Quantifying Impacts of Connected and Autonomous Vehicles on Traffic Operation using Micro-simulation in Dubai, UAE

Abstract

Connected and Autonomous Vehicles (CAVs) will change the transportation system we know with their substantial impacts on the level of safety, traffic operation, fuel consumption, air emissions among other aspects. A large segment of the general public and decision makers are still sceptical of CAVs’ benefits and impacts. This study aims at quantifying the impacts of CAVs on traffic operation using micro-simulation of a 7-kilometer-freeway segment in Dubai, UAE. The simulation was run for different market penetration rates (MPRs) ranging from 0% (no CAVs) up to 100% (all CAVs), in 10% increment. Additionally, multiple scenarios under different traffic volumes were also modelled utilizing PTV VISSIM. To quantify the impacts of CAVs, three performance measures were collected, namely the average delay, average speed, and total travel time. The results showed that the highest impact of CAVs occurs in terms of delay, with a decreased average delay of up to 86%. The other performance measures also show improvement, with 42% speed increase and 25% travel time reduction. Moreover, CAVs show more significant changes at lower traffic volume conditions (off-peak hour).