An empirical comparison of travel choice models that capture preferences for compromise alternatives

Compromise alternatives have an intermediate performance on each or most attributes rather than having a poor performance on some attributes and a strong performance on others. The relative popularity of compromise alternatives among decision-makers has been convincingly established in a wide range of decision contexts, while being largely ignored in travel behavior research. We discuss three (travel) choice models that capture a potential preference for compromise alternatives. One approach, which is introduced in this paper, involves the construction of a so-called compromise variable which indicates to what extent (i.e., on how many attributes) a given alternative is a compromise alternative in its choice set. Another approach consists of the recently introduced random regret-model form, where the popularity of compromise alternatives emerges endogenously from the regret minimization-based decision rule. A third approach consists of the contextual concavity model, which is known for favoring compromise alternatives by means of a locally concave utility function. Estimation results on a stated route choice dataset show that, in terms of model fit and predictive ability, the contextual concavity and random regret models appear to perform better than the model that contains an added compromise variable.     

An analysis of soft transport policy measures implemented in Sweden to reduce private car use

Evaluations carried out in many countries show that soft policy measures in the form of personalized travel planning reduce private car use and increase travel by public transport. Sweden is a sparsely populated country that poorly supports public transport, a country with long distances, a cold climate, and a high concentration of private cars, which is why soft policy measures implemented in Sweden may be less cost-effective than has been found in other countries. Thirty-two programs using personalized travel planning were analysed with regard to stewardship, geographic area of application, choice of techniques of exerting an influence, and effects on car use and choice of alternative travel modes. None of the evaluations of the documented programs met the method requirements for such evaluations as regards design and effect measurement. Additionally, reporting was substandard as well as non-standard in the way that is desirable in order to enable comparative analyses. With reservations for these shortcomings, it is inferred that positive effects on a par with the results in other countries have been obtained in some of the implemented programs. It is however necessary to conduct evaluations which are of higher quality. The requirements which will then have to be applied are defined.     

Decision makers and socializers, social networks and the role of individuals as participants

Models explaining and predicting human travel behavior have gone through many changes in the past few decades. As researchers attempt to explain more and predict with more accuracy, the inclusion of social interactions in modeling and simulation is being recognized as a necessity. Among these efforts, researchers have focused on issues such as the composition of social networks, and the constraints and influences that others have on spatial decisions. An important aspect that has been understudied however is the variability or heterogeneity of individuals both as social network members and as participants in these social networks. Understanding the role individuals play in decision-making in different social networks can further define our models to include more accurate representations of human behavior. This research explores the differences between social network composition, and the decision roles members play within different social networks specifically when deciding where to participate in activities. A survey was conducted in Santa Barbara, California on social network involvement, network attributes and decision-making roles within each network. Two separate latent class cluster analysis models were developed to classify social network involvement and roles. Results show that there are clearly different types of social involvement and roles within networks. Further data collection and analysis will be used to better understand how these decision-making roles manifest themselves in activity decision-making.     

Robust control for 4WS vehicles considering a varying tire-road friction coefficient

A µ-synthesis for four-wheel steering (4WS) problems is proposed. Applying this method, model uncertainties can be taken into consideration, and a µ-synthesis robust controller is designed with optimized weighting functions to attenuate the external disturbances. In addition, an optimal controller is designed using the well-known optimal control theory. Two different versions of control laws are considered here. In evaluations of vehicle performance with the robust controller, the proposed controller performs adequately with different maneuvers (i.e., J-turn and Fishhook) and on different road conditions (i.e., icy, wet, and dry). The numerical simulation shows that the designed µ-synthesis robust controller can improve the performance of a closed-loop 4WS vehicle, and this controller has good maneuverability, sufficiently robust stability, and good performance robustness against serious disturbances.     

Effects of mixture stratification on HCCI combustion of DME in a rapid compression and expansion machine

Compression ignition of homogeneous charges in internal combustion (IC) engines is expected to offer high efficiency of DI diesel engines without high levels of NOx and particulate emissions. This study is intended to find ways of extending the rich limit of HCCI operation, one of the problems yet to be overcome. Exhaust emissions characteristics are also explored through analyses of the combustion products. DME fuel, either mixed with air before induction or directly injected into the combustion chamber of a rapid compression and expansion machine, is compressed to ignite under various conditions of compression ratio, equivalence ratio, and injection timing. The characteristics of the resulting combustion and exhaust emissions are discussed in terms of the rate of heat release computed from the measured pressure, and the concentrations of THC, CO, and NOx are measured by FT-IR and CLD. The experimental data to date show that operation without knock is possible with mixtures of higher equivalence ratio when DME is directly injected rather than when it is inducted in the form of a perfectly homogeneous fuel-air mixture. Although fuel injected early in the compression stroke promotes homogeneity of the DME-air mixture in the cylinder, it causes the mixture to ignite too early to secure good thermal efficiency and knock-free operation at high loads. Low temperature reactions occur at about 660K regardless of the fueling methods, fuel injection timing and equivalence ratio. The main components of hydrocarbon emissions turned out to be unburned fuel (DME), formaldehyde and methane.     

