The urban road pricing scheme to curb pollution in Milan,Italy: Description,impacts and preliminary cost–benefit analysis assessment

Starting from January 2008 Milan implemented a charging scheme to enter an 8 km² area of the city centre. The term used to denote the scheme is Ecopass, conveying the stated political objective of the scheme: a pass to improve the quality of the urban environment (ECO). The charge depends on the Euro emission standard of the vehicle. The paper illustrates the main features and impacts of the Milan Ecopass scheme, and presents a preliminary cost–benefit analysis. The scheme has been effective in curbing not only pollution emissions, but also congestion, and the result has been achieved with low implementation costs and without major political opposition. The cost–benefits analysis presents an overall net benefit. The identification of the winners and losers of the policy is conditioned by penalty payments. Without including the penalties, the surface public transport users and the society at large are the main winners, whereas car and especially freight vehicle users are net losers.     

A forecast air pollution model applied to a hypothetical urban road pricing scheme: An empirical study in Madrid

Reducing the air pollution from increases in traffic congestion in large cities and their surroundings is an important problem that requires changes in travel behavior. Road pricing is an effective tool for reducing air pollution, as reflected currently urban road pricing outcomes (Singapore, London, Stockholm and Milan). A survey was conducted based on establishing a hypothetical urban road pricing system in Madrid (a random sample size n = 1298). We developed a forecast air pollution model with time series analysis to evaluate the consequences of possible air pollution decreases in Madrid. Results reveal that the hypothetical road pricing for Madrid could have highly significant effects on decreasing air pollution outside of the city and in the inner city during the peak operating time periods of maximum congestion (morning peak hours from 7:00 to 10:00 and evening peak hours from 18:00 to 20:00). Furthermore, this system could have significant positive effects on a shift toward using public transport and non-motorized modes inside the hypothetical toll zone. This reveals that the system has a high capacity to motivate a decrease in air pollution and impose more sustainable behavior for public transport users.     

Fast-charging station choice behavior among battery electric vehicle users

This study explores how battery electric vehicle users choose where to fast-charge their vehicles from a set of charging stations, as well as the distance by which they are generally willing to detour for fast-charging. The focus is on fast-charging events during trips that include just one fast-charge between origin and destination in Kanagawa Prefecture, Japan. Mixed logit models with and without a threshold effect for detour distance are applied to panel data extracted from a two-year field trial on battery electric vehicle usage in Japan. Findings from the mixed logit model with threshold show that private users are generally willing to detour up to about 1750 m on working days and 750 m on non-working days, while the distance is 500 m for commercial users on both working and non-working days. Users in general prefer to charge at stations requiring a shorter detour and use chargers located at gas stations, and are significantly affected by the remaining charge. Commercial users prefer to charge at stations encountered earlier along their paths, while only private users traveling on working days show such preference and they turn to prefer the stations encountered later when choosing a station in peak hours. Only private users traveling on working days show a strong preference for free charging. Commercial users tend to pay for charging at a station within 500 m detour distance. The fast charging station choice behavior is heterogeneous among users. These findings provide a basis for early planning of a public fast charging infrastructure.     

Wireless charging in California: Range,recharge, and vehicle electrification

This research evaluated the potential for wireless dynamic charging (charging while moving) to address range and recharge issues of modern electric vehicles by considering travel to regional destinations in California. A 200-mile electric vehicle with a real range of 160 miles plus 40 miles reserve was assumed to be used by consumers in concert with static and dynamic charging as a strict substitute for gasoline vehicle travel. Different combinations of wireless charging power (20–120 kW) and vehicle range (100–300 miles) were evaluated. One of the results highlighted in the research indicated that travel between popular destinations could be accomplished with a 200-mile EV and a 40 kW dynamic wireless charging system at a cost of about $2.5 billion. System cost for a 200-mile EV could be reduced to less than $1 billion if wireless vehicle charging power levels were increased to 100 kW or greater. For vehicles consuming 138 kWh of dynamic energy per year on a 40 kW dynamic system, the capital cost of $2.5 billion plus yearly energy costs could be recouped over a 20-year period at an average cost to each vehicle owner of $512 per year at a volume of 300,000 vehicles or $168 per year at a volume of 1,000,000 vehicles. Cost comparisons of dynamic charging, increased battery capacity, and gasoline refueling were presented. Dynamic charging, coupled with strategic wayside static charging, was shown to be more cost effective to the consumer over a 10-year period than gasoline refueling at $2.50 or $4.00 per gallon. Notably, even at very low battery prices of $100 per kWh, the research showed that dynamic charging can be a more cost effective approach to extending range than increasing battery capacity.     

