Maximum likelihood method of estimating the conflict-crash relationship.

The fundamental matters of how traffic conflicts are connected to crashes and how to estimate this connection with traffic conflict data is an active subject of research and refinements. There are still open questions about traffic events that can be analytically extrapolated to related crashes, and how to efficiently estimate the probability of crash associated with such events to enable conversion of observed events to the corresponding expected number of crashes. There are two important uses of a working estimation method: (1) rapid assessment of safety at specific roads locations and evaluation of countermeasures by safety engineers, (2) modeling of safety effects by analysts based on relatively short observations at multiple locations or at limited number of locations but during extended periods.

Towards human-like speed control in autonomous vehicles: A mountainous freeway case.

A driving strategy for autonomous vehicles (AVs) that is consistent with human behavior while demonstrating superior performance seems to have a good chance to be accepted by early AV users and be successful in the long run. Most of the past research focused on motion strategies affected by the presence of other vehicles. On the other hand, AV not constrained by other vehicles must select a safe and comfortable speed that is perceived as such by its occupants.

Feasibility study of highway alignment design controls for autonomous vehicles.

In recent years, the development and testing of autonomous driving technology have become widespread around the world. However, due to differences in perception abilities between autonomous vehicles and human drivers, the current geometric design controls for highway alignments, designed for the human driver, may not be applicable to the autonomous vehicle (AV). Few studies, however, have systematically investigated the design controls for autonomous vehicles, though we face full driving automation in the next few decades.

A unifying view on traffic conflicts and their connection with crashes.

After decades of research on traffic conflicts and other crash surrogate events, defining these events and conclusively connecting them with crashes continue to be the most important tasks. This paper aims to help establish a consensus on these two fundamental matters by discussing the underlying concepts by which they can be connected in a consistent construct justified with theory and empirical evidence. The importance of insight into a safety-relevant event beyond what is externally observable is emphasized by considering two distributions of crash nearness: (1) values observed by external observers and (2) driver-preferred values that are usually unobservable.

Transferability analysis of the freeway continuous speed model.

Operating speed is often used to evaluate consistency in road geometric design. In the China, the Specifications for Highway Safety Audit includes a spot-based speed model that predicts operating speed by dividing the road into homogeneous segments and observing the speeds at sparsely spaced spots. This paper presents a continuous speed model as a more representative alternative for roads with complex alignments, and can be applied to tunnel sections as one general model.

Validity of failure-caused traffic conflicts as surrogates of rear-end collisions in naturalistic driving studies.

Although the frequency and severity of crashes are direct measures of road safety, crash data are typically of limited quality and they require long data collection periods to produce conclusive results. Surrogates of crashes that would allow a quick and accurate estimation of safety have been an active topic for years. Among multiple alternatives, traffic conflicts have been established as a promising surrogate measure.

Analyzing road near departures as failure-caused events.

Surrogate measures of safety attract revived interest thanks to the advancements in traffic observations techniques and the growing need for rapid safety evaluation. A new method of safety analysis based on failure-caused traffic conflicts and the Lomax distribution was recently proposed to estimate crash frequency more efficiently than with crash data. This paper has two objectives: (1) demonstrate the method applicability to near-departure data collected in a driving simulator, and (2) provide initial evidence of the method validity.

Adequacy of negative binomial models for managing safety on rural local roads.

Count models, such as negative binomial regression, are well-established statistical methods for analyzing road safety. Although count models are widely used for arterial roads, their application to rural local roads is sparse, partly due to the concern of possible estimation bias caused by low crash counts. This paper revisits the matter to further evaluate the suitability of negative binomial models for rural local roads with low crash frequencies, comparing the performance of the model to probabilistic regression (ordered probit) proposed in the past.

Investigating factors of crash frequency with random effects and random parameters models: New insights from Chinese freeway study.

In response to the rapid economic growth in China, its freeway system has become the longest in the world and likely will continue to expand. Unfortunately, the safety issues on freeways in China have grown as well and are of great concern to Chinese transportation authorities and drivers. While many proven safety countermeasures developed and implemented by other countries are available for reference, they may be not fully transferrable to China due to the differences in driving cultures and conditions.

Estimating the expected number of crashes with traffic conflicts and the Lomax Distribution - A theoretical and numerical exploration.

This paper justifies the Lomax distribution for counterfactual modeling of the probability of crash given a traffic conflict. The pre-crash process leading to a conflict or a crash as the result of a failure is discussed as this conceptualization is the basis for proposing a simple model of the probability of a crash at the moment when a conflict is still progressing. Then, a model applicable to heterogeneous conditions is derived; and the model's relevance, useful properties, and limitations are discussed.

Analyzing crash frequency in freeway tunnels: A correlated random parameters approach.

The majority of past road safety studies focused on open road segments while only a few focused on tunnels. Moreover, the past tunnel studies produced some inconsistent results about the safety effects of the traffic patterns, the tunnel design, and the pavement conditions. The effects of these conditions therefore remain unknown, especially for freeway tunnels in China.

Barrier-relevant crash modification factors and average costs of crashes on arterial roads in Indiana.

The objective of this study was to develop crash modification factors (CMFs) and estimate the average crash costs applicable to a wide range of road-barrier scenarios that involved three types of road barriers (concrete barriers, W-beam guardrails, and high-tension cable barriers) to produce a suitable basis for comparing barrier-oriented design alternatives and road improvements. The intention was to perform the most comprehensive and in-depth analysis allowed by the cross-sectional method and the crash data available in Indiana. To accomplish this objective and to use the available data efficiently, the effects of barrier were estimated on the frequency of barrier-relevant (BR) crashes, the types of harmful events and their occurrence during a BR crash, and the severity of BR crash outcomes.

