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on Transport Economics |
| By: | Shaheen, Susan PhD; Lazarus, Jessica; Caicedo, Juan; Bayen, Alexandre PhD |
| Abstract: | On-demand mobility services including transportation network companies (also known as ridesourcing and ridehailing) like Lyft and Uber are changing the way that people travel by providing dynamic mobility that can supplement public transit and personal-vehicle use. However, TNC services have been found to contribute to increasing vehicle mileage, traffic congestion, and greenhouse gas emissions. Pooling rides ⎯ sharing a vehicle by multiple passengers to complete journeys of similar origin and destination ⎯ can increase the average vehicle occupancy of TNC trips and thus mitigate some of the negative impacts. Several mobility companies have launched app-based pooling services in recent years including app-based carpooling services (e.g., Waze Carpool, Scoop) that match drivers with riders; pooled on-demand ride services (e.g., Uber Pool and Lyft Shared rides) that match multiple TNC users; and microtransit services (e.g., Bridj, Chariot, Via) that offer on-demand, flexibly routed service, typically in larger vehicles such as vans or shuttles. However, information on the potential impacts of these options is so far limited. This research employs a general population stated preference survey of four California metropolitan regions (Los Angeles, Sacramento, San Diego, and the San Francisco Bay Area) in Fall 2018 to examine the opportunities and challenges for drastically expanding the market for pooling, accounting for differences in emergent travel behavior and preferences across the four metropolitan regions surveyed. The travel profiles, TNC use patterns, and attitudes and perceptions of TNCs and pooling are analyzed across key socio-demographic attributes to enrich behavioral understanding of marginalized and price sensitive users of on-demand ride services. This research further develops a discrete choice model to identify significant factors influencing a TNC user’s choice to pool or not to pool, as well as estimating a traveler’s value of time (VOT) across different portions of a TNC trip. This research provides key insights and social equity considerations for policies that could be employed to reduce vehicle miles traveled and emissions from passenger road transportation by incentivizing the use of pooled on-demand ride services and public transit |
| Keywords: | Engineering, Demand responsive transportation, ridesourcing, shared mobility, stated preference, surveys, travel behavior, choice models |
| Date: | 2021–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsrrp:qt44q6n0mm&r=all |
| By: | Volker, Jamey M.B. PhD; Handy, Susan L PhD |
| Abstract: | The National Center for Sustainable Transportation’s Induced Travel Calculator (Calculator) has generated substantial interest in the professional community as a method for estimating the additional vehicle miles traveled (VMT) induced by expanding the capacity of major roadways. The Institute of Transportation Studies at the University of California, Davis (ITS-Davis) initiated a technical assistance project to support Caltrans and others in applying the Calculator. This report: (1) provides an overview of the Calculator and the induced vehicle travel effect, (2) summarizes the results from an earlier study comparing the Calculator’s estimates with other induced travel analyses, (3) describes the technical assistance efforts and outcomes, and (4) discusses plans for future improvements to the Calculator. During the project, ITS-Davis advised Caltrans as it developed its Transportation Analysis Framework to guide transportation impact analysis for projects on the State Highway System. Caltrans published the final document in September 2020, in which it recommends that the Calculator be used where possible to estimate induced VMT. ITS-Davis also advised on efforts to apply the Calculator’s elasticity-based method to estimate induced VMT from out-of-state highway capacity expansion projects, including projects in Portland, Oregon, Washington, D.C., Kenya, and China. In a follow-up project, ITS-Davis will work with Caltrans to improve the Calculator documentation to answer questions raised by Caltrans and others, explore possible technical improvements to the Calculator, and explore opportunities for assessing the validity of the Calculator’s induced VMT estimates. |
| Keywords: | Engineering, Vehicle miles of travel, travel demand, road construction, traffic, traffic forecasting, calculators, mathematical models |
| Date: | 2021–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt2nr6q5rc&r=all |
| By: | Rodier, Caroline PhD; Harold, Brian MBA; Zhang, Yunwan MS |
