Takashi Nakatsuji

Application of probe-vehicle data for real-time traffic-state estimation and short-term travel-time prediction on a freeway

Traffic information from probe vehicles has great potential for improving the estimation accuracy of traffic situations, especially where no traffic detector is installed. A method for dealing with probe data along with conventional detector data to estimate traffic states is proposed. The probe data were integrated into the observation equation of the Kalman filter, in which state equations are represented by a macroscopic traffic-flow model. Estimated states were updated with information from both stationary detectors and probe vehicles. The method was tested under several traffic conditions by using hypothetical data, giving considerably improved estimation results compared to those estimated without probe data. Finally, the application of the proposed method was extended to the estimation and short-term prediction of travel time. Travel times were obtained indirectly through the conversion of speeds estimated or predicted by the proposed method. Experimental results show that the performance of travel-time estimation or prediction is comparable to that of some existing methods.

Multiple Car-Following Data with Real-Time Kinematic Global Positioning System

The real-time kinematic differential Global Positioning System (GPS) has facilitated a new horizon in traffic engineering. Multiple car-following experiments conducted with a real-time kinematic GPS with 10 vehicles participating in a probing field gave high-quality results in headway, speed, relative speed, and acceleration. The expected accuracies for measuring position and speed were 10 mm and 0.16 km/h, respectively. The vehicles were driven in a loop consisting of two parallel straight sections connected by two semicircular curves. Different driving conditions were induced in the platoon by instructing the leading driver to follow predetermined speed variations. The experiments yielded sets of continuous observations. Headway, speed, and acceleration were measured using conventional equipment for the purpose of comparing accuracy. The accuracy of the data obtained using the GPS was superior to that of the same data obtained using conventional measurements. The variation in driving characteristics down the stream of vehicles was studied using the experimental data. The results showed that the reaction time between a change in relative speed and the corresponding change in acceleration varies during the driving process. The reaction time of individual drivers also changes along the platoon. The good-quality data were able to give high-resolution plots of acceleration and relative speed illustrating that both the reaction time and the functional relationship between acceleration and relative speed do not remain constant.

Stability Analysis Based on Instantaneous Driving Behavior Using Car-Following Data

An attempt is made to analyze the stability of a platoon using experimental data measured by real-time kinematic (RTK) Global Positioning System (GPS) receivers. Car-following experiments were conducted on a test track using 10 passenger cars. Various speed patterns were tested for the lead car, including random, constant, and sinusoidal, giving different driving conditions. The responses of the following drivers were measured by RTK GPS receivers in each car. The stimulus–response car-following concept was examined, assuming that the reaction time might vary over time. A graphical method was modified to estimate the time-variant reaction time more efficiently. A new algorithm was proposed to estimate the sensitivity factor using Lissajou’s diagram between relative speed and acceleration. The statistical analysis showed that intrapersonal variability was higher than interpersonal variability for both reaction time and sensitivity factor. However, the influence of the driver’s position in the platoon and speed patterns was low. It was found that the reaction time was distributed in a lognormal function for most of the drivers. The variations in the estimated values for the sensitivity factor were relatively high. The stability analysis showed that the average responses of drivers were unstable both locally and asymptotically. The influence of speed fluctuation frequency was found insignificant for the stability of the platoon.

Experimental analysis of car-following dynamics and traffic stability

The study of car-following dynamics is useful for capacity analysis, safety research, and traffic simulation. There is also growing interest in its applications in intelligent transportation systems, such as advanced vehicle control and safety systems and autonomous cruise control systems. A large number of car-following models have been developed in the past five decades. Some of them were investigated and validated against experimental data; nevertheless, the results were not that con sistent for some models, e.g., those for the General Motors (GM) model. As a part of the problem, the data acquisition and calibration techniques were not advanced then. The past few decades have seen remark able advancements in these techniques, e.g., the use of the differential Global Positioning System (GPS) for position measurement, the use of Dopplers principle for speed measurements, and the use of genetic algorithms for optimization. It might be useful to reassess some out standing issues in car-following dynamics ...

Effect of adaptive cruise control (ACC) on traffic throughput : numerical example on actual freeway corridor

This study evaluated the effects of adaptive cruise control (ACC) on traffic flow using a microscopic traffic simulation on an actual freeway corridor, where traffic congestion was observed due to a traffic accident. Four types of ACCs were evaluated to determine their effect on travel time reduction given the low percentage of ACC equipped vehicles. A small numerical example showed that travel times could be significantly reduced only when the ACC is activated for almost all speed ranges and at least 20% of the vehicles are equipped with ACCs.

