An experimental analysis of intelligibility and efficiency of in-vehicle route guidance system displays

This study focuses on the user-interface of the route guidance system with an electronic map display. The ultimate goal of the study is to aid in designing electronic map displays that can deliver information to the user most efficiently and expeditiously with minimum confusion. To evaluate the efficiency and understandability of a map display, laboratory experiments were designed and conducted in this study. In the experiments the subjects were presented with electronic map displays of different attributes and performed a set of tasks. Their understanding of the information contents was measured based on the outcomes of the tasks, and subjective ratings of the ease of using the maps were obtained. Using the experimental data obtained, a structural equations model system is developed to explain the understandability of a map display in terms of the subject’s attributes and the characteristics of the map display. The experimental procedure and the modeling results are presented in this paper.     

The effects of added transportation capacity on travel: a review of theoretical and empirical results

(Added to the original text) A fundamental solution to the issue of congestion cannot be reached without addressing the question of life-style. This paper reviews the definitions of life-style found in the literature, and identifies variables that have been commonly associated with life-style. Using US consumer expenditure data, life-styles are analyzed longitudinally (examining trends during the 1953–1983 time frame) and cross-sectionally (comparing segments of the population stratified by income, life-cycle stage, and age), and likely relationships to travel behavior are noted. The usefulness of existing empirical findings to long-range forecasting is explored by speculating on shifts of behavioral units across life-style segments, and on shifts in the behavioral patterns within each life-style segment.     

Impact of telecommuting on spatial and temporal patterns of household travel

A spatial and temporal analysis of travel diary data collected during the State of California Telecommuting Pilot Project is performed to determine the impacts of telecommuting on household travel behavior. The analysis is based on geocoded trip data where missing trips and trip attributes have been augmented to the extent possible. The results confirm the earlier finding that the Pilot Project telecommuters substantially reduced travel; on telecommuting days, the telecommuters made virtually no commute trips, reduced peak-period trips by 60%, total distance traveled by 75%, and freeway miles by 90%. The spatial analysis of the trip records has shown that the telecommuters chose non-work destinations that are closer to home; they exhibited contracted action spaces after the introduction of telecommuting. Importantly, this contraction took place on both telecommuting days and commuting days. The telecommuters distributed their trips, over the day and avoided peak-period travel on telecommuting days. Non-work trips, however, show similar patterns of temporal distribution on telecommuting days and commuting days. Non-work trips continued to be made during the lunch period and late afternoon and evening hours.     

The sequenced activity mobility simulator (SAMS): an integrated approach to modeling transportation, land use and air quality

The persistence of environmental problems in urban areas and the prospect of increasing congestion have precipitated a variety of new policies in the USA, with concomitant analytical and modeling requirements for transportation planning. This paper introduces the Sequenced Activity-Mobility Simulator (SAMS), a dynamic and integrated microsimulation forecasting system for transportation, land use and air quality, designed to overcome the deficiencies of conventional four-step travel demand forecasting systems. The proposed SAMS framework represents a departure from many of the conventional paradigms in travel demand forecasting. In particular, it aims at replicating the adaptative dynamics underlying transportation phenomena; explicitly incorporates the time-of-day dimension; represents human behavior based on the satisficing, as opposed to optimizing, principle; and endogenously forecasts socio-demographic, land use, vehicle fleet mix, and other variables that have traditionally been projected externally to be input into the forecasting process.     

集装箱货运仿真模型在珠三角港港口投资方案评估(英文)

In the Pearl River Delta (PRD), there is severe competition between container ports, particularly those in Hong Kong, Shenzhen, and Guangzhou, for collecting international maritime container cargo. In addition, the second phase of the Nansha terminal in Guangzhou’s port and the first phase of the Da Chang Bay container terminal in Shenzhen opened last year. Under these circumstances, there is an increasing need to quantitatively measure the impact these infrastructure investments have on regional cargo flows. The analysis should include the effects of container terminal construction, berth deepening, and access road construction. The authors have been developing a model for international cargo simulation (MICS) which can simulate the movement of cargo. The volume of origin-destination (OD) container cargo in the East Asian region was used as an input, in order to evaluate the effects of international freight transportation policies. This paper focuses on the PRD area and, by incorporating a more detailed network, evaluates the impact of several infrastructure investment projects on freight movement.     

Incorporating trip chaining into analysis of destination choice

A model of destination choice is developed in this study employing “prospective utility” of a destination zone as its attraction measure. The prospective utility accounts for future dependency of destination choice and makes possible relevant treatment of interdependent choices in a trip chain. A parameter is included in the model to represent the magnitude of the future dependency. Empirical estimation results show that destination choice is in fact future dependent and coefficients of travel time and zonal attribute variables may be biased if this depedency is not accounted for.     

An analysis of time allocation to in-home and out-of-home discretionary activities across working days and non- working days

The behavior of time allocation to two types of discretionary activities is formulated as a doubly-censored Tobit model. The model is capable of incorporating cases where the entire amount of time available for discretionary activity is allocated to one type of activity and the other type of activity is not engaged at all. The model is applied to examine individuals' allocation of time to in-home and out-of-home discretionary activities on working days and non-working days, using a weekly time-use data set from the Netherlands. Workers' daily activity patterns vary significantly between working days and non-working days, while it can be expected that patterns of time allocation are correlated between working days and non-working days. A set of error components is introduced into the model to represent this correlation, adopting a mass point approach which requires no assumption about the distribution of the error components. The validity of the model is examined statistically.     

Life-style and travel demand

(Added to the original text) A fundamental solution to the issue of congestion cannot be reached without addressing the question of life-style. This paper reviews the definitions of life-style found in the literature, and identifies variables that have been commonly associated with life-style. Using US consumer expenditure data, life-styles are analyzed longitudinally (examining trends during the 1953–1983 time frame) and cross-sectionally (comparing segments of the population stratified by income, life-cycle stage, and age), and likely relationships to travel behavior are noted. The usefulness of existing empirical findings to long-range forecasting is explored by speculating on shifts of behavioral units across life-style segments, and on shifts in the behavioral patterns within each life-style segment.     

A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area

This study examined the effects of land use and attitudinal characteristics on travel behavior for five diverse San Francisco Bay Area neighborhoods. First, socio-economic and neighborhood characteristics were regressed against number and proportion of trips by various modes. The best models for each measure of travel behavior confirmed that neighborhood characteristics add significant explanatory power when socio-economic differences are controlled for. Specifically, measures of residential density, public transit accessibility, mixed land use, and the presence of sidewalks are significantly associated with trip generation by mode and modal split. Second, 39 attitude statements relating to urban life were factor analyzed into eight factors: pro-environment, pro-transit, suburbanite, automotive mobility, time pressure, urban villager, TCM, and workaholic. Scores on these factors were introduced into the six best models discussed above. The relative contributions of the socio-economic, neighborhood, and attitudinal blocks of variables were assessed. While each block of variables offers some significant explanatory power to the models, the attitudinal variables explained the highest proportion of the variation in the data. The finding that attitudes are more strongly associated with travel than are land use characteristics suggests that land use policies promoting higher densities and mixtures may not alter travel demand materially unless residents' attitudes are also changed.