Gil Tal

Measuring Nonmotorized Accessibility and Connectivity in a Robust Pedestrian Network

This paper explores measures of pedestrian accessibility and network connectivity with a network that includes pedestrian facilities in addition to the street network. Studies that focus on walkability usually use available street networks that do not include pedestrian-only facilities. The effect of missing pedestrian connections where the street network is richer than the pedestrian network has been examined in some studies, but the case of suburban environments with robust pedestrian networks has mostly been ignored. In the current study, various measures of connectivity and accessibility were compared between the pedestrian network and the street network in different suburban settings and for accessibility to different land use activities, such as schools and retail centers. Documenting the degree to which the pedestrian network enhanced pedestrian accessibility over the street network alone was motivated by the desire to inform research and to inform policy. Nine neighborhoods in the city of Davis, California, with typical suburban densities, a variety of street network types, and an extensive system of off-street bicycle and pedestrian facilities were used in the study. A network that included all minor and primary roads in the city plus pedestrian ways was also used. This network included 60 mi of off-street facilities and excluded freeways not open to pedestrians. Households were used as origins and schools and retail centers as destinations to demonstrate the effect of the pedestrian network on connectivity and accessibility in different parts of the city. The results of this study can be used to improve the measurement of built environment in studies of active travel and to increase understanding of the effect of the pedestrian network in the suburban environment.

Consumer Perceptions and Use of Driving Distance of Electric Vehicles: Changes over Time Through Lifestyle Learning Process

Popular media and even researchers commonly assume that ownership of a battery electric vehicle (BEV) provides consumers less performance and mobility than consumers expect. A common claim is that consumers have constant worry about the range of their BEVs, often termed “range anxiety.” BMW converted 450 Mini Coopers to all-electric drive (named the Mini E) and leased them to fleets and 235 private households in the Los Angeles, California, and New York–New Jersey regions from spring 2009 to spring 2010. Through the course of the 1-year lease, University of California, Davis (UCD), researchers conducted multiple online surveys and in-person interviews and administered weeklong driving diaries. This paper explores the reactions of Mini E drivers to the driving distance of the Mini E through the framework of a lifestyle learning process. Over time, Mini E drivers learned how the 104-mi range of the Mini E fit into their lifestyles. Drivers adapted and explored with their Mini E through activities such as altering driving behavior (such as speed and trip routes), optimizing charging opportunities, planning trips, and educating themselves on distances to destinations with the help of online and mobile mapping tools. In the course of the UCD Mini E consumer study, researchers found evidence suggesting that the driving range was not a major concern for these early adopters. Even with no public charging available to their vehicle, 100% of survey respondents stated that BEVs were suitable for daily use. The results of this study will be of interest to policy makers and practitioners interested in expanding the BEV market.

Children’s Biking for Nonschool Purposes: Getting to Soccer Games in Davis, California

In recent years, transportation planning has devoted new attention to the goal of increasing the nonmotorized trips of children and adults, both as a means of increasing physical activity and as a means of reducing motorized trips. For children, much discussion has focused on the journey to school, with little attention to nonschool trips. In this study, patterns of travel of both children and their parents to youth soccer games in Davis, California, are examined. The study aims to identify factors influencing mode choice among children and parents to soccer games for the Davis American Youth Soccer Organization. Data come from a survey of 1,084 parents accompanying their children to Saturday soccer games. Over three-quarters of players and their parents drove to the game on the day of the survey, with fewer than 20% biking. Multivariate models show that distance to games is a significant deterrent to bicycling or walking to them, while players who bike to school and whose parents regularly bicycle are significantly more likely to bicycle to games.

Charging Behavior Impacts on Electric Vehicle Miles Traveled: Who Is Not Plugging In?

The growing market for plug-in electric vehicles (PEVs) features new models of battery electric vehicles (BEVs) and plug-in hybrid electric vehicles (PHEVs) with varying battery sizes and electric driving ranges. How are the various models being used in the real world? A common assumption in PEV impact analysis is that PEV owners will maximize their vehicles utility by appropriately sizing the battery to their driving needs and by charging their vehicle as much as possible to recover the cost of the vehicle purchase. On the basis of these assumptions, a high correlation between PHEV owner use of the vehicle and the number of plug-in events is expected, and drivers of PHEVs with a small battery are expected to plug in more than do owners of vehicles with a larger battery and similar driving patterns. The assumptions presented are examined through a survey of more than 3,500 PEV owners conducted in California in May and June 2013. The online survey included extensive data on driving and charging behavior using web map questions. Owners of all PEV models on the market, including more than 600 Volts and 800 Prius Plug-Ins, were surveyed. The results show that small-battery PHEV electric vehicle miles traveled are lower than longer-range PHEV or BEV electric vehicle miles traveled not only because of battery size but also because of public charging availability and charging behavior. Higher electric-range PHEV and BEV drivers charge more often and report more charging opportunities in areas where smaller-battery PHEVs could not find chargers.

