An optimization framework for workplace charging strategies

The workplace charging (WPC) has been recently recognized as the most important secondary charging point next to residential charging for plug-in electric vehicles (PEVs). The current WPC practice is spontaneous and grants every PEV a designated charger, which may not be practical or economic when there are a large number of PEVs present at workplace. This study is the first research undertaken that develops an optimization framework for WPC strategies to satisfy all charging demand while explicitly addressing different eligible levels of charging technology and employees’ demographic distributions. The optimization model is to minimize the lifetime cost of equipment, installations, and operations, and is formulated as an integer program. We demonstrate the applicability of the model using numerical examples based on national average data. The results indicate that the proposed optimization model can reduce the total cost of running a WPC system by up to 70% compared to the current practice. The WPC strategies are sensitive to the time windows and installation costs, and dominated by the PEV population size. The WPC has also been identified as an alternative sustainable transportation program to the public transit subsidy programs for both economic and environmental advantages.     

Parking subsidies and travel choices: Assessing the evidence

This article reviews empirical studies of how employer-paid parking affects employees' travel choices. A strong effect is found: parking subsidies greatly increase solo driving. When employers reduce or remove parking subsidies, a significant number of solo drivers shift to carpools and/or transit. This conclusion is based on studies of parking subsidies in a variety of circumstances, including central city and suburban areas, private and public employers, and clerical and professional employees. Three measures are developed to compare changes in commute patterns: changes in the share of solo drivers. changes in the number of autos driven to work per 100 employees, and the parking price elasticity of demand for solo driving. The studies reviewed here show that 19 to 81 percent fewer employees drive to work alone when they pay for their own parking. Because 90 percent of American commuters who drive to work receive employer-paid parking, these findings are significant for designing transportation policies to reduce air pollution, traffic congestion, and energy consumption.     

Myopic loss aversion in the response of electric vehicle owners to the scheduling and pricing of vehicle charging

Upward expectations of future electric vehicle (EV) growth pose the question about the future load on the electricity grid. While existing literature on EV charging demand management has focused on technical aspects and considered EV-owners as utility maximizers, this study proposes a behavioural model incorporating psychological aspects relevant to EV-owners facing charging decisions and interacting with the supplier. The behavioural model represents utility maximization under myopic loss aversion (MLA) within an ultimatum game (UG) framework where the two players are the EV-owner and the electricity supplier. Experimental economics allowed testing the validity of the behavioural model by designing three experiments where a potential EV-owner faces three decisions (i.e., to postpone EV charging to off-peak periods for a discount proposed by the supplier, the amount of discount to request for off-peak charging at times decided by the supplier, and the amount of discount to accept for supplier-controlled charging) under two contract durations (i.e., short-term, long-term). Findings from the experiments show that indeed potential EV-owners perform charging decisions while being affected by MLA resulting from monetary considerations and the UG participation, and that presenting long-term contracts help potential EV-owners to curtail MLA behaviour and minimise cost even though the assumption of utility maximization is violated.     

Determining locations of charging stations for electric taxis using taxi operation data

The adequate provision of charging infrastructure is critical for the effective deployment of electric taxis. This study attempts to locate charging stations for electric taxis reflecting real-world taxi travel patterns identified from taxis equipped with digital tachographs. Data for one week are processed in order to estimate their charge demand. The estimated temporal distribution of charge demand indicates that it varies day-by-day and hour-by-hour. The maximum set covering model is applied for determining the locations of charging stations. The results show that the pre-specified service distance and service coverage rate (defined by the proportion of total demand served) can be critical factors for determining the number and location of charging stations. These factors should be carefully specified by considering the tradeoff between operational efficiency of charging facilities and user convenience.     

