Development of an idle speed engine model using in-cylinder pressure data and an idle speed controller for a small capacity port fuel injected SI engine

An idle speed engine model has been proposed and applied for the development of an idle speed controller for a 125 cc two wheeler spark ignition engine. The procedure uses the measured Indicated Mean Effective Pressure (IMEP) at different speeds at a constant fuel rate and throttle position obtained by varying the spark timing. At idling conditions, IMEP corresponds to the friction mean effective pressure. A retardation test was conducted to determine the moment of inertia of the engine. Using these data, a model for simulating the idle speed fluctuations, when there are unknown torque disturbances, was developed. This model was successfully applied to the development of a closed loop idle speed controller based on spark timing. The controller was then implemented on a dSPACE Micro Autobox on the actual engine. The Proportional Derivative Integral (PID) controller parameters obtained from the model were found to match fairly well with the experimental values, indicating the usefulness of the developed idle speed model. Finally, the optimized idle speed control algorithm was embedded in and successfully demonstrated with an in-house built, low cost engine management system (EMS) specifically designed for two-wheeler applications.     

Measurement of hydrocarbon and carbon monoxide emissions during the starting of automotive DI Diesel engines

Most of hydrocarbon (HC) and carbon monoxide (CO) emissions from automotive DI Diesel engines are produced during the engine warm-up period and are primarily caused by difficulties in obtaining stable and efficient combustion under these conditions. Furthermore, the contribution of engine starting to these emissions is not negligible; since this operating condition is highly unfavorable for the combustion progress. Additionally, the catalytic converter is ineffective due to the low engine temperature. In conjunction with adequate engine settings (fuel injection and fresh air control), either the glow plugs or the intake air heater are activated during a portion of the engine warm-up period, so that a nominal engine temperatures is reached faster, and the impact of these difficulties is minimized. Measurement of gaseous pollutants during engine warm-up is currently possible with detectors used in standard exhaust gas analyzers (EGA), which have response times well-suited for sampling at such transient conditions. However, these devices are not suitable for the measurement of exhaust emissions produced during extremely short time intervals, such as engine starting. Herein, we present a methodology for the measurement of the cumulative pollutant emissions during the starting phase of passenger car DI Diesel engines, with the goal of overcoming this limitation by taking advantage of standard detectors. In the proposed method, a warm canister is filled with an exhaust gas sample at constant volumetric flow, during a time period that depends on the engine starting time; the gas concentration in the canister is later evaluated with a standard EGA. When compared with direct pollutant measurements performed with a state-of-art EGA, the proposed procedure was found to be more sensitive to combustion changes and provided more reliable data.     

Assessing the employment agglomeration and social accessibility impacts of high speed rail in Eastern Australia

There is growing interest in establishing additional evidence, under the umbrella of the wider economy impacts of transport infrastructure projects, to support transport projects in general and public transport projects in particular that struggle to obtain benefit–cost ratios sufficient to gain the support of financial agencies. This paper focuses on one element of wider economy impacts, often referred to as effective economic (employment) density or employment agglomeration impacts, and another, less usually identified, social accessibility impact (SAI) which we refer to as effective social density, which in broad terms provide, correspondingly, evidence of the potential gains in work-related output (often referred to as productivity gains) and potential gains in non-work-related outputs. Both are associated with gains in individual and household benefit attributable to improved accessibility to services linked with populations and particular locations. The SAIs may capture some of the induced benefits in those jurisdictions where these are included routinely in benefit–cost analysis, and the methodology here is most appropriate to those settings where an existing calibrated demand curve may not be available. Using the proposed high speed rail (HSR) project between Sydney and Melbourne as the empirical setting, we identify economic agglomeration and social accessibility benefits for work and non-work related activity respectively. We find the former to be relatively small compared to the significant gains associated with non-work related travel activity, suggesting the greatest benefits associated with HSR, especially for those residents outside of the major metropolitan areas, will be non-work related travel activity.     

Complementing distance based charges with discounted registration fees in the reform of road user charges: the impact for motorists and government revenue

The call for a congestion charge is getting louder and more frequent in many countries as major metropolitan areas experience increasing levels of road congestion. This is often accompanied by a recognition that governments need to find new sources of revenue to maintain existing road networks and to invest in new transport infrastructure. Although reform of road pricing is almost certain to occur at some time in the future in a number of countries, a key challenge is in selling the idea to the community of road users as well as a whole raft of interest groups that influence the views of society and politicians. Simply announcing a need for a congestion charge (often misleadingly called a tax) does little to progress the reform agenda. What is required is a carefully structured demonstration of what might be done to progressively introduce adjustments in road user charges that are seen as reducing the costs to motorists while ensuring no loss of revenue to government. In this paper we show, in the context of Sydney (Australia), that this can be achieved by the reform of registration fees in the presence of a distance-based charging regime that can deliver financial gains to motorists, with prospects of revenue growth to the State Treasury.     

Accounting for travel time variability in the optimal pricing of cars and buses

A number of studies have shown that in addition to travel time and cost as the common influences on mode, route and departure time choices, travel time variability plays an increasingly important role, especially in the presence of traffic congestion on roads and crowding on public transport. The dominant focus of modelling and implementation of optimal pricing that incorporates trip time variability has been in the context of road pricing for cars. The main objective of this paper is to introduce a non-trivial extension to the existing literature on optimal pricing in a multimodal setting, building in the role of travel time variability as a source of disutility for car and bus users. We estimate the effect of variability in travel time and bus headway on optimal prices (i.e., tolls for cars and fares for buses) and optimal bus capacity (i.e., frequencies and size) accounting for crowding on buses, under a social welfare maximisation framework. Travel time variability is included by adopting the well-known mean–variance model, using an empirical relationship between the mean and standard deviation of travel times. We illustrate our model with an application to a highly congested corridor with cars, buses and walking as travel alternatives in Sydney, Australia. There are three main findings that have immediate policy implications: (i) including travel time variability results in higher optimal car tolls and substantial increases in toll revenue, while optimal bus fares remain almost unchanged; (ii) when bus headways are variable, the inclusion of travel time variability as a source of disutility for users yields higher optimal bus frequencies; and (iii) including both travel time variability and crowding discomfort leads to higher optimal bus sizes.     

