Nobuhiro Uno

Using Bus Probe Data for Analysis of Travel Time Variability

The rapid progress of information technology (IT) may provide us with new insights into understanding traffic phenomena, and could help mitigate traffic problems. One of the key applications of IT to traffic and transport analysis is the identification of the location of moving objects using the Global Positioning System (GPS). It is expected that detailed traffic analysis could be carried out using these data. In this article, we first summarize the various applications of probe data in transport analysis. GPS data are merely a sequence of locations, and further data transformation such as map-matching, data-reduction, processing, and reporting is needed to use them effectively. We then discuss the application of bus probe data to evaluating travel time variability and the level of service (LOS) of roads. A methodology for evaluating the road network from the viewpoint of travel time stability and reliability using bus probe data is proposed. Travel time distributions of arbitrary routes are estimated by statistically summing up directly observed multiple travel time distributions. Based on the development of methodologies to estimate travel time distributions of arbitrary routes covered by the bus probe survey, this study proposes an approach to evaluate the LOS of road networks based on the concept of travel time reliability.

Network Evaluation Based on Connectivity Vulnerability

Network reliability indices are generally expressed as a multiplier of the probability that the specific event may occur and the consequence of the event. It means that an inaccurate estimation of the probability of event occurrence may lead to different evaluation of the reliability. In contrast, the concept of “network vulnerability” has been proposed for evaluating the network component only by the consequence of the degradation. Though the concept of vulnerability may have avoided the uncertainty of the capacity degradation, it still requires an exact measurement of the traffic demand in the network which may not be accurate especially in the case of the disaster. We thus propose the method of critical link identification from the topological point of view, i.e., connectivity vulnerability. The concept of the k-edge-connectivity is applied in this study. The number of distinct paths with acceptable travel time between each origin-destination (OD) pair is used to measure the connectivity of that OD pair (similar to the concept of k-edge connectivity). A mathematical program for identifying acceptable distinct paths between each OD pair is formulated. The proposed method and indicator of connectivity vulnerability is then tested with the Kansai road network.

Analysis of Car-following Behavior on Sag and Curve Sections at Intercity Expressways with Driving Simulator

We analyzed the influence of road alignments such as sags and curves and the leading vehicle’s behavior on car-following behavior in a driving simulator experiment. Parameters of a car-following model were estimated from following-vehicle trajectory data collected for 37 participants. Then, relationships between the parameters and environmental factors were analyzed. The results showed that the parameters of the following-behavior model were significantly influenced by expressway alignments such as sags and curves, whereas differences in the leading vehicle’s behavior did not significantly affect the estimated parameters. These findings indicate that measures to assist the following vehicle’s acceleration and deceleration such as adaptive cruise control could be effective in preventing the breakdown of traffic flow.

Experimental Study of Effects of Travel Time Distribution Information on Dynamic Route Choice Behavior

This study focuses on the possibility that providing travelers with information on travel time distribution, along with the existing travel time information, might affect their decision making and enhance traffic control. As an initial step to confirm the effectiveness of travel time distribution information, we use a laboratory experiment to obtain panel data of route choices when information is provided. The rationality of the behavior of the respondents and the characteristics of the route choice are first analyzed by aggregation analysis and then statistically examined by specifying a mixed logit route choice model. As a result, it is revealed that both travel time information and maximum travel time information significantly affect route choice behavior when a penalty is imposed for late arrival.

ALTERNATIVE QUASI-NEWTON METHODS FOR CAPACITATED USER EQUILIBRIUM ASSIGNMENT

Two quasi-Newton methods are proposed to deal with traffic assignment in a capacitated network. The methods combine Newton formula, column generation, and penalty techniques. The first method uses the gradient of the objective function to obtain an improving feasible direction scaled by the second-order derivatives. The second one uses a Rosen gradient to obtain an improving direction scaled by the corresponding origin–destination demand. Both methods make a line search to obtain an optimal step size to guarantee the feasibility of either path or link flow. The proposed methods are of fast convergence and high accuracy at the expense of saving path information. Numerical examples verify their efficiency and stability. The quasi-Newton method with a straight gradient demonstrates more stability than the Rosen gradient for capacitated traffic assignment.

