play an important role in mitigating capacity utilization and congestion issues of highways in the future [12].