Siting public electric vehicle charging stations in Beijing using big-data informed travel patterns of the taxi fleet

Charging infrastructure is critical to the development of electric vehicle (EV) system. While many countries have implemented great policy efforts to promote EVs, how to build charging infrastructure to maximize overall travel electrification given how people travel has not been well studied. Mismatch of demand and infrastructure can lead to under-utilized charging stations, wasting public resources. Estimating charging demand has been challenging due to lack of realistic vehicle travel data. Public charging is different from refueling from two aspects: required time and home-charging possibility. As a result, traditional approaches for refueling demand estimation (e.g. traffic flow and vehicle ownership density) do not necessarily represent public charging demand. This research uses large-scale trajectory data of 11,880 taxis in Beijing as a case study to evaluate how travel patterns mined from big-data can inform public charging infrastructure development. Although this study assumes charging stations to be dedicated to a fleet of PHEV taxis which may not fully represent the real-world situation, the methodological framework can be used to analyze private vehicle trajectory data as well to improve our understanding of charging demand for electrified private fleet. Our results show that (1) collective vehicle parking “hotspots” are good indicators for charging demand; (2) charging stations sited using travel patterns can improve electrification rate and reduce gasoline consumption; (3) with current grid mix, emissions of CO₂, PM, SO₂, and NO_x will increase with taxi electrification; and (4) power demand for public taxi charging has peak load around noon, overlapping with Beijing’s summer peak power.     

Modelling and simulation of transportation system effectiveness to reduce traffic congestion: a system dynamics framework

ABSTRACT

This paper is designed to evaluate and improve the effectiveness of transportation systems and reduce traffic congestion through the use of simulation models and scenario development. A system dynamics framework is used to test and evaluate the alternatives of future strategies for the city of Surabaya, Indonesia. Some factors affecting the effectiveness of transport systems include operational effectiveness and service effectiveness, as well as uncertainty. To improve the effectiveness of transportation systems, several strategies can be implemented, such as subsidizing public transportation, increasing the cost of private vehicle parking fees, raising taxes on private vehicles, and reducing delays in public transportation through scenario development. Scenario results show that, by pursuing these strategies, effectiveness could be improved by 80% as the impact of the increase in operational and service effectiveness, helping to mitigate traffic congestion. Congestion could be reduced to 70% (on average) due to the decrease in daily traffic.     

The significant impacts on traffic and emissions of ferrying children to school in Beijing

After having implemented numerous regulations, e.g., coercive policies on vehicle use and purchase, it is becoming increasingly difficult to find further potential to control vehicle emissions in Beijing, as the air quality is still poor. This research provides a different approach for policy-makers to reduce vehicle emissions by managing demand. We found that parents ferrying their children to and from school is an important but long-neglected contributor to traffic congestion and vehicle emissions. This phenomenon is very common in China because of the social culture. In this research, parallel tests during both the school season and the non-school season were adopted, and emissions in both seasons were calculated based on travel demand and emission models. The results revealed that emissions factors (in g/km) for criteria pollutants and CO₂ increased by over 10% during rush hours during the school season due to traffic condition deterioration compared with non-school season. Daily HC, CO, NO_x, PM and CO₂ emissions from the passenger car fleet were 8.3%, 7.8%, 6.4%, 6.3% and 6.5% higher compared with those during the non-school season, respectively. These differences are greater than the total vehicular emission reduction by other control measures in 2014 in Beijing. For policy makers, providing safe and efficient ways to ferry children would be a useful and harmonious strategy for future vehicle emission control.     

Controlling vehicular emissions in Beijing during the last decade

The vehicle population of Beijing is sharply increasing at an average annual rate of 14.5%, causing severe transportation and environmental problems. The Beijing municipal government and the public have worked hard to control vehicular emissions since 1995. Strategies and measures have been introduced to regulate land use and traffic planning, emission control of in-use vehicles and new vehicles, fuel quality improvement, introduction of clean fuel vehicle technology and fiscal incentives. New development plans for Beijing will change the transportation structure by encouraging public transportation. For in-use vehicles, the I/M program has employed ASM tests since early 2003 and the government has encouraged the retirement of high-emission vehicles. For new vehicles, Beijing introduced Euro 1 and Euro 2 emission standards in early 1999 and 2003, respectively. It is also confirmed that Euro 3 standards will be introduced in 2005. At the same time, the fuel quality in Beijing was improved significantly, by banning lead and reducing sulfur among other changes. CNG and LPG were introduced in 1999 and are used in buses and taxis. Today Beijing has the largest CNG bus fleet in the world with more than 2000 dedicated CNG buses. Beijing has also focused on fiscal incentives such as tax deductions for new vehicles meeting enhanced emission standards to encourage their sales. These strategies and measures have had an impact on the control of vehicular emissions. Despite the rapid increase of the vehicle population by 60% between 1998 and 2003, total vehicular emissions have not increased. With the enhancement of vehicular emission control, the air quality in Beijing is improving as the city strives to its goal for a “Green Olympics”.     