The effect of contract renewal and competitive tendering on public transport costs,subsidies and ridership

In this paper, we aim to estimate the effect of contract renewal as well as competitive tendering on public transport costs, subsidies, and ridership. More specifically, we examine to what extent (multiple) contract renewals and introduction of competitive tendering for long-term public transport contracts affect ridership, operational costs and subsidies in concession areas governed by public transportation authorities from 2001 until 2013 in the Netherlands. Our identification strategy improves on the literature as we are able to control for all time-invariant unobserved factors, such as network and area characteristics by using panel data. We show that when renewing long-term contracts, operational costs are reduced by at least 10%, whereas subsidies fall even stronger. For contracts that are renewed at least twice, the reduction in costs is even more substantial and in the order of 16%. We find that the effect of competitive tendering is completely absent, suggesting that the threat of competitive tendering is sufficient in a market where the majority of concessions is competitive tendered. Contract renewal not only reduces costs and subsidies, but simultaneously increases public transport ridership by 7.7%. Furthermore the vehicle-hours elasticity of operational costs is 0.40, pointing to strong economies of density. The geographical scale elasticity of operational costs is around one, which indicates constant returns to scale with respect to the geographical size of the concession area. This suggest that the current size of the Dutch concession area is optimal with respect to costs.     

Will subsidies drive electric vehicle adoption? Measuring consumer preferences in the U.S. and China

We model consumer preferences for conventional, hybrid electric, plug-in hybrid electric (PHEV), and battery electric (BEV) vehicle technologies in China and the U.S. using data from choice-based conjoint surveys fielded in 2012–2013 in both countries. We find that with the combined bundle of attributes offered by vehicles available today, gasoline vehicles continue in both countries to be most attractive to consumers, and American respondents have significantly lower relative willingness-to-pay for BEV technology than Chinese respondents. While U.S. and Chinese subsidies are similar, favoring vehicles with larger battery packs, differences in consumer preferences lead to different outcomes. Our results suggest that with or without each country’s 2012–2013 subsidies, Chinese consumers are willing to adopt today’s BEVs and mid-range PHEVs at similar rates relative to their respective gasoline counterparts, whereas American consumers prefer low-range PHEVs despite subsidies. This implies potential for earlier BEV adoption in China, given adequate supply. While there are clear national security benefits for adoption of BEVs in China, the local and global social impact is unclear: With higher electricity generation emissions in China, a transition to BEVs may reduce oil consumption at the expense of increased air pollution and/or greenhouse gas emissions. On the other hand, demand from China could increase global incentives for electric vehicle technology development with the potential to reduce emissions in countries where electricity generation is associated with lower emissions.     

Area-wide travel plans—targeting strategies for greater participation in green travel initiatives: a case study of Rouse Hill Town Centre,NSW Australia

Travel planning by employers promoting more sustainable travel has delivered less car dependent behaviour for the commute in many places. Area-wide or precinct travel plans are less common but, where they exist, attempt to provide a more holistic approach through capturing synergies between employers and employees throughout a precinct. Area-based travel planning aimed at influencing employers, employees and residents are new, especially in relation to creating synergies for a single precinct that has more of an origin focus with participants travelling to diverse destinations. This paper examines various strategies that have been employed in order to achieve greener travel and to provide a self-sustaining travel planning environment. The aim of this paper is to assess the community awareness, interest and involvement with a number of green initiatives and to understand how sustainable travel planning has been absorbed by residents within a new regional centre in New South Wales, Australia. The analysis of a resident survey undertaken in 2011 distinguishes between the community awareness and their propensity to take part in each of the greener travel initiatives. The results show that a generic approach is likely to be less effective than segmenting the market so as to more directly target likely participants. Attitudes to greener travel are also highly significant and working to change them should also affect potential take up of sustainable travel initiatives. The conclusions inform the development of successful precinct based travel demand strategies both in Australia and beyond.     

