Autonomous Vehicles (AVs) with their immaculate sensing and navigating capabilities are expected to revolutionize urban mobility. Despite the expected benefits, this emerging technology has certain implications pertaining to their deployment in mixed traffic streams, owing to different driving logics than Human-driven Vehicles (HVs). Many researchers have been working to devise a sustainable urban transport system by considering the operational and safety aspects of mixed traffic during the transition phase. However, limited scholarly attention has been devoted to mapping an overview of this research area. This paper attempts to map the state of the art of scientific production about autonomous vehicles in mixed traffic conditions, using a bibliometric analysis of 374 documents extracted from the Scopus database from 1999 to 2021. The VOSviewer 1.1.18 and Biblioshiny 3.1 software were used to demonstrate the progress status of the publications concerned. The analysis revealed that the number of publications has continuously increased during the last five years. The text analysis showed that the author keywords “autonomous vehicles” and “mixed traffic” dominated the other author keywords because of their frequent occurrence. From thematic analysis, three research stages associated with AVs were identified; pre-development (1999–2017), development (2017–2020) and deployment (2021). The study highlighted the potential research areas, such as involvement of autonomous vehicles in transportation planning, interaction between autonomous vehicles and human driven vehicles, traffic and energy efficiencies associated with automated driving, penetration rates for autonomous vehicles in mixed traffic scenarios, and safe and efficient operation of autonomous vehicles in mixed traffic environment. Additionally, discussion on the three key aspects was conducted, including the impacts of AVs, their driving characteristics and strategies for their successful deployment in context of mixed traffic. This paper provides ample future directions to the people willing to work in this area of autonomous vehicles in mixed traffic conditions. The study also revealed current trends as well as potential future hotspots in the area of autonomous vehicles in mixed traffic.

Bus rapid transit (BRT) has emerged as an efficient and cost-effective transport system for urban mobility that offers safe and high-quality transport services for city dwellers. Recent research has widely discussed BRT systems’ performance evaluation, but such assessments have remained limited in the South Asian context, where users’ needs might be distinct. The present study addresses this research gap and evaluates the performance of the BRT system in Multan, Pakistan, based on the passengers’ perceptions and the BRT standard scorecard. The data were collected at 21 BRT stations, and a face-to-face questionnaire survey was carried out with 420 users. The BRT standard scorecard method was also applied by conducting an observation survey and semi-structured interviews based on the aspects as specified by the Institute of Transportation and Development Policy (ITDP). The Statistical Package for the Social Sciences (SPSS) software package was mainly utilised for data analysis. This research concluded that around 54% of passengers are highly satisfied and opted for BRT due to comfort. Cronbach’s Alpha reliability analysis concluded that most of the BRT stations possess the acceptable value (0.8 > α ≥ 0.7), with only six out of 21 stations categorised as unacceptable (α < 0.5). Multan BRT achieved overall 79 scores and classified as Silver-Standard BRT. The study suggests critical insights to improve the citizens’ mobility with the existing BRT system, serving as a benchmark for policymakers and transport planners.

Traffic simulation models have been widely used to evaluate design alternatives and to help decision-makers to select best design option for prevailing traffic conditions. This study focuses on application of microsimulation model to the performance assessment of Tight Urban Diamond Interchange (TUDI) located in a congested urban setting with population more than 9 million and current transport demand up to 13.5 million daily motorized trips. Geometric and operational data was collected by conducting multiple site visits. Traffic volume data showed the heterogeneous nature of traffic. Microsimulation model; VISSIM was applied and appropriateness of this model and the proposed methodology was assessed based on maximum queue length as Measure of Effectiveness (MOE). Calibration of model was done in two stages: system calibration and operational calibration. System calibration was done by reflecting the actual geometric and control conditions in model. While operational calibration was done by conducting Sensitivity Analysis (SA). MOE values from calibrated model were compared with the field values of maximum queue length. This study revealed that SA helps in selecting the most appropriate parameters and their values. Results from VISSIM show the cumulative difference of 32 % from the field observed values.