Forecasting automobile petrol demand in Australia: An evaluation of empirical models

Transport fuel consumption and its determinants have received a great deal of attention since the early 1970s. In the literature, different types of modelling methods have been used to estimate petrol demand, each having methodological strengths and weaknesses. This paper is motivated by an ongoing need to review the effectiveness of empirical fuel demand forecasting models, with a focus on theoretical as well as practical considerations in the model-building processes of different model forms. We consider a linear trend model, a quadratic trend model, an exponential trend model, a single exponential smoothing model, Holt’s linear model, Holt–Winters’ model, a partial adjustment model (PAM), and an autoregressive integrated moving average (ARIMA) model. More importantly, the study identifies the difference between forecasts and actual observations of petrol demand in order to identify forecasting accuracy. Given the identified best-forecasting model, Australia’s automobile petrol demand from 2007 through to 2020 is presented under the “business-as-usual” scenario.     

The role of cities in achieving the EU targets on biofuels for transportation: The cases of Berlin,London, Milan and Helsinki

Road transportation is a strongly growing source of CO₂, and use of biofuels represents one option to reduce end-of-pipe emissions of the existing car fleet. In this contribution, the implementation of the EU Biofuels Directive (2003/30/EC) and related voluntary measures at the local level are examined in Germany, UK, Italy and Finland and the cities of Berlin, London, Milan and Helsinki. Even though they are not directly involved in the implementation of the biofuel directive, all four cities studied have played an important role in emissions reduction by voluntarily participating in research and demonstration projects and by using biofuels in their own fleet. An analysis of the numerous causes and driving forces leading to different local level measures is provided. The environmental sensitivity, usually examined at national level, and the national level implementation of the EU Biofuels Directive (2003/30/EC) were not directly correlated with the city-level activities Instead, support from local businesses and acquisition of EU funds were considered to be valid explanatory factors for the city-level activities. In addition, through horizontal networking cities are starting to exchange know-how gained in their projects, contributing in this way to the accumulation of experience for future policies and technologies.     

An Adaptive Neuro-Fuzzy Inference System for estimating the number of vehicles for queue management at signalized intersections

Queue management is a valuable but underutilized technique which could be used to minimize the negative impacts of queues during oversaturated traffic conditions. One of the main obstacles of applying queue management techniques along signalized arterials is the unavailability of a robust and sufficiently accurate method for measuring the number of vehicles approaching a signalized intersection. The method based on counting vehicles as they enter and exit a specific detection zone with check-in and check-out detectors is unreliable because of the likely systematic under or over counting and the resulting cumulative errors. This paper describes the application of the Adaptive Neuro-Fuzzy Inference System (ANFIS) in the development of a new fuzzy logic-based approach for estimating the Number of Vehicles in a Detection Zone (NVDZ) by using detector time-occupancy data (instead of detector counts). Microscopic simulation results are used to evaluate the accuracy of the NVDZ estimates. Tests were carried out to determine the transferability of a tuned Fuzzy Inference System (FIS) and to check the sensitivity of the calibrated FIS to detection coverage, the location of the detection zone relative to the signalized (bottleneck) intersection, the length of the detection zone, and different signal timings at the bottleneck intersection. Results show that the NVDZ estimation based on fuzzy logic seems to be a feasible approach. Although the primary objective of developing the NVDZ estimation technique has been queue management, other applications such as ramp metering and incident detection could potentially use the same technique.     

On the macroscopic stability of freeway traffic

A simple model of traffic flow is used to analyze the spatio-temporal distribution of flow and density on closed-loop homogeneous freeways with many ramps, which produce inflows and allow outflows. As we would expect, if the on-ramp demand is space-independent then this distribution tends toward uniformity in space if the freeway is either: (i) uncongested; or (ii) congested with queues on its on-ramps and enough inflow to cause the average freeway density to increase with time. In all other cases, however, including any recovery phase of a rush hour where the freeway’s average density declines, the distribution of flow and density quickly becomes uneven. This happens even under conditions of perfect symmetry, where the percentage of vehicles exiting at every off ramp is the same. The flow-density deviations from the average are shown to grow exponentially in time and propagate backwards in space with a fixed wave speed. A consequence of this type of instability is that, during recovery, gaps of uncongested traffic will quickly appear in the unevenly congested stream, reducing average flow. This extends the duration of recovery and invariably creates clockwise hysteresis loops on scatter-plots of average system flow vs. density during any rush hour that oversaturates the freeway. All these effects are quantified with formulas and verified with simulations. Some have been observed in real networks. In a more practical vein, it is also shown that the negative effects of instability diminish (i.e., freeway flows increase) if (a) some drivers choose to exit the freeway prematurely when it is too congested and/or (b) freeway access is regulated in a certain traffic-responsive way. These two findings could be used to improve the algorithms behind VMS displays for driver guidance (finding a), and on-ramp metering rates (finding b).     

