Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles, Volume 2: Guidance (2018) / Chapter Skim
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Pages 53-63
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53 Overview The main focus of this chapter is on activity-based (AB) models.
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54 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles a simulation method that can represent detailed differences in the ways that human drivers and AVs will navigate road networks may be the most promising approach for learning how CAVs will influence traffic capacity and congestion levels. Modeling System Disaggregate modeling systems -- and AB and DTA models in particular -- are well suited to evaluating CAVs, with some modifications.
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Adapting Disaggregate/Dynamic Models to Address CAVs 55 Model Component Disaggregate AB/DTA Model Improvements Sociodemographics Population synthesizer Control for age and income Population synthesizer Add smartphone ownership and education level Built Environment Urban form Set place type by area type and development type Mobility Vehicle ownership Add CAVs as an option for households to own Vehicle ownership Add purchase cost, incentive policies, parking cost, or accessibility variables to distinguish vehicle type MaaS Add carsharing, ride-hailing, bikesharing memberships Activity Generation and Scheduling Activity generation Lift age restrictions for CAVs, add constraints for persons with disabilities and seniors using conventional vehicles Activity generation Adjust value of travel time (VOT) and review induced demand Activity generation Add representation of empty car trips Destination/Location Choice Work/school locations Integrate with land use model to provide sensitivity Mode Choice Mode choice Add new modes (CAVs, TNCs, shared modes, microtransit)
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56 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles also be important variables for modeling CAV use. As discussed in more detail below, age- and income-related preferences may be quite different for owning a private CAV as opposed to using CAV-based TNCs.
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Adapting Disaggregate/Dynamic Models to Address CAVs 57 it an all-or-nothing choice between owning CAVs or conventional vehicles. The left side of Figure 6 shows this structure in which a household first chooses what type of vehicles to buy and then how many.
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58 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles assumptions. It is also important to refine the assumptions over time as new data become available from stated preference surveys and (eventually)
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Adapting Disaggregate/Dynamic Models to Address CAVs 59 The current time-scheduling component focuses on schedule constraints for persons rather than vehicles. Adding new components that track vehicles would allow the models to constrain travel on the basis of which household vehicle is available -- a CAV or a conventional vehicle.
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60 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles • CAVs will increase the convenience and attractiveness of destinations in parking-constrained areas. Parking cost is currently an impediment to driving to these areas, and both AVs and TNCs will avoid parking charges.
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Adapting Disaggregate/Dynamic Models to Address CAVs 61 aggregate prices by time periods will be more effective than trying to expand the number of time periods, owing primarily to the added complexity and processing time required. Current pricing models for TNCs offer a carpool mode at a lower price; this is another complexity that may be difficult to implement as a separate mode.
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62 Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles Approach DTA can identify different vehicle-following distance and speed characteristics, depending on the level of automation. If these vehicles are traveling in mixed traffic, then overall travel times (i.e., skims)
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From page 63... ...
Adapting Disaggregate/Dynamic Models to Address CAVs 63 These pricing inputs can approximate dynamic pricing by time period. Since costs for new services are changing rapidly and the cost for CAVs is not yet set, planners should test many different pricing options to evaluate the range of expected outcomes.
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