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on Transport Economics |
| By: | Circella, Giovanni; Iogansen, Xiatian; Matson, Grant; Malik, Jai; Etezady, Ali |
| Abstract: | Emerging transportation services, whose development and adoption have been enabled by information and communication technology, are largely transforming people’s travel and activity patterns. This study investigates the emerging transportation trends and how they transform travel-related decision-making in the population at large through the application of a unique longitudinal approach. As part of this project, a second wave of data collection in 2018 was built with a rotating panel structure as a continuation of the research efforts that started with the collection of the 2015 California Millennials Dataset. This report focuses on the analyses of the data collected in this project, in particular on the differences in attitudes towards transportation and the environment among different generational groups, the adoption and use of shared mobility services, and their relationship with vehicle ownership, the interest in the adoption of alternative fuel vehicles, and the interest in the future adoption of connected and automated vehicles. Due to the small number of respondents who participated in both surveys, for the purposes of the analyses contained in this report, we treated the data as repeated cross-sectional and analyzed the data from each survey separately. The study helps researchers evaluate the complex relationship between observed/latent characteristics and individual travel-related choices and decision-making. The study highlights attitudinal and mode-choice differences across generations. It explores the factors impacting current adoption of and future interest in new transportation technology including alternative fuel vehicles, automated vehicles and shared mobility. Divergent consumer segments are witnessed within each of these markets, with distinctive socio-demographics, latent attitudes, built environment, and level of familiarity with new technologies, which shape the uniqueness of their vehicle ownership, residential location, travel behavior, activity patterns, and lifestyle. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Longitudinal Data, Cross-sectional Data, Millennials, Individual Lifestyles, Shared Mobility, Travel Behavior, Vehicle Ownership |
| Date: | 2021–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt2j33z72p&r= |
| By: | Carlo Cenedese; Patrick Stokkink; Nikolas Gerolimins; John Lygeros |
| Abstract: | We propose an incentive-based traffic demand management policy to alleviate traffic congestion on a road stretch that creates a bottleneck for the commuters. The incentive targets electric vehicles owners by proposing a discount on the energy price they use to charge their vehicles if they are flexible in their departure time. We show that, with a sufficient monetary budget, it is possible to completely eliminate the traffic congestion and we compute the optimal discount. We analyse also the case of limited budget, when the congestion cannot be completely eliminated. We compute analytically the policy minimising the congestion and estimate the level of inefficiency for different budgets. We corroborate our theoretical findings with numerical simulations that allow us to highlight the power of the proposed method in providing practical advice for the design of policies. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2111.05600&r= |
| By: | Bishop, Matt |
| Abstract: | As new mobility services such as ridehailing and shared micromobility have grown, so has the quantity of data available about how and where people travel. Transportation data provides government agencies and transportation companies with valuable information that can be used for identifying traffic patterns, predicting infrastructure needs, informing city planning, and other purposes. However, the data may also contain sensitive information that can identify individuals, the beginning and ending points of their trips, and other details that raise concerns about personal privacy. Even if a traveler’s name and address is suppressed, adversaries could use other parts of the information such as trip origin and destination to learn an individual’s identity and their habits. Similarly, another transportation company competing with the company that collected the data could potentially steal their customer base if they can use the data to obtain proprietary information such as frequent dropoff/pick-up locations, vehicle positioning, travel routes, or algorithms for assigning vehicles to clients. |
| Keywords: | Engineering |
| Date: | 2021–11–05 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt5rh4p7cw&r= |
| By: | Sanghamitra Mukherjee |
| Abstract: | This work studies the role of socio-economic and geospatial factors in shaping battery electric vehicle adoption for the case study of Ireland. It provides new insights on the level and timing of likely adoption at scale using a Bass diffusion model combined with a spatial model. The Bass model demonstrates that a country like Ireland may experience peak sales between 2025 and 2030 given current trends, reaching overall uptake levels that are not commensurate with current policy goals, whilst also potentially creating gulfs in regional take-up. The key conclusion from the spatial analysis is that location matters for uptake, through various channels that help or hinder adoption such as resources, information, and policy. Additional investment in public charging infrastructure facilities may also be needed as gaps in coverage exist, especially in rural areas to the West and South-West of the country. Although Ireland enjoys good network coverage overall, this study suggests that more charge points may be needed in some counties and Dublin city and suburbia where the number of charge points is currently disproportionate to a minimum network coverage comparable with the land area, population size, number of private vehicle owners, and travel behaviour. As the urgency for climate action intensifies in the coming decade, our spatio-temporal approach to studying uptake will not only help meet Ireland’s socio-ecological vision for the future, but also provide insights and strategies for comparable countries that are similarly placed in terms of electric vehicle adoption. |