An empirical assessment of the feasibility of battery electric vehicles for day-to-day driving

Driven by sustainability objectives, Australia like many nations in the developed world, is considering the option of battery electric vehicles (BEVs) as an alternative to conventional internal combustion engine vehicles (ICEVs). In addition to issues of capital and running costs, crucial questions remain over the specifications of such vehicles, particularly the required driving range, recharge time, re-charging infrastructure, performance, and other attributes that will be of importance to consumers. With this in mind, this paper assesses (hypothetically) the extent to which current car travel needs could be met by BEVs for a sample of motorists in Sydney assuming a home-based charging set-up, which is likely to be the primary option for early adopters of the technology. The approach uses five weeks of driving data recorded by GPS technology and builds up home-home tours to assess the distances between (in effect) charging possibilities. An energy consumption model based on characteristics of the vehicle, and the speeds recorded by the GPS is adapted to determine the charge used, while a battery recharge function is used to determine charging times based on the current battery level. Among the most pertinent findings are that over the five weeks, (i) BEVs with a range as low as 60 km and a simple home-charge set-up would be able to accommodate well over 90% of day-to-day driving, (ii) however the incidence of tours requiring out-of-home charging increases markedly for vehicles below 24 kWh (170 km range), (iii) recharge time in itself has little impact on the feasibility of BEVs because vehicles spend the majority of their time parked and (iv) effective range can be dramatically impacted by both how a vehicle is driven and use of electrical auxiliaries, and (v) while unsuitable for long, high-speed journeys without some external re-charging options, BEVs appear particularly suited for the majority of day-to-day city driving in big cities where average journey speeds of 34 km/h are close to optimal in terms of maximising vehicle range. The paper has implications for both policy-makers and auto manufacturers in breaking down some of the (perceived) barriers to greater uptake of BEVs in the future.     

How driver behaviour and parking alignment affects inductive charging systems for electric vehicles

Inductive charging, a form of wireless charging, uses an electromagnetic field to transfer energy between two objects. This emerging technology offers an alternative solution to users having to physically plug in their electric vehicle (EV) to charge. Whilst manufacturers claim inductive charging technology is market ready, the efficiency of transfer of electrical energy is highly reliant on the accurate alignment of the coils involved. Therefore understanding the issue of parking misalignment and driver behaviour is an important human factors question, and the focus of this paper. Two studies were conducted, one a retrospective analysis of 100 pre-parked vehicles, the second a dynamic study where 10 participants parked an EV aiming to align with a charging pad with no bay markings as guidance. Results from both studies suggest that drivers are more accurate at parking laterally than in the longitudinal direction, with a mean lateral distance from the centre of the bay being 12.12 and 9.57 cm (retrospective and dynamic studies respectively) compared to longitudinally 23.73 and 73.48 cm. With current inductive charging systems having typical tolerances of approximately ±10 cm from their centre point, this study has shown that only 5% of vehicles in both studies would be aligned sufficiently accurately to allow efficient transfer of electrical energy through induction.     

Objective correlates and determinants of bicycle commuting propensity in an urban environment

ObjectiveBicycle use for commuting is being encouraged not only to address physical inactivity, but also vehicular congestion, air pollution and climate change. The current study aimed to ascertain the urban environmental correlates and determinants of bicycle use for commuting (bicycle commuting) among the working or studying population in Barcelona, Spain.MethodsAdults (n = 769; 52% females) recruited whilst commuting within Barcelona (Spain) responded to a comprehensive telephone survey concerning their travel behaviour. Based upon responses collected from June 2011 to May 2012, participants were categorised into four groups: frequent bicyclists, infrequent bicyclists, willing non-bicyclists, and unwilling non-bicyclists. The determinants of frequency and willingness (propensity) to commute by bicycle were assessed by multinomial logistic regression models adjusted for potential confounders and covariates.ResultsThe number of public bicycle stations surrounding the home address and amount of greenness surrounding the work/study address were significant positive determinants of bicycle commuting propensity. On the other hand, the number of public transport stations surrounding the home address and elevation of the work/study address were significant negative determinants of bicycle commuting propensity. Individual age, education level, gender, nationality, physical activity level and commute distance significantly affected this propensity.ConclusionGreater availability of public bicycle stations and higher levels of urban greenness may increase bicycle use by adults commuting within a city such as Barcelona, Spain. Electrically-assisted public bicycles may address the challenge of elevation, making this system a more competitive mode against traditional motorised public transport.     

