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This paper explores the possibility of using subway maps as a planning tool to influence passenger route choice to mitigate congestion. Specifically, it tests whether extending the appearance of an overcrowded subway line on the Washington DC subway map would encourage passengers to use other underutilized lines. The experiment was conducted through the Mechanical Turk, a crowdsourcing platform, with 3056 participants, producing 21,240 route choice decisions on the official and six alternative maps. Results show that redesigned maps significantly affect participants’ route choices. Depending on the specific design, a 20% length increase of the overcrowded line could move 1.9–5.7 percentage points of ridership to an alternative, underutilized line. The change could remove up to 10 passengers per car during the highest peak, reducing the number of highly congested half-hour periods (max load = 100–120 passengers per car) on the overcrowded line from 4 to 1, and the number of crush periods (max load > 120 passengers per car) from 3 to 1. This is done at minimal or zero cost. The paper calls for more attention from transit agencies to the planning potential of transit maps. [ABSTRACT FROM AUTHOR]

The initial public offerings (IPOs) of Uber and Lyft in 2019 marked a milestone for the decade-old ridesourcing. As we start to embrace ridesourcing in our daily life, we also rearrange our daily travel amongst different modes of transportation. As the fundamental decisions in travel behavior, car ownership and car travel should be re-examined in the advent of shared mobility. In this paper, we applied a vehicle choice model that factors in ridesourcing frequency to understand the decisions about (1) how many cars an individual would declare as the primary driver of, and (2) the annual vehicle miles traveled (VMT) for all cars he or she drive. We used a subsample of the latest 2017 National Household Travel Survey (NHTS) data that focus on the Capital region (Washington, D.C. – Maryland – Virginia) as our study area. We applied a weighted regression analysis following the NHTS survey design and derived population-representative results on both decisions. In addition, we calculated the driving cost for each household vehicle based on the latest fuel economy data and incorporated driving cost into the car travel model. The results suggest that ridesourcing is associated with a smaller chance of an individual being the primary driver of a car. However, the elasticity indicates that ridesourcing usage has a small impact on the number of primarily driven cars. Furthermore, ridesourcing has no significant impact on the annual VMT, either. Driving cost, on the other hand, still plays the key role in determining driving distances. [ABSTRACT FROM AUTHOR]

• Hourly number of trips and median duration of trips for Dockless Scooter Share (DSS) and Station Based Bikeshare (SBBS) are analyzed. • DSS users behave more similarly to non-member SBBS users than to member SBBS users. • Weather is less of a disutility for DSS users than for SBBS users, regardless of membership type. • All micromobility user types are positively impacted by changing gas prices, although DSS users are more sensitive both in terms of trip count and median duration. • DSS and non-member SBBS users appear to have a competing relationship while DSS and member SBBS users appear to have a complementary relationship. Dockless, or free-floating mobility has gained unprecedented popularity in the last year, from being virtually non-existent in 2017 to facilitating over 38.5 million trips in 2018. Hitherto, few studies have analyzed dockless micromobility, and scooter-share particularly using big data. This paper analyzes and compares the determinants of dockless scooters-share (DSS) and of station-based bike-share (SBBS) rides in D.C. It made use of API data from dockless vendors and historical trip data from Capital Bikeshare from December 2018 to June 2019. Two variables were estimated: hourly number of trips and hourly median duration of trips. A negative-binomial regression model was performed at the hourly scale controlling for environmental and economic variables including weather-related data, gasoline prices, local events or disturbances, day of week, and time of day. Four groups were analyzed: all of micromobility combined and weighed, SBBS members, SBBS non-members, and DSS. Three important findings emerged: (1) Temporal use differences between the three user groups were found, but DSS users behave most similarly to SBBS non-members. (2) Weather is less of a disutility for DSS users than for SBBS users. We attribute this to the physical ease of using a scooter and to the convenience of ending a trip at the actual destination rather than a nearby docking station. (3) All micromobility user types are sensitive to changing gas prices, although DSS users appear slightly more sensitive both in terms of trip count and duration. Additionally, an analysis of the interaction between modes found a possible competition between DSS and SBBS non-members and a complementary relationship between DSS and SBBS members. We conclude that significant differences exist between the two modes, and combined with its sudden and rising popularity, micromobility and DSS in particular could have a major role in promoting a shift towards low-carbon mobility. [ABSTRACT FROM AUTHOR]