Willingness-to-pay for alternative fuel vehicle characteristics: A stated choice study for Germany

In the light of European energy efficiency and clean air regulations, as well as an ambitious electric mobility goal of the German government, we examine consumer preferences for alternative fuel vehicles (AFVs) based on a Germany-wide discrete choice experiment among 711 potential car buyers. We estimate consumers’ willingness-to-pay and compensating variation (CV) for improvements in vehicle attributes, also taking taste differences in the population into account by applying a latent class model with 6 distinct consumer segments. Our results indicate that about 1/3 of the consumers are oriented towards at least one AFV option, with almost half of them being AFV-affine, showing a high probability of choosing AFVs despite their current shortcomings. Our results suggest that German car buyers’ willingness-to-pay for improvements of the various vehicle attributes varies considerably across consumer groups and that the vehicle features have to meet some minimum requirements for considering AFVs. The CV values show that decision-makers in the administration and industry should focus on the most promising consumer group of ‘AFV aficionados’ and their needs. It also shows that some vehicle attribute improvements could increase the demand for AFVs cost-effectively, and that consumers would accept surcharges for some vehicle attributes at a level which could enable their private provision and economic operation (e.g. fast-charging infrastructure). Improvement of other attributes will need governmental subsidies to compensate for insufficient consumer valuation (e.g. battery capacity).     

Analyzing the gap between the QOS demanded by PT users and QOS supplied by service operators

This research evaluated the effectiveness of tendered bus public transportation (PT) in improving the attractiveness of that service in order to promote sustainable mobility. This was accomplished by characterizing the gap between the quality of service (QOS) supplied by contract regimes and that which is demanded by passengers. Analysis of a customer satisfaction survey aimed at bus users provided insight into their ranking of 14 QOS parameters while 13 active service contracts were analyzed for their impact on QOS. In-depth interviews with relevant experts completed the complex narrative that is Israel’s policy of privatization in PT. Both qualitative and quantitative analyses helped identify those QOS parameters most in demand by passengers and impacted by contracts. The results show that the gap is minimal, high demand parameters receive increased priority in contracts. In addition this research documented an evolution in the method contracts employed to provide QOS. Late model contracts define an increasingly higher minimum QOS; but also strongly limit the operator’s ability to make service changes. This is a trend which should improve QOS in Israel but reduce the incentive for operator enacted QOS initiatives. Despite its obvious success to date, it might be time to change again the contract regime for the provision of competitive bus services in Israel.     

Workers wanted: Changing employee accessibility with industrial development ─ Evidence from Foxconn

In response to the trends of manufacturing revitalization and workforce shortage in the U.S., this study investigates how Foxconn changes accessibility to industrial employees by automobile and by transit in Southeast Wisconsin. Results suggest that there is a mismatch between the Foxconn site and the areas with high accessibility to industrial employees. With a great demand for labor, Foxconn reduces employee accessibility by automobile throughout the region, while its impact on employee accessibility by transit is more localized. The results inform industrial firm locations, workforce housing development, and transportation service provisions. The analysis framework shifts the angle of accessibility research to focusing on the perspective of employers, and it can be applied to investigate future large-scale economic development projects.     

An evaluation of national road user charging in England

This paper explores the effects of road user charging throughout England. It develops a model to test charging scenarios including revenue raising and revenue neutral charging options, and economically efficient pricing. For each scenario we estimate effects on traffic volumes, user charges and fares, subsidies, environmental costs, benefits to consumers, government revenue, and overall net benefits. We show that appropriate charging structures coupled with compensating reductions in existing motoring taxes can make a real difference to traffic growth, congestion and environmental damage, and can relieve pressure to build new roads.     

Home-based telework in France: Characteristics,barriers and perspectives

The aim of this article is to explain the gap between high social expectations, particularly in terms of reducing commuting frequency, increasing productivity and improving work-life balance, and the reality of home-based telework. We use three French databases which give information about employers but also employees. We highlight that telework is not only a fairly restricted phenomenon but also one that lacks impetus; it is mainly an informal working arrangement. The main reasons raised by both employees and employers are the uncertain advantages coupled with immediate disadvantages. The conclusion examines different contextual factors that could alter this cost-benefits dilemma and foster the development of home-based telework.     