Electric vehicle park-charge-ride programs: A planning framework and case study in Chicago

In suburban areas, combining the use of electric vehicles (EV) and transit systems in an EV Park-Charge-Ride (PCR) approach can potentially help improve transit accessibility, facilitate EV charging and adoption, and reduce the need for long-distance driving and ensuing impacts. Despite the anticipated growth of EV adoption and charging demand, PCR programs are limited. With a focus on multi-modal trips, this study proposes a generic planning process that integrates EV infrastructure development with transit systems, develops a systematic assessment approach to fostering the PCR adoption, and illustrates a case implementation in Chicago. Specifically, this study develops a Suitability Index (SI) for EV charging locations at parking spots that are suitable for both EV charging and transit connections. SI can be customized for short-term and long-term planning scenarios. SI values are derived in Chicago as an example for (1) commuter rail stations (for work trips), and (2) shopping centers near transit stops as potential opportunities for additional weekday parking and EV charging (for multi-purpose trips/MPT). Furthermore, carbon emissions and vehicle miles travelled (VMT) across various travel modes and trip scenarios (i.e., work trips and MPT) are calculated. Compared to the baseline of driving a conventional vehicle, this study found that an EV PCR commuter can reduce up to 87% of personal VMT and 52% of carbon emissions. A more active role of the public sector in the PCR program development is recommended.     

Investigations of interactions between bus rapid transit and general traffic flows

Bus rapid transit (BRT) is a popular strategy to increase transit attraction because of its high‐capacity, comfortable service, and fast travel speed with the exclusive right‐of‐way. Various engineering designs of right‐of‐way and the violation enforcement influence interactions between BRT and general traffic flows. An empirical assessment framework is proposed to investigate traffic congestion and lane‐changing patterns at one typical bottleneck along a BRT corridor. The BRT bottleneck consists of bus lane, BRT station, video enforcement zone, and transit signal priority intersection. We analyze oblique cumulative vehicle counts and oblique cumulative lane‐changing maneuvers extracted from videos. The cumulative vehicle counts method widely applied in revealing queueing dynamics at freeway bottlenecks is extended to an urban BRT corridor. In the study site, we assume four lane‐changing patterns, three of which are verified by the empirical measurements. Investigations of interactions between buses and general traffic show that abnormal behaviors (such as lane violations and slow moving of the general traffic) induce 16% reduction in the saturation rate of general traffic and 17% increase in bus travel time. Further observations show that the BRT station and its induced increasing lane‐changing maneuvers increase the downstream queue discharge flows of general traffic. The empirical results also contribute to more efficient strategies of BRT planning and operations, such as alternative enforcement methods, various lane separation types, and optimized traffic operations. Copyright © 2014 John Wiley & Sons, Ltd.     

Reducing emissions at land border crossings through queue reduction and expedited security processing

Vehicle border crossings between Mexico and the United States generate significant amounts of air pollution, which can pose health threats to personnel at the ports of entry (POEs) as well as drivers, pedestrians, and local inhabitants. Although these health risks could be substantial, there is little previous work quantifying detailed emission profiles at POEs. Using the Mariposa POE in Nogales, Arizona as a case study, light-duty and heavy-duty vehicle emissions were analyzed with the objective of identifying effective emission reduction strategies such as inspection streamlining, physical infrastructure improvements, and fuel switching. Historical traffic information as well as field data were used to establish a simulation model of vehicle movement in VISSIM. Four simulation scenarios with varied congestion levels were considered to represent real-world seasonal changes in traffic volume. Four additional simulations captured varying levels of expedited processing procedures. The VISSIM output was analyzed using the EPA’s MOVES emission simulation software for conventional air pollutants. For the highest congestion scenario, which includes a 200% increase in vehicle volume, total emissions increase by around 460% for PM_2.5 and NO_x, and 540% for CO, SO₂, GHGs, and NMHC over uncongested conditions for a two-hour period. Expedited processing and queue reduction can reduce emissions in this highest congestion scenario by as much as 16% for PM_2.5, 18% for NO_x, 20% for NMHC, 7% for SO₂ and 15% for GHGs and CO. Other potential mitigation strategies examined include fleet upgrades, fuel switching, and fuel upgrades. Adoption of some or all of these changes would not only reduce emissions at the Mariposa POE, but would have air-quality benefits for nearby populations in both the US and Mexico. Fleet-level changes could have far-reaching improvements in air quality on both sides of the border.     

