Revisiting the impacts of virtual mobility on travel behavior: An exploration of daily travel time expenditures

2021 ◽  
Vol 145 ◽  
pp. 49-62
Author(s):  
Basar Ozbilen ◽  
Kailai Wang ◽  
Gulsah Akar
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Virtual Mobility ◽  
Time Expenditures ◽  
Daily Travel

Two Minutes per Person per Day Each Year

2005 ◽  
Vol 1917 (1) ◽  
pp. 45-53 ◽  
Author(s):  
Lavenia Toole-Holt ◽  
Steven E. Polzin ◽  
Ram M. Pendyala
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
The United States ◽  
Household Composition ◽  
Significant Implication ◽  
Data Set ◽  
Personal Transportation ◽  
Household Travel ◽  
Time Expenditures ◽  
Daily Travel

During the past several decades significant changes in travel behavior in the United States have occurred. Evidence from the Nationwide Personal Transportation Survey series and the 2001 National Household Travel Survey (NHTS) indicates that the average daily travel time per person has increased by 1.9 min per year between 1983 and 2001. The objective of this paper is to explore the growth of daily travel time expenditures. Changes in society, technology, incomes, attitudes, and sociodemographic and household structure have been hypothesized as having contributed to the travel time growth. This analysis explores those variables and their relationship to increases in travel time. Aggregate values are used to investigate the relationships between daily travel time expenditures and sociodemographic characteristics. This paper comments on the share of travel time growth that can be explained by the available variables and speculates on the implications of other factors on travel time expenditure growth. A review of the NHTS data set and an analysis of the relationships between the data set and travel time expenditures make clear that travel budget changes that appear to be related to the set of available variables do not explain the full reason for the significant increase in travel time spending. The increases are across all market segments: age, income, gender, ethnicity, household composition, and so on. Thus, shifts in demographic or other traveler conditions do not fully explain the increases in trip making. That has a significant implication for transportation planning–-traditional sociodemographic predictors for trip making do not appear to be sufficiently causal to be useful for understanding current and future factors influencing trip making and travel expenditure changes.

Investigating the Effects of Reserved Lanes for Autonomous Vehicles on Congestion and Travel Time Reliability

2017 ◽  
Vol 2622 (1) ◽  
pp. 1-12 ◽  
Author(s):  
Alireza Talebpour ◽  
Hani S. Mahmassani ◽  
Amr Elfar
Keyword(s):  
Travel Time ◽  
Autonomous Vehicles ◽  
Potential Benefit ◽  
Flow Dynamics ◽  
System Level ◽  
Market Penetration ◽  
Travel Time Reliability ◽  
Fundamental Diagram ◽  
Mandatory Use ◽  
Daily Travel

Autonomous vehicles are expected to influence daily travel significantly. Despite autonomous vehicles’ potential to enhance safety and to reduce congestion, energy consumption, and emissions, many studies suggest that the system-level effects will be minimal at low market penetration rates. Introducing reserved lanes for autonomous vehicles is one potential approach to address this limitation because these lanes increase autonomous vehicles’ density. However, preventing regular vehicles from using specific lanes can significantly increase congestion in other lanes. Accordingly, this study explored the potential effects of reserving one lane for autonomous vehicles on traffic flow dynamics and travel time reliability. A two-lane hypothetical segment with an on-ramp and a four-lane highway segment in Chicago, Illinois, was simulated under different market penetration rates of autonomous vehicles. Three strategies were evaluated: ( a) mandatory use of the reserved lane by autonomous vehicles, ( b) optional use of the reserved lane by autonomous vehicles, and (c) limiting autonomous vehicles to operate autonomously in the reserved lane. Policies based on combinations of these strategies were simulated. It was found that optional use of the reserved lane without any limitation on the type of operation could improve congestion and could reduce the scatter in a fundamental diagram. Throughput analysis showed the potential benefit of reserving a lane for autonomous vehicles at market penetration rates of more than 50% for the two-lane highway and 30% for the four-lane highway. Travel time reliability analysis revealed that the optional use of the reserved lane was also significantly beneficial.

