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on Transport Economics |
| By: | Dhaniel Ilyas (Institute for Economic and Social Research, Faculty of Economics and Business, Universitas Indonesia (LPEM FEB UI)) |
| Abstract: | Using micro commuting data in 2015, I estimate travel demand of Denpasar greater area. Motorcycle and car are still more preferred greatly compare to public transport. Faster travel time are the most important factor that drive the use of motorcycle and car in Denpasar greater area. Younger people seems to use the public transport more, including the Trans Sarbagita BRT. An incentive in pricing for older group of people and improving the bus scheduling might help increase the use of public transport. |
| Keywords: | Denpasar — Indonesia — travel demand — transportation |
| JEL: | R22 R41 |
| Date: | 2021 |
| URL: | http://d.repec.org/n?u=RePEc:lpe:wpaper:202166&r= |
| By: | Giovanni Calabro'; Andrea Araldo; Simon Oh; Ravi Seshadri; Giuseppe Inturri; Moshe Ben-Akiva |
| Abstract: | In most cities, transit consists of fixed-route transportation only, whence the inherent limited Quality of Service for travellers in sub-urban areas and during off-peak periods. On the other hand, completely replacing fixed-route with demand-responsive (DR) transit would imply huge operational cost. It is still unclear how to ingrate DR transportation into current transit systems to take full advantage of it. We propose a Continuous Approximation model of a transit system that gets the best from fixed-route and DR transit. Our model allows to decide, in each area and time of day, whether to deploy a fixed-route or a DR feeder, and to redesign line frequencies and stop spacing of the main trunk service accordingly. Since such a transit design can adapt to the spatial and temporal variation of the demand, we call it Adaptive Transit. Our numerical results show that Adaptive Transit significantly improves user cost, particularly in suburban areas, where access time is remarkably reduced, with only a limited increase of agency cost. We believe our methodology can assist in planning future-generation transit systems, able to improve urban mobility by appropriately combining fixed and DR transportation. |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2112.14748&r= |
| By: | Di Ao; Zhijie Lai; Sen Li |
| Abstract: | This paper investigates how autonomous vehicles (AV) affect passengers, for-hire human drivers, and the platform on a ride-sourcing network. We consider a ride-sourcing market where a mixture of AVs and human drivers is deployed by the platform to provide mobility-on-demand services under labor regulations. In this market, the ride-sourcing platform determines the spatial prices, fleet size, human driver payments, and vehicle relocation strategies to maximize its profit, while individual passengers choose between different transport modes to minimize their travel costs. A market equilibrium model is proposed to capture the interactions among passengers, human drivers, AVs, and the ride-sourcing platform over the network. The overall problem is formulated as a non-convex program with network constraints, and an algorithm is developed to derive its approximate solution with performance guarantee. Our study shows that ride-sourcing platform prioritizes AV deployment in high-demand areas to make a higher profit. As AVs flood into these high-demand areas, they compete with human drivers in the urban core and push them to relocate to suburbs. This leads to reduced earning opportunities for human drivers and increased spatial inequity for passengers. We also show that placing a wage floor may protect drivers from the negative impact of AVs, and meanwhile the total vehicle supply and passenger demand are almost unaffected. However, there exists a threshold beyond which the minimum wage will trigger a paradigm shift of labor supply where the platform will completely replace all human drivers with AVs. This indicates that the minimum wage should be carefully designed in the mixed environment to avoid the loss of job opportunities for human drivers. These results are validated with realistic case studies for San Francisco. |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2112.07218&r= |
| By: | Louis Balzer (Universit\'e Gustave Eiffel, ENTPE); Ludovic Leclercq (Universit\'e Gustave Eiffel, ENTPE) |
| Abstract: | The literature about tradable credit schemes (TCS) as a demand management system alleviating congestion flourished in the past decade. Most proposed formulations are based on static models and thus do not account for the congestion dynamics. This paper considers elastic demand and implements a TCS to foster modal shift by restricting the number of cars allowed in the network over the day. A trip-based Macroscopic Fundamental Diagram (MFD) model represents the traffic dynamics at the whole urban scale. We assume the users have different OD pairs and choose between driving their car or riding the transit following a logit model. We aim to compute the modal shares and credit price at equilibrium under TCS. The travel times are linearized with respect to the modal shares to improve the convergence. We then present a method to find the credit charge minimizing the total travel time alone or combined with the carbon emission. The proposed methodology is illustrated with a typical demand profile from 7:00 to 10:00 for Lyon Metropolis. We show that traffic dynamics and trip heterogeneity matter when deriving the modal equilibrium under a TCS. A method is described to compute the linearization of the travel times and compared against a classical descend method (MSA). The proposed linearization is a promising tool to circumvent the complexity of the implicit formulation of the trip-based MFD. Under an optimized TCS, the total travel time decreases by 17% and the carbon emission by 45% by increasing the PT share by 24 points. |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2112.07277&r= |
| By: | Leif Jacobs (Fraunhofer Institute for Applied Information Technology); Lara Quack (Fraunhofer Institute for Applied Information Technology); Mario Mechtel (Leuphana University of Lüneburg, Institute of Economics) |
