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on Transport Economics |
| By: | Hardman, Scott PhD; Chakraborty, Debapriya PhD; Kohn, Eben |
| Abstract: | This project investigated changes in travel behavior by owners of partially automated electric vehicles. Partial automation can control vehicle speed and steering using sensors that monitor the external environment. The researchers used review results from survey responses including 940 users of partial automation, of which 628 who have Tesla Autopilot and 312 with systems from other automakers. Autopilot users report using automation more than users of other partial automation systems. Autopilot has the largest impact on travel, notably 36% of Autopilot users reporting more longdistance travel. Respondents who are younger, have a lower household income, use automation in a greater variety of traffic, roads, and weather conditions, and those who have pro-technology attitudes and outdoor lifestyles are more likely to report doing more long-distance travel. The project used propensity score matching to investigate whether automation leads to any increase in respondents’ annual vehicle miles travelled. For simplicity, the researchers focused only on the impact of Tesla Autopilot and found that automation results in an average of 4,884 more miles being driven per year. |
| Keywords: | Engineering, Electric vehicles, intelligent vehicles, level 2 driving automation, travel behavior, travel models, vehicle miles of travel, surveys |
| Date: | 2021–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt58t7674n&r= |
| By: | Fulton, Lewis |
| Abstract: | The transportation system is undergoing three revolutions: vehicle automation, electrification, and shared mobility. While these are still nascent trends, studies suggest that they could become ubiquitous in the coming decades. How these revolutionary changes transpire will have significant implications for transportation sustainability. A key factor will be whether autonomous vehicles are deployed as shared cars that serve many travelers such as in ridesourcing or ridehailing fleets, or as privately owned vehicles that could dramatically increase vehicle miles traveled and associated environmental impacts. To anticipate how these revolutions will affect future transportation, and to develop policy to shape that future, it is important to understand the various factors that influence individuals’ travel choices. These choices include whether to travel alone or with others, and whether to use a private vehicle or a shared one. Some of these factors are monetary, such as the cost of fuel, insurance, and a driver, while others are non-monetary, such as the travel time, comfort, and reliability of each transportation option. The significance of these non-monetary factors is poorly understood and often ignored. Researchers at the University of California, Davis developed a framework for considering the monetary and non-monetary costs of future travel choices and used existing research to develop interim values for several non-monetary travel choice factors. This policy brief summarizes the findings from that research and provides policy implications. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Cost estimating, Mobility, Mode choice, Ridesourcing, Surveys, Travel behavior, Travel costs, Value of time |
| Date: | 2021–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt1kb8h9vs&r= |
| By: | Hardman, Scott; Chakraborty, Debapriya; Kohn, Eben |
| Abstract: | Research is beginning to show that vehicle automation will encourage more driving because it substantially reduces driver workload, making driving more relaxing and less stressful. This will have environmental sustainability implications, given that vehicle electrification alone will not be sufficient to meet state and federal greenhouse gas reduction targets without reductions in vehicle miles traveled (VMT). Research on the effects of vehicle automation has been somewhat speculative because fully automated vehicles are not yet commercially available. But many automakers are already incorporating automated features such as adaptive cruise control and lane keeping assist into their vehicles. These features assist in driving tasks and reduce the “cost” of driving in much the same way fully automated vehicles promise to do. Researchers at UC Davis surveyed owners of partially automated electric vehicles in California to understand the impact of partial automation on VMT. The survey asked respondents about their use of partial automation systems including BMW Driving Assistant, Ford Co-pilot360, Honda Sensing, Nissan ProPilot Assist, Tesla Autopilot, and Toyota Safety Sense. The results of this study show that partial automation has the potential to cause large increases in VMT. |
| Keywords: | Engineering |
| Date: | 2021–05–13 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt9sn5q7h0&r= |
| By: | Tal, Gil; Karanam, Vaishnavi Chaitanya; Favetti, Matthew P.; Sutton, Katrina May; Ogunmayin, Jade Motayo; Raghavan, Seshadri Srinivasa; Nitta, Christopher; Chakraborty, Debapriya; Davis, Adam; Garas, Dahlia |