Studying the PEV market in california: Comparing the PEV, PHEV and hybrid markets

Who is buying electric vehicles? Who is buying new cars in general? Is the first group a subset of the second? What are the similarities and differences of the two groups? Can we use hybrid buyers to predict the future plug-in electric vehicle (PEV) market? This study explores the characteristics of new car buyer households who purchased a new vehicle in California during 2011-2012 comparing three main populations: internal combustion engine (ICE) buyers, hybrid buyers and PEV buyers. We show that PEV households have different socio-demographic characteristics than ICE buyers with, for example, higher income, higher education, and more new cars while hybrid owners are a middle group with characteristics that fall between those of ICE and PEV owners. We also found differences among PEV buyers. Pure battery electric vehicle (BEV) and plug-in hybrid electric (PHEV) households have similar socio-demographic characteristics but they are differentiated by driving characteristics and home location. The PEV market today is based on small number of buyers and small number of potential new car buyers. Targeting the potential car buyers can more rapidly increase the market, create a used market and will open PEV options to larger segments of the population.

Exploring the Impact of the Federal Tax Credit on the Plug-In Vehicle Market

The effect of the federal Plug-In Electric Drive Vehicle Credit on plug-in electric vehicle (PEV) sales is assessed in the United States by using an ex post stated preference survey of more than 2,882 PEV owners in 11 states. This study attributes more than 30% of the PEV sales to the federal tax credit, with an impact of up to 49% for the Nissan LEAF. The incentive shifts buyers from internal combustion engine vehicles to plug-in vehicles and advances the purchase timing of new vehicles by 1 year or more. The impact of the incentive on buyers of varying sociodemographic and vehicle choice characteristics is explored through the use of three performance measures, including number of vehicles sold, kilowatt-hours of capacity sold, and electric vehicle miles traveled per year. The results of this paper add to the discussion of the impact of monetary incentives on the alternative-fuel vehicle market and present possibilities for improving the performance of monetary incentives in the PEV market.

Electric Vehicle Fast Charger Planning for Metropolitan Planning Organizations: Adapting to Changing Markets and Vehicle Technology

Presented is a tool to estimate fast charger demand and sample results on a current and future battery electric vehicle (BEV) scenario. The results highlight the data and methods needed to plan for fast charger demand. To plan for existing BEVs, origin and destination data are necessary for identifying which traffic is relevant to assess fast-charging demand. Also, as the battery size for BEVs increases, demand shifts from primarily inside metro areas to long-distance corridors outside metro areas. The sample results show the interactions of battery size, frequency of charging, and energy needed per charge. Although energy per charge increases with battery size, overall electricity demand per vehicle decreases with larger batteries.

Reduced Overestimation in Forecasting Telecommuting as a Travel Demand Management Policy

Overestimated forecasts of the impacts of new policies, that is, over-prediction of the successes of the policies, are a well-known problem. Study of the effects of forecasting methods on potential bias may help modelers, planners, and policy makers better use forecasting tools. This paper addresses the overestimation of the success of telecommuting as a travel demand management policy. The research hypothesis underlying this study posits that overestimates of performance are virtually inevitable when the effects of new policies that aim to change travel behavior are forecast but that these biases eventually decline over time. The sources of overestimated forecasts are the prediction tools used and the ways in which modelers use these tools. The sources of the reduction in overestimation are the changes made to these tools and the knowledge and the data gained over time.

Exploring the Decision to Adopt a High-End Battery Electric Vehicle: Role of Financial and Nonfinancial Motivations

The decision to adopt a battery electric vehicle (BEV) can be influenced by a number of factors. Previous research into the decision to adopt a BEV has revealed several factors important for consumers, including financial incentives. Recently, high-end BEVs, such as the Tesla Model S, have had market success. These vehicles are remarkably different from mainstream BEVs, and the adopters of these BEVs have been overlooked within the literature. An attempt is made to understand who is adopting high-end BEVs, why they are doing so, and how important are the financial incentives for this group of adopters. Data on high-end adopters were gathered through a questionnaire, which yielded 539 responses. In-depth interviews with 33 adopters were also carried out. The following are among the findings: environmental, performance, and technological motivations are reasons for adoption; the new technology brings a new segment of buyers into the market; and financial purchase incentives are not important in the consumer’s decision to adopt a high-end BEV.

Electric Vehicle Explorer

Most HCI research related to electric vehicle adoption has focused on mitigating barriers related to vehicle range and charging infrastructure, while relatively less attention has been given to helping consumers recognize the benefits of electric vehicles. A significant benefit is reduced energy costs; however, the complexity of comparing gasoline and electricity prices makes it difficult for consumers to quantify. This paper describes and evaluates an online tool called EV Explorer that enables users to compare personalized estimates of annual energy costs for multiple vehicles. We assessed the tool through an online experiment, gauging users’ perceptions—before and after using the tool—of their current energy costs, potential savings with electric vehicles, attitude toward electric vehicle charging, and intention to buy or lease an electric vehicle in the future. Statistically significant changes in each of these variables validate the tool as an educational and persuasive strategy to promote electric vehicle adoption.