Semiparametric specification of the utility function in a travel mode choice model

We propose a semiparametric approach that can capture the nonlinearity of deterministic components of the utility functions in discrete choice models and demonstrate it by analyzing travel mode choice behaviour for an interregional trip. The proposed smoothing spline-based specification method can be used to make ex ante evaluations regarding the parametric specifications of the deterministic utility functions in discrete choice models.     

Factors influencing support for local transportation sales tax measures

Sales tax measures passed at the local level and dedicated to transportation projects have become increasingly popular in the United States. While revenues from fuel taxes stagnate, growth of local transportation sales taxes (LTSTs), most approved in local elections, has led to a gradual shift of the financial base for transportation projects away from user fees and toward broader-based taxes. In this study, the relationship between voter support and the social, political, and geographic characteristics of the voters is explored. Using precinct-level voting data and census demographic data for three local transportation sales tax elections in Sonoma County, in the San Francisco Metropolitan area of California, regression models were constructed to analyze this relationship. In addition, the relationship between the outcomes of the three measures was explored to better understand which transportation projects might have garnered more support for the successful measure. It was found that the closer voters lived to the transportation projects to be funded, the greater their support. Higher incomes were also positively related to support, controlling for other variables. Political leanings were found to affect support, with the direction of the effect dependent upon the project list in each measure’s expenditure plan. Finally, it appears that the latest measure, which passed successfully, benefited greatly from its multi-modal expenditure plan.     

Wave propagation in head on bonnet impact: Material and design issues

Head on bonnet impact is becoming more and more important in automotive design as regulations on pedestrian safety become more demanding. Despite the relatively low amount of energy involved, these impacts are truly dynamic phenomena as the event duration is comparable with the traveling time of the different wavefronts generated by the impact. In this paper, we show that we can build up a simplified model for the impact based on wave propagation analysis. Using this model, we can analyze head acceleration on existing bonnets or predict it on new ones. Head acceleration in a bonnet impact can thus be estimated over the whole area of the bonnet with a few minutes of CPU.     

Comparison of fuel efficiency and exhaust emissions between the aged and new DPF systems of Euro 5 diesel passenger car

This study was conducted to examine the impact of aged and new DPF systems of the Euro 5 diesel passenger car on fuel efficiency and exhaust emissions. Test diesel vehicle used in this study was equipped with diesel oxidation catalyst (DOC) and diesel particulate filter (DPF) as aftertreatment systems, and satisfied the Euro-5 emissions standard. The displacement volume of engine was 1.6 L and the cumulative mileage was 167,068 km before the test. The FTP-75 test procedure was used, and the time resolved and weight based exhaust emissions of total hydrocarbon (THC), carbon monoxide (CO) and nitrogen oxides (NOx) were measured. The results show that the vehicle with the new DPF system has lower emissions of THC, CO and NOx than the aged one, and fuel efficiency also increased about 5 percent. The aged DPF system had higher backpressure due to the particulate matter (mostly in the form of ash) accumulated in the DPF. As was shown in the analysis using X-CT (X-ray computer tomography), the aged DPF system had particulate matter (PM) accumulated to a length of 46.6 mm. In addition, a component analysis of PM through XRF (X-ray fluorescence) analysis found that 50 % or more of the components consisted of the P, S, Ca, and Zn.     

Schlieren,Shadowgraph, Mie-scattering visualization of diesel and gasoline sprays in high pressure/high temperature chamber under GDCI engine low load condition

Three visualization methods, Schlieren, Shadowgraph, and Mie-scattering, were applied to compare diesel and gasoline spray structures in a constant volume chamber. Fuels were injected into a high pressure/high temperature chamber under the same in-cylinder pressure and temperature conditions of low load in a GDCI (gasoline direct injection compression ignition) engine. Two injection pressures (40 MPa and 80 MPa), two ambient pressures (4.2 MPa and 1.7 MPa), and two ambient temperatures (908 K and 677 K) were use. The images from the different methods were overlapped to show liquid and vapor phases more clearly. Vapor developments of the two fuels were similar; however, different liquid developments were seen. At the same injection pressure and ambient temperature, gasoline liquid propagated more quickly and disappeared more rapidly than diesel liquid phase. At the low ambient temperature and pressure condition, gasoline and diesel sprays with higher injection pressures showed longer liquid lengths due to higher spray momentum. At the higher ambient temperature condition, the gasoline liquid length was shorter for the higher injection pressure. Higher volatility of gasoline is the main reason for this shorter liquid length under higher injection pressure and higher ambient temperature conditions. For a design of GDCI engine, it is necessary to understand the higher volatility of gasoline.     

