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on Transport Economics |
| By: | Ferguson, Beth; Sanguinetti, Angela PhD |
| Abstract: | Micromobility has the potential to reduce greenhouse gas emissions, traffic congestion, and air pollution, particularly when replacing private vehicle use and working in conjunction with public transit for first- and last-mile travel. The design of the built environment in and around public transit stations plays a key role in the integration of public transit and micromobility. This research presents a case study of rail stations in the San Francisco Bay Area, which are in the operation zone of seven shared micromobility operators. Nineteen stations and their surroundings were surveyed to inventory design features that could enable or constrain use of micromobility for first- and last-mile access. Shared mobility service characteristics, crime records, and connections to underserved communities were also documented. An interactive Bay Area Micromobility Transit ArcGIS map tool was created to aid analysis and provide a useful resource to stakeholders. The map shows layers such as train stations, bike lanes, bike share kiosks, and micromobility operation zones that vary between Oakland, Emeryville, Berkeley, San Francisco, and San Jose. Key design solutions were identified based on the findings, including protected bike lanes, increased shared bike and scooter fleet size and service area, and clear signage indicating bike rack parking corral and docking points. |
| Keywords: | Architecture, Micromobility, shared mobility, public transit, rail transit stations, accessibility, urban design, digital mapping, case studies |
| Date: | 2021–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt5gb6h1j5&r= |
| By: | Passmore, Reid; Watkins, Kari E.; Guensler, Randall |
| Abstract: | Bicycle transportation is often excluded from travel demand and route choice models. Even when bicycle modes are incorporated, models may use a simplified network that does not contain all streets and bicycle paths that a cyclist could feasibly take. These models may also only use trip distance and travel time when modelling a cycling trip; research on revealed route choice preferences of cyclists has shown that cyclist routing is influenced by other factors, such as the presence of a bicycle facility or road elevation gain. The City of Atlanta plans to triple its mileage of protected bicycle infrastructure in the next two years, and needs a tool to be able to plan and prioritize these projects based on the estimated effects on bicycle accessibility, bicycle mode share, energy usage, and emissions, to make the best use of the limited funding. The objective of this project is to develop this analytical tool and an associated network that includes all possible bicycle paths (i.e., roads, bicycle paths, cut-through paths, etc.) for a 12 square mile study area in the City of Atlanta that can be expanded later to the Atlanta Metro area. The tool, BikewaySim, is a shortest path calculator that uses Dijkstra’s shortest path algorithm to find both the preferred route from any origin to any destination within the study area using lowest travel time and lowest total impedance cost. The BikewaySim network was created by conflating network data from the Atlanta Regional Commission (ARC), OpenStreetMap (OSM), and HERE into a whole road and pathway for BikewaySim and future use in the ARC’s activity-based travel demand model. The methods for conflating networks and developing the shortest path model are publicly available resources. The final model is destined to include all viable pathways and incorporate cyclist preferences for use in planning and modelling bicycle travel for research, planning, and design. The framework allows other organizations and researchers to contribute to the project over time. View the NCST Project Webpage |
| Keywords: | Engineering, Bicycle route choice, network conflation, bicycle facility preference |
| Date: | 2021–12–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt23n9389j&r= |
| By: | Hernández, Carlos Eduardo |
| Abstract: | This paper studies waits and delays in the trucking industry of a developing country: Colombia. We follow 186,000 longhaul trips over 926 routes between 2015 and 2019, using GPS devices located in trucks. We find that waits, rather than periods when the truck is moving, are the largest drivers of travelntimes: on average, trucks spend 38% of their travel time movingn between origin and destination, 38% parked at the side of the road, and 24% parked before or after the trip. Furthermore, waiting time accounts for 82% of the variation in travel times across trips, whereas moving time only explains 18%. Overall, the cost of waits amounts to 46% of freight rates, whereas the cost of delays amounts to 7%. Most of the cost of delays is generated during waits, rather than when the truck is moving. Shipper, carrier, truck and driver characteristics, as well as the day of the week and the hour of the day in which loading and unloading occurs, explain 35% of the variation in waiting times across trips. There are large potential gains from reducing waiting times and delays through capacity building and optimization. |
