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on Transport Economics |
| By: | Jaller, Miguel |
| Abstract: | California has set goals for transitioning the freight sector to near-zero-emission and zero-emission vehicles (ZEVs). California offers several incentive programs to encourage adoption of ZEVs, but purchase decisions are driven by complex factors beyond simple purchase price. Understanding the behaviors and attitudes of freight stakeholders toward ZEVs can inform the design of more effective incentive programs to meet California’s goals. Researchers at the University of California, Davis deployed a stated-preference survey of fleet and carrier companies to collect information about vehicle purchase preferences and how they might be influenced by various incentive programs. This policy brief summarizes the findings from that research and provides policy implications. View the NCST Project Webpage |
| Keywords: | Social and Behavioral Sciences, Behavior, Forecasting, Freight transportation, Incentives, Market penetration, Surveys, Travel demand, Trucks, Zero emission vehicles |
| Date: | 2021–09–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt0p14c77j&r= |
| By: | Denissa Sari Darmawi Purba; Eleftheria Kontou; Chrysafis Vogiatzis |
| Abstract: | As the number of adopted alternative fuel vehicles increases, communities that are susceptible to hazardous events, such as hurricanes and wildfires, need to create new evacuation plans that account for their refueling needs. During emergencies that require preemptive evacuation, drivers using alternative fuel vehicles are left vulnerable under conventional evacuation routes which do not provide access to refueling stations on their way to shelters. In this paper, we formulate a novel evacuation routing problem which considers multiple types of fuel vehicles. Specifically, we introduce a $k$-spanning evacuation tree problem with hop constraints that capture the refueling needs of each vehicle fuel type $k \in K$ as they are routed to a shelter. We provide a mixed integer mathematical formulation for the problem along with a path-based reformulation which allows us to create a column-generation based matheuristic to efficiently solve the problem. Next, we apply the proposed framework to the Sioux Falls transportation network considering that refueling stations for alternative fuel vehicles are placed to serve habitual demands. We present a series of numerical experiments where we discuss optimal travel and refueling times under different driving ranges for each vehicle type. Our findings show that the characteristics of each vehicle fuel type (driving range and infrastructure siting) play a pivotal role in determining the optimal evacuation trees. Evacuation routes that are optimal for one type of vehicles are often infeasible for the remaining vehicles; furthermore, driving range constraints and the need to refuel could force evacuees to detour prior to reaching safety. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.01578&r= |
| By: | Maher Said; Emma R. Zajdela; Amanda Stathopoulos |
| Abstract: | One of the most notable global transportation trends is the accelerated pace of development in vehicle automation technologies. Uncertainty surrounds the future of automated mobility as there is no clear consensus on potential adoption patterns, ownership versus shared use status and travel impacts. Adding to this uncertainty is the impact of the COVID-19 pandemic that has triggered profound changes in mobility behaviors as well as accelerated the adoption of new technologies at an unprecedented rate. This study examines the impact of the COVID-19 pandemic on willingness to adopt the emerging new technology of self-driving vehicles. Using data from a survey disseminated in June 2020 to 700 respondents in contiguous United States, we perform a difference-in-difference regression to analyze the shift in willingness to use autonomous vehicles as part of a shared fleet before and during the pandemic. The results reveal that the COVID-19 pandemic has a positive and highly significant impact on consideration of autonomous vehicles. This shift is present regardless of techsavviness, gender or political views. Individuals who are younger, left-leaning and frequent users of shared modes of travel are expected to become more likely to use autonomous vehicles once offered. Understanding the effects of these attributes on the increase in consideration of AVs is important for policy making, as these effects provide a guide to predicting adoption of autonomous vehicles - once available - and to identify segments of the population likely to be more resistant to adopting AVs. |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2108.01615&r= |
| By: | MELIS, Lissa; QUEIROZ, Michell; SÖRENSEN, kenneth |
| Abstract: | In this work we analyse the performance of integrating a large-scale on-demand bus system with a fixed line public transport network in an urban context. Given are a high-speed metro network, a set of real-time requests, a set of bus station locations and a fleet of fixed capacity minibuses. Requests have a set of possible departure/arrival1 bus stations within walking distance of the actual departure/arrival location and have to be served within a certain time window. The aim is to simultaneously (1) decide on the trip type for each passenger (only bus, metro or mixed), (2) route the on-demand buses, (3) assign each passenger to a departure and arrival bus station (bus station assignment), and (4) in the case of a metro-leg in the trip, decide the assigned transfer station(s) and used metro lines (transfer station assignment). We call this problem the integrated on-demand bus routing problem. After presenting a mathematical model, we propose a quick and scalable insertion-based heuristic to solve the problem. The results found by the heuristic are further used to compare the performance of an integrated system, to a system that only uses on-demand buses. It is concluded that the integrated system always performs better regarding the service rate or number of served requests. Depending on the speed and layout of the metro network, also the average user ride time per passenger improves by the integration. |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ant:wpaper:2021004&r= |