A Modeling Analysis of Impact from E-Hailing Service on Non-Work Travel Mode in Shanghai, China

2018 ◽  
Vol 2672 (47) ◽  
pp. 125-134 ◽  
Author(s):  
Jiayu Zhong ◽  
Xin Ye ◽  
Ke Wang ◽  
Dongjin Li
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Choice Model ◽  
Mode Choice ◽  
Rapid Development ◽  
Influential Factors ◽  
Travel Mode ◽  
Explanatory Variables ◽  
Bus Travel Time ◽  
Vehicle Travel Time

With the rapid development of mobility services, e-hailing service have been highly prevalent and e-hailing travel has become a part of daily life in many cities in China. At the same time, travelers’ mode choice behaviors have been influenced to some degree by different factors, and in this paper, a web-based retrospective survey initially conducted in Shanghai, China is used to analyze the extent to which various factors are influencing mode choice behaviors. Then, a multinomial-logit-based mode choice model is developed to incorporate the e-hailing auto mode as a new travel mode for non-work trips. The developed model can help to identify influential factors and quantify their impact on mode choice probabilities. The developed model involves a variety of explanatory variables including e-hailing/taxi fare, bus travel time, rail station access/egress distance, trip distance, car in-vehicle travel time as well as travelers’ socioeconomic and demographic characteristics, etc. The model indicates that the e-hailing fare, travel companions and some travelers’ characteristics (e.g., age, income, etc.) are significant factors influencing the choice of e-hailing mode. The alternative-specific constant in the e-hailing utility equation is adjusted to match the observed market share of the e-hailing mode. Based on the developed model, elasticities of LOS attributes are computed and discussed. The research methods used in this paper have the potential to be applied to investigate travel behavior changes under the influence of emerging travel modes. The research findings can aid in evaluating policies to manage e-hailing services and improve their levels of services.

Quantifying the Impact of the COVID-19 Pandemic on Passenger Vehicle Drivers’ Willingness to Pay for Travel Time Savings and Reliability

2021 ◽  
pp. 036119812110388
Author(s):  
Tristan Cherry ◽  
Mark Fowler ◽  
Claire Goldhammer ◽  
Jeong Yun Kweun ◽  
Thomas Sherman ◽  
...  
Keyword(s):  
Willingness To Pay ◽  
Travel Time ◽  
Travel Behavior ◽  
Local Governments ◽  
Consumer Preferences ◽  
Stated Preference ◽  
Travel Time Reliability ◽  
Travel Time Savings ◽  
Time Savings ◽  
The Impact

The COVID-19 pandemic has fundamentally disrupted travel behavior and consumer preferences. To slow the spread of the virus, public health officials and state and local governments issued stay-at-home orders and, among other actions, closed nonessential businesses and educational facilities. The resulting recessionary effects have been particularly acute for U.S. toll roads, with an observed year-over-year decline in traffic and revenue of 50% to 90% in April and May 2020. These disruptions have also led to changes in the types of trip that travelers make and their frequency, their choice of travel mode, and their willingness to pay tolls for travel time savings and travel time reliability. This paper describes the results of travel behavior research conducted on behalf of the Virginia Department of Transportation before and during the COVID-19 pandemic in the National Capital Region of Washington, D.C., Maryland, and Northern Virginia. The research included a stated preference survey to estimate travelers’ willingness to pay for travel time savings and travel time reliability, to support forecasts of traffic and revenue for existing and proposed toll corridors. The survey collected data between December 2019 and June 2020. A comparison of the data collected before and during the pandemic shows widespread changes in travel behavior and a reduction in willingness to pay for travel time savings and travel time reliability across all traveler types, particularly for drivers making trips to or from work. These findings have significant implications for the return of travelers to toll corridors in the region and future forecasts of traffic and revenue.

Performance Analyses of Information-Based Managed Lane Choice Decisions in a Connected Vehicle Environment

2020 ◽  
Vol 2674 (11) ◽  
pp. 120-133 ◽  
Author(s):  
Xiaoyu Guo ◽  
Yongxin Peng ◽  
Sruthi Ashraf ◽  
Mark W. Burris
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Information Exchange ◽  
Traffic Management ◽  
Connected Vehicle ◽  
Market Penetration ◽  
Performance Measurements ◽  
Time Saving ◽  
Travel Time Savings ◽  
Time Savings

Connected vehicle (CV) technology can connect, communicate, and share information between vehicles, infrastructure, and other traffic management systems. Recent research has examined and promoted CV and connected automated vehicle (CAV) technology on managed lane systems to increase capacity and reduce congestion, as managed lane systems could be equipped with advanced infrastructure relatively quickly. However, the effect on travel considering, information-based managed lane choice decisions in a CV environment is not clear. Therefore, this research analyzed the potential effects on a managed lane system with connected vehicles considering several travel behavior elements, including drivers’ willingness to reroute and their choice of managed lanes based on individual travel time savings. This study analyzed the potential effects on a managed lane system by assigning different market penetration rates (0%, 10%, 50%, 100%) of CVs and informing CV drivers about travel time savings for a 10-mi stretch at 5-min intervals. How the traffic performance measurements (i.e., throughput, travel time saving, average speed and average travel time) vary under different market penetration rates of CVs is then investigated. Two major conclusions are reached: (i) although information exchange was assumed to be instantaneous between vehicles and the system, there existed a response time (or time delay) in the macroscopic traffic reflection; (ii) managed lane use may decrease, when travel time information becomes available, since drivers perceive they are saving more travel time than they actually do save.

