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on Transport Economics |
| By: | Halse, Askill H. (Institute of Transport Economics); Hauge, Karen E. (Ragnar Frisch Centre for Economic Research); Isaksen, Elisabeth T. (Ragnar Frisch Centre for Economic Research); Johansen, Bjørn G. (Institute of Transport Economics); Rauum, Oddbjørn (Ragnar Frisch Centre for Economic Research) |
| Abstract: | We study how the adoption of battery electric vehicles – a key technology for decarbonizing transportation – responds to two local privileges: road toll exemption and bus lane access. Combining rich Norwegian microdata with a quasi-experimental research design where we exploit household-level variations in incentives on work commutes, we find sizable and positive effects on electric vehicle ownership. The increase in electric vehicles from having road tolls and bus lanes on work commutes is offset by a similar decline in conventional vehicles. Road tolls also reduce brown driving, but lower CO2 emissions are largely explained by the existence of fewer conventional vehicles. |
| Keywords: | electric vehicles; local incentives; road tolls; bus lanes |
| JEL: | H23 Q55 Q58 R41 R48 |
| Date: | 2022–03–07 |
| URL: | http://d.repec.org/n?u=RePEc:hhs:osloec:2022_001&r= |
| By: | Wang, Pei; McKeever, Benjamin; Chan, Ching-Yao |
| Abstract: | Automated vehicle (AV) deployment can bring about transformational changes to transportation and society as a whole. The infrastructure owner-operators (IOOs), who own, maintain, and operate the infrastructure, have the opportunity to work jointly with the AV industry to provide safe and efficient operations. A key question for the IOOs is, “What transportation infrastructure improvements do AV manufacturers believe will facilitate and improve AV performance?” This study was designed to address this question through a comprehensive survey approach, including an online survey and follow-up interviews. A list of ten questions was discussed, covering the physical and digital infrastructure, infrastructure maintenance, standards and specifications, policy support, data sharing, and so forth. The researchers reached out to more than 60 entities who hold the AV testing permit in California. In total, 20 companies responded. They were from different sectors and well represented the AV industry. From the results of this study, it is concluded that the most important roadway characteristics that have the potential to benefit the automated driving system (ADS) are: (1) digital mapping and signage; (2) lane markings; (3) work zone and incident information; (4) vehicle-to-everything (V2X) communications; (5) actual traffic signals; (6) general signage; and (7) lighting. The digital features considered most critical to help accelerate ADS deployment include work zone and road closure information, traffic signal phase and timing, and traffic congestion. This study provides diverse voices and in-depth insights into topics that the AV industry and IOOs should engage in to advance AVs’ deployment. |
| Keywords: | Engineering |
| Date: | 2022–03–09 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsrrp:qt8h554837&r= |
| By: | Vital, Filipe; Ioannou, Petros |
| Abstract: | The transportation sector is responsible for a significant part of the U.S.’s greenhouse emissions, with a considerable amount being generated by medium-and heavy-duty trucks. However, when it comes to the trucking industry, ‘green’ routing studies do not consider other critical practical factors, like working hours regulations and parking availability. Due to parking shortages, routes and schedules that do not account for parking availability may lead to last-minute changes that make them more polluting than expected. Similarly, working hours regulations influence the timing of required rest stops, which may force drivers to deviate from initially selected routes and schedules with negative consequences to fuel consumption and emissions. This study addresses a variant of the shortest path and truck driver scheduling problem under parking availability constraints which focuses on optimizing fuel consumption and emissions by controlling the truck's travel speed and accounting for time-dependent traffic conditions. As it is impossible to be absolutely certain about the future parking availability of any location during planning, the case of stochastic parking availability was also studied. When studying the trade-offs between prioritizing emissions reduction or trip duration, it was found that although focusing on emissions reduction can increase trip duration significantly, this impact is greatly reduced when considering scenarios with limited parking availability. The problem formulation was further extended to model drivers’ possible recourse actions when unable to find parking and the ensuing costs. This formulation was used to study how the solutions are affected by the level of information provided to drivers. It was found that ignoring uncertainty in parking availability results in inconsistent performance even when restricting parking to periods when probability of finding parking is high. Furthermore, results might not reflect the intent of the cost function used, e.g., minimizing illegal parking events and/or the priority assigned to emissions reduction. Giving drivers full information about the probability of finding parking at any time/location significantly improves performance and reduces illegal parking-related risks, but also substantially increase problem complexity and computation time. Using full information regarding parking availability but restricting the parking times to high availability time-windows can reduce complexity while maintaining consistent, although reduced, performance. View the NCST Project Webpage |