Traffic and emissions impact of congestion charging in the central Beijing urban area: A simulation analysis

Congestion charging is being considered as a potential measure to address the issue of substantially increased traffic congestion and vehicle emissions in Beijing. This study assessed the impact of congestion charging on traffic and emissions in Beijing using macroscopic traffic simulation and vehicle emissions calculation. Multiple testing scenarios were developed with assumptions in different charging zone sizes, public transit service levels and charging methods. Our analysis results showed that congestion charging in Beijing may increase public transit use by approximately 13%, potentially reduce CO and HC emissions by 60–70%, and reduce NOx emissions by 35–45% within the charging zone. However, congestion charging may also result in increased travel activities and emissions outside of the charging zone and a slight increase in emissions for the entire urban area. The size of charging zone, charging method, and charging rate are key factors that directly influence the impact of congestion charging; improved public transit service needs to be considered as a complementary approach with congestion charging. This study is used by Beijing Transportation Environment and Energy Center (BTEC) as reference to support the development of Beijing’s congestion charging policy and regulation.     

Assessing CO2 emissions of electric vehicles in Germany in 2030

Electric vehicles are often said to reduce carbon dioxide (CO₂) emissions. However, the results of current comparisons with conventional vehicles are not always in favor of electric vehicles. We outline that this is not only due to the different assumptions in the time of charging and the country-specific electricity generation mix, but also due to the applied assessment method. We, therefore, discuss four assessment methods (average annual electricity mix, average time-dependent electricity mix, marginal electricity mix, and balancing zero emissions) and analyze the corresponding CO₂ emissions for Germany in 2030 using an optimizing energy system model (PERSEUS-NET-TS). Furthermore, we distinguish between an uncontrolled (i.e. direct) charging and an optimized controlled charging strategy. For Germany, the different assessment methods lead to substantial discrepancies in CO₂ emissions for 2030 ranging from no emissions to about 0.55 kg/kWh_el (110 g/km). These emissions partly exceed the emissions from internal combustion engine vehicles. Furthermore, depending on the underlying power plant portfolio and the controlling objective, controlled charging might help to reduce CO₂ emissions and relieve the electricity grid. We therefore recommend to support controlled charging, to develop consistent methodologies to address key factors affecting CO₂ emissions by electric vehicles, and to implement efficient policy instruments which guarantee emission free mobility with electric vehicles agreed upon by researchers and policy makers.     

China’s electric car frustrations

By 2020, the vehicle population in China will likely exceed 280 million—exacerbating national energy security, urban air pollution, and traffic congestion. In response, many local and regional governments in China are pursuing an expanding array of measures to restrain growth in personal vehicle ownership and, along with the central government, reducing emissions and energy use of vehicles. One prominent strategy is the promotion of new energy vehicles, especially plug-in electric vehicles (PEVs). Large subsidies were offered—up to $27,600 (171,000 RMB) per vehicle in some regions, including almost $9200 (57,000 RMB) from the central government—which suggests that China is making a major commitment to PEVs. But sales have been meager. In 2013, only 17,600 PEVs, mostly buses and utility trucks, were sold, less than 0.1% of total civilian vehicle sales. Several factors explain the failure of PEV sales to take off: (1) protectionism by local governments; (2) uncertainty over which electric-drive vehicle technologies to promote and what consumers are willing to pay, (3) lagging investments in charging infrastructure, and (4) conservative investment behavior by automakers and battery manufacturers. The central government issued directives to local governments in late 2013 to reduce barriers to out-of-town companies, resulting in modest sales increases in early 2014, but a more coherent, broader, and effective set of policies, incentives, and strategies are needed to overcome consumer and industry resistance and the lack of charging infrastructure.     

Electric vehicle parking in European and American context: Economic,energy and environmental analysis