The economics of road safety

In this paper we present a theoretical framework for the analysis of road safety in different contexts characterized by the following factors: the presence or the absence of externalities, moral hazard, taxes (subsidies), government regulation, liability insurance and multi-period insurance contracts. The main results are the following: (i) A Pareto optimal solution for insurance coverage and road safety is characterized by full insurance and a level of prevention which takes into account externalities between drivers. (ii) Without asymmetrical information, such a Pareto optimal solution can be obtained with or without a fault system for negligence if an adequate rating system is set up in order to induce individuals to take into account externalities. Taxes and subsidies can also be efficient. Government regulation of road safety is another way to reduce inefficies due to externalities. However, these interventions will not generally lead to a socially optimal level of road safety under asymmetrical information. (iii) Under asymmetrical information, two mechanisms are examined in some detail: fault for negligence and multi-period insurance contracts. It is shown that one-period liability insurance contracts (assuming that the legal system can observe the individual's level of road safety activities when accidents occur) or multi-period no-fault insurance contracts (assuming an infinite horizon with no discounting) based in part on the individual's past driving record can give individually rational self-protection activity levels which are socially efficient in presence of both moral hazard and externalities. Under less stringent assumptions, these contracts can give second-best solutions.     

Forecasting electricity demand of electric vehicles by analyzing consumers’ charging patterns

The spread of electric vehicles (EVs) and their increasing demand for electricity has placed a greater burden on electricity generation and the power grid. In particular, the problem of whether to expand the electricity power stations and distribution facilities due to the construction of EV charging stations is emerging as an immediate issue. To effectively meet the demand for additional electricity while ensuring the stability of the power grid, there is a need to accurately predict the charging demands for EVs. Therefore, this study estimates the changes in electricity charging demand based on consumer preferences for EVs, charging time of day, and types of electric vehicle supply equipment (EVSE) and elucidates the matters to be considered for constructing EV infrastructure. The results show that consumers mainly preferred charging during the evening. However, when we considered different types of EVSEs (public and private) in the analysis, people preferred to charge at public EVSEs during the day. During peak load time, people tended to prefer charging using fast public EVSEs, which shows that consumers considered the tradeoffs between the full charge time and the price for charging. Based on these findings, this study provides key political implications for policy makers to consider in taking preemptive measures to adjust the electricity supply infrastructure.     

Who can recharge a plug-in electric vehicle at home?

We construct consumer-informed estimates of residential access to vehicle charging to guide understanding of plug-in electric vehicle demand, use, and energy impacts. Using a web-based survey, study 1 estimates that about half of new car-buying US households park at least one vehicle within 25 ft of a Level 1 (110/120 V) electrical outlet at home. Study 2 estimates that just under one-third of new car-buying households in San Diego County have access to Level 2 (220/240 V) charging. Further, 20% of the sample are both able and willing to install Level 2 PEV recharging infrastructure at the prices examined.     

Impact of an electrified parkade on the built environment: An unsupervised learning approach

Proposed legislation in British Columbia would require 30 percent of new car sales to be zero-emission vehicles by 2030, and 100 percent by 2040. The growing amount of energy demand and usage data from smart meters or internet of things (IoT) devices enables new research areas. We reporton machine learning approaches to reevaluate the impacts of battery electric vehicles (BEV) on the built environment. We developed a daily power profile analysis based on unsupervised learning, to understand the underlying structure of building and BEV charging station demand data. In addition, we have implemented a load aggregation method based on the features revealed by a clustering process. This aggregation method simulates the electricity demand of an arbitrary number of charging stations, all of which are connected to the main feeder of a building. Several scenarios are simulated using charging stations and building demand data from the University of British Columbia campus in Vancouver. Results for 150 charging stations revealed that the feeder load could increase from a peak load scenario of 300 kW to more than 1000 kW during a high-consumption weekday.     

