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Date | Time | Session No & Location | Title & Authors |
|---|---|---|---|
Sunday, 13 January | 1:30 PM- 5:30 PM | Convention Center, 146B | A System of Shared Autonomous Vehicles for Chicago: Anticipating Impacts at Multiple Stages of Adoption |
Monday, 14 January | 8:00 AM- 9:45 AM | Convention Center, Hall A | Competition Among Automated Taxis, Transit, and Conventional Passenger Vehicles: Traffic Effects in the San Francisco Bay Area |
8:00 AM- 9:45 AM | Convention Center, Hall A | Simulation-Optimization Framework to Evaluate a Sustainable First Mile Transit Access Program Using Shared Mobility | |
8:00 AM- 9:45 AM | Convention Center, 151A | Congestion Pricing in a World of Self-Driving Vehicles: An Analysis of Different Strategies in Alternative Future Scenarios | |
1:30 PM- 3:15 PM | Convention Center, Hall A | Operator and User Perspectives on Fleet Mix, Parking Strategy, and Drop-Off Bay Size for Autonomous Transit on Demand | |
3:45 PM- 5:30 PM | Convention Center, 151A | How Much Parking Space Can Carsharing Save? | |
Tuesday, 15 January | 8:00 AM- 9:45 AM | Convention Center, Hall A | Environmental Aspects in Integrated Land Use/Transportation Models: The Impact of Traffic Noise on Rent Prices Nico Kuehnel, Technical University of Munich |
Wednesday, 16 January | 8:00 AM - 9:45 AM | Convention Center, Hall A | Robo-Taxi Service Fleet Sizing: Assessing the Impact of User Trust and Willingness to Use Reza Vosooghi, IRT SystemX |
8:00 AM - 9:45 AM | Convention Center, Hall A | Simulating a Rich Rideshare Mobility Service Using Agent-Based Models Pau Segui-Gasco, Immense Simulations Limited, | |
10:15 AM- 12:00 PM | Convention Center, 146A | A Joint Optimization Scheme for the Planning and Operations of Shared, Autonomous, Electric Vehicle Fleets Serving Mobility on Demand | |
10:15 AM- 12:00 PM | Convention Center, 146B | Pairing Discrete Mode Choice Models and Agent-Based Transport Simulation with MATSim | |
10:15 AM- 12:00 PM | Convention Center, 146B | Microscopic Travel Demand Modeling: Using the Agility of Agent-Based Modeling Without the Complexity of Activity-Based Models |
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