Improving fuel consumption and CO2 emissions calculations in urban areas by coupling a dynamic micro traffic model with an instantaneous emissions model

Τhis study demonstrates the combination of a microscopic traffic simulator (AIMSUN) with an instantaneous emissions model (AVL CRUISE) to investigate the impact of traffic congestion on fuel consumption on an urban arterial road. The micro traffic model was enhanced by an improved car-following law according to Morello et al. (2014) and was calibrated to replicate measured driving patterns over an urban corridor in Turin, Italy, operating under adaptive urban traffic control (UTC). The method was implemented to study the impact of congestion on fuel consumption for the category of Euro 5 diesel <1.4 l passenger cars. Free flow and congested conditions led to respective consumption differences of −25.8% and 20.9% over normal traffic. COPERT 5 rather well predicted the impact of congestion but resulted to a much lower relative reduction in free flow conditions. Start and stop system was estimated to reduce consumption by 6% and 11.9% under normal and congested conditions, respectively. Using the same modelling approach, UTC was found to have a positive impact on CO₂ emissions of 8.1% and 4.5% for normal and congested conditions, respectively, considering the Turin vehicle fleet mix for the year 2013. Overall, the study demonstrates that the combination of detailed and validated micro traffic and emissions models offers a powerful combination to study traffic and powertrain impacts on greenhouse gas and fuel consumption of on road vehicles over a city network.     

A cost-competitiveness analysis of charging infrastructure for electric bus operations

This study investigates the cost competitiveness of different types of charging infrastructure, including charging stations, charging lanes (via charging-while-driving technologies) and battery swapping stations, in support of an electric public transit system. To this end, we first establish mathematical models to investigate the optimal deployment of various charging facilities along the transit line and determine the optimal size of the electric bus fleet, as well as their batteries, to minimize total infrastructure and fleet costs while guaranteeing service frequency and satisfying the charging needs of the transit system. We then conduct an empirical analysis utilizing available real-world data. The results suggest that: (1) the service frequency, circulation length, and operating speed of a transit system may have a great impact on the cost competitiveness of different charging infrastructure; (2) charging lanes enabled by currently available inductive wireless charging technology are cost competitive for most of the existing bus rapid transit corridors; (3) swapping stations can yield a lower total cost than charging lanes and charging stations for transit systems with high operating speed and low service frequency; (4) charging stations are cost competitive only for transit systems with very low service frequency and short circulation; and (5) the key to making charging lanes more competitive for transit systems with low service frequency and high operating speed is to reduce their unit-length construction cost or enhance their charging power.     

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.     

集聚经济视角下轨道交通投资对城市系统均衡的影响

随着城镇化进程加快,城市规模增加所带来的集聚效应和交通拥堵等负外部性之间的矛盾越来越突出,优化城市交通基础设施建设是缓解该矛盾的重要举措。本文同时考虑了集聚经济和交通拥挤两种外部性,构建并求解了一个两区域城市空间结构模型,分三种情况探究了轨道交通的投资引入和道路容量的优化对城市规模和城市空间结构均衡的影响。结果表明,轨道交通的投资引入能够增加城市人口规模和社会福利,使城市结构更加紧凑。但是,随着集聚经济水平的提高,城市规划者应逐步完善公交配套设施,以降低公交拥挤成本,提高公交出行分担率;还应制定相应的福利政策,避免由于个体效用下降而导致人口流出。     

Observed and simulated traffic impacts from the 2013 Bay Area Rapid Transit strike

Despite high costs, many cities build public transit to address regional equity, environmental and economic goals. Although public transit accounts for a minority of trips (～5%), the impact is widely felt when service is suspended during a strike through excess road demand and slower journeys. In 2013, Bay Area Rapid Transit (BART) workers participated in two brief strikes, and the resulting traffic conditions illustrate the value of transit to drivers in the San Francisco Bay Area region. This paper tests the impact of rail transit service interruption on freeway traffic conditions using volumes and travel times. During the strike, regional freeway conditions showed negligible change. However, on facilities that parallel BART service, the impacts are as bad as the worst day of a typical week. Conditions on the San Francisco–Oakland Bay Bridge showed significant impacts with travel times and volumes nearly doubling the baseline median values on the worst day.     