Influence of the geometric parameters of the vehicle frontal profile on the pedestrian’s head accelerations in case of accidents

The goal of this paper is to determine how the geometry of the vehicle’s frontal profile is influencing the pedestrian’s head accelerations (linear and angular) in car-to-pedestrian accidents. In order to achieve this goal, a virtual multibody dummy of the pedestrian was developed and multiple simulations of accidents were performed using vehicles with different frontal profile geometry, from different classes. The type of accidents considered is characteristic for urban areas and occur at relatively low speed (around 30 km/h) when an adult pedestrian is struck from the rear and the head acceleration variation are the measurement of the accident severity. In the accident simulation 3D meshes were applied on the geometry of the vehicles, in order to define the contact surface with the virtual dummy, similar with real vehicles. The validation of the virtual pedestrian dummy was made by performing two crash-tests with a real dummy, using the same conditions as in the simulations. The measured accelerations in the tests were the linear and angular accelerations of the head during the impact, and these were compared with the ones from the simulations. After validating the virtual model of the car-to-pedestrian accident, we were able to perform multiple simulations with different vehicle shapes. These simulations are revealing how the geometric parameters of the vehicle’s frontal profile are influencing the head acceleration. This paper highlights the main geometric parameters of the frontal profile design that influence the head injury severity and the way that the vehicles can be improved by modifying these parameters. The paper presents an approach to determine the “friendliness” of the vehicle’s frontal profile in the car-to-pedestrian collision.     

Belief and fuzzy theories for driving behavior assessment in case of accident scenarios

The estimation of the overspeed risk before the accident is among the main goals of this paper. The proposed method uses the Energy Equivalent Speed (EES) to assess the severity of an eventual accident. However, the driver behavior evaluation should take into account the parameters related to the Driver, the Vehicle and the Environment (DVE) system. For this purpose, this paper considers a two-level strategy to predict the global risk of an event using the Dempster-Shafer Theory (DST) and the Fuzzy Theory (FT). This paper presents two methods to develop the Expert Model-based Basic Probability Assignment (EM based BPA), which is the most important task in the DST. The first one is based on the accident statistics and the second method deals with the relationship between the Fuzzy and Belief measurements. The experimental data is collected by one driver using our test vehicle and a Micro-intelligent Black Box (Micro-iBB) to collect the driving data. The sensitivity of the developed models is analysed. Our main evaluation concerns the Usage Based Insurance (UBI) applications based on the driving behavior. So, the obtained masses over the defined referential subsets in the DST are used as a score to compute the driver’s insurance premium.     

Detection of Cognitive and Visual Distraction Using Radial Basis Probabilistic Neural Networks

This paper suggests a real-time method for detecting a driver’s cognitive and visual distraction using lateral driving performance measures. The algorithm adopts radial basis probabilistic neural networks (RBPNNs) to construct classification models. In this study, combinations of two driving performance data measures, including the standard deviation of lane position (SDLP) and steering wheel reversal rate (SRR), were considered as measures of distraction. Data for training and testing the RBPNN models were collected under simulated conditions in which fifteen participants drove on a highway. While driving, they were asked to complete auditory recall tasks or arrow search tasks to create cognitively or visually distracted driving periods. As a result, the best performing model could detect distraction with an average accuracy of 78.0 %, which is a relatively high accuracy in the human factors domain. The results demonstrated that the RBPNN model using SDLP and SRR could be an effective distraction detector with easy-to-obtain and inexpensive inputs.     

Product Quality Evaluation Method Based on Product Gene Theory

Traditional quality inspection based product quality evaluation method with complex process has high operating cost and requires more professional knowledge. To remove the above limitation, this paper leads product gene theory into product quality evaluation. Methods of quality influencing factors based modeling and encoding are established. Combined with similarity theory and product gene theory, a product gene similarity analysis based quality evaluation method is proposed. The proposed method is low cost, operates easily and requires less specialized knowledge. A case study is conducted to prove the correctness and feasibility of this method.     

Reliability Modeling and Maintenance Policy Optimization for Deteriorating System Under Random Shock

Performance degradation and random shock are commonly regarded as two dependent competing risks for system failures. One method based on effective service age is proposed to jointly model the cumulative effect of random shock and system degradation, and the reliability model of degradation system under Nonhomogeneous Poisson processes (NHPP) shocks is derived. Under the assumption that preventive maintenance (PM) is imperfective and the corrective maintenance (CM) is minimal repair, one maintenance policy which combines PM and CM is presented. Moreover, the two decision variables, PM interval and the number of PMs before replacement, are determined by a multi-objective maintenance optimization method which simultaneously maximizes the system availability and minimizes the system long-run expect cost rate. Finally, the performance of the proposed maintenance optimization policy is demonstrated via a numerical example.