Analysis of road potential and bottlenecks based on operating speed

Vehicle detectors have been installed at approximately every 300 meters on each lane on Tokyo metropolitan expressway. Various traffic data such as traffic volume, average speed and time occupancy are collected by vehicle detectors. We can understand traffic characteristics of every point by comparing traffic data collected at consecutive points. In this study, we focused on average speed, analyzed road potential by operating speed during free-flow conditions, and identified latent bottlenecks. Furthermore, we analyzed effects for road potential by the rainfall level and day of the week. It’s expected that this method of analysis will be utilized for installation of ITS such as drive assist, estimation of parameters for traffic simulation and feedback to road design as congestion measures

Effect of rain on travel demand and traffic accidents

This paper studies the effect of rain on travel demand measured on the Tokyo Metropolitan Expressway (MEX). Rainfall data monitored by the Japan Meteorological Agency's meso-scale network of weather stations are used. This study found that travel demand decreases during rainy days and, in particular, larger reductions occur over the weekend. The effect of rainfall on the number of accidents recorded on 10 routes on the MEX is also analysed. Statistical testing shows that the average frequency of accidents, during periods of rainfall, is significantly different from the average frequency at other times

The international traffic database project

For transportation studies and applications, practitioners as like as researchers spend an enormous amount of time to gather suitable data and to convert this data into a format that can be processed by their working tools or developed models. This work slows down their job and leads to tons of unused data in archives that is inaccessible for other people working in the same field. This paper presents a web based approach for an International Traffic Database to overcome this drawback and to open the possibilities for world-wide collaboration of transportation research and study.</p

Travel time prediction: issues and benefits

ABSTRACT This paper addresses the issues and benefits pertaining to travel time prediction and incorporates an on-line survey of the Tokyo Metropolitan Expressways (MEX) users. While travel time has the potential to mitigate congestion spatially and temporally, little is known about how the travel time information is used. The MEX survey found that 78% of drivers would change route or departure time if there is time savings. However, the amount of time savings to prompt drivers taking such action depends on the characteristic of the drivers. Not surprisingly drivers rate pre-trip information higher than on-route information as a more desired information because pre-trip information allows drivers to make a more informed travel decision. The MEX survey clearly shows that users&apos; acceptance of prediction accuracy is dependent on the amount of time gain or lost and is insensitive to the trip length. Approximately 70% of the survey participants acknowledge that ±5 minutes as an acceptable level of accuracy. Therefore a more appropriate measure when evaluating travel time prediction models, taking users&apos; expectation into account, would be to use percentage error within ±5 minutes or ±10 minutes

Benefit of accident reduction considering the improvement of travel time reliability

Traffic accidents often cause lane closure, and diminish stability of travel time as well as the level of road services. On the other hand, research on the implementation of ITS services aiming at the reduction of traffic accidents has made considerable progress lately. However there has been little discussion on the benefits obtained by traffic accident reduction from the view point of travel time reliability. Therefore, in this research, relationships between traffic accidents and travel time reliability are examined, and the benefit of traffic accident reduction is calculated based on the scheduling model under travel time uncertainties. The results show the significance of traffic accident reduction for the improvement of travel time reliability

Travel time prediction: issues and benefits

ABSTRACT This paper addresses the issues and benefits pertaining to travel time prediction and incorporates an on-line survey of the Tokyo Metropolitan Expressways (MEX) users. While travel time has the potential to mitigate congestion spatially and temporally, little is known about how the travel time information is used. The MEX survey found that 78% of drivers would change route or departure time if there is time savings. However, the amount of time savings to prompt drivers taking such action depends on the characteristic of the drivers. Not surprisingly drivers rate pre-trip information higher than on-route information as a more desired information because pre-trip information allows drivers to make a more informed travel decision. The MEX survey clearly shows that users&apos; acceptance of prediction accuracy is dependent on the amount of time gain or lost and is insensitive to the trip length. Approximately 70% of the survey participants acknowledge that ±5 minutes as an acceptable level of accuracy. Therefore a more appropriate measure when evaluating travel time prediction models, taking users&apos; expectation into account, would be to use percentage error within ±5 minutes or ±10 minutes