Habitual travel behaviour: Evidence from a six-week travel diary

This paper introduces different methods to measure similarity of travel behaviour addressing the question of how repetitious travel behaviour actually is. It compares empirical results of the different methods based on the data from a six-week travel diary. In general, the results show that the day-to-day behaviour is more variable if measured with trip-based methods instead of methods based on time budgets. Furthermore, it is confirmed that the similarity declines if the method captures more of the complexity of the travel pattern. It is also shown that travel behaviour is neither totally repetitious nor totally variable. Even for the whole observation period, it is demonstrated that two days always have some common elements. Additionally, it is found that the different methods yield the same pattern of variability for different types of day. Travel behaviour is clearly more stable on work days. Similar results for all methods are also obtained concerning the question of how long the minimum period of observation should be. All measures show that the period should not be less than two weeks if one aims at measuring variability.     

Train scheduling simulation that minimises operational conflicts due to service constraints

This paper presents an attempt made to facilitate re‐scheduling of trains to minimize operational delays and accommodate uniform headways for off peak sub urban services subject to resource constraints such as locomotive availability, poor track conditions and stations without siding facilities. The paper describes the computer simulation model designed to optimize train schedules on single‐track rail lines. Using this simulation program it is possible to plan and optimize timetables for railway networks with train runs within short time periods for both single track and double track conditions. The paper describes the capabilities of presenting the results of the simulation runs. These include the time‐distance graph, the network with train movements, dialog boxes with information about selected trains. The programme is capable of changing the starting point, departure time, train destinations and adding or deleting a stop etc. from the user interface. Four objects of array variables are used in the simulation process to keep train and station data. Two object arrays are used for the train movements in up and down directions. The stations' data are stored in the other two object arrays. One of these arrays of stations contains all the stations of the line while the other one contains only the stations with siding facilities. A case study that covers a 61 km long single‐track line with 14 stations is presented to highlight the model capabilities.     

Process Save Reduction by Macro Joint Approach: The Key to Real Time and Efficient Vehicle Simulation

Applying a non-linear model reduction method to the tire suspension system of road vehicles enables an automatic transfer of complex offline simulation vehicle models to a mathematical model, which fits the real time simulation requirements. The basic assumption, that high frequent inner suspension dynamics are not relevant to handling manoeuvres, converts the differential algebraic equation system (DAE) of suspensions with kinematical closed loops into pure elasto-kinematical linkage equations. The equations of motions can be represented as an ordinary differential equation system (ODE) and considerable simulation time reductions are obtained for the off-line simulation and real time simulation is enabled. This so-called macro joint approach is an alternative modelling method to the well-known look-up table representation of suspension kinematics but it keeps the parameterisation of the original suspension model and is suitable to parameterised real time MBS models. With a second step the dynamics, caused by compliance in the suspension bushings, are reduced to their quasi-static behaviour. The consideration of these quasi-elasticity has nearly no influence on the necessary simulation time. This contribution shows the theoretical background and demonstrates the advantage of the macro joint model reduction approach on a typical vehicle example.     

Correlation between automotive CO, HC, NO, and PM emission factors from on-road remote sensing: implications for inspection and maintenance programs

Carbon monoxide (CO), hydrocarbon (HC), and nitrogen oxide (NO) emission factors (EFs) are measured with a commercial vehicle emissions remote sensing system (VERSS) during a large-scale vehicle exhaust emissions study in Las Vegas. Particulate matter (PM) EFs are simultaneously measured for individual vehicles with a newly developed PM-VERSS based on ultraviolet backscatter light detection and ranging (Lidar). The effectiveness of CO and HC EFs as proxy for NO and PM EFs for spark-ignition vehicles is evaluated. Poor correlations were found between EFs for pollutants on an individual vehicle basis indicating that high EFs for one or more pollutants cannot be used as a predictor of high EFs for other pollutants. Stronger functional relationships became evident after averaging the EF data in bins based on rank-order of a single pollutant EF. Low overlap between the highest 10% emitters for CO, HC, NO, and PM was found. These results imply that for an effective reduction of the four pollutants, inspection and maintenance (I/M) programs, including clean screening, should measure all four pollutants individually. Fleet average CO and HC concentrations determined by gaseous VERSS were compared with fleet average CO and HC concentrations measured at low-idle and at high-idle during local I/M tests for spark-ignition vehicles. The fleet average CO concentrations measured by I/M tests at either idle were about half of those measured by remote sensing. The fleet average high-idle HC concentration measured by I/M tests was about half of that measured by VERSS while low-idle I/M and VERSS HC average concentrations were in better agreement. For a typical vehicle trip, most of the fuel is burned during non-idle conditions. I/M measurements collected during idling conditions may not be a good indicator of a vehicle’s potential to be a high emitter. VERSS measurements, when the vehicle is under a load, should more effectively identify high emitting vehicles that have a large contribution to the mobile emissions inventory.     