Overcoming public aversion to congestion pricing

We have completed a survey of Southern California residents designed to examine whether the details of policy design can make congestion pricing more attractive to the motoring public. A congestion fee proposal is often regarded as simply a tax increase; also, especially in the US, motorists apparently regard the use of congestion fees as coercive, in that they often have few if any practical alternatives to paying the fee. Unlike most opinion surveys on congestion pricing, our survey was quite explicit about the fate of the collected revenues. For example, we presented respondents with policies that returned a substantial portion of the revenues to the public, either in the form of cash (through reductions in sales taxes and vehicle registration fees or through income tax credits) or in the form of coupons to be used for vehicle emissions equipment repair, transit, and the like. In addition, we examined whether the typically intense opposition to congestion pricing if applied only to a part of a roadway, leaving the motorist free to choose between free lanes and toll lanes. We find that a promise to offset the imposition of congestion fees by other taxes can result in a 7% point increase in support for congestion pricing policies, and the restriction of congestion pricing to a single lane on a freeway attracts from 9% to 17% points of additional support.     

A dynamic stochastic model for evaluating congestion and crowding effects in transit systems

One of the most common motivations for public transport investments is to reduce congestion and increase capacity. Public transport congestion leads to crowding discomfort, denied boardings and lower service reliability. However, transit assignment models and appraisal methodologies usually do not account for the dynamics of public transport congestion and crowding and thus potentially underestimate the related benefits.This study develops a method to capture the benefits of increased capacity by using a dynamic and stochastic transit assignment model. Using an agent-based public transport simulation model, we dynamically model the evolution of network reliability and on-board crowding. The model is embedded in a comprehensive framework for project appraisal.A case study of a metro extension that partially replaces an overloaded bus network in Stockholm demonstrates that congestion effects may account for a substantial share of the expected benefits. A cost-benefit analysis based on a conventional static model will miss more than a third of the benefits. This suggests that failure to represent dynamic congestion effects may substantially underestimate the benefits of projects, especially if they are primarily intended to increase capacity rather than to reduce travel times.     

The efficacy of low emission zones in central London as a means of reducing nitrogen dioxide concentrations

This paper considers the effects of different strategies that might be considered to reduce the impact made by road traffic on air pollution in London. The management of road traffic in large urban areas is one of many options being considered to reduce pollutant emissions to meet statutory air pollution objectives. Increasingly, the concept of a low emission zone (LEZ) is being proposed as a means of achieving this reduction. An assessment has been made of different LEZ scenarios in central London, which involve reducing traffic flow or modifying the vehicle technology mix. Methods of predicting annual mean nitrogen dioxide concentrations utilising comprehensive traffic data and air pollution measurements have been used to develop empirical prediction models. Comparisons with statutory air pollution objectives show that significant action will be required to appreciably decrease concentrations of nitrogen dioxide close to roads. The non-linear atmospheric chemistry leading to the formation of nitrogen dioxide, results in a complex relationship between vehicle emissions and ambient concentrations of the pollutant. We show that even ambitious LEZ scenarios in central London produce concentrations of nitrogen oxides that are achieved through a “do nothing” scenario only five years later.     

Jointly optimizing cost, service, and environmental performance in demand-responsive transit scheduling

In certain fleet systems, the environmental impacts of operation are, to some extent, a controllable function of vehicle routing and scheduling decisions. However, little prior work has considered environmental impacts in fleet vehicle routing and scheduling optimization, in particular, where the impacts were assessed systematically utilizing life-cycle impact assessment methodologies such as those described by the Society of Environmental Chemistry and Toxicology. Here a methodology is presented for the joint optimization of cost, service, and life-cycle environmental consequences in vehicle routing and scheduling, which we develop for a demand-responsive (paratransit or dial-a-ride) transit system. We demonstrate through simulation that, as a result of our methodology, it is possible to reduce environmental impacts substantially, while increasing operating costs and service delays only slightly.     