| Abstract: | Results from this report highlight how alternative fuel vehicles are used based on data collected between 2015 and 2020. Alternative fuel vehicles include plug-in electric vehicles (PEVs), vehicles that are either battery electric vehicles (BEVs) or plug-in hybrid electric vehicles (PHEVs), and fuel cell vehicles (FCVs). This category of vehicle technologies is included in the California Air Resources Board’s Zero Emission Vehicle regulations and is referred to as ZEV in this report. We explore the environmental impacts of driving, charging behavior and infrastructure. In households with ZEVs, the data from surveys, loggers, and interviews indicate that those vehicles are being used extensively. This report, which combined the data collected in two consecutive studies between 2015-2020, includes first and second generation PEVs popular in California between 2011-2018. The BEVs include the first-generation, shortrange Nissan Leaf and the long range BEVs such as the Chevrolet Bolt and Tesla Model S. The PHEVs include short range sedans such as the Toyota Prius Plug-in and longer-range vehicles such as the Toyota Prius Prime, Chevrolet Volt and Chrysler Pacifica. The FCVs include the most popular fuel cell vehicle, the Toyota Mirai. |
| Keywords: | Engineering |
| Date: | 2021–04–19 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt2v0853tp&r= |
| By: | Alexander Nollau; Friedrich Thieszen (Aviation Working Group, TU Chemnitz) |
| Abstract: | Many current problems in air traffic are related to the number of aircraft movements. Over-crowding in the airspace, difficult coordination at airports, high emissions of noise and pollu-tants as well as complexity of airlines are side effects of too many aircraft movements.This study examines the extent to which the number of flight movements in Europe can be reduced without change in transport performance. For this purpose, the number of flight move-ment for a European network of the 140 most frequently flown serviced routes will be opti-mised. The reference date is November 17th, 2017.It shows that with the same passenger transport performance, the number of flight movements can be reduced to 1/3 of the current level (from 2.040 flights per day to 738 flights per day). In some cases, the quality of the connections can even be improved because all flights in the optimised network are coordinated.This proves that the current air traffic structure has considerable weak points. There are too many redundant aircraft movements. Our proposed reform measures can contribute to the needed reduction in the number of aircraft movements without reducing passenger transport services and travel quality. |
| Date: | 2021–05 |
| URL: | http://d.repec.org/n?u=RePEc:tch:wpaper:cep044&r= |
| By: | Giuliano, Genevieve; Dessouky, Maged; Dexter, Sue; Fang, Jiawen; Hu, Shichun; Steimetz, Seiji; O'Brien, Thomas; Miller, Marshall; Fulton, Lewis |
| Abstract: | California is pursuing multiple policies to spur the transition to a cleaner heavy-duty vehicle fleet. Achieving these targets will require massive change in the heavy-duty short-haul industry, and many unanswered questions remain. How do battery-electric heavy-duty trucks compare to diesel in everyday short-haul operations? How much would it cost to transition to a zero-emission truck fleet, and who would pay? To begin to answer these questions, researchers at the National Center for Sustainable Transportation conducted a comprehensive analysis of the potential for zero-emission or near-zero-emission heavy-duty trucks to be used in short-haul drayage services. The researchers considered operational, economic, and environmental impacts through simulation modeling, interviews, case studies, stated preference surveys, and cost-effectiveness analyses. View the NCST Project Webpage |
| Keywords: | Business, Engineering, Law, Air quality management, Alternate fuels, Alternatives analysis, Benefit cost analysis, Case studies, Forecasting, Freight traffic, Heavy duty trucks, Market share, Recommendations, Short haul, Simulation, Surveys, Zero emission vehicles |
| Date: | 2021–05–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt1221f4wx&r= |
| By: | Janotta, Frederica; Peine, Louisa; Hogreve, Jens |
| Abstract: | With growing populations in metropolitan areas and increasing individual traffic, new, safe and efficient transport modes are being explored to meet rising social and environmental demands. So-called Unmanned Aerial Vehicles (UAV), which are autonomously controlled and capable of vertical take-off and landing, allow for a range of different use cases, including the transport of packages, medical goods, or passengers. Manufacturers such as Airbus, Lilium or Volocopter already have successfully carried out the first test flights with unmanned drones in Germany, underlining their ambitions to launch UAM operations in the near future. However, next to technological, legal and infrastructural barriers, one of the main challenges ahead of market introduction is the acceptance of UAM operations by potential users and the public. Therefore, the goal of this research is to explore public acceptance of various use cases of Urban Air Mobility as well as the factors that influence the individuals’ intention to use UAM services in the future. |
