Freeway Characteristics Research Articles

Speed behaviour upon approaching freeway curves

The actual speed behaviour when drivers approach a curve is very relevant to assess the road design and safety but is mostly overlooked in the scientific literature. Most research into curve driving behaviour is focussed at the behaviour inside the curve, although the speed selection is done before curve entry. The main objective of this research is to identify which freeway characteristics play a role in driving speed selection. High Frequency Floating Car Data, detailed reconstruction of the curves and their surroundings, as well as three dimensional sight distance analysis, were used to analyse individual speed profiles on 153 Dutch freeway curves. By defining the positions where the acceleration approaches 0 m/s2 before and after a curve starts, the positions when the driver started and stopped decelerating upon curve entry were defined. Further correlation and regression analysis of those positions revealed that the radius of the curve is indeed a main explaining variable, as well as the speed driven before deceleration starts. Sight distances and cross section characteristics play a further role in determining the position where deceleration starts. Deceleration ends at approximately 135 m after curve start, and the speed in a curve is also correlated with the deflection angle and length of a curve. Sight distances do not play a role in selecting the speed in a curve based on this research. Overall, the findings indicate a non-constant nature and variability of speed behaviour upon curve entry. This can be used for safer freeway curve design and to assess traffic safety based on actual speed behaviour.

Understanding the formation of rubbernecking queues on urban freeways

Rubbernecking on freeways is a common problem that arises when queuing traffic develops in the opposite direction of a freeway incident. The goals of this study are to evaluate the effects of rubbernecking on traffic, investigate incident and freeway characteristics associated with it, evaluate rubbernecking models, and analyze drivers’ behavior in relationship to rubbernecking. To this end, traffic data around a major incident were analyzed. Results revealed that rubbernecking can instigate significant queue lengths, congestion durations, and traffic delays. In addition, analysis of 637 incidents revealed that 12% of incidents instigated rubbernecking queues. A logistic regression model was also fitted to the data. Results from the model suggest that on-ramps, high-occupancy vehicle (HOV) lanes, and percent of trucks are factors associated with rubbernecking. In addition, validation analyses of rubbernecking models pointed to limitations of estimated statistical models in effectively predicting rubbernecking events. Furthermore, results from a drivers’ behavior self-reporting survey suggest that a majority of drivers tend to decrease their speed around an incident in the opposite direction of traffic. It was also observed that respondents attributed these actions to habits and behavior more frequently than incident and freeway characteristics. Findings from this work can be used to help develop targeted rubbernecking traffic control measures, enhance rubbernecking data collection methods and modeling, and advance behavioral interventions to reduce the onset of rubbernecking queues on freeways.

Lane flow distribution of congested traffic on three-lane freeways

Abstract This research presents an empirical analysis of lane flow distribution (LFD) in three-lane congested freeways. Data from 72 sites were analyzed to investigate LFD trends with respect to flow and the traffic and freeway characteristics that influence lane-specific traffic behavior. Regression analysis was employed to identify recurrent linear LFD trends with respect to flow and evaluate the factors that instigate the observed LFD patterns. It was found that varying LFD trends are just as prevalent as constant LFD trends and that LFD is not uniform. In addition, four recurrent combinations of varying LFD trends were observed among the sites. Regression models were estimated to represent class-specific linear LFD trends for sites with varying LFD. Results show that the estimated models represent the observed linear LFD trends reasonably well. It was also observed that proximity to freeway merges increases the probability of varying LFD trends, while the presence of HOV lanes reduces it.

Estimating Crash Rate of Freeway Segments Using Simultaneous Equation Model

This study develops crash rate prediction models based on the premise that crash frequencies observed from adjacent paired non-weaving and weaving freeway segments are spatially correlated and therefore requires a simultaneous equation modeling approach. Simultaneous equation models for paired freeway non-weaving segments and weaving segments along with combined three freeway segments upstream and downstream were developed to investigate the relationship of crash rate with freeway characteristics. The endogenous variables have significant coefficients which indicate that unobserved variables exist on these contiguous segments, resulting in different crash rates. AADT is a variable that can show the interaction between the traffic and crashes on these contiguous segments. The results corroborate such an interaction. By comparing the simultaneous equation model and the multiple linear regression model, it is shown that more model parameters in the simultaneous models are significant than those from linear regression model. This demonstrates the existence of the correlation between the interchange and between-interchange segments. It is crucial that some variables like segment length can be identified significant in the simultaneous model, which provides a way to quantify the safety impact of freeway development.

Use of Performance Measurement System Data to Diagnose Freeway Bottleneck Locations Empirically in Orange County, California

To improve freeway modeling and operations, it is important to understand how traffic conditions evolve in both time and space. The widespread availability of freeway sensor data makes detailed operational analysis possible in ways that were not available in the past. This study, inspired by several other studies of a 6-mi segment of Interstate 405 in Orange County, California, describes the evolution of traffic conditions over one morning peak period by using inductive loop detector data, including vehicle count and lane occupancy measured at 30-s intervals. With cumulative curves of vehicle count and occupancy, transformed in ways that enhanced their resolution, 10 bottleneck activations were identified in time and space over one morning peak period. At bottleneck activation, queue propagation was observed in generally predictable ways. Bottleneck outflows were carefully measured only while the bottlenecks were active, that is, while queued conditions persisted upstream and unqueued (freely flowing) conditions prevailed downstream. When bottlenecks were activated immediately following freely flowing conditions, outflow reductions were observed at queue formation. These reductions were consistent with those in previous studies. The study was limited in that only one day's data were analyzed and ramp data were not available on the day analyzed. Future research will include further analysis of the same site by using more recent data now that ramp counts are available in the California Performance Measurement System database. Understanding the mechanisms that lead to bottleneck activation is a critical step toward improving the understanding of how freeways function and is necessary for addressing operational issues. This clear understanding provides a foundation for determining ramp metering rates and addressing the freeway characteristics that cause bottlenecks to form.

Indivisibilities, Economies of Scale, and Optimal Subsidy Policy for Freeways

In our 1976 paper, Herbert Mohring, Thomas Pinfold and I attempted to quantify optimal congestion tolls, volume/ capacity ratios, and subsidies for freeways. In doing so, we made the simplifying assumption of perfectly divisible traffic lanes. Of course, freeway lanes are not divisible, and with two to four lanes typically provided in each direction, the size of the indivisibility is large. This paper quantifies optimal freeway characteristics with indivisibilities taken into account. We find that failure to account for indivisibilities can lead to