Comparing and presenting city-level transportation CO2 emissions using GIS

In 2011, the European Pollutant Release and Transfer Register (E-PRTR) inventory of diffuse emissions became available, providing data on a range of atmospheric emissions at a 5 km resolution across Europe. The data are produced from spatially disaggregated emissions totals for countries, and must be validated before being used at a sub-national level. The UK government maintains a 1 km resolution emissions inventory based on a bottom-up methodology by which a validation is possible. The UK National Atmospheric Emissions Inventory data are used to assess at what geographic scale the new E-PRTR data might be most useful. This paper compares the two data sets and estimates city-level transportation CO₂ emissions for 149 EU cities. We find that at a functional boundary level the two datasets match well.     

Railway traffic disturbance management—An experimental analysis of disturbance complexity,management objectives and limitations in planning horizon

With the increasing traffic volumes in European railway networks and reports on capacity deficiencies that cause reliability problems, the need for efficient disturbance management becomes evident. This paper presents a heuristic approach for railway traffic re-scheduling during disturbances and a performance evaluation for various disturbance settings using data for a large part of the Swedish railway network that currently experiences capacity deficiencies. The significance of applying certain re-scheduling objectives and their correlation with performance measures are also investigated. The analysis shows e.g. that a minimisation of accumulated delays has a tendency to delay more trains than a minimisation of total final delay or total delay costs. An experimental study of how the choice of planning horizon in the re-scheduling process affects the network on longer-term is finally presented. The results indicate that solutions which are good on longer-term can be achieved despite the use of a limited planning horizon. A 60 min long planning horizon was sufficient for the scenarios in the experiments.     

Aircraft trajectory forecasting using local functional regression in Sobolev space

This paper considers the problem of short to mid-term aircraft trajectory prediction, that is, the estimation of where an aircraft will be located over a 10–30 min time horizon. Such a problem is central in decision support tools, especially in conflict detection and resolution algorithms. It also appears when an air traffic controller observes traffic on the radar screen and tries to identify convergent aircraft, which may be in conflict in the near future. An innovative approach for aircraft trajectory prediction is presented in this paper. This approach is based on local linear functional regression that considers data preprocessing, localizing and solving linear regression using wavelet decomposition. This algorithm takes into account only past radar tracks, and does not use any physical or aeronautical parameters. This approach has been successfully applied to aircraft trajectories between several airports on the data set that is one year air traffic over France. The method is intrinsic and independent from airspace structure.     

Stochastic dynamic switching in fixed and flexible transit services as market entry-exit real options

The first analytical stochastic and dynamic model for optimizing transit service switching is proposed for “smart transit” applications and for operating shared autonomous transit fleets. The model assumes a region that requires many-to-one last mile transit service either with fixed-route buses or flexible-route, on-demand buses. The demand density evolves continuously over time as an Ornstein-Uhlenbeck process. The optimal policy is determined by solving the switching problem as a market entry and exit real options model. Analysis using the model on a benchmark computational example illustrates the presence of a hysteresis effect, an indifference band that is sensitive to transportation system state and demand parameters, as well as the presence of switching thresholds that exhibit asymmetric sensitivities to transportation system conditions. The proposed policy is computationally compared in a 24-hour simulation to a “perfect information” set of decisions and a myopic policy that has been dominant in the flexible transit literature, with results that suggest the proposed policy can reduce by up to 72% of the excess cost in the myopic policy. Computational experiments of the “modular vehicle” policy demonstrate the existence of an option premium for having flexibility to switch between two vehicle sizes.     

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.     

Simulation based population synthesis

Microsimulation of urban systems evolution requires synthetic population as a key input. Currently, the focus is on treating synthesis as a fitting problem and thus various techniques have been developed, including Iterative Proportional Fitting (IPF) and Combinatorial Optimization based techniques. The key shortcomings of these procedures include: (a) fitting of one contingency table, while there may be other solutions matching the available data (b) due to cloning rather than true synthesis of the population, losing the heterogeneity that may not have been captured in the microdata (c) over reliance on the accuracy of the data to determine the cloning weights (d) poor scalability with respect to the increase in number of attributes of the synthesized agents. In order to overcome these shortcomings, we propose a Markov Chain Monte Carlo (MCMC) simulation based approach. Partial views of the joint distribution of agent’s attributes that are available from various data sources can be used to simulate draws from the original distribution. The real population from Swiss census is used to compare the performance of simulation based synthesis with the standard IPF. The standard root mean square error statistics indicated that even the worst case simulation based synthesis (SRMSE = 0.35) outperformed the best case IPF synthesis (SRMSE = 0.64). We also used this methodology to generate the synthetic population for Brussels, Belgium where the data availability was highly limited.     

