Space, Money, Life-cycle, and the Allocation of Time

Allocation of time to various activities is known to be a function of various demographic, socio-economic, seasonal, and scheduling factors. This paper examines those variables through exploration of the 1990 Nationwide Personal Transportation Survey, which has been inverted to track activity durations. The data are examined in single and multi-variate contexts. Two key issues are considered. First, to what extent does activity duration influence travel duration after controlling for activity frequency. This is tested with a set of models explaining travel duration. The data show activity duration does have positive and significant effects on travel duration, supporting recent arguments in favor of activity based models. Second, which is a more important effect in explaining the large changes in travel and activity patterns over the past thirty years accompanied by the increase in female labor force participation, the loss of discretionary time due to work, the change in metropolitan location, or the rise in per capita income. To examine this second question more rigorously, a choice model is constructed which examines both the decision to undertake an activity and the share of time within a 24 hour budget allocated to several primary activities: home, work, shop, and other activities. The utility functions for the activities are comprised of demographic, socio-economic, temporal, and spatial factors. The data also suggest that income and location have modest effects on time allocation compared with the loss of discretionary time due to working. .

Simulating Congestion Dynamics of Train Rapid Transit using Smart Card Data

Investigating congestion in train rapid transit systems (RTS) in today's urban cities is a challenge compounded by limited data availability and difficulties in model validation. Here, we integrate information from travel smart card data, a mathematical model of route choice, and a full-scale agent-based model of the Singapore RTS to provide a more comprehensive understanding of the congestion dynamics than can be obtained through analytical modelling alone. Our model is empirically validated, and allows for close inspection of the dynamics including station crowdedness, average travel duration, and frequency of missed trains---all highly pertinent factors in service quality. Using current data, the crowdedness in all 121 stations appears to be distributed log-normally. In our preliminary scenarios, we investigate the effect of population growth on service quality. We find that the current population (2 million) lies below a critical point; and increasing it beyond a factor of $\sim10\%$ leads to an exponential deterioration in service quality. We also predict that incentivizing commuters to avoid the most congested hours can bring modest improvements to the service quality provided the population remains under the critical point. Finally, our model can be used to generate simulated data for analytical modelling when such data are not empirically available, as is often the case.Comment: 10 pages, 5 figures, submitted to International Conference on Computational Science 201

ATLAS: A new way to exploit world-wide mobility services

Abstract Despite the extent of the ecosystem of mobility services and the disparate functionalities they offer, organizing journeys by properly exploiting them and enhancing their interoperability is still a complex task. Moreover, the high degree of dynamicity characterizing modern service-based systems requires to make them able to self-adapt at runtime. In this paper, we present ATLAS , a world-wide travel assistant able to provide accurate and context-aware traveling solutions, supporting users for the whole travel duration. ATLAS has been realized by exploiting a tool to engineer adaptive by design service-based systems operating in open and dynamic environments

The welfare effects of freight travel time savings

In this article we investigate the welfare effect of freight travel time savings. The general setup of this article is to suppose that transport operators face a constraint on minimum travel time and to examine what is occurring when this minimum travel time is changed. We briefly examine the current assessment methods and propose a less restrictive approach, in which we analyse how different economic agents trade off between the duration and cost of the different operations that are used in production and transport activities. We analyse how the change in the minimum travel time affects the different economic agents and investigate how these changes should be valued in cost benefit analysis.freight value of time; cost benefit analysis

Self-reported versus GPS-derived indicators of daily mobility in a sample of healthy older adults

In light of novel opportunities to use sensor data to observe individuals' day-to-day mobility in the context of healthy aging research, it is important to understand how meaningful mobility indicators can be extracted from such data and to which degree these sensor-derived indicators are comparable to corresponding self-reports. We used sensor (GPS and accelerometer) and self-reported data from 27 healthy older adults (≥67 years) who participated in the MOASIS project over a 30-day period. Based on sensor data we computed three commonly used daily mobility indicators: life space (LS), travel duration using passive (i.e., motorized) modes of transportation (pMOT) and travel duration using active (i.e., non-motorized) modes of transportation (aMOT). We assessed the degree to which these sensor-derived indicators compare to corresponding self-reports at a within-person level, computing intraindividual correlations (iCorrs), subsequently assessing whether iCorrs can be associated with participants’ socio-demographic characteristics on a between-person level. Moderate to large positive mean iCorrs between the respective self-reported and sensor-derived indicators were found (r = 0.75 for LS, 0.51 for pMOT and 0.36 for aMOT). In comparison to sensor-derived indicators, self-reported LS slightly underestimates, while self-reported aMOT as well as pMOT considerably overestimate the amount of daily mobility. Participants with access to a car have higher probabilities of agreement in the pMOT indicator. Sensor-based assessments are promising as they are “objective”, involve less participant burden and observations can be extended over long periods. The findings of this paper help researchers on mobility and aging to estimate the magnitude and direction of potential differences in the assessed variable due to the assessment methods

Design and Implementation of 12-Bit Arithmetic Logic Unit with 8 Operation Codes to Field Programmable Gate Array

Digital system has been a part of human life since the invention of the computer with a microprocessor as the central brain. At the heart of a processor is an Arithmetic Logic Unit (ALU) that handles arithmetic and logic operations. The need for high-speed computation to handle complex computations demands microprocessors with higher performance. The existing 4-opcode 8-bit ALU cannot handle multiplication operations, so a solution is needed. In this research, while raising the appeal of beginners, a 12-bit ALU with eight operation codes (opcode) was designed and implemented in Xilinx’s Field Programmable Gate Array using a schematic diagram approach through logic gates. The designed and implemented ALU provides addition, subtraction, multiplication, square, AND, OR, NAND, and XOR operations. The multiplication operation was tested by performing the computation to provided datasets to obtain the distance travelled by ten military aircraft based on their maximum speed and air travel duration to ensure its performance. The computation performance comparison with an 8-bit ALU with four opcodes was also done. The computation was done for air travel between 10 to 60 minutes with a 10-minute difference. It was found that the 12-bit ALU with eight opcodes outperformed its contender with computation differences between 130.815 ns and 1,468.214 ns. This high performance is supported by the multiply operation that does repeated addition at one time. Based on this finding, the 8-opcode 12-bit ALU is more efficient in the context of computation time, with consistent accuracy. Moreover, the computation time required to calculate military aircraft data with different maximum speeds and air travel duration is only 119.501 ns