| By: | Apanasevic, Tatjana; Rudmark, Daniel |
| Abstract: | In the last decade, private companies have successfully used crowdsourcing to revolutionise mobility, while public transport companies are still mostly failing to utilise the benefits of crowdsourcing. The application of crowdsourcing in public transport is a new area of academic research, and research on crowdsourcing en route in real-time is missing. This research aims to address this gap, explore opportunities and challenges of this type of crowdsourcing, and conceptualise this phenomenon. The research is based on empirical data collected in five Northern European countries. Our research findings help identify areas where crowdsourcing en route can add value to public transport: new forms of communication, opportunities to communicate with third parties, and improved transit planning and optimisation. Identified challenges are related to behavioural change for users, a need to develop infrastructure to enable crowdsourcing en route, and financial rationalities. |
| Keywords: | Future of transportation,public transportation,emerging technologies,automated vehicles,crowdsourcing |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itsb21:238005&r= |
| By: | MELIS, Lissa; SÖRENSEN, Kenneth |
| Abstract: | The real-time on-demand bus routing problem (ODBRP) supports the online routing of buses in a large-scale ride-sharing system. Given are a set of buses with fixed capacity, a set of bus stations and a set of transportation requests, only part of which are known before the planning horizon. A request consists of a set of possible departure and arrival stations, as well as an earliest departure and latest arrival time. The aim is to (1) assign each passenger to a departure and arrival bus station and (2) develop a set of bus routes to fulfill each request within its time window while minimizing the total user ride time. Including the possibility for requests to be issued after the start of the planning horizon, i.e., when buses have already started servicing other requests, requires a dynamic re-optimization of a partially executed solution. Compared to the case in which all requests are known beforehand, the solution quality, expressed as the total user ride time, is expected to decline. This decline in objective function value can be seen as the ”cost” of the dynamic requests. In this paper, we introduce the real-time ODBRP as a new optimization problem and present a heuristic to deal with dynamic requests. In addition, an extensive set of experiments allows us to conclude that dynamic requests indeed lead to higher user ride times, especially for passengers who submit their request at the last minute. Passengers are therefore encouraged to send their request well in advance, as this results in lower and more stable user ride times, higher customer satisfaction, and higher revenues for the operating on-demand bus company. |
| Keywords: | Public transport, Transportation, Metaheuristic, Mobility on demand |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:ant:wpaper:2021003&r= |
| By: | Janak Parmar; Gulnazbanu Saiyed; Sanjaykumar Dave |
| Abstract: | The concept of transportation demand management (TDM) upholds the development of sustainable mobility through the triumph of optimally balanced transport modal share in cities. The modal split management directly reflects on TDM of each transport subsystem, including parking. In developing countries, the policy-makers have largely focused on supply-side measures, yet demand-side measures have remained unaddressed in policy implications. Ample literature is available presenting responses of TDM strategies, but most studies account mode choice and parking choice behaviour separately rather than considering trade-offs between them. Failing to do so may lead to biased model estimates and impropriety in policy implications. This paper seeks to fill this gap by admitting parking choice as an endogenous decision within the model of mode choice behaviour. This study integrates attitudinal factors and built-environment variables in addition to parking and travel attributes for developing comprehensive estimation results. A mixed logit model with random coefficients is estimated using hierarchical Bayes approach based on the Markov Chain Monte Carlo simulation method. The results reveal significant influence of mode/parking specific attitudes on commuters choice behaviour in addition to the built-environment factors and mode/parking related attributes. It is identified that considerable shift is occurring between parking-types in preference to switching travel mode with hypothetical changes in parking attributes. Besides, study investigates the heterogeneity in the willingness-to-pay through a follow-up regression model, which provides important insights for identifying possible sources of this heterogeneity among respondents. The study provides remarkable results which may be beneficial to planning authorities for improving TDM strategies especially in developing countries. |