Thermodynamic,environmental and economic effects of diesel and biodiesel fuels on exhaust emissions and nano-particles of a diesel engine

In this study, diesel (JIS#2) and various biodiesel fuels (BDF20, BDF50, BDF100) are used to operate the diesel engine at 100 Nm, 200 Nm and full load; while the engine speed is 1800 rpm. The system is experimentally studied, and the energy, exergy, sustainability, thermoeconomic and exergoeconomic analyses are performed to the system. The Engine Exhaust Particle Sizer is used to measure the size distribution of engine exhaust particle emissions. Also, the data of the exhaust emissions, soot, particle numbers, fuel consumptions, etc. are measured. It is found that (i) most of the exhaust emissions (except NO_x) are directly proportional to the engine load, (ii) maximum CO₂ and NO_x emissions rates are generally determined for the BDF100 biodiesel fuel; while the minimum ones are calculated for the JIS#2 diesel fuel. On the other hand, the maximum CO and HC emissions rates are generally computed for the JIS#2 diesel fuel; while the minimum ones are found for the BDF100 biodiesel fuel, (iii) fuel consumptions from maximum to minimum are BDF100 > BDF50 > BDF20 > JIS#2 at all of the engine loads, (iv) particle concentration of the JIS#2 diesel fuel is higher than the biodiesel fuels, (v) soot concentrations of the JIS#2, BDF20 and BDF50 fuels are directly proportional to the engine load; while the BDF100 is inversely proportional, (vi) system has better energy and exergy efficiency when the engine is operated with the biodiesel fuels (vii) sustainability of the fuels are BDF100 > BDF50 > BDF20 > JIS#2, (viii) thermoeconomic and exergoeconomic parameters rates from maximum to minimum are JIS#2 > BDF20 > BDF50 > BDF100.     

Regional climate impact of aerosols emitted by transportation modes and potential effects of policies on demand and emissions

The transportation system is one of the main sectors with significant climate impact. In the U.S. it is the second main emitter of carbon dioxide. Its impact in terms of emission of carbon dioxide is well recognized. But a number of aerosol species have a non-negligible impact. The radiative forcing due to these species needs to be quantified. A radiative transfer code is used. Remote sensing data is retrieved to characterize different regions. The radiative forcing efficiency for black carbon are 396 ± 200 W/m²/AOD for the ground mode and 531 ± 190 W/m²/AOD for the air transportation, under clear sky conditions. The radiative forcing due to contrail is 0.14 ± 0.06 W/m² per percent coverage. Based on the forcing from the different species emitted by each mode of transportation, policies may be envisioned. These policies may affect demand and emissions of different modes of transportation. Demand and fleet models are used to quantify these interdependencies. Depending on the fuel price of each mode, mode shifts and overall demand reduction occur, and more fuel efficient vehicles are introduced in the fleet at a faster rate. With the introduction of more fuel efficient vehicles, the effect of fuel price on demand is attenuated. An increase in fuel price of 50 cents per gallon, scaled based on the radiative forcing of each mode, results in up to 5% reduction in emissions and 6% reduction in radiative forcing. With technologies, significant reduction in climate impact may be achieved.     

Analytical model for information flow propagation wave under an information relay control strategy in a congested vehicle-to-vehicle communication environment