| Keywords: | Engineering, Hours of Service Regulations, Truck Driver Scheduling, Fuel Consumption Optimization, Parking-aware Planning |
| Date: | 2022–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt8rw99523&r= |
| By: | Liu, Diyi; Guin, Angshuman |
| Abstract: | Community-based carpooling has the potential to alleviate traffic congestion and reduce the transportation carbon footprint. Once technology, communication, demographic, and economic barriers are overcome, community-based carpooling can be fully exploited. One of the major barriers to implementation is the difficulty of optimizing carpool formation in large systems. This study utilizes two different methods to solve the carpooling optimization problem: 1) bipartite algorithm and 2) integer linear programming. The bipartite method determines the maximum number of carpooling pairs given acceptable reroute costs and travel delays. The linear programming method defines the most optimal performance that minimizes the most vehicular travel mileage. These two methods are carefully compared to evaluate the carpooling potentials among single-occupancy vehicles based on the output of activity-based model’s (ARC ABM) home-to-work single-occupancy vehicle (SOV) trips that can be paired together towards designated regional employment centers. The experiment showed that under strict assumptions, an upper bound of around 13.6% of such trips could carpool together. The results are promising in terms of higher-than-anticipated carpool match rates and the predicted decrease in total vehicle mileage. Moreover, the framework is flexible enough with the potential to act as a simulation testbed, to optimize vehicular operations, and to match potential carpool partners in real-time. View the NCST Project Webpage |
| Keywords: | Engineering, Carpooling, Demographics, Sustainability, Traffic, Modeling |
| Date: | 2022–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt9c749361&r= |
| By: | Qian, Xiaodong; Jaller, Miguel |
| Abstract: | Bikeshare is an increasingly prevalent transportation option that offers users access to a bicycle without owning it. Both dockbased (requiring users to return bicycles to a fixed station) and dockless (free-floating) services have grown significantly over the past decade. Previous research has found that a well-designed bikeshare system has great potential to improve accessibility for disadvantaged communities. However, systems currently underserve these communities. Moreover, there is a lack of research about the performance and impacts of dock-based versus dockless bikeshare systems in terms of providing equitable access to disadvantaged communities. Researchers at the University of California, Davis analyzed the difference in service levels among dock-based and dockless systems in the cities of San Francisco and Los Angeles. The researchers analyzed the spatial distribution of service areas, availability of bikes and bike idle times, trip statistics, rebalancing, and other metrics to understand how well or poorly these systems serve designated “communities of concern” (CoCs). Finally, using crowdsourced suggestions from online platforms, the researchers conducted a comparative assessment of actual station locations with the users’ suggestions of potential station locations. These analyses can help planning agencies and local governments to better understand and manage these systems. This policy brief summarizes the findings from that research and provides policy implications. View the NCST Project Webpage |
| Keywords: | Engineering, Social and Behavioral Sciences, Bicycles, Equity (Justice), Spatial analysis, Transportation disadvantaged persons, Vehicle sharing |
| Date: | 2022–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt5k72q2j0&r= |
| By: | Congressional Budget Office |
| Abstract: | The federal government has long provided significant financial support for public transportation. Federal spending accounted for about one-sixth of the $79 billion in public spending on transit in 2019. During the coronavirus pandemic, lawmakers allocated nearly $70 billion in onetime supplemental funding. Lawmakers also passed the Infrastructure Investment and Jobs Act, which increased the federal government’s annual funding for public transit from $14 billion to $18 billion per year through 2026 and provided funding for new surface transportation programs. |
| JEL: | H54 R42 R48 |
| Date: | 2022–03–22 |
| URL: | http://d.repec.org/n?u=RePEc:cbo:report:57636&r= |
| By: | Ivaldi, Marc; Nunez, Walter |