The transportation sector faces increasing challenges related to energy consumption and local and global emissions profiles. Thus, alternative vehicle technologies and energy pathways are being considered in order to overturn this trend and electric mobility is considered one adequate possibility towards a more sustainable transportation sector.In this sense, this research work consisted on the development of a methodology to assess the economic feasibility of deploying EV charging stations (Park-EV) by quantifying the tradeoff between economic and energy/environmental impacts for EV parking spaces deployment. This methodology was applied to 4 different cities (Lisbon, Madrid, Minneapolis and Manhattan), by evaluating the influence of parking premium, infrastructure cost and occupancy rates on the investment Net Present Value (NPV). The main findings are that the maximization of the premium and the minimization of the equipment cost lead to higher NPV results. The NPV break-even for the cities considered is more “easily” reached for higher parking prices, namely in the case of Manhattan with the higher parking price profile. In terms of evaluating occupancy rates of the EV parking spaces, shifting from a low usage (LU) to a high usage (HU) scenario represented a reduction in the premium to obtain a NPV = 0 of approximately 14% for a 2500 € equipment cost, and, in the case of a zero equipment cost (e.g. financed by the city), a NPV = 0 was obtained with approximately a 2% reduction in the parking premium. Moreover, due to the use of electric mobility instead of the average conventional technologies, Well-to-Wheel (WTW) gains for Lisbon, Madrid, Minneapolis and Manhattan were estimated in 58%, 53%, 52% and 75% for energy consumption and 66%, 75%, 62% and 86% for CO₂ emissions, respectively.This research confirms that the success of deploying an EV charging stations infrastructure will be highly dependent on the price the user will have to pay, on the cost of the infrastructure deployed and on the adhesion of the EV users to this kind of infrastructure. These variables are not independent and, consequently, the coordination of public policies and private interest must be promoted in order to reach an optimal solution that does not result in prohibitive costs for the users.     

Demonstration of reduced airport congestion through pushback rate control

Airport surface congestion results in significant increases in taxi times, fuel burn and emissions at major airports. This paper describes the field tests of a congestion control strategy at Boston Logan International Airport. The approach determines a suggested rate to meter pushbacks from the gate, in order to prevent the airport surface from entering congested states and to reduce the time that flights spend with engines on while taxiing to the runway. The field trials demonstrated that significant benefits were achievable through such a strategy: during eight four-hour tests conducted during August and September 2010, fuel use was reduced by an estimated 12,250–14,500 kg (4000–4700 US gallons), while aircraft gate pushback times were increased by an average of only 4.4 min for the 247 flights that were held at the gate.     

Edinburgh's Congestion Charging Plans: An Analysis of Reasons for Non-Implementation

Abstract

The City of Edinburgh in Scotland in the UK had advanced plans for a congestion charging scheme until 25 February 2005. However, these plans were abandoned at that time after a referendum that resulted in a ‘no vote’. This paper explains the origins of the scheme, outlines its nature, extent, charging technology and predicted effect; it also analyses the difficulties that exist when attempting to plan and implement such a scheme in a particular governance context, and when there is little unanimity of public opinion about the need for a scheme.

As well as the primary documentation from the proposals (e.g. public inquiry submissions, papers to government), the paper also draws upon a series of face-to-face interviews that were undertaken with key stakeholders. It also provides an analysis of press coverage in the local (Edinburgh) and national (Scottish) newspapers in the run-up to the referendum. These sources explain both the systemic and more local barriers to the scheme's implementation.

The paper draws key lessons which are important for authorities considering the implementation of a road user charging scheme, by suggesting how legislative and governance barriers to implementation can be reduced. The lessons are of relevance world wide.     

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.     

A network-based dispatch model for evaluating the spatial and temporal effects of plug-in electric vehicle charging on GHG emissions

The well-to-wheel emissions associated with plug-in electric vehicles (PEVs) depend on the source of electricity and the current non-vehicle demand on the grid, thus must be evaluated via an integrated systems approach. We present a network-based dispatch model for the California electricity grid consisting of interconnected sub-regions to evaluate the impact of growing PEV demand on the existing power grid infrastructure system and energy resources. This model, built on a linear optimization framework, simultaneously considers spatiality and temporal dynamics of energy demand and supply. It was successfully benchmarked against historical data, and used to determine the regional impacts of several PEV charging profiles on the current electricity network. Average electricity carbon intensities for PEV charging range from 244 to 391 gCO₂e/kW h and marginal values range from 418 to 499 gCO₂e/kW h.     

Statistical modeling of Electric Vehicle electricity consumption in the Victorian EV Trial,Australia

The market share of Electric Vehicles (EVs), an attractive alternative to conventional vehicles, is expected to exceed 30% of all vehicles by 2033 in Australia. Although the expected EV uptake may place greater burdens on electricity networks, the potential impacts contributed by different EV user categories and vehicle models to peak loads at different times during the day are not well understood. This paper addresses the issue through statistical analysis of the charge events in the Victorian EV Trial in Australia as well as modeling the charging behaviors according to participant categories and vehicle models. The analysis was performed on 4933 charge events that were recorded by both private and public Electric Vehicle Supply Equipment. In total, these events consumed over 33 MW h of energy over 12,170 h by the 178 trial participants, out of which about 70% were household participants while the others were fleet participants. Based on a range of EV uptake scenarios and modeled charging behaviors from the trial, the power demand in the summer of 2032/33 was estimated for all of Victoria. The results of the simulations show that the broad scale uptake of EVs produces a relatively small increase in overall power demand (estimated to be between 5.72% and 9.79% in 2032/33).     

