A comparative study on crash-influencing factors by facility types on urban expressway

This study aims at identifying crash-influencing factors by facility type of Nagoya Urban Expressway, considering the interaction of geometry, traffic flow, and ambient conditions. Crash rate （CR） model is firstly developed separately at four facility types： basic, merge, and diverge segments and sharp curve. Traffic flows are thereby categorized, and based on the traffic categories, the significances of factors affecting crashes are analyzed by principal component analysis. The results reveal that, the CR at merge segment is significantly higher than those at basic and diverge segments in uncongested flow, while the value is not significantly different at the three facility types in congested flow. In both un- and congested flows, sharp curve has the worst safety performance in view of its highest CR. Regarding influencing factors, geometric design and traffic flow are most significant in un- and congested flows, respectively. As mainline flow increases, the effect of merging ratio affecting crash is on the rise at basic and merge segments as opposed to the decreasing significance of diverging ratio at diverge segment. Mean- while, longer acceleration and deceleration lanes are adverse to safety in uncongested flow, while shorter acceleration and deceleration lanes are adverse in congested flow. Due to its special geometric design, crashes at sharp curve are highly associated with the large centrifugal force and heavy restricted visibility.

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.

Making Data-Driven Transportation Decisions for Freight Operations

Using Louisiana’s Interstate system, this paper aims to demonstrate how data can be used to evaluate freight movement reliability, economy, and safety of truck freight operations to improve decision-making. Data mainly from the National Performance Management Research Data Set (NPMRDS) and the Louisiana Crash Database were used to analyze Truck Travel Time Reliability Index, commercial vehicle User Delay Costs, and commercial vehicle safety. The results indicate that while Louisiana’s Interstate system remained reliable over the years, some segments were found to be unreliable, which were annually less than 12% of the state’s Interstate system mileage. The User Delay Costs by commercial vehicles on these unreliable segments were, on average, 65.45% of the User Delay Cost by all vehicles on the Interstate highway system between 2016 and 2019, 53.10% between 2020 and 2021, and 70.36% in 2022, which are considerably high. These disproportionate ratios indicate the economic impact of the unreliability of the Interstate system on commercial vehicle operations. Additionally, though the annual crash frequencies remained relatively constant, an increasing proportion of commercial vehicles are involved in crashes, with segments (mileposts) that have high crash frequencies seeming to correspond with locations with recurring congestion on the Interstate highway system. The study highlights the potential of using data to identify areas that need improvement in transportation systems to support better decision-making.