Investigating autonomous vehicle impacts on individual activity-travel behavior

2021 ◽  
Vol 148 ◽  
pp. 402-422
Author(s):  
Katherine A. Dannemiller ◽  
Aupal Mondal ◽  
Katherine E. Asmussen ◽  
Chandra R. Bhat
2016 ◽  
Vol 38 (1) ◽  
pp. 6-12 ◽  
Author(s):  
Adam Millard-Ball

Autonomous vehicles, popularly known as self-driving cars, have the potential to transform travel behavior. However, existing analyses have ignored strategic interactions with other road users. In this article, I use game theory to analyze the interactions between pedestrians and autonomous vehicles, with a focus on yielding at crosswalks. Because autonomous vehicles will be risk-averse, the model suggests that pedestrians will be able to behave with impunity, and autonomous vehicles may facilitate a shift toward pedestrian-oriented urban neighborhoods. At the same time, autonomous vehicle adoption may be hampered by their strategic disadvantage that slows them down in urban traffic.


Author(s):  
Jesse Cohn ◽  
Richard Ezike ◽  
Jeremy Martin ◽  
Kwasi Donkor ◽  
Matthew Ridgway ◽  
...  

As investments in autonomous vehicle (AV) technology continue to grow, agencies are beginning to consider how AVs will affect travel behavior within their jurisdictions and how to respond to this new mobility technology. Different autonomous futures could reduce, perpetuate, or exacerbate existing transportation inequities. This paper presents a regional travel demand model used to quantify how transportation outcomes may differ for disadvantaged populations in the Washington, D.C. area under a variety of future scenarios. Transportation performance measures examined included job accessibility, trip duration, trip distance, mode share, and vehicle miles traveled. The model evaluated changes in these indicators for disadvantaged and non-disadvantaged communities under scenarios when AVs were primarily single-occupancy or high-occupancy, and according to whether transit agencies responded to AVs by maintaining the status quo, removing low-performing routes, or applying AV technology to transit vehicles. Across the performance measures, the high-occupancy AV and enhanced transit scenarios provided an equity benefit, either mitigating an existing gap in outcomes between demographic groups or reducing the extent to which that gap was expanded.


Author(s):  
Olu Ashiru ◽  
John W. Polak ◽  
Robert B. Noland

Accessibility is a fundamental concept in human existence, which goes to the heart of the notion of society, equity, and justice. However, despite the importance of the concept, the mathematical measures that have historically been used to quantify accessibility levels have been relatively poorly defined and have encompassed a limited range of observed forms of travel behavior. Existing space–time locational benefit measures are extended to encapsulate more realistic temporal constraints on activity participation and the associated perceived user benefit. The development of a family of space–time route benefit measures is outlined. Despite their apparent theoretical attractiveness, hitherto researchers have not used such measures. It is demonstrated how these route benefit measures can be used to develop an associated family of disaggregate activity-based space–time utility accessibility measures applicable to individual activity schedules and how income constraints can be incorporated within the space–time utility accessibility measures. Finally, the means by which stochastic frontier models can be used in conjunction with existing travel–activity diary data sets to operationalize the proposed measure of accessibility are briefly described.


2019 ◽  
Vol 11 (1) ◽  
pp. 9
Author(s):  
Ehsan Sabri Islam ◽  
Ayman Moawad ◽  
Namdoo Kim ◽  
Aymeric Rousseau

Transportation system simulation is a widely accepted approach to evaluate the impact of transport policy deployment. In developing a transportation system deployment model, the energy impact of the model is extremely valuable for sustainability and validation. It is expected that different penetration levels of Connected-Autonomous Vehicles (CAVs) will impact travel behavior due to changes in potential factors such as congestion, miles traveled, etc. Along with such impact analyses, it is also important to further quantify the regional energy impact of CAV deployment under different factors of interest. The objective of this paper is to study the energy consumption of electrified vehicles in the future for different penetration levels of CAVs deployment in the City of Chicago. The paper will further provide a statistical analysis of the results to evaluate the impact of the different penetration levels on the different electrified powertrains used in the study.


Author(s):  
Patrícia S. Lavieri ◽  
Venu M. Garikapati ◽  
Chandra R. Bhat ◽  
Ram M. Pendyala ◽  
Sebastian Astroza ◽  
...  

Considerable interest exists in modeling and forecasting the effects of autonomous vehicles on travel behavior and transportation network performance. In an autonomous vehicle (AV) future, individuals may privately own such vehicles, use mobility-on-demand services provided by transportation network companies that operate shared AV fleets, or adopt a combination of those two options. This paper presents a comprehensive model system of AV adoption and use. A generalized, heterogeneous data model system was estimated with data collected as part of the Puget Sound, Washington, Regional Travel Study. The results showed that lifestyle factors play an important role in shaping AV usage. Younger, urban residents who are more educated and technologically savvy are more likely to be early adopters of AV technologies than are older, suburban and rural individuals, a fact that favors a sharing-based service model over private ownership. Models such as the one presented in this paper can be used to predict the adoption of AV technologies, and such predictions will, in turn, help forecast the effects of AVs under alternative future scenarios.


Author(s):  
Yanbo Ge ◽  
Andisheh Ranjbari ◽  
Elyse O’C. Lewis ◽  
Eric Barber ◽  
Don MacKenzie

With the goal of understanding autonomous vehicle (AV) adoption and use behavior, numerous behavioral studies and surveys have included variables intended to capture individuals’ perceptions of and attitudes toward AVs. However, the selection of questions to measure these psychometric variables appears to be ad hoc and, in many cases, arbitrary. In contrast, this study defines psychometric latent variables (LVs) that are related to the adoption and use of AVs and develops a set of questions to reliably measure them. By considering three psychological concepts (norms, perceptions, and attitudes) and nine qualitative utility constructs that influence individuals’ travel behavior, this study defines a comprehensive list of LVs and identifier questions to support their construction. A factor analysis of a nationwide n = 347 sample was used to obtain a minimum set of relevant LVs and questions to measure them. Ultimately, the factor analysis resulted in a final set of nine LVs specified by 44 questions (four or five questions for each LV). The final set of questions may be used by researchers or survey organizations interested in studying future trends of demand and adoption for AVs or other emerging transportation modes. The approach used in this study may also be employed in other contexts to define psychometric variables of interest and the questions needed to reliably measure them.


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