| Keywords: | Battery electric vehicle adoption; Spatial analysis; Consumer behaviour; Bass diffusion model; Ireland |
| JEL: | D1 D9 O3 Q4 |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ucn:wpaper:202119&r= |
| By: | Bishop, Matt |
| Abstract: | Data about mobility provides information to improve city planning, identify traffic patterns, detect traffic jams, and route vehicles around them. This data often contains proprietary and personal information that companies and individuals do not wish others to know, for competitive and personal reasons. This sets up a paradox: the data needs to be analyzed, but it cannot be without revealing information that must be kept secret. A solution is to sanitize the data—i.e., remove or suppress the sensitive information. The goal of sanitization is to protect sensitive information while enabling analyses of the data that will produce the same results as analyses of the unsanitized data. However, protecting information requires that sanitized data cannot be linked to data from other sources in a manner that leads to desanitization. This project reviews typical strategies used to sanitize datasets, the research on how some of these strategies are unsuccessful, and the questions that must be addressed to better understand the risks of desanitization. |
| Keywords: | Engineering, Data, traffic data, data sharing, data cleaning, data fusion, data privacy, computer security, transportation planning |
| Date: | 2021–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt6ct4b3g9&r= |
| By: | Jan K. Brueckner; Achim I. Czerny; Alberto A. Gaggero |
| Abstract: | This paper offers a simple approach for identifying propagated departure delays and measuring their contribution to arrival delays. Under our approach, a propagated departure delay occurs when the arrival delay of the inbound flight exceeds the subsequent flight’s ground buffer. The size (or frequency) of such propagated delays relative to the size (or frequency) of arrival delays then measures the contribution of propagated delays to late arrivals. This approach differs from earlier attempts to quantify the contribution of delay propagation since it focuses on an individual flight and its immediate predecessor, without attempting to trace the sources of delay propagation back through the entire sequence of prior flights. The paper’s empirical results show that the contribution of propagated departure delays to arrival delays depends on several key determinants. |
| JEL: | L93 R41 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:ces:ceswps:_9369&r= |
| By: | Xi He (Center for Agricultural and Rural Development (CARD) at Iowa State University); Guilherme DePaula (Center for Agricultural and Rural Development (CARD) at Iowa State University); Wendong Zhang (Center for Agricultural and Rural Development (CARD) at Iowa State University) |
| Abstract: | In 2013, Brazil surpassed the United States to become the world's largest soybean exporter. Brazil's soybean production and exports have accelerated since its trade liberalization in the mid-1990s, and it has gained extra competitiveness over the United States in the export market during the US-China trade war, when China imposed several waves of retaliatory tariffs on US soybeans. For interested readers, a tool is available on the CARD website that shows historical revealed comparative advantages for six leading export countries. In the 2019/20 marketing year, Brazil's soybean exports reached 92 million metric tons, about twice that of US soybean exports. While Brazil's increasing competitiveness in the oilseed market depends critically on its advanced soybean production technology, its adaptation of a double-cropping soy-corn system in the savanna, extended periods of currency depreciation, and declining transportation costs resulting from expanding transportation infrastructure network are key factors as well. |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:ias:cpaper:apr-fall-2021-1&r= |
| By: | Gunadi, Christian |
| Abstract: | This article examines the effect of recreational cannabis dispensary sales on traffic crashes by employing difference-in-differences model that exploits the variation in the timing of recreational marijuana dispensary entry across counties within Colorado. Using marijuana-related hospital discharge as a proxy for marijuana use, the results indicate a sizable rise in marijuana-related hospital discharges after the entry of retail cannabis stores. However, there is a lack of evidence that traffic crash incidents are affected by the entry. The preferred estimate suggests that, at 90% confidence level, a large increase in traffic crashes by more than 5% can be ruled out. |
| Keywords: | Recreational Marijuana Laws,Cannabis Access,Traffic Crashes |
| JEL: | K00 I1 R41 H23 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:glodps:964&r= |