High Occupancy Toll (HOT) lanes are emerging as a solution to address the underutilization of High Occupancy Vehicle (HOV) lanes and also means of generating revenue for state department of transportation. This paper proposes a method for dynamically determining the HOT toll price in response to the changes in traffic condition and documents procedures for estimating parameters needed for the proposed pricing strategies: revenue maximization and delay minimization. The proposed strategies have been applied to 14-miles of freeway segment in the San Francisco Bay Area, and the findings show that utilizing all the available HOV lane capacity (i.e. difference between HOV lane capacity and HOV demand) to serve the HOT demand does not result in maximizing the total revenue. There exists optimal level of HOV lane capacity that can be allowed for the use of HOT vehicle to maximize the revenue.

From a recent study of safety evaluation of HOV-equipped freeways, it was found that limited-access HOV lanes appear to have a safety performance disadvantage when measured by collision distribution or collision rates for the HOV lane alone and for the HOV and left lanes combined. This paper describes the work performed to verify the statistical significance of related findings. Several statistical tests were used: empirical cumulative density function (CDF), Kolmogorov-Smirnov Tests, and comparison of means based on Poisson Distributed Samples. The conclusion that continuous-access HOV lanes perform better than limited-access ones by several safety metrics is confirmed by the three separate approaches. In addition, the historical data for the HOV segments and the general-purpose lanes are extracted and compared, which offers supporting evidence for similar conclusions. The work described in this paper offers a methodology of statistical verification and can provide support to assist policy-making in selecting HOV configurations.

Freeway collisions are thought to be affected by traffic states. To reduce the number of collisions, the study to reveal how the traffic states influence collisions are required. Therefore, the purpose of the paper is to suggest a method to relate traffic states to collision frequency in freeway. We first defined section- based traffic phases showing traffic state of a section using upstream and downstream traffic states: free flow (FF), back of queue (BQ), bottleneck front (BN) and congestion (CT). Secondly, by integrating freeway collision data and traffic data from the California PeMS database, over a three-year period, we obtained the collision frequency for each traffic phase, and compared for a 32mile section of the I-880 freeway. The results show that collision rate in BN, BQ, and CT phase are approximately 5 times higher than the collision rate in FF. Also, the proposed method shows potential for predicting collision frequencies on freeway sections when combined by traffic simulation.

Pedestrian-involved crashes that occurred in the city of San Francisco over a six-year period, 2002–2007, were analyzed to examine various influential factors on the injury severity of pedestrian crashes. The crash data extracted from the Statewide Integrated Traffic Records System (SWITRS) include five categorical levels of injury severity in traffic crashes also in addition to detailed information about the features of each crash. This study applied an ordered probit model for injury severity analysis to specify the ordinal nature of injury categories. To draw unbiased implications from the estimated parameters, statistical tests were performed on the parameters based on robust standard errors. Then, the marginal effects of each variable on the likelihood of each injury level were computed. The variables that significantly increased the probability of severe injury and fatality were: i) age (under age 15 and over age 65), alcohol consumption and cell phone use among pedestrian characteristics; ii) nighttime, weekends and rainy weather among environmental characteristics; and iii) influence of alcohol, larger vehicles (pickups, buses and trucks) and vehicle proceeding straight when striking a pedestrian among crash characteristics. Crash characteristics were found to influence significantly on the level of pedestrian injury. Based on the findings of this analysis, policy implications and countermeasures are also discussed.

This paper describes comparisons of traffic safety during the morning and afternoon peak hours in extended stretches of eight High Occupancy Vehicle (HOV) lanes with two different types of access – four corridors with continuous access and the others with limited access. Traffic collision patterns in two different types of HOV lanes were investigated by evaluating 1) the differences in collision distribution, severity, types of collisions and per lane traffic utilization, 2) spatial distribution of collision concentrations by using Continuous Risk Profile (CRP) approach, and 3) collision rates in the vicinity of access points in HOV lanes with limited access. In the paper, the authors conducted detailed analysis on collision data occurred during peak hours in relation to geometry and traffic features. Based on the findings from the assessment on eight routes, the limited access HOV lanes appear to offer no safety advantages over the continuous access HOV lanes. Such difference is due to more frequent and sporadic distribution of collision concentration in limited access HOV lanes.