Dynamic estimation of origin-destination travel time and flow on a long freeway corridor : Neural Kalman filter

A model was formulated for estimating dynamic origin-destination (O-D) travel time and flow on a long freeway with a neural Kalman filter originally developed by the authors. The model predicts O-D travel times and flows simultaneously by using traffic detector data such as link traffic volumes, spot speeds, and off-ramp volumes. The model is based on a Kalman filter that consists of two equations: state and measurement. First, the state and measurement equations of the Kalman filter were modified to consider the influence of traffic states for some previous time steps. Then artificial neural network models were integrated with the Kalman filter to enable nonlinear formulations of the state and measurement equations. Finally, a macroscopic traffic flow simulation model was introduced to simulate traffic states on a freeway in advance and predict traffic variables such as O-D travel times, link traffic volumes, spot speeds, and off-ramp volumes. The new model was compared with a regression Kalman filter in which the state and measurement equations are defined by regression models. The numerical analysis indicated that the new model was capable of estimating nonlinearity of dynamic O-D travel time and flow and helped to improve their estimation precision under free-flow traffic states as well as congested flow states.

Psychological Factors Influencing Behavioral Intention Toward Future Sky Train Usage in Phnom Penh, Cambodia

A study is presented on an extension of the theory of planned behavior (TPB) to investigate the commuters behavioral intention toward future sky train usage in Phnom Penh, the capital city of Cambodia. Several psychological factors and socioeconomic variables that might help explain the likelihood of future sky train usage were measured by a questionnaire survey. Responses were collected from 398 motorcyclists who traveled along the planned sky train line linking the central market in the central business district to the airport. The survey was conducted on the basis of psychological constructs, including attitude, subjective norm, perceived behavioral control, moral obligation, and awareness of consequence. With structural equation modeling, it was found that the main TPB constructs, that is, attitude, subjective norm, and perceived behavioral control, significantly influenced the behavioral intention of using the future sky train. A further investigation revealed that moral obligation and the awareness of consequences were also found to be significant determinants for the behavioral intention. In addition, to some degree, socioeconomic variables can also be used to explain the intention. The outcome of the study can help in understanding commuters’ current behavioral intention and give some ideas on the feasibility of such an investment in regard to potential demand.

Asymptotic Stability and Vehicle Safety in Dynamic Car-Following Platoon

A vehicle in a platoon sometimes faces the risk of causing a rear-end collision when it is following a vehicle in front. The stability theory of the well-known General Motors car-following models says that the fluctuations of vehicle speeds and headways will increasingly propagate to the rear vehicle in a platoon if the platoon is asymptotically unstable. However, almost no research has been done to validate this phenomenon with the real car-following platoon data. Therefore, the car-following platoon data, including 10 vehicle trajectories, were used to evaluate asymptotic stability in the platoon. The asymptotic stability in vehicle safety is evaluated on the assumption that the vehicle in the rear position is exposed to riskier conditions than the vehicle positioned in front because of the shorter headways created by increased fluctuations of speeds and headways in a platoon if the asymptotic stability is unstable. Three indicators for safety are defined: potential danger time, impact speed, and expected impact speed. The outcomes in these safety indicators did not show that the car-following platoon was in asymptotically unstable conditions. Therefore, two supplemental indicators were defined to closely observe asymptotic stability: maximum speed amplitude and maximum spacing amplitude. These stability indicators were used to explain that the car-following platoon was under asymptotically unstable conditions. As a result, a hidden aspect of the relationship between asymptotic stability and vehicle safety was discovered in the real car-following platoon.

Real-Time Traffic State Estimation on Urban Road Network: The Application of Unscented Kalman Filter

Feedback approach for real-time traffic state estimation on urban road with signalized intersection is presented. The conventional discretization of kinematic wave model for freeway based on demand and supply concept is modified in order to be capable of describing traffic state on urban road with signalized intersection and to better estimate traffic speed. The novel filter, namely Unscented Kalman filter (UKF), is used as a correction algorithm to make the estimate to be consistent with the conventional model on speed estimation and the improvement in flow estimation when combining the model with UKF.

RELATIONSHIP BETWEEN WINTER ROAD-SURFACE CONDITIONS AND VEHICULAR MOTION: MEASUREMENTS BY PROBE VEHICLES EQUIPPED WITH GLOBAL POSITIONING SYSTEM

A major concern of drivers in winter is the current road condition. Taxis, which move ceaselessly around a wide area, have great potential as sensors for detecting road-surface conditions in a given area. To establish a method with which to estimate road conditions based on the vehicular motion of taxis, field experiments were conducted by using probe vehicles fitted with vehicular-motion sensors and a Global Positioning System device, before implementation in taxis. Preliminary analyses were performed by using data measured on a test track, urban streets, and an expressway. The slip ratio, defined as the relative difference in speed between vehicle and tire wheel, was effective in indicating how slippery the road surfaces were. Taxi vehicular-motion data were collected for more than 1 month, although unlike with probe vehicles, the wheel speed was not measured. Some features of vehicular motion specific to slippery roads were identified, and the discriminability of road conditions, whether icy or dry, without the use of wheel-speed data, was examined.