| Abstract: | Based on Bike-sharing system (BSS) data for Toulouse, Lyon, and Montreal, we study the Covid19 impact on relevant variables of BSS use. Our results show significant changes related to longer travel distance, which would be explained by those users who use the BSS at peak hour. Also, after Covid-19 outbreak there is evidence about higher willingness to use the BSS in adverse weather conditions (such as rain and wind), lower substitution with the public transport system in Lyon, and a recovery and even a slight increase of BSS trips for Toulouse and Lyon respectively. In our opinion, these results most likely represent permanent changes in user’ habits, being an excellent opportunity to make specific investments in this system and thus strongly promote the bicycle use and its permanence. |
| Keywords: | Bike-sharing system;Covid-19 effects; long-term changes. |
| JEL: | R40 L91 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:tse:wpaper:126722&r= |
| By: | Zheng, Han; Hongtao, Li |
| Abstract: | This paper offers a variant of Ricardian model able to structurally interpret the estimate of country-specific variable—transportation infrastructure in a commonly used fixed effect gravity estimation. Guided by this new theoretical framework, this paper shows that transportation infrastructure enhances international trade more than internal trade and this result is robust to various estimation methods and different versions of transportation infrastructure measures. Moreover, it shows that the transportation infrastructure has a non-negative effect on internal trade. Further quantitative analysis suggests 10% increase in transportation infrastructure induce 3.9% increase in real income and more than 95% of the gains concentrate on the infrastructure improving country. All the above results suggest that better infrastructure leads to sizable gains providing additional empirical support to policies aiming to improve transportation infrastructure. This paper also suggests, contrary to what ACR formula claims, domestic goods expenditure share change is no longer sufficient to predict how real income changes. |
| Keywords: | Gravity model, Transportation infrastructure, Internal trade cost |
| JEL: | F10 F14 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:hit:hiasdp:hias-e-119&r= |
| By: | Štěpán Mikula (Masaryk University, Brno, Czech Republic); Peter Molnár (University of Stavanger, Stavanger, Norway, Prague University of Economics and Business, Prague, Czech Republic, Nicolaus Copernicus University in Torun, Torun, Poland) |
| Abstract: | This paper studies the impact of expected transport accessibility improvement on house prices. We identify the effect exploiting a quasi-natural experiment created by the approval and construction of the Ryfast tunnel system in Rogaland, Norway, which shortened the travelling time to the affected municipality from 62 to 24 minutes. Estimates of a repeated sales model in a difference-in-differences framework show that the expectation of improvement in transport accessibility connected with the construction of the tunnel system led to an increase in house prices by 10.1–12.8\% on average. That effect grew as the opening of the tunnel drew closer and was driven by less valuable houses. |
| Keywords: | transport accessibility; expectations; house prices; Ryfast tunnel system; construction; Norway |
| JEL: | R3 R4 |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:mub:wpaper:2022-05&r= |
| By: | Vital, Filipe; Ioannou, Petros |
| Abstract: | The transportation sector is responsible for 28% of US greenhouse emissions, with a considerable amount being generated by medium- and heavy-duty trucks. Multiple strategies will be needed to improve efficiency and reduce carbon dioxide (CO2) emissions in the trucking industry. Researchers at the University of Southern California developed a truck routing model that minimizes fuel consumption and reduces emissions while explicitly accounting for parking availability and hours-of-service constraints. The researchers used the model to test various scenarios that reflect the practical constraints faced by drivers. View the NCST Project Webpage |
| Keywords: | Engineering, Hours of Service Regulations, Truck Driver Scheduling, Fuel Consumption Optimization, Parking-aware Planning |
| Date: | 2022–03–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt4xj5w07g&r= |
| By: | Brian Buh; Stefanie Peer |
| Abstract: | This paper investigates which factors determine the intention to take a night train, emphasizing the role of environmental concern. We employ a Theory of Planned Behavior framework. We built a survey based on elicitation study, which resulted in an online survey being conducted on a convenience sample in Vienna (Austria). Our results show that in particular environmental concern and familiarity with night train services play a significant role in the formation of the intention to take a night train. Among the significant factors that are associated with a high intention to take a night train are the belief that night trains are comfortable, that one can save the cost of a night in a hotel, and that night trains tend to arrive at and depart from the city center. Factors that deter travelers from taking a night train include a high price, the sharing of cabins, and long travel times. |
| Keywords: | Environmental Concern, Mode Choice, Night Trains, Theory of Planned Behavior, Long-distance travel |