Spatiotemporal analysis of real freeway traffic reveals that carpool lanes are not as damaging as previously reported. To the contrary, the analysis unveils a surprising benefit of carpool lanes that should be even greater when special lanes are used to segregate very different vehicle classes, such as buses and cars. The paper pursues this finding and shows how reserving lanes on freeways and city streets for bus-use only can favorably affect not just buses, but also cars.

Collision data from High Occupancy Vehicle (HOV) facilities with two different types of access, continuous and limited, are examined in this paper. The findings show that HOV facilities with limited access offer no safety advantages over those with a continuous access. Compared with continuous access HOV lanes, a higher percentage of collisions was concentrated on limited access HOV lanes. Limited access HOV lanes also had higher collision rates. Findings from investigating the relationship between collision rates in HOV lanes with respect to shoulder width, length of access, and the proximity of access to its neighboring ramps are also documented. These findings provide enhanced understanding about the effects of geometric factors on the collision rates in HOV lanes.

An earlier empirical study of San Francisco Bay Area freeways concluded that HOV lanes unfavorably affect freeway traffic by creating congestion. That study attributed the observed congestion to HOV lanes and tentatively recommended their elimination over the full lengths of the freeways it examined; and even from all Bay Area freeways. It recognized, however, that its analysis is fragmentary and recommended further work to solidify its conclusions. This is logical since the study lacks a spatiotemporal analysis to pinpoint where and how congestion first forms (at bottlenecks).

The present report re-examines the same set of freeway sites in spatiotemporal detail to understand more deeply how HOV lanes are affecting traffic. It enriches the data from the original study with data from neighboring detector stations, to identify: first the locations (bottlenecks) where queues are triggered; and second the role that HOV lanes play in this phenomenon. This study includes an even more detailed analysis of high-resolution video data from a bottleneck where the HOV lane initially seemed to be having an unfavorable effect.

To our surprise, we found no compelling evidence that the HOV lanes were triggering delays and queues on the freeway sites in the earlier study. In all cases queues formed first at bottlenecks and, save for one questionable case, formed for reasons unrelated to the HOV lanes. This was true even on additional days that we studied. Moreover, data did not conclusively show that HOV lanes were reducing bottleneck flows or prolonging the queues; no adverse effects could be confirmed. To the contrary, and quite remarkably, the HOV lane seemed to increase the capacity of the bottleneck that was videotaped, even though that lane was underutilized. (The video data show that higher than normal discharge flows arose in the remaining lanes when the HOV lane was underutilized – enough even to compensate for that lane’s underutilization. Reassuringly, this effect had been predicted in earlier simulations.)

Although the sites assessed in this and the original study may not contain bottlenecks where the HOV lane is contributing to problems, the present study recognizes that such bottlenecks exist. They are just less prevalent than originally suspected. Fortunately for society, an HOV lane can be useful in most of these cases: theory and simulations indicate that if an HOV lane is rescinded near a problematic bottleneck but is preserved on the entire queued freeway stretch upstream, the lane will neither affect the bottleneck’s discharge flow nor the delay to vehicles that pass through the bottleneck. For typical freeways with four or more lanes, delay to all vehicles would change little. The HOV lane would allow HOVs to bypass most of the congestion without significantly increasing total vehicle-hours of travel.

This means that even in problematic cases, HOV lanes can usually be preserved and allowed to perform their intended societal function: reducing people-hours of travel without significantly increasing vehicle-hours of travel by favoring HOVs where freeway queues arise. To avoid increased vehicle delays, however, and perhaps even to increase bottleneck capacities, some HOV-lane installations should be modestly altered near bottlenecks. This report also describes field studies necessary to determine where and how such alterations should be deployed.