| Abstract: | In rural areas, cost-effective transit service is challenging to provide due to greater travel distances, lower population densities, and longer travel times than in cities. The people who rely on public transit contend with infrequent and slow service. Access to a personal car is often essential to the quality of life for most residents, enabling them to more easily access work, health care, education, healthy food, and other essential services. However, keeping two (or sometimes even one) car in reliable working order can consume an estimated 22% to 56% of the household budget for low-income families in California. Rural residents often have lower incomes than their urban counterparts, and the most fuel-efficient vehicles, particularly electric vehicles (EVs), are often outside their financial reach. An EV carsharing pilot, called Míocar, was launched in August 2019 to explore the potential of a shared mobility service to offer a cost-effective mobility option for residents of rural disadvantaged communities and to help reduce greenhouse gas emissions. Affordable housing complexes host the round-trip EV carsharing hubs in southern San Joaquin Valley (CA) communities with low levels of intercity transit service and personal vehicles. The goals of the pilot program are (a) to provide carsharing at a price point that is more affordable than owning a personal vehicle to price-sensitive populations with low transit access; and (b) to help reduce greenhouse gas emissions. This report summarizes the data collected during the 10-month operational rampup of the Míocar service—the entire dataset links members and their service use data with results from member and post reservation surveys. The results provide initial insights into who, how, and why members are using Míocar. |
| Keywords: | Social and Behavioral Sciences, Electric vehicles, vehicle sharing, social equity, rural areas, rural transportation, pilot studies, low income groups, data collection |
| Date: | 2021–02–01 |
| URL: | http://d.repec.org/n?u=RePEc:cdl:itsdav:qt0rj0z090&r=all |
| By: | Anna Kowalska-Pyzalska; Rafał Michalski; Marek Kott; Anna Skowrońska-Szmer; Joanna Kott |
| Abstract: | Alternative fuel vehicles (AFVs) are an important element of sustainable development and electromobility. Within our complex, two stages survey (CATI and CAWI) we used the conjoint method to compare and balance the important factors responsible for consumers' preferences towards AFV, in one study, allowing a relative assessment to be made. As a result, we got 6 separate conjoints (depending on the type of purchase: direct purchase or leasing) and the type of vehicle (HEV, PHEV and BEV). Although each conjoint contains different sets of factors, the methodological regime is followed. Our results indicate that surprisingly safety is the most important feature of a good AFV car. Then, the price, range and type of the car also matter. These findings recommend car manufactures and policy makers what they should focus on while designing and promoting AFV. |
| Keywords: | Consumer preferences; Electric vehicles; Plug-in electric vehicles; Hybrid electric vehicles; Conjoint analysis; On-line survey; Sustainable transport |
| Date: | 2021–02–09 |
| URL: | http://d.repec.org/n?u=RePEc:ahh:wpaper:worms2102&r=all |
| By: | Xu, Lili; Lee, Sang-Ho |
| Abstract: | This paper focuses on the international transportation market in which a high-speed rail (HSR) firm competes with both the domestic and foreign airline firms providing differentiated transport services. We investigate and compare two types of corporate social responsibility (CSR)—mandatory and voluntary CSR—imposed on HSR under a government subsidy policy. We show that, when the transport substitutability is high (low) in a domestic travel leg, mandatory CSR is lower (higher) than voluntary CSR, and the optimal subsidy under mandatory CSR is lower (higher) than that under voluntary CSR. We also examine the effect of privatization policy of the HSR with transposition subsidy on welfare. We show that full privatization with CSR activities always improves social welfare under an appropriate subsidy, independent of the transport substitutability and types of CSR activities. |
| Keywords: | High-speed rail, corporate social responsibility, transportation subsidy, privatization policy, mixed market |
| JEL: | D43 H25 L21 L33 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:106259&r=all |
| By: | Aldred, Rachel; Verlinghieri, Ersilia; Sharkey, Megan; Itova, Irena; Goodman, Anna |
| Abstract: | In this article we examine equity in new active travel infrastructure in London, UK. We focus on Low Traffic Neighbourhood schemes (LTNs) introduced during Covid-19. These mainly involve ‘modal filters’ that restrict through motor traffic from residential streets. Such approaches to traffic management are traditional in the Netherlands, but relatively new in London and other global cities such as Barcelona. LTNs are often controversial, with one criticism being that they are implemented in affluent areas and hence benefit richer residents. London represents an excellent opportunity to investigate the extent to which these rapidly introduced schemes have so far been equitably distributed. We focused on LTNs introduced between March and September 2020 and still present at the end of October 2020. Having generated datasets representing these new LTN locations and their boundary roads, we matched these to Output Areas (OAs, administrative areas containing around 300 residents). We then examined the extent to which LTN implementation was associated with age, ethnicity, disability, employment and car ownership (Census 2011) and small-area deprivation (Index of Multiple Deprivation 2019). We estimated that 3.7% of all Londoners live inside a new LTN, and 8.8% live within 