Danjue Chen

Evolution of Oscillations in Congested Traffic: Improved Estimation Method and Additional Empirical Evidence

This paper provides additional empirical evidence confirming a recently proposed theory on the evolution of oscillations in congested traffic. It also proposes an improved method for computing the variation in oscillation amplitude, consisting in evaluating the oscillation amplitude along characteristic lines that travel at a constant wave speed. It is also shown that the theory is robust in that approximate input parameters can be used with little loss in accuracy. The paper, in addition, provides a finding on the evolution of oscillations in freeway segments with no entrances or exits. Although previous studies found an increase in oscillation amplitude in such segments, data in this study indicate that this is not the case in general. This finding can have important implications for understanding driver behavior in homogeneous freeway segments.

Analysis of driver response and traffic evolution under variable speed limit control

Field test results of a variable speed limit (VSL) control algorithm, a speed-controlling algorithm using shock wave theory (SPECIALIST), were analyzed to elucidate driver response and traffic flow evolution under VSL control. Successful VSL control was characterized by nearly constant, or decreasing, demand over time. In contrast, failed VSL control was attributed to (a) significant increase in demand (during control) and (b) significant net inflow from ramps. The demand increase was found to be the leading cause of the failed control, underscoring that the efficacy of the VSL control greatly relies on its ability to incorporate demand patterns during control. On the basis of these findings, some potential improvements are offered, including a parameter design strategy that incorporates demand patterns.

Car-Following and Lane-Changing Behavior Involving Heavy Vehicles

This paper presents empirical findings on car-following and lane-changing behavior involving heavy vehicles; trajectory data from the next generation simulation program were used in the study. It was found that when following passenger cars, heavy vehicles tended to reduce speed variations caused by traffic disturbances and thereby dampened traffic oscillations. In contrast, passenger cars following heavy vehicles tended to amplify traffic disturbances, although with lower probability and magnitude compared with the dampening effect. Moreover, heavy vehicles tended to discourage lane changes, especially behind them. This finding has convoluted implications: although reduced lane changes can improve traffic stability by preventing or reducing disturbances, large gaps can persist behind heavy vehicles and contribute to underutilization of road capacity.

Integrated Traffic Flow Models and Analysis for Automated Vehicles

With the emergence of connected and automated vehicle (CAV) technologies, research on traffic flow modeling and analysis will play a very important role in improving our understanding of the fundamental characteristics of traffic flow. The frontier of studies on CAV systems have examined the impacts of CAVs on freeway bottleneck capacity, and macroscopic traffic flow, CAV applications on optimization of individual vehicle trajectories, potentials of CAV in traffic signal control, and applications of CAV in network routing. For current and future research initiatives, the greatest challenge lies in the potential inconsistencies between user, operator, and manufacturer goals. Specific research needs were identified on data collection and analysis on CAV behavior and applications. This paper summarizes the presentations and discussions during the Automated Vehicles Symposium 2015 (AVS15) held in Ypsilanti, Michigan, on July 20–23, 2015.