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.     

Simulating the impacts of household travel on greenhouse gas emissions,urban air quality,and population exposure

This paper establishes a link between an activity-based model for the Greater Toronto Area (GTA), dynamic traffic assignment, emission modelling, and air quality simulation. This provides agent-based output that allows vehicle emissions to be tracked back to individuals and households who are producing them. In addition, roadway emissions are dispersed and the resulting ambient air concentrations are linked with individual time-activity patterns in order to assess population exposure to air pollution. This framework is applied to evaluate the effects of a range of policy interventions and 2031 scenarios on the generation of vehicle emissions and greenhouse gases in the GTA. Results show that the predicted increase of approximately 2.6 million people and 1.3 million jobs in the region by 2031 compared to 2001 levels poses a major challenge in achieving meaningful reductions in GHGs and air pollution.     

Isolating high-priority metro and feeder bus transfers using smart card data

Fixed-rail metro (or ‘subway’) infrastructure is generally unable to provide access to all parts of the city grid. Consequently, feeder bus lines are an integral component of urban mass transit systems. While passengers prefer a seamless transfer between these two distinct transportation services, each service’s operations are subject to a different set of factors that contribute to metro-bus transfer delay. Previous attempts to understand transfer delay were limited by the availability of tools to measure the time and cost associated with passengers’ transfer experience. This paper uses data from smart card systems, an emerging technology that automatically collects passenger trip data, to understand transfer delay. The primary objective of this study is to use smart card data to derive a reproducible methodology that isolates high priority transfer points between the metro system and its feeder-bus systems. The paper outlines a methodology to identify transfer transactions in the smart card dataset, estimate bus headways without the aid of geographic location information, estimate three components of the total transfer time (walking time, waiting time, and delay time), and isolate high-priority transfer pairs. The paper uses smart card data from Nanjing, China as a case study. The results isolate eight high priority metro-bus transfer pairs in the Nanjing metro system and finally, offers several targeted measures to improve transfer efficiency.     

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.     

Fuel consumption of fuel cell hybrid vehicles considering battery SOC differences

Fuel cell hybrid vehicles (FCHVs) have become one of the most promising candidates for future transportation due to current energy supply problem and environmental problem. Fuel economy is an important factor in FCHVs. In order to properly evaluate the fuel economy of an FCHV, the initial battery state of charge (SOC) and the final battery SOC have to be identical so that the effect of the battery energy usage on the fuel economy is neglected. In the simulation or in the real driving, however, the final battery SOC is usually different from the initial battery SOC, and the final battery SOC often depends on the power management strategy. To consider the difference between the two battery SOC values, the concept of equivalent fuel consumption is presented by two methods. One is based on the relationship between delta SOC and delta fuel consumption, and the other is based on the optimal control theory. Two rule-based power management strategies for an FCHV are presented, and for each strategy, the fuel economy is evaluated based on the two methods. The characteristics of the two methods are discussed and compared, and the superior one is selected based on the comparison.     

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.     

Vibration reduction of H/Shaft using an electromagnetic damper with mode change

The objective of this study is to develop a damper that can reduce the amplitude of vibration in various frequency ranges. Previous H/Shaft vibration reduction methods work in a passive way. A dynamic damper reduces the amplitude of vibration at its first mode, but vibration still appears at the second mode. A mass damper or hollow shaft can shift the natural frequency to a lower or higher region. The fixed operating frequency prevents vibration from being reduced outside the operating frequency range. The proposed damper uses electromagnets as either masses or actuators to change the damper mode between dynamic damper mode and mass damper mode. The electromagnetic damper (EMD) can change its mode to respond to the vibration excitation at both low and high frequencies. The vibration reduction performance was evaluated by FRF tests in laboratory and vehicle conditions. The results were compared with those of a dynamic damper and indicate that the amplitude of vibration is reduced by 95.6 % when the EMD is implemented on an H/Shaft, whereas only 61.9 % vibration reduction is achieved by the dynamic damper.     

Simulation of mixed gas formation for a spray-wall complex guided LPG direct injection engine

To obtain an ultralean air-fuel ratio and to reduce engine-out NOX and HC emissions induced by the richer mixture near the spark plug, a spray and wall complex guided combustion system has been developed by utilizing the fuel characteristics of LPG. The new combustion system configuration is optimized by using a commercial CFD code, FIRE V2013, and the reliability of the system has been experimentally demonstrated by Plane Laser-Induced Fluorescence (PLIF). The mixture formation in the new combustion system under part load (2,000 rpm) is numerically simulated. With an injection timing of 40°CA BTDC, the LPG spray which is injected from two upper holes, reaches the ignition point, and the other part of the LPG spray which is injected from the bottom hole, is directed to the ignition point through the vertical vortices at the same time. At the ignition timing of about 20°CA BTDC, the two-part mixtures have been shown to form a stable and richer stratified mixture around the ignition point, and the maximum global air-fuel ratio reaches to 60: 1.     

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.