Potential benefits of an adaptive forward collision warning system

Forward collision warning (FCW) systems can reduce rear-end vehicle collisions. However, if the presentation of warnings is perceived as mistimed, trust in the system is diminished and drivers become less likely to respond appropriately. In this driving simulator investigation, 45 drivers experienced two FCW systems: a non-adaptive and an adaptive FCW that adjusted the timing of its alarms according to each individual driver’s reaction time. Whilst all drivers benefited in terms of improved safety from both FCW systems, non-aggressive drivers (low sensation seeking, long followers) did not display a preference to the adaptive FCW over its non-adaptive equivalent. Furthermore, there was little evidence to suggest that the non-aggressive drivers’ performance differed with either system. Benefits of the adaptive system were demonstrated for aggressive drivers (high sensation seeking, short followers). Even though both systems reduced their likelihood of a crash to a similar extent, the aggressive drivers rated each FCW more poorly than their non-aggressive contemporaries. However, this group, with their greater risk of involvement in rear-end collisions, reported a preference for the adaptive system as they found it less irritating and stress-inducing. Achieving greater acceptance and hence likely use of a real system is fundamental to good quality FCW design.     

Torsional stiffness and weight optimization of a real bus structure

In this paper, the structural optimization of a real bus structure is proposed. The proposed optimization has been accomplished by means of genetic algorithms. The structural behavior of the bus structure when subjected to weight and torsion was also analyzed using the finite element method (FEM). The results demonstrate that improved weight and torsional stiffness are achieved with the optimized structure.     

Performance of radial-type metal foam diesel particulate filters

An analytical study of the performance of a radial-type, metal foam diesel particulate filter is reported. A mathematical model for the filtration and regeneration of soot in a metal foam filter was developed. Nickel foam was selected for the filter medium due to its large specific area, high porosity, and high thermal resistance. For various metal foams, the filtration efficiency and the pressure drop through the filter were calculated, as was the deposition of soot. The results from the analytical model were compared with experimental data. In comparison with a conventional wall flow filter, the metal foam diesel particulate filter (DPF) is effective in utilizing the volume of material, due to the porous structures. As the size of the metal foam pores in the DPF increases from 580 μm to 800 μm, the filtration efficiency decreases from 90% to 50%, and the pressure drop decreases from 380 mbar to 20 mbar. The metal foam DPF with a large pore size is effective in utilizing the volume of material with a small pressure drop. The regeneration is completed within four minutes by the flow of hot exhaust gases under full load conditions.     

Minimizing vehicle post impact path lateral deviation using optimized braking and steering sequences

This paper investigates the optimal control of a vehicle, after a light impact during a traffic accident. To reduce the risk of secondary events, the control target is set: to minimize the maximum lateral deviation from the initial path. In previous analysis path control was achieved by the active control of individual wheel braking. The present paper examines potential benefits from the additional control of front steering angles. Numerical optimization is used to determine optimal control sequences for both actuator configurations. It is found that steering provides significant control benefits, though not for all post-impact kinematics. For all cases considered, the optimal control operates at the boundary of the control domain of available forces and moments. This domain is expanded when steering is available, and there exists an expanded range of conditions for which coupled control of yaw moments and lateral forces is the most effective control strategy. The sensitivity of vehicle response to the individual actuator controls is studied; it reveals this sensitivity is related to the actuator bandwidth and the lack of any dynamic cost in the longitudinal direction. This motivates a further analysis which includes longitudinal and lateral dynamics in the cost function. This is broadly related to real-world crash risks. Further, different versions of such cost functions are compared as a basis for implementation in a closed-loop controller.     

Data-driven State-of-Charge estimator for electric vehicles battery using robust extended Kalman filter

An accurate battery State-of-Charge (SoC) estimation method is one of the most significant and difficult techniques to promote the commercialization of electric vehicles. This paper tries to make two contributions to the existing literatures through a robust extended Kalman filter (REKF) algorithm. (1) An improved lumped parameter battery model has been proposed based on the Thevenin battery model and the global optimization-oriented genetic algorithm is used to get the optimal polarization time constant of the battery model. (2) A REKF algorithm is employed to build an accurate data-driven based robust SoC estimator for a LiFePO4 lithium-ion battery. The result with the Federal Urban Driving Schedules (FUDS) test shows that the improved lumped parameter battery model can simulate the dynamic performance of the battery accurately. More importantly, the REKF based SoC estimation approach makes the SoC estimation with high accuracy and reliability, it can efficiently eliminate the problem of accumulated calculation error and erroneous initial estimator state of the SoC.     

New tyre-road contact model for applications at low speed

Most of the tyre models have been developed for high speed, combined forces, etc., however, in certain tests it is necessary to know tyre behaviour at very low speed in order to evaluate different systems. So, during vehicle inspection and maintenance of the steering and brake system, by means of sideslip tester and roller brake tester respectively, the forces transmitted by the tyres are measured; all of these inspections are carried out at low speeds. Furthermore, usually, automobile vehicles run at low speeds during an important part of their operating life (less than 60 km/h), mainly during urban traffic, and in steady state conditions. Therefore, it is particularly interesting to develop an accurate model of the contact patch tyrepavement for low speeds without the complexity of models that cover a wide speed range but provide less precision at very low speeds. The dynamometer plate has proved to be an appropriate test equipment to characterise the tyre-pavement contact at low speed and the steering geometry and wheel alignment. It has the feature of being able to carry out tests with the tyre installed in the vehicle as in completely real conditions. The main aim of this research is to set up a contact model between tyre and pavement at very low speed based on the measurement of longitudinal and lateral forces. A test methodology that allows carrying out the experimental tests in a systematic and controlled way with the dynamometer plate has also been developed. From this model it will be possible to estimate the forces that tyres are capable of transmitting in different situations to act in the parameters which affect these forces and maximize them.