Mobility Behavior Responses to TNC Services

Tom Wenzel; Alejandro Henao

Mobility Behavior Responses to TNC Services

Tom Wenzel, Alejandro Henao

Center for Integrated Mobility Sciences

Lawrence Berkeley National Laboratory

Research output: NREL › Management

Abstract

Transportation Network Companies (TNC) that provide ridesourcing/ridehailing services such as Uber and Lyft are becoming a popular alternative to conventional modes of personal transportation. However, there are scarce data and little research conducted to understand travelers’ choice of this transportation mode and impacts on travel behavior and energy consumption. This task analyzes the relationship between the supply of TNCs in a region and impacts on mobility and travel behavior (e.g., vehicle ownership, deadheading, vehicle miles of travel or VMT) and energy use. The results are useful as inputs for travel activity models used in other pillars (e.g., BEAM and POLARIS) to test the sensitivity of the availability of these services to travel and energy use.

Original language	American English
Number of pages	11
State	Published - 2020

Bibliographical note

See the Vehicle Technologies Office Energy Efficient Mobility Systems 2019 Annual Progress Report at https://www.energy.gov/sites/prod/files/2020/06/f76/VTO_2019_APR_EEMS_COMPILED_REPORT_FINAL_compliant_.pdf

NREL Publication Number

NREL/MP-5400-78657

Keywords

mobility
personal transportation
transportation network companies
travel behavior

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Cite this

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title = "Mobility Behavior Responses to TNC Services",

abstract = "Transportation Network Companies (TNC) that provide ridesourcing/ridehailing services such as Uber and Lyft are becoming a popular alternative to conventional modes of personal transportation. However, there are scarce data and little research conducted to understand travelers{\textquoteright} choice of this transportation mode and impacts on travel behavior and energy consumption. This task analyzes the relationship between the supply of TNCs in a region and impacts on mobility and travel behavior (e.g., vehicle ownership, deadheading, vehicle miles of travel or VMT) and energy use. The results are useful as inputs for travel activity models used in other pillars (e.g., BEAM and POLARIS) to test the sensitivity of the availability of these services to travel and energy use.",

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T1 - Mobility Behavior Responses to TNC Services

AU - Wenzel, Tom

AU - Henao, Alejandro

N1 - See the Vehicle Technologies Office Energy Efficient Mobility Systems 2019 Annual Progress Report at https://www.energy.gov/sites/prod/files/2020/06/f76/VTO_2019_APR_EEMS_COMPILED_REPORT_FINAL_compliant_.pdf

PY - 2020

Y1 - 2020

N2 - Transportation Network Companies (TNC) that provide ridesourcing/ridehailing services such as Uber and Lyft are becoming a popular alternative to conventional modes of personal transportation. However, there are scarce data and little research conducted to understand travelers’ choice of this transportation mode and impacts on travel behavior and energy consumption. This task analyzes the relationship between the supply of TNCs in a region and impacts on mobility and travel behavior (e.g., vehicle ownership, deadheading, vehicle miles of travel or VMT) and energy use. The results are useful as inputs for travel activity models used in other pillars (e.g., BEAM and POLARIS) to test the sensitivity of the availability of these services to travel and energy use.

AB - Transportation Network Companies (TNC) that provide ridesourcing/ridehailing services such as Uber and Lyft are becoming a popular alternative to conventional modes of personal transportation. However, there are scarce data and little research conducted to understand travelers’ choice of this transportation mode and impacts on travel behavior and energy consumption. This task analyzes the relationship between the supply of TNCs in a region and impacts on mobility and travel behavior (e.g., vehicle ownership, deadheading, vehicle miles of travel or VMT) and energy use. The results are useful as inputs for travel activity models used in other pillars (e.g., BEAM and POLARIS) to test the sensitivity of the availability of these services to travel and energy use.

KW - mobility

KW - personal transportation

KW - transportation network companies

KW - travel behavior

M3 - Management

ER -

Mobility Behavior Responses to TNC Services

Abstract

Bibliographical note

NREL Publication Number

Keywords

UN SDGs

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Cite this