A Hybrid Approach Combining Macroscopic Traffic and Life Cycle Simulations to Evaluate Environmental Loads of Regional Transportation Including Ridesharing

Achieving the targets set by the Paris Agreement requires significant reduction in cumulative CO₂ emissions. Among various sectors, road transport accounts for approximately 18% of global CO₂ emissions, making its decarbonization an urgent priority. While battery electric vehicles emit less CO₂ during operation compared to internal combustion engine vehicles, their higher environmental impact during manufacturing limits the effectiveness of a simple one-to-one replacement. An alternative approach gaining attention is reducing the total number of vehicles through ridesharing. However, ride-sharing services may divert demand away from lower-emission public transportation modes such as rail and buses, and the extent of this impact varies by region. To accurately assess the CO₂ reduction potential of ridesharing, it is necessary to account for its interaction with public transport systems and evaluate the life cycle CO₂ emissions of the entire transportation system. This study proposes a hybrid simulation method that combines macro-scale transportation simulation to estimate changes in travel demand patterns, including shifts involving public transit, and life cycle simulation to quantify the effects of increased vehicle utilization and fleet size reduction. The method was applied to two areas in Osaka Prefecture: a rural area and an urban area. The results show that in the rural area, ridesharing significantly replaced private vehicle trips, leading to an approximate 20% reduction in life cycle CO₂ emissions from the transportation system. In contrast, in the urban area, ride-sharing substituted public transit trips, resulting in negligible CO₂ reduction.