Vehicular traffic congestion in a vehicle-to-vehicle (V2V) communication environment can lead to congestion effects for information flow propagation. Such congestion effects can impact whether a specific information packet of interest can reach a desired location, and if so, in a timely manner to influence the traffic system performance. Motivated by the usefulness and timeliness of information propagation, this paper aims to characterize the information flow propagation wave (IFPW) for an information packet in a congested V2V communication environment under an information relay control strategy. This strategy seeks to exclude information that is dated in the communication buffer under a first-in, first-out queue discipline, from being relayed if the information flow regime is congested. It trades off the need to enable the dissemination of every information packet as far as possible, against the congestion effects that accrue because of the presence of multiple information packets. A macroscopic two-layer model is proposed to characterize the IFPW. The upper layer is formulated as integro-differential equations to characterize the information dissemination in space and time under this control strategy. The lower layer adopts the Lighthill-Whitham-Richards model to capture the traffic flow dynamics. Based on the upper layer model, a necessary condition is derived which quantifies the expected time length that needs to be reserved for broadcasting the information packet of interest so as to ensure the formation of an IFPW under a given density of V2V-equipped vehicles. When the necessary condition is satisfied under homogeneous conditions, it is shown that the information packet can be propagated at an asymptotic speed whose value can be derived analytically. Besides, under the proposed control strategy, only a proportion of vehicles (labeled asymptotic density of informed vehicles) can receive the specific information packet, which can be estimated by solving a nonlinear equation. The asymptotic IFPW speed, the asymptotic density of informed vehicles, and the necessary condition for the IFPW, help in evaluating the timeliness of information propagation and the influence of traffic dynamics on information propagation. In addition, the proposed model can be used to numerically estimate the IFPW speed for heterogeneous conditions, which can aid in the design of traffic management strategies built upon the timely propagation of information through V2V communication.     

Capitalization of BRT network expansions effects into prices of non-expansion areas

A before and after hedonic model is used to determine the property value impacts on properties already served by the transit system caused by extensions to Bogotá’s bus rapid transit system. Asking prices of residential properties belonging to an intervention area (N = 1407 before, 1570 after) or a control area (N = 267 before, 732 after) and offered for sale between 2001 and 2006 are used to determine capitalization of the enhanced regional access provided by the extension. Properties offered during the year the extension was inaugurated and in subsequent years have asking prices that are between 13% and 14% higher than prices for properties in the control area, after adjusting for structural, neighborhood and regional accessibility characteristics of each property. Furthermore, the appreciation is similar for properties within 500 m and properties between 500 m and 1 km of the BRT.     

Biofuels in aviation: Fuel demand and CO2 emissions evolution in Europe toward 2030

This article presents the results of a scenario-based study carried out at the European Commission’s Joint Research Centre aimed at analyzing the future growth of aviation, the resulting fuel demand and the deployment of biofuels in the aviation sector in Europe. Three scenarios have been produced based on different input assumptions and leading to different underlying patterns of growth and resulting volumes of traffic. Data for aviation growth and hence fuel demand have been projected on a year by year basis up to 2030, using 2010 as the baseline. Data sources are Eurostat statistics and actual flight information from EUROCONTROL. Relevant variables such as the number of flights, the type of aircrafts, passengers or cargo tonnes and production indicators (RPKs) are used together with fuel consumption and CO₂ emissions data. The target of the European Advanced Biofuels Flightpath to ensure the commercialization and consumption of 2 million tons of sustainably produced paraffinic biofuels in the aviation sector by 2020, has also been taken into account. Results regarding CO₂ emission projections to 2030, reveal a steady annual increase in the order of 3%, 1% and 4% on average, for the three different scenarios, providing also a good correlation compared to the annual traffic growth rates that are indicated in the three corresponding scenarios. In absolute values, these ratios correspond to the central, the pessimistic and the optimistic scenarios respectively, corresponding to 360 million tonnes CO₂ emissions in 2030, ranging from 271 to 401 million tonnes for the pessimistic and optimistic scenarios, respectively. This article also reports on the supply potential of aviation biofuels (clustered in HEFA/HVOs and biojet) based on the production capacity of facilities around the world and provides an insight on the current and future trends in aviation based on the European and national policies, innovations and state-of-the art technologies that will influence the future of sustainable fuels in aviation.     

A big data approach for clustering and calibration of link fundamental diagrams for large-scale network simulation applications

Existing methods for calibrating link fundamental diagrams (FDs) often focus on a limited number of links and use grouping strategies that are largely dependent on roadway physical attributes alone. In this study, we propose a big data-driven two-stage clustering framework to calibrate link FDs for freeway networks. The first stage captures, under normal traffic state, the variations of link FDs over multiple days based on which links are clustered in the second stage. Two methods, i.e. the standard k-means algorithm combined with hierarchical clustering and a modified hierarchical clustering based on the Fréchet distance, are applied in the first stage to obtain the FD parameter matrix for each link. The calibrated matrices are input into the second stage where the modified hierarchical clustering is re-employed as a static approach resulting in multiple clusters of links. To further consider the variations of link FDs, the static approach is extended by modifying the similarity measure through the principle component analysis (PCA). The resulting multivariate time-series clustering models the distributions of the FD parameters as a dynamic approach. The proposed framework is applied on the Melbourne freeway network using one-year worth of loop detector data. Results have shown that (a) similar roadway physical attributes do not necessarily result in similar link FDs, (b) the connectivity-based approach performs better in clustering link FDs as compared with the centroid-based approach, and (c) the proposed framework helps achieving a better understanding of the spatial distribution of links with similar FDs and the associated variations and distributions of the FD parameters.     