Exploring the impact of walk–bike infrastructure,safety perception,and built-environment on active transportation mode choice: a random parameter model using New York City commuter data

This study estimates a random parameter (mixed) logit model for active transportation (walk and bicycle) choices for work trips in the New York City (using 2010–2011 Regional Household Travel Survey Data). We explored the effects of traffic safety, walk–bike network facilities, and land use attributes on walk and bicycle mode choice decision in the New York City for home-to-work commute. Applying the flexible econometric structure of random parameter models, we capture the heterogeneity in the decision making process and simulate scenarios considering improvement in walk–bike infrastructure such as sidewalk width and length of bike lane. Our results indicate that increasing sidewalk width, total length of bike lane, and proportion of protected bike lane will increase the likelihood of more people taking active transportation mode This suggests that the local authorities and planning agencies to invest more on building and maintaining the infrastructure for pedestrians. Further, improvement in traffic safety by reducing traffic crashes involving pedestrians and bicyclists, will increase the likelihood of taking active transportation modes. Our results also show positive correlation between number of non-motorized trips by the other family members and the likelihood to choose active transportation mode. The model would be an essential tool to estimate the impact of improving traffic safety and walk–bike infrastructure which will assist in investment decision making.     

Time Gap Modeling under Mixed Traffic Condition: A Statistical Analysis

This paper attempts to model vehicular time gap, which is defined as the time interval between any two successive arrivals of vehicles at a reference point of measurement on a road segment. Such an approach is justified under the non-lane-based heterogeneous traffic conditions prevailing in developing countries such as India, characterized by many “zero” time gaps due to simultaneous arrivals within a given road width. In addition, time gap data are characterized by a significant amount of data in the tail region due to long headways. Nevertheless, many researchers of time gap modeling have used light-tailed distributions that modeled time gaps satisfactorily due to two reasons: (a) The tail data was merged into a single bin; and (b) goodness-of-fit tests such as the Chi-square test, which has many limitations, were used. Further, some researchers have suggested different distributions for the same range of traffic flows, leading to ambiguity in distribution selection. In addition, bin size, which dictates the degree of fit of any distribution, has been ascribed very less importance in time gap modeling. Hence, this paper tries to consolidate and standardize the existing research in time gap modeling research by addressing all these issues. Two new distributions, namely Generalized Pareto (GP) and Generalized Extreme Value (GEV) with better tail modeling properties, have been proposed along with other conventional distribution to model vehicular time gaps over a wide range of flow from 550 vph to 4,100 vph. Two types of goodness-of-fit tests, namely Area-based and Distance-based tests, have been used. It has been found from the study that GP distribution fits the time gap data well (overall and tails) up to a flow range of 1,500 vph based on both kinds of tests, and GEV fits the data well for the flow levels above 1,500 vph based on the area test only.     

A Simplified Model for the Effect of Weld-Induced Residual Stresses on the Axial Ultimate Strength of Stiffened Plates

The present work investigates the compressive axial ultimate strength of fillet-welded steel-plated ship structures subjected to uniaxial compression, in which the residual stresses in the welded plates are calculated by a thermo-elasto-plastic finite element analysis that is used to fit an idealized model of residual stress distribution. The numerical results of ultimate strength based on the simplified model of residual stress show good agreement with those of various methods including the International Association of Classification Societies (IACS) Common Structural Rules (CSR), leading to the conclusion that the simplified model can be effectively used to represent the distribution of residual stresses in steel-plated structures in a wide range of engineering applications. It is concluded that the widths of the tension zones in the welded plates have a quasi-linear behavior with respect to the plate slenderness. The effect of residual stress on the axial strength of the stiffened plate is analyzed and discussed.     

Analysis of the effectiveness of control measures to mitigate road dust emissions in a regional network

The effectiveness of control measures to reduce road dust emissions is analyzed using a year’s data of road dust emissions collected with a mobile sampling platform and a survey of road maintenance practices in the Lake Tahoe Basin of Nevada and California US. Attributes such as sweeping practices, anti-icing, shoulder improvement, pavement condition, trackout, and abrasive material from road segments were analyzed with a feature subset selection algorithm. Street sweeping was found to be an effective means of controlling dust emissions from roads. Road dust from dirty tertiary roads served as a continuous source of suspendable material for adjacent high-speed roads in the winter time. To be most effective, emission control strategies require that not only primary roads, but all roads be swept after snow storms to recover applied abrasive material.     

Do parking requirements significantly increase the area dedicated to parking? A test of the effect of parking requirements values in Los Angeles County

Minimum parking requirements (MPRs) are the norm for urban and suburban development in the United States (Davidson et al., 2002). The justification for MPRs is that overflow parking will occupy nearby street or off-street parking. Shoup (1999a) and Willson (1995) provide cases where there is reason to believe that parking space requirements have forced parcel developers to place more parking than they would in the absence of parking requirements. However, to our knowledge the existing literature does not test the effect of parking minimums on the amount of lot space devoted to parking beyond a few case studies. This paper tests the hypothesis that MPRs bind for most land uses using data on suburban office, commercial, industrial and retail property sales from Los Angeles County using both direct and indirect approaches. Our indirect test of the effects of parking requirements is similar to the one used by Glaeser and Gyourko (2003). A simple theoretical model shows that the marginal value of additional parking to the sale price of a building should be equal to the cost of land plus the cost of parking construction. We estimate the marginal values of parking and lot area with spatial methods using a large data set from the Los Angeles area non-residential property sales and find that for most of the property types the marginal value of parking is significantly below that of the parcel area. In addition, we directly examine required and supplied parking and find that on average parking supplied is quite close to the required amount.