A Microsimulation Modelling Approach to Quantify Environmental Footprint of Autonomous Buses

In this study a novel microsimulation-based methodology for environmental assessment of urban systems is developed to address the performance autonomous mass-mobility against conventional approaches. Traffic growth and microsimulation models, calibrated using real data, are utilised assess four traffic management scenarios: business-as-usual; public bus transport case; public-bus rapid transit (BRT) and, traffic-demand-responsive-autonomous-BRT case, focusing on fuel energy efficiency, headways, fleet control platooning lifecycle analysis (2015–2045) case 3.5 km long 5-lane dual-carriageway section. Results showed that both consumption exhaust emission rates depend upon volume flow rate factors vehicle speed-time curves; acceleration-deceleration; braking rate. The results measured over-reliance private cars utilising fossil cause congestions high footprint roads worsen causing excessive travel times. Public promotion was found be an effective easy-to-implement burden reduction strategy. significant potential reduce traffic, provided adequate mode-shift can achieved. utility microsimulations emissions assessment, it linked network with policies empirical models headway service frequency comparisons at levels. operation prediction long-term policy implications tracking accurate yearly simulation real-world profiles applicable other sustainability-oriented studies.