Our teams’ findings and conclusions:
Economically viable model
- All our research confirm that from an economical standpoint, the Autonomous Minibus (AM) model is perfectly viable.
- For a specific scenario in 2040 in Geneva, total savings from replacing 18% of the current modal share of private vehicles (expected situation at this date) with AMs is around 6’455 M€.
Capital and operation expenditures / external costs savings
- The Automated Minibus (AM) advent will decrease the costs related to externalities mainly through congestion reduction.
- On our Luxembourg deployment for example, the cost per passenger and for the entire fleet is higher for AMs than for ICEVs (until safety drivers will not be needed anymore) but there is a significative reduction in the local external costs (half lower per passenger and per vehicle/km).
- Capital and operation expenditures are higher for AMs than for ICEVs, but extra revenues will compensate (advertising, data commercialization, etc.).
Very attractive Business Opportunity
Autonomous Minibus (AM) sector can be a very attractive Business Opportunity with long-term perspectives for AMPT solution providers (safe position, niche segments).
Public Transport increased marketshare
AMs advent will increase overall Public Transit ridership and thus its marketshare on the global mobility sector.
Importance of the AM model choice / Planned deployment strategy
- Replacing traditional Public Transit services without a planned strategy would drastically worsen the external costs of deploying Autonomous Minibuses (AMs).
- Strategic direction needs to be elaborated/push forward as multiple modalities, applications, platforms, services, data regulations and governance concepts are developing.
- AM economic long-term impact and profitability are highly depending on the model deployed.
More conclusions based on 6 scenarios each focusing on a different modal shift caused by the AM deployment
We first settled 6 scenarios for a potential Autonomous Minibuses (AMs) deployment in each AVENUE demonstrator city and the resulting external costs, each focusing on a different modal shift caused by the AMs deployment. Our methodology pinpointed the pros and cons of each option showing us the one the mobility should evolve towards and allowed us a whole series of findings:
- AM integration within a MaaS (Mobility-as-a-Service) environment is the most realistic, suitable and providing the best results option, offering seamless and intermodal trips, reducing externalities and having a strong social acceptance. In Geneva, it may reduce external costs by 83.3 M€.
- Replacing all cars with AMs would also highly decreases external costs.
- AMs suburban implantation should have positive financial results (helping switch to PT), particularly if they cover long distances and connect communes.
- Of all AVENUE deployments, it is in Geneva center that AMs have the highest reduction in externalities potential, mainly because of the high congestion current situation.
- If the AM advent is supported by urban policies (road pricing, no-car zones etc.) it will increase the modal shift to this technology.
- AMs need to operate without any driver to cut the costs and facilitate its adoption.
More conclusions based on 4 Business Ecosystem (BES) scenarios
We also set 4 Business Ecosystem (BES) scenarios, each projecting that a very different group of stakeholders will be at the heart of the Autonomous Minibus Ecosystem (PTOs, automotive sector, new mobility providers or customers/MaaS), that enabled us to assess that:
- The MaaS centered scenario is the most probable and suitable one. It provides many strengths and opportunities, but faces weaknesses (technical, organizational, conceptional) and threats to be mastered before showing its benefits. Multiple potential MaaS BES pattern has been identified and a public/private stakeholders’ combination is seen as most advantageous
- Value-added AM services are an attractive business for future automotive centered mobility providers (digitalization / “big data” being highly profitable).
- New Mobility Providers lack some AM competencies; it can be offset by partnerships or by listening AM specialized companies like AVENUE that can help them seize opportunities, fend off threats and ramp up fast in this market.
- Partnership collaboration among mobility innovators (strategic synergies, integrations) is needed for business success.
- Vehicle maintenance or fleet management services may be an attractive partnering offering for New innovation-based Mobility Providers.
- New Mobility Providers’ centered BES (data business, technology innovations, transaction networks) can find a manageable playing field for mastering the challenge of a BES extension by AM engagement and they can enhance the AM business.
- Data related issues and the “data giants” impact are key success factors for the AM business.
- AM solution providers can engage in various ways in MaaS centered BES depending on their offering. They can generally apply their whole solution portfolio to the Public and Private MaaS centered Ecosystem and intensify their niche position by specialization.
How to increase AM customer base and profitability
- Proposing some attractive individualized offers included in multiplatform ticket offers.
- Integrating customized mobility services (route planning, forms of payment, infotainment features, integrated customer service, etc.).
- Adding special services for people with disabilities, a follow my kids’ option, etc.
- Offering an on demand/door-to-door service.
More on the EASI-AV© tool
The EASI-AV© tool can calculate:
- The economic impact of Autonomous Minibuses (AMs) before and after implementation regarding different cost variables (staff, infrastructure, energy costs).
- The economic viability of AM as a part of an integrated PT system.
- AM introduction cost savings concerning total cost of ownership as well as externalities.
- The cost per kilometre or per passenger.
- Results at a local (designing/implementing costs) and global (macro external costs) scale.
- The number of AM needed to satisfy mobility needs and replace ICE vehicles in a particular area. In the on-demand context, complex algorithms taking into account multiple parameters (waiting/charging time, vehicle capacity, operation cities trip data, local mobility behaviour, modal shares of the calculations’ desired area) are needed.
- The fleet total ownership costs (AVENUE deployments permitted to refine cost estimations).
- The local external costs of implementing an AM service (per passenger or per vehicle/km).
- The expected profit margins taking into account the given context.
For all these points it can provide a comparative approach with any other transport mode.