Marginal costs of freeway traffic congestion with on-road pollution exposure externality

The health cost of on-road air pollution exposure is a component of traffic marginal costs that has not previously been assessed. The main objective of this paper is to introduce on-road pollution exposure as an externality of traffic, particularly important during traffic congestion when on-road pollution exposure is highest. Marginal private and external cost equations are developed that include on-road pollution exposure in addition to time, fuel, and pollution emissions components. The marginal external cost of on-road exposure includes terms for the marginal vehicle’s emissions, the increased emissions from all vehicles caused by additional congestion from the marginal vehicle, and the additional exposure duration for all travelers caused by additional congestion from the marginal vehicle. A sensitivity analysis shows that on-road pollution exposure can be a large portion (18%) of marginal social costs of traffic flow near freeway capacity, ranging from 4% to 38% with different exposure parameters. In an optimal pricing scenario, excluding the on-road exposure externality can lead to 6% residual welfare loss because of sub-optimal tolls. While regional pollution generates greater costs in uncongested conditions, on-road exposure comes to dominate health costs on congested freeways because of increased duration and intensity of exposure. The estimated marginal cost and benefit curves indicate a theoretical preference for price controls to address the externality problem. The inclusion of on-road exposure costs reduces the magnitudes of projects required to cover implementation costs for intelligent transportation system (ITS) improvements; the net benefits of road-pricing ITS systems are increased more than the net benefits of ITS traffic flow improvements. When considering distinct vehicle classes, inclusion of on-road exposure costs greatly increases heavy-duty vehicle marginal costs because of their higher emissions rates and greater roadway capacity utilization. Lastly, there are large uncertainties associated with the parameters utilized in the estimation of health outcomes that are a function of travel pollution intensity and duration. More research is needed to develop on-road exposure modeling tools that link repeated short-duration exposure and health outcomes.     

Including congestion effects in urban road traffic CO2 emissions modelling: Do Local Government Authorities have the right options?

Tailpipe emissions from vehicles on urban road networks have damaging impacts, with the problem exacerbated by the common occurrence of congestion. This article focuses on carbon dioxide because it is the largest constituent of road traffic greenhouse gas emissions. Local Government Authorities (LGAs) are typically responsible for facilitating mitigation of these emissions, and critical to this task is the ability to assess the impact of transport interventions on road traffic emissions for a whole network.This article presents a contemporary review of literature concerning road traffic data and its use by LGAs in emissions models (EMs). Emphasis on the practicalities of using data readily available to LGAs to estimate network level emissions and inform effective policy is a relatively new research area, and this article summarises achievements so far. Results of the literature review indicate that readily available data are aggregated at traffic level rather than disaggregated at individual vehicle level. Hence, a hypothesis is put forward that optimal EM complexity is one using traffic variables as inputs, allowing LGAs to capture the influence of congestion whilst avoiding the complexity of detailed EMs that estimate emissions at vehicle level.Existing methodologies for estimating network emissions based on traffic variables typically have limitations. Conclusions are that LGAs do not necessarily have the right options, and that more research in this domain is required, both to quantify accuracy and to further develop EMs that explicitly include congestion, whilst remaining within LGA resource constraints.     

Numerical analysis of electric bus fast charging strategies for demand charge reduction

Electric transit buses have been recognized as an important alternative to diesel buses with many environmental benefits. Electric buses employing lithium titanate batteries can provide uninterrupted transit service thanks to their ability of fast charging. However, fast charging may result in high demand charges which will increase the fuel costs thereby limiting the electric bus market penetration. In this paper, we simulated daily charging patterns and demand charges of a fleet of electric buses in Tallahassee, Florida and identified an optimal charging strategy to minimize demand charges. It was found that by using a charging threshold of 60–64%, a $160,848 total saving in electricity cost can be achieved for a five electric bus fleet, comparing to a charging threshold of 0–28%. In addition, the impact of fleet sizes on the fuel cost was investigated. Fleets of 4 and 12 buses will achieve the lowest cost per mile driven when one fast charger is installed.     

Making do: The effects of a mass transit strike on travel behavior

A brief transit strike in early December 1976 disrupted bus services to the city of Pittsburgh and surrounding Allegheny County. That strike provided an opportunity for testing a variety of approaches to increase ride-sharing and to reduce traffic congestion, and for examining the effect of the strike on traffic congestion and on individual travel behavior. Even though over 60% of the commuters to the CBD use transit, the effects of the strike were relatively mild. There was some increase in traffic flow into the CBD and some spreading of the peak period. The largest proportion of the transit commuters who made trips to the CBD during the strike were dropped off by a non-commuter, increasing highway traffic. The most severe impact was felt by those transit commuters who had no cars in the household; 25% of these commuters (only 3% of the total CBD commuters) stayed home from work on the first day of the strike. Most attempts to mitigate the impact of the strike had little effect, largely because most commuters were able to manage adequately during the short strike. The anticipated parking problem, on which much of the contingency planning was focused, did not emerge, largely because of the use of carpooling and drop-off mode by many of the transit users.