Development and validation of a questionnaire to assess pedestrian receptivity toward fully autonomous vehicles

This study analyzes pedestrian receptivity toward fully autonomous vehicles (FAVs) by developing and validating a pedestrian receptivity questionnaire for FAVs (PRQF). The questionnaire included sixteen survey items based on attitude, social norms, trust, compatibility, and system effectiveness. 482 Participants from the United States (273 males and 209 females, age range: 18–71 years) responded to an online survey. A principal component analysis determined three subscales describing pedestrians’ receptivity toward FAVs: safety, interaction, and compatibility. This factor structure was verified by a confirmatory factor analysis and reliability of each subscale was confirmed (0.7 < Cronbach’s alpha < 0.9). Regression analyses investigated associations with scenario-based responses to the three PRQF subscale scores. Pedestrians’ intention to cross the road in front of FAVs was significantly predicted by both safety and interaction scores, but not by the compatibility score. Accepting FAVs in the existing traffic system was predicted by all three subscale scores. Demographic influence on the receptivity revealed that males and younger respondents were more receptive toward FAVs. Similarly, those from urban areas and people with higher personal innovativeness showed higher receptivity. Finally, a significant effect of pedestrian behavior (as measured by the pedestrian behavior questionnaire) on receptivity is explored. People who show positive behavior believed that the addition of FAVs will improve overall traffic safety. Those who show higher violation, lapse and aggression scores, were found to feel more confident about crossing the road in front of a FAV. This questionnaire can be a potential research tool for designing and improving FAVs for road-users outside the vehicles.     

Environmental benefits from improving transportation efficiency in wood procurement systems

Forest operations use fossil fuels, which should be considered when environmental impact in the wood procurement is of concern. Road freight transportation is the most common operation in timber transportation, and thus is an important source of greenhouse gas emissions. This study assesses the impact of the new larger and heavier vehicles (LHV) on environmental emissions using the synchronized calculation method. The maximum (theoretical) and operational effects of 76 t LHV with calculations made for three weight limits (60, 64 and 68 t) are compared in Finland. Based on Enterprise Resource Planning (ERP) data, environmental energy efficiency (measured in relation to the trip) increased 9.2%. The reduction in fuel consumption was 12.5%, though this is likely to under-estimate the long-term effects that will be achieved when forest operations are fully adjusted to the maximum weight limit. A comparison with the European countries and a preliminary sensitivity analysis of the system demonstrate that the technological development to improve the transporting efficiency is essential for realizing 76 t LHV utilization in Finland.     

Fueling for contingencies: The hidden cost of unpredictability in the air transportation system

The aviation community is increasing its attention on the concept of predictability when conducting aviation service quality assessments. Reduced fuel consumption and the related cost is one of the various benefits that could be achieved through improved flight predictability. A lack of predictability may cause airline dispatchers to load more fuel onto aircraft before they depart; the flights would then in turn consume extra fuel just to carry excess fuel loaded. In this study, we employ a large dataset with flight-level fuel loading and consumption information from a major US airline. With these data, we estimate the relationship between the amount of loaded fuel and flight predictability performance using a statistical model. The impact of loaded fuel is translated into fuel consumption and, ultimately, fuel cost and environmental impact for US domestic operations. We find that a one-minute increase in the standard deviation of airborne time leads to a 0.88 min increase in loaded contingency fuel and 1.66 min in loaded contingency and alternate fuel. If there were no unpredictability in the aviation system, captured in our model by eliminating standard deviation in flight time, the reduction in the loaded fuel would between 6.12 and 11.28 min per flight. Given a range of fuel prices, this ultimately would translate into cost savings for US domestic airlines on the order of $120–$452 million per year.     