Multi‐criteria analysis for evaluating the impacts of intelligent speed adaptation

Road safety is a policy priority due to the high casualties and costs associated with road accidents. Since speed is a major cause of road accidents, in‐vehicle speed limiters or Intelligent Speed Adaptation (ISA), seems a promising solution. ISA implementation, however, is hindered by large uncertainties, for example about the impacts of ISA, the way users might respond to ISA, and the relationship between speed and accidents. Traditional Multi‐Criteria Analysis (MCA) has limitations in handling these uncertainties. We present an MCA approach based on exploratory modeling, which uses computational experiments to explore the multiple outcomes of ISA policies (safety, emissions, throughput, and cost) across a range of future demand scenarios, functional relationships for performance criteria, and user responses to ISA. As an illustration, by testing the impacts of different ISA penetration levels on two driver groups, we show that when compliance with ISA is expected to be low, a policy aimed only at novice drivers outperforms other ISA policies on safety improvement.     

When strike comes to town… anticipated and actual behavioural reactions to a one-day,pre-announced,complete rail strike in the Netherlands

We conducted secondary analysis on data collected among rail users, days before and after a national rail strike in the Netherlands. Our aim was to compare anticipated and actual behavioural reactions to the rail strike, investigate associations with traveller and trip characteristics, and perceived behavioural control and satisfaction with the chosen alternative. Forty-four percent of the people who had anticipated to travel by train on the day of the strike abandoned their trip, 24% switched to car as driver, 14% switched to another mode (as passenger), 18% stayed with the train and rescheduled the planned activity to another day. Almost half of people who had anticipated travelling by car expected to change behaviour as well. Multinomial logistic regression showed low preference for car among rail users. Considerable marginal effects were found for several variables, e.g.: young people and females were less likely to switch to car; short and middle distance trips were less likely abandoned or switched to another day; commute and business trips were more likely done by car, and business trips less likely cancelled. Despite high levels of perceived behavioural control and satisfaction with the chosen alternative, permanent modal shift as result of this strike is not expected.     

Analyzing loss aversion and diminishing sensitivity in a freight transport stated choice experiment

Choice behaviour might be determined by asymmetric preferences whether the consumers are faced with gains or losses. This paper investigates loss aversion and diminishing sensitivity, and analyzes their implications on willingness to pay and willingness to accept measures in a reference pivoted choice experiment in a freight transport framework. The results suggest a significant model fit improvement when preferences are treated as asymmetric, proving both loss aversion and diminishing sensitivity. The implications on willingness to pay and willingness to accept indicators are particular relevant showing a remarkable difference between symmetric and asymmetric model specifications. Not accounting for loss aversion and diminishing sensitivity, when present, produces misleading results and might affect significantly the policy decisions.     

Relationship between proximity to transit and ridership for journey-to-work trips in Chicago

The use of privately owned vehicles (POVs) contributes significantly to US energy consumption (EC) and greenhouse gas emissions (GHGe). Strategies for reducing POV use include shifting trips to other modes, particularly public transit. Choices to use transit are based on characteristics of travelers, their trips, and the quality of competing transportation services. Here we focus on the proximity of rail stations to trip origins/destinations as a factor affecting mode choice for work trips. Using household travel survey data from Chicago, we evaluate the profile of journey-to-work (JTW) trips, assessing mode share and potential for more travelers to use rail. For work trips having the origin/destination as close as 1 mile from rail transit stations, POVs were still the dominant travel mode, capturing as much as 61%, followed by rail use at 14%. This high degree of POV use coupled with the proportion of JTW trips within close proximity to rail stations indicated that at least some of these trips may be candidates for shifting from POV to rail. For example, shifting all work trips with both the origin/destination within 1 mile of commuter rail stations would potentially reduce the energy associated with all work-related POV driving trips by a maximum of 24%. Based on the analysis of trips having the origin and destination closest to train stations, a complete shift in mode from POV to train could exceed CO₂ reduction goals targeted in the Chicago Climate Action Plan. This could occur with current settlement patterns and the use of existing infrastructure. However, changes in traveler behavior and possibly rail operation would be necessary, making policy to motivate this change essential.     

A traffic analysis zone definition: a new methodology and algorithm

This paper develops a comprehensive approach to the definition of transportation analysis zones (TAZ), and therein, presents a new methodology and algorithm for the definition of TAZ embedded in geographic information systems software, improves the base algorithm with several local algorithms, and comprehensively analyses the obtained results. The results obtained are then compared to these presently used in the transportation analysis process of the Lisbon Metropolitan Area. The proposed algorithm presents a new methodology for TAZ design based on a smoothed density surface of geocoded travel demand data. The algorithm aims to minimise the loss of information when moving from a continuous representation of the origin and destination of each trip to their discrete representations through zones, and focuses on the trade-off between the statistical precision, geographical error, and the percentage of intra-zonal trips of the resulting OD matrix. The results for the Lisbon Metropolitan Area case study suggest a significant improvement in OD matrix estimates compared to current transportation analysis practises based on administrative units.