scholarly journals Travel Behavior Analysis Using 2016 Qingdao’s Household Traffic Surveys and Baidu Electric Map API Data

2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Ge Gao ◽  
Zhen Wang ◽  
Xinmin Liu ◽  
Qing Li ◽  
Wei Wang ◽  
...  
Keyword(s):  
Statistical Analysis ◽  
Field Study ◽  
Behavior Analysis ◽  
Travel Time ◽  
Travel Behavior ◽  
High Accuracy ◽  
Travel Distance ◽  
Distance Analysis ◽  
Trip Time ◽  
Time Information

Household traffic surveys are widely used in travel behavior analysis, especially in travel time and distance analysis. Unfortunately, any one kind of household traffic surveys has its own problems. Even all household traffic survey data is accurate, it is difficult to get the trip routes information. To our delight, electric map API (e.g., Google Maps, Apple Maps, Baidu Maps, and Auto Navi Maps) could provide the trip route and time information, which remedies the traditional traffic survey’s defect. Thus, we can take advantage of the two kinds of data and integrate them into travel behavior analysis. In order to test the validity of the Baidu electric map API data, a field study on 300 taxi OD pairs is carried out. According to statistical analysis, the average matching rate of total OD pairs is 90.74%, which reflects high accuracy of electric map API data. Based on the fused data of household traffic survey and electric map API, travel behavior on trip time and distance is analyzed. Results show that most purposes’ trip distances distributions are concentrated, which are no more than 10 kilometers. It is worth noting that students have the shortest travel distance and company business’s travel distance distribution is dispersed, which has the longest travel distance. Compared to travel distance, the standard deviations of all purposes’ travel time are greater than the travel distance. Car users have longer travel distance than bus travelers, and their average travel distance is 8.58km.

Anticipated Travel Time, Information Acquisition, and Actual Experience: Hanshin Expressway Route Closure, Osaka-Sakai, Japan

2000 ◽  
Vol 1725 (1) ◽  
pp. 79-85 ◽  
Author(s):  
Satoshi Fujii ◽  
Ryuichi Kitamura
Keyword(s):  
Travel Time ◽  
Travel Behavior ◽  
Information Acquisition ◽  
Information Support ◽  
Travel Times ◽  
Driving Experience ◽  
Actual Experience ◽  
Central Business Districts ◽  
Travel Decision ◽  
Types Of Information

Travel time is one of the most fundamental and important determinants of travel behavior. However, the travel time on which a travel decision is based is a subjective one (i.e., it is an anticipated travel time). A conceptual model of the formation of an anticipated travel time through information acquisition and initial driving experience is proposed. Day-to-day data of anticipated travel times were collected during a closure of the Hanshin Expressway Sakai Route, a toll road connecting the central business districts of Osaka and Sakai, which is located approximately 20 km south of the Osaka route closure. A test was conducted of the information dominance hypothesis (i.e., as drivers acquire more information on travel time, they can predict travel time more precisely and refer less to anticipated travel times used in the past to anticipate travel times) and the experience dominance hypothesis (i.e., influences of information not from driving experience on anticipated travel time is weaker with actual driving experience than without actual experience). Although word of mouth information does not have impacts consistent with these two hypotheses, results with other types of information support both hypotheses.

Toward More Sustainable Behavior: A Systematic Review of the Impacts of Involuntary Workplace Relocation on Travel Mode Choice

2018 ◽  
Vol 34 (1) ◽  
pp. 38-58 ◽  
Author(s):  
Z. Zarabi ◽  
S. Lord
Keyword(s):  
Systematic Review ◽  
Travel Behavior ◽  
Mode Choice ◽  
Travel Mode ◽  
Travel Mode Choice ◽  
Home Work ◽  
Habitual Behavior ◽  
Sustainable Behavior ◽  
Transport Modes ◽  
Daily Travel

Daily home–work travel is a habitual behavior that can be disrupted when the location of work, as one of the behavioral contexts, changes. It is then likely that individuals will reconsider their travel behavior more intentionally and choose alternative transport modes. To identify motivations and barriers to incorporating the use of sustainable modes into the individual’s daily travel, this article systematically reviews the literature on the impacts of involuntary workplace relocation on commuting behavior. Effective measures that incentivize sustainable commuting behavior are also discussed. This study on involuntary workplace relocation informs considerations of changes in travel behavior related to other contextual changes.

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