Introducing specific power to bicycles and motorcycles: Application to electric mobility

Electric bicycles and motorcycles have emerged as a possible way of improving the transportation system sustainability. This work’s aim was to quantify the energy consumption, the trip travel and the driving dynamics on specific routes in Lisbon, Portugal. Six electric and conventional bicycles and motorcycles were monitored, and a methodology to quantify the power required in each driving second was developed: Motorcycle and Bicycle Specific Power (MSP and BSP respectively). MSP and BSP allows characterizing energy consumption rates based on on-road data and to define real-world operation patterns (driving power distribution), as well as to benchmark the different propulsion technologies under the same baseline of specific power. For negative MSP and BSP modes, the conventional and the electric motorcycles and bicycles demonstrated a similar pattern. However, their behavior was different for positive modes, since electric technologies allow reaching higher power conditions. The methodology developed estimates accurately the energy consumption (average deviation of −0.19 ± 6.76% for motorcycles and of 1.41 ± 8.91% for bicycles). The MSP and BSP methodologies were tested in 2 Lisbon routes. For the electric motorcycle an increase in trip time (+36%) was observed when compared to the conventional one, while for the electric bicycle a 9.5% decrease was verified when compared to the conventional one. The Tank-to-Wheel (TTW) energy consumption for motorcycles was reduced by 61% when shifting to electric mobility, while a 30% Well-to-Wheel (WTW) reduction is obtained. For the electric bicycles, an additional energy use is quantified due to the battery electricity consumption.     

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.     

Characteristics of air pollutants at near and far field regions of a national highway located at an industrial complex

This paper presents the characterization of air quality monitored at near field region (NFR) and far field region (FFR) of a national highway located at an industrial complex. The pollutants such as PM₁₀, SO₂ and NO₂ were monitored in two campaigns (11th September to 18th October 2012 and 18th January to 17th February 2013). The 24 h average PM₁₀ concentration at NFR and FFR were found to be 86.69 ± 18.56 μg/m³; 73.16 ± 16.21 μg/m³ and 89.44 ± 18.69 μg/m³; 81.91 ± 16.42 μg/m³, respectively during first and second campaign. In both the campaigns PM₁₀, SO₂ and NO₂ concentration at NFR was higher than FFR. The chemical characterization of PM₁₀ at NFR and FFR indicated the abundance of major elements such as Na (NFR = 30% and FFR = 32%), Ca (NFR = 12% and FFR = 14%) and ions namely NO₃⁻ (NFR = 71% and FFR = 68%) and NH₃⁺ (NFR = 15% and FFR = 19%). Further, at FFR, SO₄²⁻ and NO₃⁻ were found to be 18% and 35% higher than NFR indicating the conversions of SO₂ and NO₂ concentration into secondary particles. The measured SO₂ and NO₂ concentrations were 23 and 21% lower at FFR when compared to NFR confirms the secondary formation.The CALPUFF, EPA regulatory model was set up to understand the dynamics of air pollutants at the industrial complex. The predicted PM₁₀, SO₂ and NO₂ concentrations at NFR and FFR were found to be 32.31 ± 1.56 μg/m³ and 31.35 ± 1.27 μg/m³; 0.37 ± 0.21 μg/m³ and 0.06 ± 0.04 μg/m³; 12.83 ± 6.55 μg/m³ and 4.67 ± 2.77 μg/m³, respectively. The model showed moderate predictions for PM₁₀ (R² = 0.44–0.52), SO₂ (R² = 0.41–0.51) and NO₂ (R² = 0.45–0.61) concentrations.     

On-line estimation of state-of-charge of Li-ion batteries in electric vehicle using the resampling particle filter

Accurate battery state-of-charge (SOC) estimation is important for ensuring reliable operation of electric vehicle (EV). Since a nonlinear feature exists in the battery system and particle filter (PF) performs well in solving nonlinear or non-Gaussian problems, this paper proposes a new PF-based method for estimating SOC. Firstly, the relationships between the battery characteristics and SOC are analyzed, then the suitable battery model is developed and the unknown parameters in the battery model are on-line identified using the recursive least square with forgetting factors. The proposed battery model is considered as the state space model of PF and then SOC is estimated. All experimental data are collected from the running EVs in Beijing. The experimental errors of SOC estimation based on PF are less than 0.05 V, which confirms the good estimation performance. Moreover, the contrastive results of three nonlinear filters show PF has the same computational complexity as extend Kalman filter (EKF) and unscented Kalman filter (UKF) for low dimensional state vector, but PF have significantly better estimation accuracy in SOC estimation.