Florian Marczak

New Filtering Method for Trajectory Measurement Errors and Its Comparison with Existing Methods

Dynamic traffic simulation tools are increasingly being used to help traffic managers and urban planners to make decisions. Therefore, simulation tool users require a validated methodology guaranteeing that simulation results can be trusted. This study contributes to the identification and correction of a possible deficiency in detailed calibration and validation of car-following models: the data errors of individual trajectory data. Some studies addressed the problem of filtering trajectory data. A new filtering technique to reduce the measurement errors on trajectories, speed profiles, and acceleration profiles is proposed here. This technique is based on some piecewise polynomials termed “splines.” The proposed technique is compared with a set of filtering techniques found in the literature. A complete trajectory data set available within the NGSIM program is used. As a quality indicator of the various filtering techniques, velocity distribution, acceleration distribution, and jerk analysis are used for the whole data set. Also, analyzing acceleration standard deviations for each trajectory of the data set is suggested. The main findings are as follows: (a) of the methods compared within this work, the I-spline method with the action points most reduces the spikes in the velocity distribution; (b) moreover, the I-spline method most reduces the percentage of jerk values higher than 15 m/s3 as well as the percentage of the 1-s windows with more than one sign inversion of the jerk; and (c) in some cases, this method increases the acceleration variability of smoothed trajectories.

Capacity drops at merges: New analytical investigations

This paper focuses on the derivation of analytical formulae to estimate the effective capacity at freeway merges. It extends previous works by proposing a generic framework able to account for a refined description of the physical interactions between upstream waves and downstream voids created by inserting vehicles within the merge area. The provided analytical formulae permits to directly and accurately compute the capacity values when the merge is self-active, i.e. when both upstream roads are congested while downstream traffic conditions are free-flow.

Analytical Derivation of Capacity at Diverging Junctions

Freeway congestion occurs mainly at discontinuities of the road network, such as merges, weaving sections, and diverges. Reliable tools are needed for estimating the operations at these discontinuities and evaluating their capacity. This paper proposes an analytical model that estimates the capacity at a diverging junction according to the kinematic wave theory of Lighthill, Whitham, and Richards. The model assumes that exiting vehicles drive temporarily at a speed that is lower than the free-flow speed. The slow vehicles are considered moving bottlenecks. In the methodology, the acceleration is assumed to be infinite in a first step. But, because it is a key factor in explaining the capacity drop, this assumption is relaxed in a second step through a constant acceleration rate used for all the vehicles. In this study, the moving bottleneck theory is used to compute the effective flow passing the diverging junction and the corresponding relative capacity drop. The analytical results are assessed with microsimulation results.