| Keywords: | Infraestructura, Investigación socioeconómica, Movilidad urbana, Políticas públicas, Servicios públicos, Transporte, |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:dbl:dblwop:1724&r= |
| By: | Gimenez-Nadal, J. Ignacio (University of Zaragoza); Gracia-Lazaro, Carlos (University of Zaragoza); Molina, José Alberto (University of Zaragoza) |
| Abstract: | This paper analyzes a bike-sharing service from both network efficiency and demand profiles perspectives. Specifically, it focuses on the BIZI service in the city of Zaragoza (Spain), which was launched in May 2008 with the aim of increasing the use of the bicycle in the city. Since then, the number of users has increased smoothly, and the service currently constitutes an integrated transport mode as an alternative to the use of cars and public transport in the city. The paper analyzes the evolution of the use of the BIZI service, using network analysis to show that efficiency increased rapidly over time until reaching an optimum value after two years. Furthermore, using regression models the paper characterizes the groups that most use this service, and relates service demand to factors such as weather conditions, number of bike lanes, and service extensions. This analysis will allow us to characterize the demand for this service, which can be of great importance when developing integrated transport payment systems. |
| Keywords: | BIZI service, efficiency, weather conditions, socio-demographic characteristics, bike lanes, bike stations |
| JEL: | R40 C45 |
| Date: | 2021–10 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14818&r= |
| By: | Belmar, José; Gentile Passaro, Diego |
| Abstract: | We estimate the impact of railroad and road infrastructure on local economic development through the study of massive transport infrastructure changes in Argentina. Following a World Bank study, 10,000 kilometers of railroads were closed and 18,000 kilometers of paved roads were built between 1960 and 1991. Our empirical strategy relies on instrumental variables that exploit a discontinuity in how experts chose railroad segments to be studied for closure and hypothetical networks connecting main cities. We show that conventional IV estimates can be misleading when omitting potential substitution of different transport modes. We find that dismantling railroads had a negative impact on population and industrial production, and shifted the distribution of labor away from agriculture. On the other hand, we find weak evidence of roads construction having a positive impact on the share of employment in manufacturing and non-tradable industries, but no impacts on total population nor industrial production. |
| Keywords: | Aduanas, Agricultura, Ciudades, Comunicación, Infraestructura, Investigación socioeconómica, Políticas públicas, Transporte, |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:dbl:dblwop:1714&r= |
| By: | Echeverría, Lucía (University of Zaragoza); Gimenez-Nadal, J. Ignacio (University of Zaragoza); Molina, José Alberto (University of Zaragoza) |
| Abstract: | Carpooling is a sustainable daily mobility mode, implying significant reductions in energy consumption and CO2 emissions, although it remains an uncommon practice. With the aim of stimulating this green transportation mode, this paper focus on understanding why certain individuals will agree to share a car to a common destination, apart from the obvious environmental benefit in emissions. It first describes the profile of users and then explores the relationship between this transportation mode and the participants' well-being. To that end, we have selected two countries, the UK and the US, where the use of cars represents a high proportion of daily commuting. We use the UK Time Use Survey (UKTUS) from 2014-2015 and the Well-Being Module of the American Time Use Survey (ATUS) from 2010-2012-2013 to identify which groups in the population are more likely to pool their cars, and with whom those individuals enjoy carpooling more. Results indicate that individuals with certain socio-demographic characteristics and occupations are more likely to commute by carpooling, but the profile seems to be country-specific. Furthermore, our evidence reveals a positive relationship between carpooling and well-being during commuting. |
| Keywords: | carpooling, green mobility, user profiles, subjective well-being |
| JEL: | R40 J22 |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:iza:izadps:dp14736&r= |
| By: | Leonzio Rizzo; Massimiliano Ferraresi; Riccardo Secomandi |
