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The National Academies

NCHRP 20-102(09) [Final]

Updating Regional Transportation Planning and Modeling Tools to Address Impacts of Connected and Automated Vehicles
[ NCHRP 20-102 (Impacts of Connected Vehicles and Automated Vehicles on State and Local Transportation Agencies--Task-Order Support) ]

  Project Data
Funds: $300,000
Research Agency: Texas A&M Transportation Institute
Principal Investigator: Johanna Zmud
Effective Date: 9/7/2016
Completion Date: 6/30/2018

NOTE

The research report is published in three parts: an Executive Summary (Volume 1), the Research Report 896 (Volume 2), and a PowerPoint presentation that can be adapted for presentations to agency decision makers.

Under requirements for long-range transportation planning established by MAP-21 Federal Statewide and Metropolitan Planning regulations, state DOTs and regional MPOs are required to have a multimodal transportation plan with a minimum 20-year time horizon. Current estimates are that vehicles with varying levels of connectivity and automation will be present on the highway system in significant numbers well before the year 2035, the minimum time horizon for plans initiated in the current year. Consequently, there is an urgent need for guidance on how to incorporate the impacts of automated and connected vehicles into the planning process, especially with the aim of updating the regional modeling and forecasting processes and support the development of long-term transportation plans. 
 
The products of this task are particularly critical considering the large changes in infrastructure needs and travel demand possible with the introduction and gradual adoption of AVs and CVs. Limited experiences have been developed, to date, by some agencies and selected research institutions in this area, but the experiences to date appear to be partial, and largely based on different modeling assumptions.
 
The objective of this task was to provide support to state DOTs and regional MPOs in the form of appropriate guidelines and information related to the updates needed in their modeling and forecasting tools, to more appropriately account for the expected impacts of AV and CV on transportation supply, road capacity, and travel demand components.
 
As part of this task, the contractor developed the theoretical basis and specifications that included automated vehicles and connected vehicles as available modes in models to estimate travel demand and network performance, and identified data needs (including both an assessment of potentially already available data and data that will become available in future years) required to support the re-estimation/update of the modeling frameworks. The final report provides guidance to planning agencies, state DOT and regional MPO modeling offices and consultants, and identifies a set of guidelines that will assure appropriate updates and modifications are introduced in models used in different regions, in a consistent way across different regions and contexts.
 
The contractor worked in cooperation with the project panel in identifying the high-level goals for the development of the guidelines for updating regional transportation modeling frameworks. Based on this interaction with and feedback from the panel, the contractor defined CVs and AVs on transportation systems. Such modifications relate to robust ways to model issues that include, and are not necessarily limited to, infrastructure capacity for different road types, regulations for the use of CVs and AVs (e.g. dedicated lanes, eventual restrictions on the use of these vehicles on specific types of infrastructures, etc.), vehicle ownership, adoption of car-sharing programs, travel demand by mode, vehicle occupancy, evaluation of choice attributes, value of travel time, among others.
 
Additional considerations relevant to the development of this task included ways to realistically model (1) the market for vehicle ownership and how these vehicles will be used; (2) how AV use will impact other modes, including non-automated vehicles, transit, and non-vehicular modes; (3) the additional capabilities of CVs and AVs to adapt en-route to changing traffic conditions will require additional feedback into the models for assignment of vehicle trips to the road network.

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