Market dynamics and indirect network effects in electric vehicle diffusion

The diffusion of electric vehicles (EVs) is studied in a two-sided market framework consisting of EVs on the one side and EV charging stations (EVCSs) on the other. A sequential game is introduced as a model for the interactions between an EVCS investor and EV consumers. A consumer chooses to purchase an EV or a conventional gasoline alternative based on the upfront costs of purchase, the future operating costs, and the availability of charging stations. The investor, on the other hand, maximizes his profit by deciding whether to build charging facilities at a set of potential EVCS sites or to defer his investments.The solution of the sequential game characterizes the EV-EVCS market equilibrium. The market solution is compared with that of a social planner who invests in EVCSs with the goal of maximizing the social welfare. It is shown that the market solution underinvests EVCSs, leading to slower EV diffusion. The effects of subsidies for EV purchase and EVCSs are also considered.     

Deployment of stationary and dynamic charging infrastructure for electric vehicles along traffic corridors

As charging-while-driving (CWD) technology advances, charging lanes can be deployed in the near future to charge electric vehicles (EVs) while in motion. Since charging lanes will be costly to deploy, this paper investigates the deployment of two types of charging facilities, namely charging lanes and charging stations, along a long traffic corridor to explore the competitiveness of charging lanes. Given the charging infrastructure supply, i.e., the number of charging stations, the number of chargers installed at each station, the length of charging lanes, and the charging prices at charging stations and lanes, we analyze the charging-facility-choice equilibrium of EVs. We then discuss the optimal deployment of charging infrastructure considering either the public or private provision. In the former, a government agency builds and operates both charging lanes and stations to minimize social cost, while in the latter, charging lanes and stations are assumed to be built and operated by two competing private companies to maximize their own profits. Numerical experiments based on currently available empirical data suggest that charging lanes are competitive in both cases for attracting drivers and generating revenue.     

Optimal locations of electric public charging stations using real world vehicle travel patterns

We propose an optimization model based on vehicle travel patterns to capture public charging demand and select the locations of public charging stations to maximize the amount of vehicle-miles-traveled (VMT) being electrified. The formulated model is applied to Beijing, China as a case study using vehicle trajectory data of 11,880 taxis over a period of three weeks. The mathematical problem is formulated in GAMS modeling environment and Cplex optimizer is used to find the optimal solutions. Formulating mathematical model properly, input data transformation, and Cplex option adjustment are considered for accommodating large-scale data. We show that, compared to the 40 existing public charging stations, the 40 optimal ones selected by the model can increase electrified fleet VMT by 59% and 88% for slow and fast charging, respectively. Charging demand for the taxi fleet concentrates in the inner city. When the total number of charging stations increase, the locations of the optimal stations expand outward from the inner city. While more charging stations increase the electrified fleet VMT, the marginal gain diminishes quickly regardless of charging speed.     

Optimal dynamic parking pricing for morning commute considering expected cruising time

This paper investigates how recurrent parking demand can be managed by dynamic parking pricing and information provision in the morning commute. Travelers are aware of time-varying pricing information and time-varying expected occupancy, through either their day-to-day experience or online information provision, to make their recurrent parking choices. We first formulate the parking choices under the User Equilibrium (UE) conditions using the Variational Inequality (VI) approach. More importantly, the System Optimal (SO) parking flow pattern and SO parking prices are also derived and solved efficiently using Linear Programming. Under SO, any two parking clusters cannot be used at the same time by travelers between more than one Origin–Destination (O–D) pairs. The SO parking flow pattern is not unique, which offers sufficient flexibility for operators to achieve different management objectives while keeping the flow pattern optimal. We show that any optimal flow pattern can be achieved by charging parking prices in each area that only depend on the time or occupancy, regardless of origins and destinations of users of this area. In the two numerical experiments, the best system performance is usually achieved by pricing the more preferred (convenient) area such that it is used up to a terminal occupancy of around 85–95%. Optimal pricing essentially balances the parking congestion (namely cruising time) and the level of convenience.