| Abstract: | It is widely recognized that politicians deliberately allocate goods and services just prior to the election, and road investments are arguably among the most visible infrastructure to influence voters. Using a comprehensive dataset on Italian municipalities over the period 2010-2015, we test whether investments in roads and transport services are affected by political manipulations close to elections using as independent variables the year-in-term dummies. We exploit the staggered time of local election to show, indeed, that investment spending on road and transport in the year before election is 30% higher than in the electoral year. Further analyses suggest that our results are more marked (i) in cities guided by a mayor who can run for re-election and (ii) in municipalities with a lower share of educated voters. We isolated the portion of the (exogenous) correlation between the probability of observing an accident and the amount of expenditure on road services that is induced by the political cycle by using the year-in-the-term dummies as instruments. We did not detect any relationship between the increase of investments in road services induced by the political cycle and the local need for road safety, as the probability of having an accident in local roads remained unchanged. Taken together, these findings suggest that politicians manipulate the budget only for re-electoral purposes. Therefore, it is needed a rule, binding visible expenditures, such as those on road services, of the year before the election, or allowing visible expenditures not to exceed those of the previous year within the mandate of the mayor. Such rules would let avoid or at least reduce the estimated inefficient spending by properly programming investment according to real needs and not to electoral convenience. |
| Keywords: | Political Budget Cycle; road accidents; municipalities; local elections; road investments |
| JEL: | D72 H12 H77 Z18 |
| Date: | 2021–12–02 |
| URL: | http://d.repec.org/n?u=RePEc:udf:wpaper:20210710&r= |
| By: | Macfarlane, Jane PhD; Patire, Anthony PhD; Deodhar, Kanaad; Laurence, Colin |
| Abstract: | Quality data is critically important for research and policy-making. The availability of device location data carrying rich, detailed information on travel patterns has increased significantly in recent years with the proliferation of personal GPSenabled mobile devices and fleet transponders. However, in its raw form, location data can be inaccurate and contain embedded biases that can skew analyses. This report describes the development of a method to process, clean, and enrich location data. Researchers developed a computational framework for processing large scale location datasets. Using this framework several hundred days of location data from the San Francisco Bay Area was (a) cleaned, to identify and discard inaccurate or problematic data, (b) enriched, by filtering and annotating the data, and (c) matched to links on the road network. This framework provides researchers with the capability to build link-level metrics across large scale geographic regions. Various applications for this enriched data are also discussed in this report (including applications related to corridor planning, freight planning, and disaster and emergency management) along with suggestions for further work. |
| Keywords: | Engineering, Transportation planning, mobility applications, GPS data, smartphones, data quality, data fusion, data cleaning, pipeline processing, cloud computing |
| Date: | 2021–11–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsrrp:qt1hd8s86g&r= |
| By: | Benjamin Jones (University College London); Viet Nguyen-Tien (London School of Economics); Robert J R Elliott (University of Birmingham) |
| Abstract: | The emergence of a mass market for Electric vehicles (EVs) offers considerable development opportunities for countries that have abundant resources of cobalt, nickel, lithium, copper, aluminium, and manganese. Not surprisingly, developing countries have proposed ambitious plans to expand their domestic EV raw material sectors. However, because of the complexity, opacity, and volatility in these industries it is important that the implications of the changing demand for the critical materials needed by the EV global value chain and carefully understood. One observation from the resource curse literature is that countries need to strengthen their institutions if they are to mitigate the risk of poorly directed, often excessively procyclical, investment. In this paper we draw on results from the CoMIT model (Jones et al. 2020) to help analyse the outlook for EV demand and associated raw material usage paying particular attention to the key drivers and sensitivities required to track future market transformations. We assess key fiscal, regulatory, environmental, and institution reform priorities and the market barriers that may prevent successful domestic resource mobilisation in these resource chains. |
| Keywords: | Electric vehicle, global value chains, critical materials, resource mobilization |
| JEL: | F63 F64 L62 L61 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:bir:birmec:21-15&r= |