Jorge A. Laval

A mechanism to describe the formation and propagation of stop-and-go waves in congested freeway traffic

This paper introduces a parsimonious theory for congested freeway traffic that describes the spontaneous appearance of oscillations and their ensuing transformation into stop-and-go waves. Based upon the analysis of detailed vehicle-trajectory data, we conclude that timid and aggressive driver behaviours are the cause for this transformation. We find that stop-and-go waves arise independently of the details of these behaviours. Analytical and simulation results are presented.

VERIFICATION OF A SIMPLIFIED CAR-FOLLOWING THEORY

A simple car-following rule proposed by G.F. Newell was verified by measuring vehicles discharging from long queues at signalized intersections. Observations indicated that the time-space trajectory of a jth vehicle discharging on a homogeneous intersection approach was essentially the same as the j-1th vehicle except for a translation in time and space. These fixed translations are merely the time and distance required for driver j to reach the spacings she chooses for following vehicle j-1 as a function of j-1s velocities. This description is far simpler, and uses fewer parameters, than other car-following models.

Relaxation Phenomenon After Lane Changing: Experimental Validation with NGSIM Data Set

A calibration and an analysis of a recently proposed relaxation model that requires only one additional parameter ∊ are presented. The relaxation phenomenon takes place whenever a lane change occurs at a short spacing that falls outside the fundamental diagram. Such nonequilibrium spacing poses problems to car-following rules that can only handle equilibrium ones. The relaxation model has been already calibrated with macroscopic data. Trajectory data from NGSIM are used here to undertake a more rigorous calibration and validation. It is found that for a given driver there exists a value of ∊ that reproduces the relaxation process with uncanny accuracy and that the mean ∊-value does not worsen the fit significantly.

Impacts of Lane Changes at Merge Bottlenecks: A Theory and Strategies to Maximize Capacity

Recent empirical observations at freeway merge bottlenecks have revealed (i) a drop in the bottleneck discharge rate when queues form upstream, (ii) an increase in lane-changing maneuvers simultaneous with this “capacity drop”, and (iii) a reversal of the drop when the ramp is metered.

Stochastic Processes of Moving Bottlenecks: Approximate Formulas for Highway Capacity

This paper presents a general framework for developing formulas to estimate the capacity of freeway bottlenecks caused by the presence of slow vehicles. These underperforming vehicles may represent trucks on an uphill grade, cautious lane changers at a weaving section, or any other stream of vehicles moving consistently—at least for a short period of time—more slowly than prevailing traffic. From modeling of the under-performing stream as simplified yet realistic stochastic processes, closed-form expressions for the segments capacity can be obtained. Four such processes are presented and exemplified for the case of short uphill grades, a type of facility where existing capacity formulas fail. The proposed models—which do not need calibration—improve current estimates, and one in particular explains existing data with remarkable accuracy.

Effects of Merging and Diverging on Freeway Traffic Oscillations: Theory and Observation

Continuum theory is used to explain why stop-and-go oscillations in congested freeway traffic change their amplitudes when they encounter the vehicular merging and diverging maneuvers that take place near ramps. The theory describes how oscillations diminish in amplitude when they propagate past a queued (and unmetered) on-ramp and how they grow when they propagate past an off-ramp. The premise is that merging (diverging) flows change in response to freeway oscillations and that these changes in flow dampen (amplify) oscillations. The theorys descriptions are simple and rational; all its inputs and outputs are directly observable; and its predictions are shown to match real data. The theory is tested against real data collected over multiple days from congested merge and diverge sites with videos and inductive loop detectors. For merges, predictions are found to agree with observation to within 10%, and for diverges, to within 12%. The paper thus resolves in a simple way a puzzling traffic feature reported in previous studies.

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.

Stochastic Extension of Newell's Three-Detector Method

A stochastic extension of Newells three-detector method is presented. The method predicts the traffic states at an intermediate location given boundary data from downstream and upstream detectors. The method presented takes into account day-to-day variations in the arrivals, sensor detection errors, and variability in the fundamental diagram parameters. The output is the probabilistic distribution of predicted cumulative counts, which can be used to obtain confidence bounds on any traffic variable. The method is tested with empirical data.

The Distribution of Congestion on a Class of Stochastic Kinematic Wave Models

This paper shows that a wide range of stochastic extensions of the kinematic wave model tend to the same parameter-free expression for the probability of congestion at a given time-space point. This is shown for white noise initial density with deterministic and stochastic fundamental diagram in the case of Riemann problems and the bottleneck problem. It is also found that the stochastic solution i preserves the structure of the deterministic solution and ii tends to the deterministic solution with time at a given location.

Microsimulation-Based Framework for Freeway Travel Time Forecasting

This paper presents a microsimulation-based framework for generating short-term forecasts of travel time on freeway corridors. The microsimulation model that was developed replicated freeway capacity drop and relaxation phenomena critical for modeling non–steady state conditions. This framework was evaluated offline on a real-world freeway corridor by using data from manual counts and the Georgia Department of Transportations video detection system. The travel time forecasts were compared with ground truth travel time data; the comparison demonstrated the efficacy of this framework to produce realistic forecasts.