| Date: | 2021–08 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.01045&r= |
| By: | Yiduo Huang; Zuojun Max Shen |
| Abstract: | The recovery of the public transportation system is critical for both social re-engagement and economic rebooting after the shutdown during pandemic like COVID-19. In this study, we focus on the integrated optimization of service line reopening plan and timetable design. We model the transit system as a space-time network. In this network, the number of passengers on each vehicle at the same time can be represented by arc flow. We then apply a simplified spatial compartmental model of epidemic (SCME) to each vehicle and platform to model the spread of pandemic in the system as our objective, and calculate the optimal open plan and timetable. We demonstrate that this optimization problem can be decomposed into a simple integer programming and a linear multi-commodity network flow problem using Lagrangian relaxation techniques. Finally, we test the proposed model using real-world data from the Bay Area Rapid Transit (BART) and give some useful suggestions to system managers. |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2109.03940&r= |
| By: | Degrande, Thibault; Vannieuwenborg, Frederic; Colle, Didier; Verbrugge, Sofie |
| Abstract: | To date, traffic remains a major source of societal costs in terms of safety and environment. In Flanders, as in other regions and Member States in the European Union, the government counts on current developments in cooperative, connected and autonomous mobility (CCAM) to achieve European societal objectives. However, the first set of Cooperative Intelligent Transport Systems (C-ITS) services has overlapping objectives with the functionalities of present ITS infrastructure. Therefore, this paper provides a methodology for road authorities to determine, bottom-up, the incremental benefits C-ITS can bring for the highway segments they operate, given the presence of ITS gantries on those segments. This allows to prioritize segments for C-ITS roadside unit (RSU) deployments, taking into account legacy ITS infrastructure. Results show that segments with dense ITS deployments, though having high traffic volumes, should not be prioritized in RSU deployment selection. |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:zbw:itsb21:238016&r= |
| By: | Prateek Bansal; Rubal Dua; Rico Krueger; Daniel Graham (King Abdullah Petroleum Studies and Research Center) |
| Abstract: | India has the world’s third highest carbon dioxide (CO2) emissions, after China and the United States. The transportation sector is the third largest contributor to carbon dioxide emissions in India, accounting for roughly 11% of all carbon dioxide emissions in 2016. Road transport accounts for around 94% of the total carbon dioxide emissions of the transportation sector. |
| Keywords: | Aviation consumption, Aviation oil demand, Crude oil, Diesel |
| Date: | 2021–08–24 |
| URL: | http://d.repec.org/n?u=RePEc:prc:dpaper:ks--2021-dp13&r= |
| By: | Gianluca Mattarocci; Gibilaro Lucia |
| Abstract: | Local railway service is a key instrument to support the survival and the growth of small towns increasing the demand by individuals that are not interested to live in the main cities and that could accept the cost of commuting day-by-day for working. The existence of a local railway station connected with the main surrounding cities reduces the transportation cost for people leaving in small towns that cannot work in the town and reduces the risk of migration of citizens to the main cities. The paper analyses a representative sample of Italian towns in the Lazio area for the time period 1996-2017 in order to measure the contribution of the local railway service on the land value for housing investment. Results show that the existence of local railway service matters for both the rental and ownership market but the effect may be different on the basis of the type of service provided by the railway company. The main features that affect the house value are the number of train lines servicing the station, the distance from the main cities and the number of towns served by each train line. |
| Keywords: | housing; Local railway; Ownership; Rent |
| JEL: | R3 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2021_129&r= |
| By: | Gabi Troeger-Weiss; Sebastian Winter |
| Abstract: | In the course of the pandemic triggered by the corona virus SARS-CoV-2 (hereinafter referred to as the corona pandemic), new and changed behaviors are appearing in citizen groups. These behaviors are particularly evident in the areas of consumer, mobility and travel behavior. The new behavioral patterns have a significant impact on (contact-intensive) companies, especially in the areas of retail, mobility companies (e.g. airlines, train companies, bus companies, rental car companies, etc.) as well as hotels and restaurants. In the medium and long-term view, permanent and irreversible effects on currently existing offerings and infrastructures could result from low utilization and thus have a lasting impact on and weaken the regional and local economic structure and crucial pillars of adding value at regional and local level. Relevant from a spatial and regional scientific point of view and of great research interest is the question of whether the economic and infrastructures, particularly in rural areas, may be at greater risk than in metropolitan regions and thus structural weaknesses in regions may tighten by the corona pandemic. |
| Keywords: | and travel; citizen groups; consumer spending; Corona pandemic; Mobility; spatial relevance |
| JEL: | R3 |
| Date: | 2021–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:arz:wpaper:eres2021_156&r= |