An insight into the performance of road barriers - redistribution of barrier-relevant crashes.

Unlike most of traffic safety treatments that prevent crashes, road barriers reduce the severity of crash outcomes by replacing crashes with a high risk of severe injury and fatality (such as median crossover head-on collisions or collisions with high-hazard objects) with less risky events (such as collisions with barriers). This "crash conversion" is actually more complex than one-to-one replacement and it has not been studied yet. The published work estimated the reduction of selected types of crashes (typically, median crossover collisions) or the overall effect of barriers on crash severity.

Evaluating the rollover propensity of trucks--A roundabout example.

The rollover propensity of SUVs and trucks has long been recognized as a potential safety issue. The propensity may increase with the growing number of roundabouts that are being built on high-speed roadways designed for 50 mi/h or higher. This paper presents a research methodology developed to evaluate the rollover propensity of trucks on existing roundabouts and other roads with tight curves and high-speed traffic.

The influence of combined alignments on lateral acceleration on mountainous freeways: a driving simulator study.

Combined horizontal and vertical alignments are frequently used in mountainous freeways in China; however, design guidelines that consider the safety impact of combined alignments are not currently available. Past field studies have provided some data on the relationship between road alignment and safety, but the effects of differing combined alignments on either lateral acceleration or safety have not systematically examined. The primary reason for this void in past research is that most of the prior studies used observational methods that did not permit control of the key variables.

Effectiveness of cable barriers, guardrails, and concrete barrier walls in reducing the risk of injury.

Roadway departure crashes tend to be severe, especially when the roadside exposes the occupants of errant vehicles to excessive injury hazards. As a cost-effective method when the clear zone width is insufficient, road barriers are often installed to prevent errant vehicles from colliding with dangerous obstacles or traversing steep slopes. This paper focuses on the safety performance of road barriers in Indiana in reducing the risk of injury.

Emerging research methods and their application to road safety.

The study of road safety has seen great strides over the past few decades with advances in analytical methods and research tools that allow researchers to provide insights into the complex interactions of the driver, vehicle, and roadway. Data collection methods range from traditional traffic and roadway sensors to instrumented vehicles and driving simulators, capable of providing detailed data on both the normal driving conditions and the circumstances surrounding a safety critical event. In September 2011, the Third International Conference on Road Safety and Simulation was held in Indianapolis, Indiana, USA, which was hosted by the Purdue University Center for Road Safety and sponsored by the Transportation Research Board and its three committees: ANB20 Safety Data, Analysis and Evaluation, AND30 Simulation and Measurement of Vehicle and Operator Performance, and ABJ95 Visualization in Transportation.

Predicting crash likelihood and severity on freeways with real-time loop detector data.

Real-time crash risk prediction using traffic data collected from loop detector stations is useful in dynamic safety management systems aimed at improving traffic safety through application of proactive safety countermeasures. The major drawback of most of the existing studies is that they focus on the crash risk without consideration of crash severity. This paper presents an effort to develop a model that predicts the crash likelihood at different levels of severity with a particular focus on severe crashes.

Use of crash surrogates and exceedance statistics to estimate road safety.

The limited ability of existing safety models to properly reflect crash causality has its source in cross-sectional analysis applied to the estimation of the intrinsically complex safety factors with highly aggregated and frequently poor quality of data. The adequacy of the data may be improved thanks to the unprecedented progress in sensing technologies and the invention of the naturalistic driving method of data collection. Proposed in this paper is a new modeling paradigm that integrates several types of safety models.

Pedestrian injury analysis with consideration of the selectivity bias in linked police-hospital data.

Evaluation of crash-related injuries by medical specialists in hospitals is believed to be more exact than rather a cursory evaluation made at the crash scene. Safety analysts sometimes reach for hospital data and use them in combination with the police crash data. One issue that needs to be addressed is the, so-called, selectivity (or selection) bias possible when data used in analysis are not coming from random sampling.

Modeling drivers' speed selection as a trade-off behavior.

This paper proposes a new model of driver-preferred speeds derived from the assumption that drivers trade-off a portion of their safety for a time gain. The risk of receiving a ticket for speeding is also considered. A trip disutility concept is selected to combine the three components of speed choice (safety, time, and enforcement).

Markov switching negative binomial models: an application to vehicle accident frequencies.

In this paper, two-state Markov switching models are proposed to study accident frequencies. These models assume that there are two unobserved states of roadway safety, and that roadway entities (roadway segments) can switch between these states over time. The states are distinct, in the sense that in the different states accident frequencies are generated by separate counting processes (by separate Poisson or negative binomial processes).

Tobit analysis of vehicle accident rates on interstate highways.

There has been an abundance of research that has used Poisson models and its variants (negative binomial and zero-inflated models) to improve our understanding of the factors that affect accident frequencies on roadway segments. This study explores the application of an alternate method, tobit regression, by viewing vehicle accident rates directly (instead of frequencies) as a continuous variable that is left-censored at zero. Using data from vehicle accidents on Indiana interstates, the estimation results show that many factors relating to pavement condition, roadway geometrics and traffic characteristics significantly affect vehicle accident rates.

The extreme value theory approach to safety estimation.

Crash-based safety analysis is hampered by several shortcomings, such as randomness and rarity of crash occurrences, lack of timeliness, and inconsistency in crash reporting. Safety analysis based on observable traffic characteristics more frequent than crashes is one promising alternative. In this research, we proposed a novel application of the extreme value theory to estimate safety.

Perception-based road hazard identification with Internet support.

One of the most important tasks faced by highway agencies is identifying road hazards. Agencies use crash statistics to detect road intersections and segments where the frequency of crashes is excessive. With the crash-based method, a dangerous intersection or segment can be pointed out only after a sufficient number of crashes occur.