| JEL: | N74 R40 L92 Q57 D01 |
| Date: | 2022 |
| URL: | http://d.repec.org/n?u=RePEc:wiw:wiwsre:sre-disc-2022_02&r= |
| By: | Daniel Clarke (OECD); Florian Flachenecker (OECD); Emmanuelle Guidetti (OECD); Pierre-Alain Pionnier (OECD) |
| Abstract: | By moving goods and people over large distances, air transport facilitates international trade and tourism and thus contributes to economic growth and job creation. At the same time, it also comes with environmental challenges, largely related to air emissions and their impact on global warming. Air transport has been disproportionately negatively affected by the COVID-19 pandemic with associated reductions in air emissions. However, recent projections show that, in the absence of accelerated technological developments and more ambitious policy measures, aviation-related carbon dioxide (CO2) emissions will grow again at a rapid pace after the pandemic. This paper describes a new OECD database providing near-real-time and global information on aviation-related CO2 emissions, with allocations across countries following either the territory or the residence principle. This database provides a public good for both statistical measurement and environmental policy analysis. On the statistical front, it will facilitate the compilation of global Air Emission Accounts according to the System of Environmental Economic Accounting (SEEA), bring granular and timely information on a significant source of CO2 emissions, and allow tracking their evolution during and after the COVID-19 pandemic. The comparison with official statistics that are available with a significant delay and at lower frequency demonstrates the accuracy of the OECD estimates. On the environmental policy front, it is expected that the OECD database will help monitor the impact of technological developments and policy measures to curb aviation-related CO2 emissions in the future. |
| Keywords: | air transport, big data, climate change, CO2 emissions, covid-19, environmental-economic accounting, seea, UNFCCC inventories |
| JEL: | L93 Q53 Q56 |
| Date: | 2022–03–08 |
| URL: | http://d.repec.org/n?u=RePEc:oec:stdaaa:2022/04-en&r= |
| By: | Daniel Nachtigall; Jane Ellis; Sofie Errendal |
| Abstract: | This paper assesses the role of carbon pricing in a sustainable recovery from COVID-19. It tracks the policy changes in carbon pricing within OECD and G20 countries between January 2020 and August 2021 of the COVID-19 pandemic. Carbon pricing as defined here includes emissions trading schemes, fossil fuel support and carbon, fuel excise or aviation taxes. The paper also highlights the need for the recovery to be sustainable and discusses the advantages, limitations and uses of carbon pricing therein. In addition, it describes additional challenges to as well as increased rationale for carbon pricing in the pandemic. It provides evidence on the effects of carbon pricing on the challenges and discusses carbon pricing design elements to help overcome those challenges. The paper concludes that there were more policy changes with an expected negative impact on climate. However, it is likely that the impact of the climate-positive changes – which are broader in coverage and scope - will outweigh the climate-negative changes. |
| Keywords: | sustainable recovery, COVID-19, carbon pricing, carbon tax, emissions trading system, ETS, Fossil fuel subsidies, revenue recycling, climate change, climate mitigation, NDC |
| JEL: | H23 Q54 Q56 Q58 |
| Date: | 2022–03–10 |
| URL: | http://d.repec.org/n?u=RePEc:oec:envaaa:191-en&r= |
| By: | Laurens Cherchye; Bram De Rock; Dieter Saelens; Marijn Verschelde; Bart Roets |
| Abstract: | Performance analytics are commonly used in managerial decision making, but are vulnerable to an omitted variable bias issue when there is incomplete information on the used production factors. In this paper, we relax the standard assumption in productive efficiency analysis that all input quantities are observed, and we propose a nonparametric methodology for cost inefficiency measurement that accounts for the presence of unobserved inputs. Our main contribution is that we bridge the OR/MS and the economic literature by addressing the general critique of Stigler (1976) on the concept of inefficiency (Leibenstein, 1966), which states that found inefficiencies reflect unobserved inputs rather than waste. Our methodology explicitly differentiate between cost inefficiency (i.e. waste; deviations from optimizing behavior) and unobserved input usage (i.e. optimally chosen input factors that are unobserved to the empirical analyst). We apply our novel method to a purpose-built dataset on Belgian railway traffic management control rooms. Our _findings show the existence of meaningful inefficiencies that cannot be attributed to use of unobserved inputs or environmental factors. In addition, we document how the omitted variable bias impacts cost efficiencies of individual observations in a dissimilar way in case the use of unobserved inputs is not controlled for. |
| Keywords: | efficiency measurement, unobserved heterogeneity, omitted variable |
| Date: | 2022–03 |
| URL: | http://d.repec.org/n?u=RePEc:eca:wpaper:2013/341171&r= |