Assessing Lifecycle Environmental Footprint of Autonomous Mass-Mobility for Urban Highways by Microsimulation-Modelling

Traffic growth and microsimulation models are utilised to assess four traffic management scenarios: business-as-usual; public bus transport case; public bus rapid transit (BRT) case; and, a traffic demand-responsive autonomous-BRT case, focusing on fuel energy efficiency, headways, fleet control and platooning for lifecycle analysis (2015–2045) of a case study 3.5 km long 5-lane dual-carriageway section. Results show that both energy consumption and exhaust emission rates depend upon traffic volume and flow rate factors of vehicle speed-time curves; acceleration-deceleration; and braking rate. Public transport promotion was found to be an effective and easy-to-implement environmental burden reduction strategy. Over 30-years analysis period, "Bus Case" reduced energy use, CO2, NOx and PM exhaust emissions by 25%, 24%, 29%, and 18%, respectively. BRT reduced 35%, 35%, 45% and 20%, respectively. Autonomous-BRT resulted in the highest reduction in energy consumption (56%), CO2 (55%), NOx (50%) and PM (25%) exhaust emissions.