500m walking distance of a new modal filter. Across London as a whole, people in the most deprived quarter of OAs were 2.7 times more likely to live in or near a new LTN, compared to Londoners in the least deprived quarter. While overall Black, Asian and Minority Ethnic (BAME) people were slightly more likely than White Londoners to live in a new LTN, this varied by ethnic group. Specifically, Black Londoners were somewhat more likely, and Asian Londoners somewhat less likely than White people to live in or near a new LTN. Car-free households were more likely to live in or near a new LTN. Within London’s districts – which lead the implementation of LTNs - there was wide variation, with people in more deprived areas and/or ethnic minorities more likely to live in an LTN in some districts, less likely in others. In the median (‘typical’) district, people in more deprived areas were more likely to live in an LTN than people in less deprived areas, suggesting that, on average, individual districts have prioritised their more deprived areas. However, in the median district, BAME residents were slightly less likely to live in an LTN than White residents. Finally, at the micro level, residents living in LTNs were demographically similar to neighbours living in OAs that touched an LTN boundary road. We conclude that LTN implementation has been broadly equitable at the city level and at the micro level, but not always at the district level. Such metrics should be used in policy and research to monitor and improve the equity of active travel interventions. |
| Date: | 2021–02–26 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:q87fu&r=all |
| By: | Jennie Lioris (ENPC - École des Ponts ParisTech); Neila Bhouri (COSYS-GRETTIA - Génie des Réseaux de Transport Terrestres et Informatique Avancée - Université Gustave Eiffel) |
| Abstract: | The level lane location problem of sensor equipped vehicles circulating within arbitrary highway infrastructures is addressed. A first approach of a flexible probabilistic decision-making policy is developed utilizing sensor signals. Unmanned vehicles independently of the automation degree are related to challenging executive schemes such as adaptive cruise control systems, real time routing models involving lane changing options and speed control, platoon formation operations etc. An adaptive, closed loop methodology is presented localizing suitable detections while involving uncertainty within data, sensor vagueness and trust. The whole scheme is associated with low computational complexity where no additional investment on external devices is required. The outlined framework pronounces a significantly progressed study regarding a previously presented elementary pattern. The new model focuses in the case of invalid sensor detections due to traffic context, various environmental disturbances and failures for which no response was previously available. The effectiveness of the suggested scheme is measured when applied to detailed simulation scenarios fed by ground truth data. Different complex spatiotemporal contexts elicit varying driving profiles and pragmatic behavior-change interventions unaccessible from direct recordings provided by professional drivers. The proposed methodology is compared with a non-probabilistic model. Analysis illustrates noteworthy accuracy, precision and frequency on the resulting responses. |
| Keywords: | HIGHLY AUTOMATED DRIVING FUCTIONS - HADF,LANE IDENTIFICATION,REAL TIME PATH AND TARGET TRACKING CONTROL,DATA MINING,ROAD NAVIGATION,AUTOPILOT PERCEPTION,ENVIRONMENT PERCEPTION,ADAPTIVE POLICY FOR SMART SENSOR UTILIZATION |
| Date: | 2020–11–26 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-03130694&r=all |
| By: | Kishore Bhoopalam, A.; van den Berg, R.; Agatz, N.A.H.; Chorus, C.G. |
| Abstract: | With the rapid progress of automated driving technology, self-driving vehicles are on the horizon. In this study, we look at what is likely to be the first implementation of a form of automated driving on public roads, i.e., truck platooning, where virtually connected trucks drive at short headways to save fuel and associated emissions. With progressing technology, we may see platoons with drivers resting while being in the truck or even platoons in which not all trucks require drivers. Hence, platooning technology has a significant impact on the jobs of truck drivers. Driver acceptance of this emerg- ing technology is therefore an important factor in the implementation of platooning and, consequently, automated driving in general. In this study, we explore the range of per- spectives that exist among drivers by conducting focus groups in the Netherlands. These discussions indicate that drivers foresee that platooning will eventually become a reality but believe it will have a negative impact on the quality of their work and their job satisfaction. |
| Keywords: | automated trucking, driver focus groups, self-driving vehicles, truck platooning |
| Date: | 2021–02–04 |
| URL: | http://d.repec.org/n?u=RePEc:ems:eureri:134317&r=all |
| By: | Di Foggia, Giacomo |
