Statistical Distance-Based Travel-Time Reliability Measurement for Freeway Bottleneck Identification and Ranking

Freeway bottleneck identification is an essential component in the process of deploying mitigation strategies to reduce congestion at freeway bottlenecks. Most previous studies on bottleneck identification focus on recurrent bottlenecks, and limited work has been conducted to identify the locations of non-recurrent bottlenecks. Therefore, in this study, we propose a new travel time reliability (TTR) measurement and develop a freeway bottleneck identification method based on this measurement, which can identify with high probability not only recurrent bottlenecks but also the locations of non-recurrent bottlenecks. The TTR measurement is developed based on statistical distance between travel time distributions. Three statistical distance measurements, Jensen–Shannon divergence, Wasserstein distance, and Hellinger distance, are applied in the TTR measurement. The bottleneck identification method is evaluated in a case study on I-15 freeway corridor in Salt Lake City, Utah. The three statistical distance measurements show good consistency in ranking locations by the impacts of recurrent and non-recurrent congestion, especially for extreme cases with very high or low variation between travel time distributions. The recurrent bottlenecks identified in this study show their clustering characteristics, which is similar to the generating and dismissing process of recurrent congestion. The locations with high probability of non-recurrent bottlenecks scatter both spatially and temporally, which agrees with the random characteristic of non-recurrent congestion.

Examining Freeway Bottleneck Features During a Mass Evacuation

Traffic features were investigated for a bottleneck that was observed on a 30 mi northbound section of Florida’s Turnpike (SR-91) during the mass evacuation in advance of Hurricane Irma that occurred in September 2017. Radar detector data (at 1 min intervals) from the Regional Integrated Transportation Information System were utilized to determine the periods when a bottleneck was active adjacent to a service plaza along the roadway. Three distinct time periods were identified during which a bottleneck was active at the service plaza off-ramp, for a total of 27.5 h during the evacuation period. To identify and confirm each bottleneck activation and duration, and to measure the traffic flow features that characterized the bottleneck, curves of cumulative vehicle count and occupancy were utilized. Analysis of these curves revealed time periods during which excess vehicle accumulation and delay occurred between successive detector stations along the Turnpike. Results demonstrate distinct queued and free flowing traffic states between adjacent detectors in the vicinity of an off-ramp into a service plaza. The apparent bottleneck discharge features presented substantially lower flows than what would be expected for a limited access facility with high operational speeds. Findings from this paper present important considerations for evacuation planning and modeling as roadway traffic features may only present themselves during evacuations and if not accounted for may drastically reduce the precision of models and simulations.

Comparison of Stochastic Estimates of Capacity and Critical Density for U.S. and German Freeways

The randomness of freeway capacity has been analyzed in a large number of studies. In contrast, relatively little attention has been paid to the critical density at capacity and its relationship to breakdown occurrence, although density is used as a quality of service criterion for freeways. In the paper, distributions of freeway capacity and critical density are estimated and compared based on traffic data samples from 38 freeway bottleneck sections in the U.S. and Germany. It is shown that the well-established methods for stochastic capacity analysis can be applied to estimate critical density distributions by replacing volume with density in the corresponding mathematical models. Comparison of the estimated capacity and critical density distribution functions reveals that the relative variability of the capacity is lower than the variability of the critical density. This suggests that traffic volume is the more appropriate parameter to represent the trigger of traffic breakdowns than traffic density. The empirical results also show that the rather smooth traffic flow on U.S. freeways leads to a smaller variance of both the capacity and the critical density distribution compared with German freeways, whereas the average capacity per lane is roughly the same.

Analysis of the Long-Term Variations in Traffic Capacity at Freeway Bottleneck

In this paper, the long-term variation in traffic capacity at nine typical bottlenecks on intercity expressways in Japan is analyzed. The evaluation indices of traffic capacity are defined based on three factors: the ease of phase transition from free flow to congested flow is represented by the fifth-percentile traffic volume of breakdown probability; its reliability is defined by the gap between the 50th- and fifth-percentile traffic volume of breakdown probability; and the smoothness of traffic flow after the capacity drop is evaluated as the mean of the queue discharge flow rate. The findings show that: (i) the fifth-percentile traffic volume of traffic breakdown probability shows a long-term decreasing tendency, and the values in August and December are lower than the yearly average; and (ii) the gap between the 50th- and fifth -percentile traffic volume of traffic breakdown probability and discharge flow rate tend to decrease, but the trends are not significant. Finally, we suggest that the decreasing trends might be attributed to slight changes in driving skills, driving characteristics, or vehicle types.

Integrated Variable Speed Limits Control and Ramp Metering for Bottleneck Regions on Freeway

To enhance the efficiency of the existing freeway system and therefore to mitigate traffic congestion and related problems on the freeway mainline lane-drop bottleneck region, the advanced strategy for bottleneck control is essential. This paper proposes a method that integrates variable speed limits and ramp metering for freeway bottleneck region control to relieve the chaos in bottleneck region. To this end, based on the analyses of spatial-temporal patterns of traffic flow, a macroscopic traffic flow model is extended to describe the traffic flow operating characteristic by considering the impacts of variable speed limits in mainstream bottleneck region. In addition, to achieve the goal of balancing the priority of the vehicles on mainline and on-ramp, increasing capacity, and reducing travel delay on bottleneck region, an improved control model, as well as an advanced control strategy that integrates variable speed limits and ramp metering, is developed. The proposed method is tested in simulation for a real freeway infrastructure feed and calibrates real traffic variables. The results demonstrate that the proposed method can substantially improve the traffic flow efficiency of mainline and on-ramp and enhance the quality of traffic flow at the investigated freeway mainline bottleneck.