Perceived and actual costs of operating cars

The perception that drivers have of car operating costs is an important factor in determining modal split characteristics. Theoretical figures derived from discriminant analysis models suggest that drivers perceive only petrol costs, but this has not been cor roborated by detailed surveys. This report examines in detail perceived and actual journey to work petrol costs of a sample of London commuters. The perception is also examined of related factors, such as petrol consumption and distance, in an attempt to throw some light on the perception mechanism itself.     

Junction interactions and monotonicity in traffic assignment

We consider the traffic equilibrium problem when the travel demand is inelastic and stationary in time. Junction interactions, which abound in urban road networks, are permitted. We prove that the set of equilibria (solutions to the assignment problem) is convex when certain monotonicity and continuity conditions are statisfied at each junction.     

The dynamics of traffic assignment and traffic control: A theoretical study

The paper considers traffic assignment, with traffic controls, in an increasingly dynamic way. First, a natural way of introducing the responsive policy, P_o, into steady state traffic assignment is presented. Then it is shown that natural stability results follow within a dynamical version of this static equilibrium model (still with a constant demand). We are able to obtain similar stability results when queues are explicitly allowed for, provided demand is constant. Finally we allow demand to vary with time; we consider the dynamic assignment problem with signal-settings now fixed. Here we assume that vehicles are very short and that deterministic queueing theory applies, and show that the time-dependent queueing delay at the bottleneck at the end of a link is a monotone function of the time-dependent input profile to the bottleneck. We have been unable to obtain results when dynamic demand and responsive signal control are combined.     

Prediction of the dimensional deformation of the addendum and dedendum after the warm shrink fitting process using a correction coefficient

The warm shrink fitting process is generally used to assemble automobile transmission parts (shafts/gears). However, this process causes a deformation in the addendum and dedendum of the gear depending on the fitting interference and gear profile, and this deformation causes additional noise and vibration between the gears. To address these problems, the warm shrink fitting process is analyzed by considering the error in the dimensional deformation of the addendum and dedendum found when comparing the results of a theoretical analysis and finite element analysis (FEA). A correction coefficient that reduces this error is derived through an analysis of the difference in the cross-sectional area between the shapes used for the theoretical analysis and that of the actual gear, and a closed-form equation to predict the dimensional deformation of the addendum and dedendum is proposed. The FEA method is proposed to analyze the thermal-structural-thermal coupled field analysis of the warm shrink fitting process (heating-fitting-cooling process). To verify the closed-form equation using the correction coefficient, measurements are made of actual helical gears used in automobile transmissions. The results are in good agreement with those given by the closed-form equation.     

Major sources of hydrocarbon emissions in a premixed charge compression ignition engine

Although premixed charge compression ignition (PCCI) combustion engines are praised for potentially high efficiency and clean exhaust, experimental engines built to date emit more hydrocarbons (HCs) and carbon monoxide (CO) than the conventional machines. These compounds are not only strictly controlled components of the exhaust gas of road vehicles but are also an energy loss indicator. The prime objective of this study was to investigate the major sources of the HCs formed in the combustion chamber of an experimental PCCI engine in order to suggest some effective technologies for HC reduction. In this study, to explore the dominant sources of HC emissions in both operation modes, a single cylinder engine was prepared such that it could operate using either conventional diesel combustion or PCCI combustion. Specifically, the contributions of the top-ring crevice volume in the combustion chamber and the bulk quenching of the lean mixture were investigated. To understand the influence of the shape and magnitude of the crevice on HC emissions, the engine was operated with 12 specially prepared pistons with different top-ring crevices installed one after another. The engine emitted proportionally more HCs as the depth of the crevice increased as long as the width remained narrower than the prevailing quench distance. The top-ring-crevice-originated exhaust HCs comprised approximately 31% of the total HC emissions in the baseline condition. In a series of tests to estimate the effects of bulk quench on exhaust HC emissions, intake air was heated from 300K to 400K in steps of 25K. With the intake air heated, HC and CO emissions decreased with a gradually diminishing rate to zero at 375K. In conclusion, the most dominant sources of HC emissions in PCCI engines were the crevice volumes in the combustion chamber and the bulk quenching of the lean mixtures. The key methods for reducing HC emissions in PCCI engines are minimizing crevice volume in the combustion chamber and maximizing intake air temperature allowed based on the permissible NOx level.     