| Abstract: | Low-carbon economy roadmaps aim to reduce transport emissions by relying, at least to some extent, on electric vehicles. The uptake of electric vehicles on a mass scale requires the simultaneous adoption of such vehicles for private and commercial purposes. Although literature regarding the private sphere is consistent, there is comparatively less empirical research seeking to explain the factors that enable and hinder the uptake of electric vehicles at a commercial level at which fleet managers have a prominent role. Based on an empirical survey conducted in Italy, this paper investigates the role of technical and financial information in fleet managers’ procurement decision-making. Results suggest a lack of awareness regarding technical characteristics of vehicles, given that 59% of the fleet managers surveyed scored low to medium. Furthermore, a misalignment related to the expected investment payback period was observed, considering that 49% declared that they expect a payback period within three years. Given that exposure to electric vehicles within fleets constitutes an incentive for private purchase, well-designed policies for corporate fleets’ electrification would lead to remarkable growth of the electric vehicles market. |
| Date: | 2021–02–11 |
| URL: | http://d.repec.org/n?u=RePEc:osf:socarx:b3e56&r=all |
| By: | Yuhei Miyauchi; Kentaro Nakajima; Stephen J. Redding |
| Abstract: | We provide new theory and evidence on the role of consumption access in understanding the agglomeration of economic activity. We combine smartphone data that records user location every 5 minutes of the day with economic census data on the location of service-sector establishments to measure commuting and non-commuting trips within the Greater Tokyo metropolitan area. We show that non-commuting trips are frequent, more localized than commuting trips, strongly related to the availability of nontraded services, and occur along trip chains. Guided by these empirical findings, we develop a quantitative urban model that incorporates travel to work and travel to consume non-traded services. Using the structure of the model, we estimate theoretically-consistent measures of travel access, and show that consumption access makes a sizable contribution relative to workplace access in explaining the observed variation in residents and land prices across locations. Undertaking counterfactuals for changes in travel costs, we show that abstracting from consumption trips leads to a substantial underestimate of the welfare gains from a transport improvement (because of the undercounting of trips) and leads to a distorted picture of changes in travel patterns within the city (because of the different geography of commuting and non-commuting trips). |
| Keywords: | agglomeration, urbanization, transportation |
| JEL: | O18 R12 R40 |
| Date: | 2021–02 |
| URL: | http://d.repec.org/n?u=RePEc:cep:cepdps:dp1745&r=all |
| By: | Desjardins, Denise (HEC Montreal, Canada Research Chair in Risk Management); Dionne, Georges (HEC Montreal, Canada Research Chair in Risk Management); Lu, Yang (Concordia University) |
| Abstract: | We propose a hierarchical random effect model for the posterior insurance ratemaking of vehicles belonging to a fleet by allowing random effects for fleet, vehicle, and time. The model is an alternative to the gamma-Dirichlet model of Angers et al (2018), which does not allow for a closed form posterior ratemaking formula. Our theoretical extension derives a simple and tractable closed form ratemaking formula based on a hierarchical random effects specification. We estimate the corresponding econometric model and compute insurance premiums in relation to the past experience of both the vehicle and the fleet. Our econometric model can also be applied to any other dynamic count modeling application with random individual, time, and common effects, such as labor contracting, chirurgical accidents, or any other random event implying principals and many agents. |
| Keywords: | Hierarchical model; vehicle insurance pricing; posterior ratemaking; random effect; hierarchical random effects; panel data |
| JEL: | C23 C25 C55 G22 |
| Date: | 2021–02–18 |
| URL: | http://d.repec.org/n?u=RePEc:ris:crcrmw:2021_002&r=all |
| By: | Fernando E. Alvarez (University of Chicago - Department of Economics; NBER); David O. Argente (Pennsylvania State University - Department of Economics) |
| Abstract: | We use three quasi-natural experiments in Mexico and one in Panama to estimate the effects of having the option to pay with cash on Uber rides. The ability to pay in cash affects the demand for rides, which is reflected in large changes in the total number of trips, fares, miles, and number of users after Uber introduced cash payments, particularly in lower-income city blocks. On the other hand, the effects on prices, estimated times of arrival, and competitor pricing are negligible, consistent with the supply of trips being very elastic. Although cash payments naturally increase the fraction of users that pay exclusively with cash, more than half of the users have access to both cards and cash, and alternate between payment methods. We find evidence consistent with cash and card payments being imperfectly substitutable at both the intensive and extensive margins, which magnifies the impact of policies that restrict the availability of payment methods. |
| JEL: | E41 |
| Date: | 2020 |
| URL: | http://d.repec.org/n?u=RePEc:bfi:wpaper:2020-173&r=all |