## 4 Limitations of Past Research and Implementation Barriers

Table 1: A critical comparison of the methodologies, findings and limitations of 22 primary research studies covered in this paper. \begin{table}
\begin{tabular}{c c c c c} \hline
**Researchers** & **Methodology** & \multicolumn{2}{c}{**Findings**} & **Limitations (for Future Works)** \\ \hline [PERSON] et al. [30] & Microscopic simulation & - & AV PT bus platooning is feasible. & - & Delay impacts of AV PT. \\  & & AV-buses had 60 s wait times and & - & Multiple traffic demand. \\  & & 44 s travel times. & - & Vehicle-road surface interactions. \\  & & - & Psychological barriers for AVs. & - & Interpretability of results \\  & & - & AV buses can reduce personal & among countries. \\ [PERSON] and [PERSON] [31] & Analytical & & costs, congestions, waiting times & - & Technology awareness \\  & & - & and emissions. & of respondents. \\  & & - & Vehicle costs, infrastructure costs & - & Stakeholder engagement. \\  & & & and safety risks exist for AV bus. & - & Actual performance results. \\  & & - & ITS can be applied for traffic data & - & Technology dependent. \\ [PERSON] et al. [39] & Field experiment & & collection and collision warning. & - & Data security. \\  & & - & ITS reduce network interruption. & - & Changes in data network. \\  & & - & ITS ramp metering and speed & \\  & & - & limits improve travel time by 9\%. & - & Impact of different traffic \\  & & - & Bus delays reduced by 81.5\%. & - & management scenarios. \\ [PERSON] and [PERSON] & Microscopic simulation & - & Traffic delays reduced by 29.1\%. & - & Open-source simulation software. \\  & [48] & modelling & - & Average speed increase by 12.7\%. & - & Performance testing using several \\  & & - & ITS reduce bottlenecks by 2.8\%. & - & merging points. \\  & & - & Fuel use reduced by 78.2\%. & - & Automatic model optimisation. \\  & & - & Emissions reduced by 17.3\%. & - & \\  & & - & Respondents expressed negative & - & Level of awareness. \\  & & - & feelings for AV ambulances. & - & Exposure of people to AV \\  & & - & Respondents from Kazakhstan & - & ambulance service. \\  & [52] & Analytical & & less trusting than & - & Representative population \\  & & - & Hungarian respondents. & surveys needed. \\  & & - & Readiness to ride is not influenced & - & Sensitivity to emergency level \\  & & & by gender. & and severity. \\  & Economic input-output & - & ITS traffic camera-generated & - & Traffic impacts of construction. \\  & LCA and & - & sustainable road construction. & - & Ramp metering. \\  & microsimulation & - & ITS strategy should be weighed & - & Automation of transport. \\  & modelling & & more for sustainable roads. & - & Social factors. \\  & & & & - & AV impact on PT travel time \\  & & - & AVs favour urban sprawl. & - & Intra-zonal demand. \\ [PERSON] et al. [65] & Transport modelling & - & AVs may replace PT in & - & Only average traffic data \\  & & - & low-density urban areas. & - & were modelled. \\  & & & - & Road capacity. \\  & & - & AVs may result in urban sprawl. & - & Travel time costs and fares. \\  & & - & AVs increase travel time (suburb & - & Small sample size (–200) \\ [PERSON] et al. [66] & Analytical (surveys) and & & to city centre) by 12\%, due to & & considered (i.e., population \\  & traffic simulation & & urban relocation. & & representation needed). \\  & & - & SAVs reduce travel time by 19\%. & - & Mode choice impacts. \\  & & - & AVs may result in urban sprawl. & - & Ownership of AVs. \\  & & - & AVs and TOD integration. & - & SAV integration with AV PT and \\  & & - & Heterogeneity in preferences for & transport system. \\ [PERSON] et al. [70] & Analytical & & TOD and AVs. & - & Real traffic data for \\  & & - & Results were dependent on time & simulation modelling. \\  & & - & - & Cost and policy initiatives. \\ \hline \end{tabular}
\end{table} 
Table 1: _Cont._