Abstract: An increasing number of legislative efforts have been undertaken to prohibit the use of hand-held wireless devices while driving. As of July 2012, ten states and the District of Columbia enforce laws banning the use of hand-held cell phones while driving. Thirty-nine states and the District of Columbia have banned text messaging while driving. Recent studies of driver behavior suggest that hand-held wireless device usage negatively impacts driver performance. However few studies at the aggregate level address the plausible link between the use of hand-held wireless devices while driving, increased risk of automobile accidents, and government legislative efforts to reduce such risk. This paper analyzes data at the aggregate level and builds a regression model to estimate the long term accident rate reduction due to a hand-held ban. This model differs from previous studies, which consider short term accident rate reduction, by considering time trends in the accident rate due to the ban. Additionally, counties considered in this analysis are placed into groups based on driver density, defined by the number of licensed drivers per centerline mile of roadway, and a separate analysis is performed within these groups. This approach allows one to better quantify the effect of hand-held bans in counties of different driver densities. Results from this paper suggest that bans on hand-held wireless device use while driving reduce the rate of personal injury accidents in counties with high levels of driver density, but may increase accident rates in counties with low driver density levels. These results can inform transportation policymakers interested in reducing automobile-accident-risk attributable to the use of hand-held wireless devices while driving. [Copyright &y& Elsevier]

Abstract: Despite considerable interest in the role of social interactions and social context on transportation, there have been very few attempts to explore specific cases of social interaction influencing transportation systems. This paper explores the social practice of slugging, an informal system of carpooling in the Washington, DC area. Slugging emerged in response to the establishment of Virginia’s High Occupancy Vehicle (HOV) lanes in the early 1970s, as single drivers picked up riders alongside the road (slugs) in order to meet the requirements for driving in the less congested HOV lanes. Drawing on the work of sociologist Anthony Giddens, as well as the sociological insights of Georg Simmel and Stanley Milgram, we suggest that the practice of slugging highlights the processes of institutionalization and structuration. This paper details how the region’s mass transportation policies and urban culture have combined to result in an institutionalized practice with particular norms and logics of behavior. We conclude that looking at specific cases where social context has affected transportation, like slugging, could provide useful insights on the impact of social context on transportation policies and systems. [Copyright &y& Elsevier]

Abstract: As of November 2008, the number of cell phone subscribers in the US exceeded 267 million, nearly three times more than the 97 million subscribers in June 2000. This rapid growth in cell phone use has led to concerns regarding their impact on driver performance and road safety. Numerous legislative efforts are under way to restrict hand-held cell phone use while driving. Since 1999, every state has considered such legislation, but few have passed primary enforcement laws. As of 2008, six states, the District of Columbia (DC), and the Virgin Islands have laws banning the use of hand-held cell phones while driving. A review of the literature suggests that in laboratory settings, hand-held cell phone use impairs driver performance by increasing tension, delaying reaction time, and decreasing awareness. However, there exists insufficient evidence to prove that hand-held cell phone use increases automobile-accident-risk. In contrast to other research in this area that uses questionnaires, tests, and simulators, this study analyzes the impact of hand-held cell phone use on driving safety based on historical automobile-accident-risk-related data and statistics, which would be of interest to transportation policy-makers. To this end, a pre-law and post-law comparison of automobile accident rate measures provides one way to assess the effect of hand-held cell phone bans on driving safety; this paper provides such an analysis using public domain data sources. A discussion of what additional data are required to build convincing arguments in support of or against legislation is also provided. [Copyright &y& Elsevier]