Effects of valve timing and intake flow motion control on combustion and time-resolved HC & NOx formation characteristics

In SI engines, valve events have a major influence on volumetric efficiency, fuel economy and exhaust emissions. Moreover, swirl and tumble motions in the intake charge also improve combustion speed and quality by stratifying the mixture as well as intensifying the mixing rate of air and fuel. This paper investigates the behaviors of an engine and the combustion phenomenon for various intake valve timings and intake charge motions using CVVT system and port masking schemes. Test condition includes a part load and a cold idle condition inclusive of a cold start of the engine. Time-resolved HC and NOx emissions were also measured at an exhaust port to examine their formation mechanisms and behaviors with fast response HC/NOx analyzers. In conclusion, the fast burning of fuel and improved combustion quality by enhanced charge motions reduced unburned HC emissions, and advancing the intake valve opening reduced HC as well as NOx. Furthermore, HCs during the cold transient phase and idle conditions decreased with recalibrated start parameters such as lean air-fuel ratio and spark retardation via the enhancement of intake charge motions.     

The multi‐actor,multi‐criteria analysis methodology (MAMCA) for the evaluation of transport projects: Theory and practice

In this paper the multi‐actor multi‐criteria analysis (MAMCA) method to evaluate transport projects is presented. This evaluation method specifically focuses on the inclusion of qualitative as well as quantitative criteria with their relative importance, defined by the multiple stakeholders, into one comprehensive evaluation process in order to facilitate the decision making process by the different stakeholders. The MAMCA methodology is introduced by an overview of other evaluation methods for transport projects in the past and is illustrated by means of two practical cases. The introduction will lead us to the theoretical conception of the MAMCA method where we draw the attention to the proven usefulness of the MAMCA for the evaluation of transport projects and the inclusion of different kinds of stakeholders, individuals as well as groups, into the evaluation process.     

How do local actions affect VMT? A critical review of the empirical evidence

In this paper, we present a discussion of the challenges for research on the topic of vehicle miles traveled. We then summarize and critique evidence from the US on the association between 14 distinct factors and vehicle miles traveled. Our results quantify how much vehicle miles traveled can be expected to change in response to changes in policy or land use factors, including residential density and land use mix, as well as specific transport policies and programs such as transit improvements, road pricing, and programs aimed at changing people’s travel choices. Overall, though individual studies differ as to exact effect sizes, it is clear that local-level policymakers can take actions that are likely to affect vehicle miles traveled. However, we highlight gaps in the knowledge base at a time when decision makers at the local level are being increasingly called upon to take action to reduce vehicle miles traveled. Variation in effect size based on local context or interaction with related policies and programs has been left largely unexplored. In addition, experimental research designs that can identify causal direction are rare, and appropriate data that quantifies vehicle miles traveled are often lacking.     

Feasibility of using time–space prism to represent available opportunities and choice sets for destination choice models in the context of dynamic urban environments

H?gerstrand??s original framework of time geography and the subsequent time?Cspace prism computational methods form the foundation of a new computational method for potential path areas (PPA) in a realistic representation of dynamic urban environments. In this paper the time?Cspace prism framework is used to assess sensitivity of PPA size to different parameters and to build choice sets for regional destination choice models. We explain the implication of different parameters to choice set formation in a step-wise manner and illustrate not only the complexity of the idea and the high computational demand but also behavioral realism. In this context, this paper tests the feasibility of using constraint-based time?Cspace prism to find the choice sets for a large-scale destination choice model, and identifies a variety of implementation issues. Computational demand is estimated based on a household travel survey for the Southern California Association of Government, and the feasibility of using time?Cspace prisms for destination choice models is assessed with different levels of information on the network and destinations available. The implications of time of day effects and flexibility in scheduling on choice set development due to varying level of service on the network and availability of activity opportunities are discussed and numerically assessed.     

An analysis of the factors influencing differences in survey-reported and GPS-recorded trips

Recent advances in global positioning systems (GPS) technology have resulted in a transition in household travel survey methods to test the use of GPS units to record travel details, followed by the application of an algorithm to both identify trips and impute trip purpose, typically supplemented with some level of respondent confirmation via prompted-recall surveys. As the research community evaluates this new approach to potentially replace the traditional survey-reported collection method, it is important to consider how well the GPS-recorded and algorithm-imputed details capture trip details and whether the traditional survey-reported collection method may be preferred with regards to some types of travel. This paper considers two measures of travel intensity (survey-reported and GPS-recorded) for two trip purposes (work and non-work) as dependent variables in a joint ordered response model. The empirical analysis uses a sample from the full-study of the 2009 Indianapolis regional household travel survey. Individuals in this sample provided diary details about their travel survey day as well as carried wearable GPS units for the same 24-h period. The empirical results provide important insights regarding differences in measures of travel intensities related to the two different data collection modes (diary and GPS). The results suggest that more research is needed in the development of workplace identification algorithms, that GPS should continue to be used alongside rather than in lieu of the traditional diary approach, and that assignment of individuals to the GPS or diary survey approach should consider demographics and other characteristics.