Using Electronic Toll Collection Data to Understand Traffic Demand

In this study, we explored the potential of using electronic toll collection (ETC)-derived data that are a part of intelligent transport systems (ITS). Dynamic origin–destination (OD) traffic volumes were estimated using ETC data on the Hanshin Expressway. A dynamic OD estimation model that was suggested in a previous study was used, and abundant ETC data were input to improve the estimation accuracy. The results of OD estimation were analyzed to understand traffic demand and its variation. External factors were clarified that have an influence on variances in the OD flows, and statistical analysis methods for the variations were proposed depending on the factors. Moreover, the improvements in traffic simulation accuracy and performance as a result of using ETC data as input variables in the simulation models were discussed. According to the results of this study, ETC data have potential to assist in understaningd traffic demand and its variation, and the results can be applied to network management.

Experimental analysis approach to analyze dynamic route choice behavior of driver with travel time information

In order to investigate the effect of providing traffic information, which is one of the possible strategies for traffic management, this study attempts to analyze the relation between information and route choice behavior. The aims of this study are to investigate the effects both of introducing an advanced traffic information system and of quality of information provided on the route choice mechanism. The authors propose an experimental analysis approach in which participants with travel time information are repeatedly asked for their hypothetical route choices. It is found that participants tend to choose routes based mainly on provided information and that duality of information might affect their route choice mechanisms.<<ETX>>

Network Evaluation Based on Connectivity Reliability and Accessibility

Our daily lives and activities rely heavily on transportation systems, particularly road networks. At the same time, we face the risk of various types of natural disasters. It is, therefore, extremely important to establish road networks that are robust and reliable under conditions of network degradation caused by natural disasters. Even immediately after a disaster, an area should retain connectivity with its neighboring areas, while at the same time residents in the area should have access to adequate urban services, such as medical facilities, at a reasonable travel cost. To achieve the former goal, the concept of connectivity reliability has been developed, and to achieve the latter, accessibility measures have been proposed. This study proposes a method of evaluating road network robustness against a natural disaster by applying the concepts of connectivity reliability and accessibility. A new network evaluation measure, which considers both the risk of link disruption and the number of opportunities in an area, was first established. Then, the measure was applied to test networks, and the influence of network topology and distribution of opportunities were analyzed. Finally, the road network and medical facilities in Kyoto Prefecture were evaluated using the proposed measure.

Analysis of variation in demand and performance of urban expressways using dynamic path flow estimation

Understanding the dynamic characteristics of traffic demand is a key issue in designing a more reliable transport network. Identifying variations in link flow is easy, but it is impossible to determine variations in demand directly from observed traffic data. In this study, demand fluctuation was analysed using the dynamic path flow estimation method. Path flows were estimated using 1 year data from the Hanshin Expressway in Japan, and demand variations were analysed using the estimated results. This article also discusses the relationship between demand variations and external conditions such as weather and commercial practises. The results provide a valuable background for more detailed traffic control measures.

Model for Location of Medical Facility and Evaluation of Vulnerability and Accessibility of Road Network

This study proposes a method of evaluating the robustness of a road network against a natural disaster and aims to determine the optimal allocation of medical facilities if road network degradation occurs because of severe natural disasters. Connectivity vulnerability and accessibility are important concepts in evaluating the strength and reliability of road networks. This paper first introduces a new network evaluation measure, the distinct paths–based accessibility index (DPAI), which is based on the concepts of both connectivity vulnerability and accessibility; considers the number of distinct paths between a certain origin–destination pair, free-flow travel time, and the number of opportunities in an area; and develops a solution algorithm. A medical facility location model that optimizes the allocation of a medical facility to each centroid according to the DPAI is then formulated, and the results are applied to a real network. Although the optimal allocation of a medical facility varies according to the minimum DPAI, the robustness of an actual network may be improved by reallocating medical facilities. Moreover, the allocation results depend on the value of the importance placed on the number of distinct paths. These results imply that it is critical to set the parameter on the importance of the number of distinct paths by considering risks and geographical features in the subject area.