| Date: | 2021–05–05 |
| URL: | http://d.repec.org/n?u=RePEc:osf:osfxxx:5m924&r= |
| By: | Lukin, Artyom |
| Abstract: | This paper examines political and economic dimensions of the Russia-China relationship, with an emphasis on Russia's involvement in Beijing's Belt and Road Initiative (BRI). Being the largest, and trans-continental, Eurasian country, Russia occupies an important place in China's BRI. The current relationship between the two great Eurasian powers can be characterized as an entente, or quasi-alliance. Moscow welcomes the BRI, but, unlike many other governments across the world, it has never signed an agreement to formally join the initiative. This signals Russia's stance that Eurasian integration should not be dominated by China, as well as the Kremlin's insistence on status equality with China. In recent years there has been a noticeable rise in shipments from China to Europe, and in the reverse direction, using the rail routes via Russia. However, despite the increase in its trans-continental freight traffic going via Russia, China still refrains from investing in the upgrade of Russia's transport networks, such as railroads, ports and highways, and is overall reluctant to invest in the Russian economy. The reasons are both economic, such as the relatively high risks and low profit margins in the Russian market, and political ones, related to Russia's insistence on parity and equality with China. |
| Keywords: | Russia-China relations,the Belt and Road Initiative,Eurasia |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:opodis:20213&r= |
| By: | Grigolon, Laura |
| Abstract: | Prominent features of differentiated product markets are segmentation and product proliferation blurring the boundaries between segments. I develop a tractable demand model, the Ordered Nested Logit, which allows for asymmetric substitution between segments. I apply the model to the automobile market where segments are ordered from small to luxury. I find that consumers, when substituting outside their vehicle segment, are more likely to switch to a neighboring segment. Accounting for such asymmetric substitution matters when evaluating the impact of new product introduction or the effect of subsidies on fuel-efficient cars. |
| JEL: | D11 D12 L62 M3 |
| Date: | 2021–01 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:15630&r= |
| By: | Saparya Suresh (Indian Institute of Management Kozhikode) |
| Abstract: | India has aimed for a 30% electric vehicle adoption by 2030. As a part of the electric vehicle adaptation, the government is moving towards coming up with a policy framework for electric vehicles and related sectors like raw material sourcing, battery manufacturing, charging stations, etc. This paper is intended to draw a comparative analysis between the ICE vehicles and Battery Electric Vehicles on operational aspects as well as its environmental implications. The paper stands out in highlighting certain important factors which are needed to be considered while devising a policy framework towards electric vehicle adoption. Based on the conclusion, few policy suggestions are made for a better sustainable policy framework for the effective adaptation of electric vehicles for the future in an Indian context. |
| Keywords: | Electric Vehicles, Environmental Impact, Policy Framework, Lithium Batteries |
| Date: | 2021–03 |
| URL: | http://d.repec.org/n?u=RePEc:iik:wpaper:409&r= |
| By: | Imani, Saba; Vahed, Majid; Vahed, Mohammad |
| Abstract: | Introduction As the outbreak of novel coronavirus disease (COVID-19) continues to spread rapidly throughout the world, steps are being taken to limit the impact on public health. In the realm of infectious diseases like COVID-19, social distancing is effective to avoid exposure to the virus and reduce its spread. However, current studies about public transit did not consider social distancing which plays a fundamental role in the current outbreak. Therefore, it is vital to study how to optimally manage public transit systems in order to minimize risks related to COVID-19. Methods In this study we present a novel web-based application, T-Ridership based on a hybrid optimized dynamic programming inspired by neural networks algorithm to optimize public transit for safety with respect to COVID-19. Two main steps are taken in the analysis through Metropolitan Transportation Authority (MTA): the first is detecting high-density stations by input data normalization, and then, using these results, the T-Ridership tool automatically determines optimal station order planning. Results We evaluated the performance of our web tool by comparing the results with real data extracted from MTA. The number of passengers in a route dropped significantly after normalization by T-Ridership. These results can be used in expanding on and improving policy in public transit, to better plan the scheduled time of trains in a way that prevents high-volume human contact, increasing social distance and reducing the possibility of disease transmission (available at: http://t-ridership.com). |
| Date: | 2021–05–05 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:casb7&r= |