Journal of Transportation Safety & Security 

About: Journal of Transportation Safety & Security is an academic journal published by Taylor & Francis. The journal publishes majorly in the area(s): Poison control & Crash. It has an ISSN identifier of 1943-9962. Over the lifetime, 562 publications have been published receiving 6222 citations. The journal is also known as: Journal of transportation safety and security.

Exploring the relationship between average speed, speed variation, and accident rates using spatial statistical models and gis

Abstract: The primary objective of this article is to contribute to the debate on the relationship between average speeds, speed variations, and accident rates. This is achieved by the use of two advanced statistical models: (1) a nonspatial random-effects negative binomial model and (2) a spatial Poisson-lognormal model using a full hierarchical Bayesian model to explore the relationship. Disaggregated segment-based traffic, road geometry, and accident data from 266 road segments including 13 different motorways (including the M25 motorway) and 17 different trunk A-class roads around London from 2003 to 2007 are used in the analysis. GIS tools are used to achieve the appropriate data and to derive the weight matrix among neighboring segments that is necessary for the spatial model. The results suggest that average speeds are not associated with accident rates when controlling for other factors affecting accidents such as traffic volume, road geometry (e.g., grade and curvature), and number of lanes. However, speed variation is found to be statistically and positively associated with accident rates. A 1% increase in speed variation is associated with a 0.3% increase in accident rates, ceteris paribus. The results for all other factors are found to be consistent with existing studies. Policy implications of the findings are then discussed.

Alternative Ordered Response Frameworks for Examining Pedestrian Injury Severity in New York City

Abstract: This article focuses on identifying the appropriate ordered response structure for modeling pedestrian injury severity. The alternative ordered response approaches considered for the empirical analysis include ordered logit model (OL), generalized ordered logit model (GOL), and latent segmentation based ordered logit model (LSOL). The GOL and LSOL models enhance the traditional OL model in different ways. The GOL model relaxes the restrictive thresholds in the OL model by allowing for individual-level exogenous variable impacts on the threshold parameters. On the other hand, the LSOL model allows for differential impact on the alternatives by segmenting the pedestrian crash population into various segments with segment-specific OL parameters. In this study, the authors focus on examining the performance of these two model structures relative to the traditional OL model in the context of pedestrian injury severity. The performance of the formulated injury severity models are tested based on the New York City (NYC) Pedestrian Research Data Base for the years 2002 through 2006. To the authors’ knowledge, the study provides a first of its kind comparison exercise among OL, GOL, and LSOL models for examining pedestrian injury severity. The model estimation results clearly highlight the presence of segmentation based on the crash location attributes of pedestrian accidents. The crash location attributes that affect the allocation of pedestrians into these segments include regional county, functional classification of roadway, pedestrian location on roadway, number of travel lanes, and number of parking lanes in the roadway system. The key factors influencing pedestrian injury severity are weather condition, lighting condition, vehicle types, pedestrian age, and season. Overall, the results of the empirical analysis provide credence to the hypothesis that LSOL model is a promising ordered framework to accommodate population heterogeneity in the context of pedestrian injury severity.

Robust Shelter Locations for Evacuation Planning with Demand Uncertainty

Abstract: This article presents a robust approach for determining optimal locations of public shelters and their capacities, from a given set of potential sites during evacuation planning under demand uncertainty. Demand uncertainty in the article refers to the uncertainty associated with the number of people using the public shelters during evacuation. It is assumed that a planning authority determines the number of shelters, their locations, and capacities whereas evacuees choose a shelter to evacuate and the routes to access it. The proposed model is formulated as a mathematical program with complementarity constraints and is solved by a cutting-plane scheme. A numerical example on the Sioux Falls network demonstrates that robust plans are able to achieve nearly the same level of performance with a significant lower cost as compared to a conservative plan, which assumes the highest demand of each origin node.

Transit-Based Emergency Evacuation Simulation Modeling

Abstract: Several recent mass evacuations, including those in advance of Hurricane Katrina in New Orleans and Hurricane Rita in Houston, have demonstrated the effects of limited planning for carless populations. The lack of planning left a significant portion of the mobility-limited population of both these cities unable to flee in advance of the storms. Since 2005, however, both of these cities (as well as others across the United States) have developed transit-assisted mass evacuation plans at various levels of detail. Because these plans are relatively recent and do not have a history of experience on which to base their performance, it is difficult to know how well, or even if, they will work. This article describes one of the first attempts to systematically model and simulate transit-based evacuation strategies. In it, the development of and the results gained from an application of the TRansportation ANalysis and SIMulation System (TRANSIMS) agent-based transportation simulation system to model assisted evac...

Curve Collisions: Road and Collision Characteristics and Countermeasures

Abstract: Horizontal curves are relatively dangerous portions of roadway networks. Agencies optimizing the use of safety funds should be aware of characteristics of the collisions on those segments. However, few previously published articles attempted to characterize collisions on horizontal curves. This article describes an effort that characterized collisions reported to be on curves in North Carolina using the Highway Safety Information System. More than 51,000 North Carolina (NC) collisions on two-lane road curves were compared to collisions on all two-lane roads and on all roads. In doing so we gained a perspective of how well various curves perform relative to other road areas. We investigated numerous two-lane curve-collision types. Those most overrepresented included: collisions on grades, rural, severe injury or fatal, fixed object (particularly tree, ditch, and embankment), overturn, off-peak hours (particularly during darkness on unlighted roads), weekend, holiday periods, and wet, icy, or snowy pavement. The analysis also revealed that there were few short roadway segments (of 0.1- to 1-mile length) with more than 10 reported curve collisions in 3 years. This article provides recommendations from the literature to treat overrepresented collision types on horizontal curves. Based on the analysis findings, agencies should target countermeasures for the most common and overrepresented collision types.