| Abstract: | We introduce a new microsimulation model built on household transport data to study the distributional effects of carbon-based fuel taxation of private road transport in Germany. Our data includes annual mileage at the car-level, the distinction between fuel types, as well as car-specific fuel consumption, allowing for a very detailed analysis. The model allows focusing on different types of households as well as identifying effect heterogeneity across the income distribution. We compare the recent fuel tax scheme with three policy reform scenarios to empirically test several hypotheses regarding distributional effects of carbon pricing. We find that the legal status quo of the fuel tax has overall regressive effects, with the tax on petrol acting regressive and the tax on diesel acting progressive. A transformation of the current tax into a revenue-neutral carbon-harmonised fuel tax yields a progressive distributional effect, while an introduction of a new carbon tax on transport fuels is neither learly regressive nor progressive. Combining both tax schemes also has non-regressive effects. Our results suggest that policy makers face various options for pricing road transport greenhouse gas emissions without causing an overall disproportionate tax burden on low-income households. |
| Keywords: | carbon pricing, fuel tax, distributional effects, road transport, microsimulation, exante impact assessment |
| JEL: | H22 H23 Q48 Q58 R48 |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:lue:wpaper:405&r= |
| By: | Lijing Zhu (China University of Petroleum); Jingzhou Wang (China University of Petroleum); Arash Farnoosh (IFPEN - IFP Energies nouvelles - IFPEN - IFP Energies nouvelles, IFP School); Xunzhang Pan (China University of Petroleum) |
| Abstract: | To reduce traffic congestion and protect the environment, license plate control (LPC) policy has been implemented in Beijing since 2011. In 2019, 100,000 vehicle license plates were distributed, including 60,000 for electric vehicle (EV) and 40,000 for gasoline vehicle (GV). However, whether the current license plate allocation is optimal from a social welfare maximization perspective remains unclear. This paper proposes a two-level Stackelberg game which portrays the interaction between vehicle applicants and the government to quantify the optimal EV license plates under the LPC policy in Beijing. The equilibrium number of EV license plates derived from the Stackelberg model is 58,800, which could increase the social welfare by 0.38%. Sensitivity analysis is conducted to illustrate the impact of important influential factors — total license plate quota, vehicle rental fee, and energy price — on EV adoption. The LPC policy under COVID-19 is also studied through a scenario analysis. If the government additionally increases the total quota by 20,000, 24% could be allocated to GV and 76% to EV. One third reduction of the current vehicle rental fee could increase EV license plates by 10.5%. Interms of energy prices, when gasoline price is low, reducing electricity price could contribute to EV adoption significantly, while that effect tapers off as the gasoline price rises. |
| Keywords: | License plate quota,Stackelberg game theory,License plate control (LPC) policy,Electric vehicle |
| Date: | 2021–09 |
| URL: | http://d.repec.org/n?u=RePEc:hal:wpaper:hal-03500766&r= |
| By: | Helene Laurent (University of Namur); Marc Sangnier; Carole Treibich |
| Abstract: | We use a simple model of drivers’ vigilance effort choice to show that drivers’ propensity to follow traffic rules has two opposite effects on road safety. On the one hand, it lowers the frequency of dangerous situations. On the other hand, it also reduces drivers’ vigilance effort as each driver anticipates that dangerous situations will be less frequent. These two opposite effects may lead to a non-monotonic relationship between compliance with road rules and the incidence of road traffic accidents. We present cross-country estimates that support the existence of a bellshaped relationship between norms of compliance with rules and traffic fatalities. |
| Date: | 2021–11 |
| URL: | http://d.repec.org/n?u=RePEc:nam:defipp:2103&r= |
| By: | Frédéric Dobruszkes; Christian Vandermotten |
| Abstract: | Investigating the determinants of air traffic has become somewhat commonplace. However, previous papers have neglected to distinguish between domestic and international markets and to think about spatial units. This paper examines the factors of passenger air traffic for the whole world and considers both national and sub-national units. The study finds that the relevant factors partially diverge between domestic and international markets. It also appears that it is more valuable to consider sub-national spatial units than countries, notwithstanding econometric results. Indeed, the geography of residuals is much richer by sub-national units, while national units clearly mask centre-periphery patterns and/or significant disparities within large countries. |
| Keywords: | Air services; Aviation; Air transport geography; Spatial units |
| Date: | 2022–01–01 |
| URL: | http://d.repec.org/n?u=RePEc:ulb:ulbeco:2013/336304&r= |
| By: | Ritika Jain; Shreya Biswas |
| Abstract: | This study examines the relationship between road infrastructure and crime rate in rural India using a nationally representative survey. On the one hand, building roads in villages may increase connectivity, boost employment, and lead to better living standards, reducing criminal activities. On the other hand, if the benefits of roads are non-uniformly distributed among villagers, it may lead to higher inequality and possibly higher crime. We empirically test the relationship using the two waves of the Indian Human Development Survey. We use an instrumental variable estimation strategy and observe that building roads in rural parts of India has reduced crime. The findings are robust to relaxing the strict instrument exogeneity condition and using alternate measures. On exploring the pathways, we find that improved street lighting, better public bus services and higher employment are a few of the direct potential channels through which road infrastructure impedes crime. We also find a negative association between villages with roads and various types of inequality measures confirming the broad economic benefits of roads. Our study also highlights that the negative impact of roads on crime is more pronounced in states with weaker institutions and higher income inequality. |
| Date: | 2021–12 |
| URL: | http://d.repec.org/n?u=RePEc:arx:papers:2112.07314&r= |