Reconstructing maximum likelihood trajectory of probe vehicles between sparse updates

Data from connected probe vehicles can be critical in estimating road traffic conditions. Unfortunately, current available data is usually sparse due to the low reporting frequency and the low penetration rate of probe vehicles. To help fill the gaps in data, this paper presents an approach for estimating the maximum likelihood trajectory (MLT) of a probe vehicle in between two data updates on arterial roads. A public data feed from transit buses in the city of San Francisco is used as an example data source. Low frequency updates (at every 200 m or 90 s) leaves much to be inferred. We first estimate travel time statistics along the road and queue patterns at intersections from historical probe data. The path is divided into short segments, and an Expectation Maximization (EM) algorithm is proposed for allocating travel time statistics to each segment. Then the trajectory with the maximum likelihood is generated based on segment travel time statistics. The results are compared with high frequency ground truth data in multiple scenarios, which demonstrate the effectiveness of the proposed approach, in estimating both the trajectory while moving and the stop positions and durations at intersections.     

Analysis of plug-in hybrid electric vehicles’ utility factors using GPS-based longitudinal travel data

The benefit of using a PHEV comes from its ability to substitute gasoline with electricity in operation. Defined as the proportion of distance traveled in the electric mode, the utility factor (UF) depends mostly on the battery capacity, but also on many other factors, such as travel pattern and recharging pattern. Conventionally, the UFs are calculated based on the daily vehicle miles traveled (DVMT) by assuming motorists leave home in the morning with a full battery, and no charge occurs before returning home in the evening. Such an assumption, however, ignores the impact of the heterogeneity in both travel and charging behavior, such as going back home more than once in a day, the impact of available charging time, and the price of gasoline and electricity. Moreover, the conventional UFs are based on the National Household Travel Survey (NHTS) data, which are one-day travel data of each sample vehicle. A motorist’s daily travel distance variation is ignored. This paper employs the GPS-based longitudinal travel data (covering 3–18 months) collected from 403 vehicles in the Seattle metropolitan area to investigate how such travel and charging behavior affects UFs. To do this, for each vehicle, we organized trips to a series of home and work related tours. The UFs based on the DVMT are found close to those based on home-to-home tours. On the other hand, it is seen that the workplace charge opportunities significantly increase UFs if the CD range is no more than 40 miles.     

Development of a corrected average speed model for calculating carbon dioxide emissions per link unit on urban roads

The purpose of our study is to develop a “corrected average emission model,” i.e., an improved average speed model that accurately calculates CO₂ emissions on the road. When emissions from the central roads of a city are calculated, the existing average speed model only reflects the driving behavior of a vehicle that accelerates and decelerates due to signals and traffic. Therefore, we verified the accuracy of the average speed model, analyzed the causes of errors based on the instantaneous model utilizing second-by-second data from driving in a city center, and then developed a corrected model that can improve the accuracy. We collected GPS data from probe vehicles, and calculated and analyzed the average emissions and instantaneous emissions per link unit. Our results showed that the average speed model underestimated CO₂ emissions with an increase in acceleration and idle time for a speed range of 20 km/h and below, which is the speed range for traffic congestion. Based on these results, we analyzed the relationship between average emissions and instantaneous emissions according to the average speed per link unit, and we developed a model that performed better with an improved accuracy of calculated CO₂ emissions for 20 km/h and below.     

The Stockholm congestion – charging trial 2006: Overview of effects

The Stockholm congestion charging trial in 2006 demonstrated the effects of a full-scale time-differentiated urban road toll scheme. Improvements in travel times were large enough to be perceived by the general public. This was pivotal to the radical change of public attitudes that occurred during the trial and that resulted in a positive outcome of a subsequent referendum on a proposal for making the system permanent. This paper summarises the effects of the trial and analyses to what extent targets were met. Effects on congestion reduction were larger than anticipated, which also resulted in favourable economic and environmental effects. The trial showed that a single-cordon toll could affect traffic within a large area, i.e., not just close to the zone limits.