Aerodynamic design optimization of rear body shapes of a sedan for drag reduction

This study proposes an aerodynamically optimized outer shape of a sedan by using an Artificial Neural Network (ANN), which focused on modifying the rear body shapes of the sedan. To determine the optimization variables, the unsteady flow field around the sedan driving at very fast speeds was analyzed by CFD simulation, and fluctuations of the drag coefficient (C _D ) and pressure around the car were calculated. After consideration of the baseline result of CFD, 6 local parts from the end of the sedan were chosen as the design variables for optimization. Moreover, an ANN approximation model was established with 64 experimental points generated by the D-optimal methodology. As a result, an aerodynamically optimized shape for the rear end of the sedan in which the aerodynamic performance is improved by about 5.64% when compared to the baseline vehicle is proposed. Finally, it is expected that within the accepted range of shape modifications for a rear body, the aerodynamic performance of a sedan can be enhanced so that the fuel efficiency of the sedan can be improved. The YF SONATA, a sedan manufactured by Hyundai Motors Corporate, played a major role in this research as the baseline vehicle.     

High-strain-rate fracture of adhesively bonded composite joints in DCB and TDCB specimens

Double-cantilever beam (DCB) and tapered double-cantilever beam (TDCB) specimens are the test configurations most commonly used to measure the fracture toughness of composites and adhesive joints. Strain rates of 1 to 18.47 m/s were applied to the test specimens via high-speed hydraulic test equipment. Because the fracture occurs through the adhesively bonded joints and the cracks grow rapidly, the crack length and beam displacement were recorded by a high-speed camera. An energy range from 0 to 10 J was often observed in the high-strain-rate fracture experiments for nonlinear plastic behavior of the dynamically loaded adhesively bonded DCB and TDCB specimens. The range of energy release rates (fracture energy) for TDCB specimen was 2 to 3 times higher than that of a DCB specimen for all high strain rates. The fracture energy of automotive adhesive joints can be estimated using the experimental results in this study for the fracture toughness (G_IC) under high rates of loading. The crack grows as the applied fracture energy exceeds the value of the critical energy release rate (G_IC) at the crack tip. The energy release rate was calculated using the fracture mechanics formula. The key fracture mechanics parameter, the fracture energy GIC, was ascertained as a function of the test rate and can be used to assess and model the overall joint performance.     

Policy challenges of increasing automation in driving

The convergence of information and communication technologies (ICT) with automotive technologies has already resulted in automation features in road vehicles and this trend is expected to continue in the future owing to consumer demand, dropping costs of components, and improved reliability. While the automation features that have taken place so far are mainly in the form of information and driver warning technologies (classified as level I pre-2010), future developments in the medium term (level II 2010–2025) are expected to exhibit connected cognitive vehicle features and encompass increasing degree of automation in the form of advanced driver assistance systems. Although autonomous vehicles have been developed for research purposes and are being tested in controlled driving missions, the autonomous driving case is only a long term (level III 2025 +) scenario. This paper contributes knowledge on technological forecasts regarding automation, policy challenges for each level of technology development and application context, and the essential instrument of cost-effectiveness for policy analysis which enables policy decisions on the automation systems to be assessed in a consistent and balanced manner. The cost of a system per vehicle is viewed against its effectiveness in meeting policy objectives of improving safety, efficiency, mobility, convenience and reducing environmental effects. Example applications are provided that illustrate the contribution of the methodology in providing information for supporting policy decisions. Given the uncertainties in system costs as well as effectiveness, the tool for assessing policies for future generation features probabilistic and utility-theoretic analysis capability. The policy issues defined and the assessment framework enable the resolution of policy challenges while allowing worthy innovative automation in driving to enhance future road transportation.     

Fuzzy-logic applied to yaw moment control for vehicle stability

In this paper, we propose a new yaw moment control based on fuzzy logic to improve vehicle handling and stability. The advantages of fuzzy methods are their simplicity and their good performance in controlling non-linear systems. The developed controller generates the suitable yaw moment which is obtained from the difference of the brake forces between the front wheels so that the vehicle follows the target values of the yaw rate and the sideslip angle. The simulation results show the effectiveness of the proposed control method when the vehicle is subjected to different cornering steering manoeuvres such as change line and J-turn under different driving conditions (dry road and snow-covered).     

Quantifying travel time variability at a single bottleneck based on stochastic capacity and demand distributions

Travel time reliability, an essential factor in traveler route and departure time decisions, serves as an important quality of service measure for dynamic transportation systems. This article investigates a fundamental problem of quantifying travel time variability from its root sources: stochastic capacity and demand variations that follow commonly used log-normal distributions. A volume-to-capacity ratio-based travel time function and a point queue model are used to demonstrate how day-to-day travel time variability can be explained from the underlying demand and capacity variations. One important finding is that closed-form solutions can be derived to formulate travel time variations as a function of random demand/capacity distributions, but there are certain cases in which a closed-form expression does not exist and numerical approximation methods are required. This article also uses probabilistic capacity reduction information to estimate time-dependent travel time variability distributions under conditions of non-recurring traffic congestion. The proposed models provide theoretically rigorous and practically useful tools for understanding the causes of travel time unreliability and evaluating the system-wide benefit of reducing demand and capacity variability.