IMPLEMENTATION SCENARIOS AND USER ACCEPTANCE OF SHARED AUTONOMOUS (ELECTRIC) VEHICLE FLEETS IN GERMAN CITIES. EE-54 I Lisa Kissmer I 30.11.2016
RELEVANCE OF TOPIC. GM s Maven expands in California (USA) and looking to China Fortune.com (28.10.2016) Car2Go crosses two million global member milestone Car2Go Press Release (04.10.2016) Tesla s Self-Driving Uber Service Could Kill off Taxis Forever Inverse.com (16.11.2016) Two main trends in the automobile industry: 1. On-demand urban mobility services 2. Autonomous Driving (Google) Seite 2
STATE OF THE ART. Source Content Limitations OECD & International Transport Forum (2015) Traffic impacts of shared-self driving cars User acceptance, potential users Holistic SAEV approach Fagnant et al. (2014) Spieser et al. (2014) Chen (2015) Traffic simulation implementation of a small SAV fleet 100% Replacement of public means of transport by SAV fleet SAEV Fleet Simulation: Synergy effects between electric mobility and autonomous driving Recommendations to overcome rised VMTs Political regulation scenarios Operation & ownership of SAV fleet Implementation scenarios Scientific assupmtions Carsharing problems Research Questions: What will SAEV Systems look like in German cities? Seite 3
RESEARCH DESIGN. Qualitative Research o Expert interviews (n=20) o Qualitative content analysis o Evaluation & theoretical framework 1,2,3 : Sampling: Maximum variation strategy Semi-structured interview Sampling criteria Sample o Carsharing Business (n=5) Free-floating Station-based o Carsharing Association (n=1) o Urban Mobility and Transportation Researchers (n=8) Universities & Institutes Research departments o Cities (n=5) o OEM (n=1) Questions to Experts o Future urban mobility behaviour, developements and needs o User acceptance o Political Regulation o Potential and Risks of SAEV Systems Implementation Model of SAEV Systems in German cities Sources: 1)Mayring, P. (2015). Qualitative Inhaltsanaylse. Grundlagen und Techniken. Weinheim: Beltz Verlag 2)Flick, U. (2007). Qualitative Sozialforschung. Hamburg: Rowohlt Taschenbuch Verlag. 3)Gioia, D., Corley, K., & Hamilton, A. (2012). Seeking qualitative: Rigor in inductive research: Notes on the Gioia Methodolody. 16 (1), 15-31. Seite 4
SAEV FLEETS IN CARSHARING. Carsharing in German cities: DriveNow in Munich 3 Key Players: 1. City 2. Carsharing Users 3. DriveNow Vehicles / Operator Main Problems in Carsharing: Vehicle in Cold Zone Drink and Drive Driver license Utilization Availability Future SAEV Systems: Process: 1. Customer Request 2. Pick up 3. Ride 4. Drop off Legend: vehicle City User Aim Seite 5
RESULTS: POTENTIALS AND RISKS OF SA(E)V FLEETS IN GERMANY. Potential Elderly people Younger early-adopters High user acceptance Risk Early-phase: unsuitable for children and disabled people Rise of VMT Luxury trips Seite 6
RESULTS: POTENTIALS AND RISKS OF SA(E)V FLEETS IN GERMANY. Potential Risk Complement to public transit Traffic flow & road capacity Space utilization Reduction of car ownership Add-on Mobility Traffic Volume Space utilization Seite 7
RESULTS: POTENTIALS AND RISKS OF SA(E)V FLEETS IN GERMANY. Potential New customers High degree in vehicle model and pricing differentiation Carsharing boom Solving carsharing problems (e.g. parking, damages, driving licences etc.) Times & costs Utilization & availability Risk Regulated by government Government as monopolist Empty rides: Legal prohibition Technology failures Loss in brand awareness Take over of small, station based CS businesses Seite 8
RESULTS: IMPLEMENTATION SCENARIOS FOR GERMAN CITIES 1/2 Maintenance & repair shops Centralised parking spots / hubs Modal Split Seite 9
RESULTS: IMPLEMENTATION SCENARIOS FOR GERMAN CITIES 2/2 P+R P+R Prohibited vehicles Commuting traffic: private AEVs Maintenance & repair shops P+R P+R P+R Centralised parking spots / hubs Decentralised Parking Hub Seite 10
RESULTS: POLITICAL REGULATION SCENARIOS. Political conviction Road charges: autonomous private cars Alternative public transit City centre autonomous & electric SAEV pricing Last-stopp Last support mile in public support transit Empty rides a)taxes b) Legal Prohibition Seite 11
RESULTS: KEY FINDINGS FOR THE GERMAN MARKET. Cities: 1) SAEV cannot repalce public transit 100% SAEV within a German city will not exist Autnomous (electric) mini busses as replacement for railbound transportation 2) SAEV only beneficial when private cars are reduced 3) Mobility behaviour patterns will not change Operators 1) Carsharing boom due to AVs 2) High User accpetance: step-bystep implementation process 3) No greater benefit in maintenance areas Realistic SAEV implementation model scenarios and assumptions Main Problems in Germany: Private car ownership, parking, public transportation capacity Electric mobility as an intermediate technology Seite 12
SUMMARY & OUTLOOK. Summary Carsharing concept as implementation platform for SAEV Systems best way to launch for the general public Different cities mean different implementation models Political regulation on SAEV is important Realistic estimation of higly and fully automated vehicle scenarios Future Work User acceptance survey SAEV traffic Simulation Seite 13