Micro-simulation of daily activity-travel patterns for travel demand forecasting

The development and initial validation results of a micro-simulator for the generation of daily activity-travel patterns are presented in this paper. The simulator assumes a sequential history and time-of-day dependent structure. Its components are developed based on a decomposition of a daily activity-travel pattern into components to which certain aspects of observed activity-travel behavior correspond, thus establishing a link between mathematical models and observational data. Each of the model components is relatively simple and is estimated using commonly adopted estimation methods and existing data sets. A computer code has been developed and daily travel patterns have been generated by Monte Carlo simulation. Study results show that individuals' daily travel patterns can be synthesized in a practical manner by micro-simulation. Results of validation analyses suggest that properly representing rigidities in daily schedules is important in simulating daily travel patterns. This revised version was published online in June 2006 with corrections to the Cover Date.     

Platoon-based traffic flow model for estimating breakdown probability at single-lane expressway bottlenecks

This study investigates the mechanism of traffic breakdown and establishes a traffic flow model that precisely simulates the stochastic and dynamic processes of traffic flow at a bottleneck. The proposed model contains two models of stochastic processes associated with traffic flow dynamics: a model of platoon formation behind a bottleneck and a model of speed transitions within a platoon. After these proposed models are validated, they are applied to a simple one-way, one-lane expressway section containing a bottleneck, and the stochastic nature of traffic breakdown is demonstrated through theoretical exercises.     

Application of a genetic algorithm to the optimal structural design of a ship's engine room taking dynamic constraints into consideration

The genetic algorithm, known as GA, is used to optimize engine room structure, not only under static constraints, but also under dynamic constraints. A penalty function method is used to handle the complicated constraint conditions based on the numerical results of dynamic and static analyses. There are several ways to take the dynamic effect into account in the optimum design of ship structure. First, the inequality constraint condition is applied to separate the natural frequency and the exciting frequency. Second, generalized design variables are introduced in order to transfer not only the dynamic but also the static equilibrium equations into the equality constraints, resulting in the optimal structural design without the need to solve these equilibrium equations. Third, the magnitudes of the acceleration and displacement are constrained instead of applying the natural frequency constraint condition. In order to achieve better convergency in the optimization with least resources, several operators and methods are considered and then introduced into the structural design of the engine room. The new operator, called either objective elitism or fitness elitism, is introduced to improve the efficiency of the method. The effect of boundary mutation and nonuniform mutation on the performance of the GA is examined. Not only binary representation but also floating-point representation are used to express the design gene in the GA. Fuzzy theory is applied in the GA to handle the uncertainty of the constraint conditions. Two ways of solving fuzzy optimization are investigated in order to obtain a fuzzy solution and a crisp solution. Received: October 2, 2000 / Accepted: November 30, 2000     

Traffic problems in Southeast Asia featuring the case of Cambodia's traffic accidents involving motorcycles

This article provides the background to the special issue by reviewing the status of traffic problems in South East Asian countries, and in particular, the case of Cambodia. The “Make Roads Safe” report by the Commission for Global Road Safety (2011) confirms traffic accidents as the primary cause of youth mortality worldwide. Thus, the United Nations declared the decade from 2011 to 2020 as the “UN Decade of Action for Road Safety 2011-2020”, promoting road safety and to reduce the number of deaths in road accidents by 2020. Furthermore, the “Sustainable Development Goals” adopted in 2015 highlight the important role of sustainable transport in tackling the exclusion of vulnerable groups. On the other hand, the World Health Organization in 2015 indicate an increase in the death rate due to traffic accidents in low-income countries since 2000. Traffic accidents were already recognized as a social problem before the 2000s in countries such as Thailand and the Philippines. At the same time, other ASEAN member states such as Vietnam and Cambodia which have experienced rapid economic growth since the 2000s are now experiencing the seriousness of traffic problems. It is said that 70% of road accidents in Thailand, Cambodia and Laos involve motorcycles and three-wheelers, but despite this situation, the regulatory framework for motorcycles remains undeveloped. In the case of Cambodia, speeding by young people remains the major cause of road deaths and this can be explained by the fact that people can now travel at a higher speed because of road developments but remaining challenges related to underdeveloped traffic legislation, and limited public awareness and knowledge of road safety are overlooked. In 2010, the Cambodian National Road Safety Action Plan 2010–2020 was drafted, aiming to halve the number of deaths in traffic accidents in 2020. However, in reality, the number of road deaths did not decrease to the level anticipated in the action plan until 2016. In this article, the authors emphasize the importance of implementing the “three Es” namely Engineering, Enforcement and Education in developing countries such as Cambodia. In particular, the authors claim that the role of education to increase people's road safety awareness is neglected compared to the other two dimensions and thus, it is highly important to raise people's road safety awareness through education among the young people.     

A review of household dynamic vehicle ownership models: holdings models versus transactions models

Among disaggregate vehicle ownership models, which model the number and/or type of vehicles owned at the household level, one can distinguish holdings models, which deal with the (optimal) household fleet at a single point in time, and transactions models. The latter type of model explains changes to the household fleet, such as replacement and disposal. The paper describes previous attempts at such dynamic models and sketches how a vehicle transactions model could look (as an example we discuss an application to The Netherlands). This includes discussions of transaction probabilities, two-stage budgeting, introducing vehicle quality in the utility functions, and the envisaged model structure and data it could use.     

Exploration of route choice behavior with advanced traveler information using neural network concepts

A model of driver's route choice behavior under advanced traveler information system (ATIS) is developed based on data collected from learning experiments using interactive computer simulation. The experiment subjected drivers to 32 simulated days in which they were to choose between the freeway or a side road. A neural network model is used as a convenient modeling technique in this initial phase of the analysis. The results indicated that most subjects made route choices based mainly on their recent experiences. It was also demonstrated that route choice behaviors are related to the personal characteristics as well as the characteristics of the respective routes. Travel experiences have less effect on the choice of the side road compared to the freeway and the results indicate that the prediction accuracy of the model, the acceptance rate of advice, and the quality of advice are closely correlated. The model developed here was for advice consistently provided at a level of 75 percent accuracy. The paper concludes with a discussion of experimental limitations and suggestions for future research.