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Cycling provides an important alternative to environmental-friendly transportation modes in urban areas. However, cyclists are vulnerable road users and often suffer severe injuries once crashes occur, which has impeded the growth of bicycle uses. Identification of factors that influence injury severities of crashes involving cyclists can help policy-makers form efficient strategies to mitigate crashes. Moreover, crashes involving cyclists at daytime and nighttime are very likely to present different patterns. Hence, the objective of this study is to explore the underlying factors to injury severity in crashes involving cyclists in the daytime and nighttime separately. Mixed logit model approach is employed due to its advantage of accounting for heterogeneity in observations and four factors are found to have random effects in the mixed logit model for daytime. The differences of crash mechanisms at daytime and nighttime are discussed, and the results of this research would help to develop effective policies that aim to mitigate the injury severities of cyclists while promoting the use of bicycles.

Connected and autonomous vehicle (CAV) technologies are expected to improve the quality of intersection operations through Vehicle-to-Infrastructure (V2I) and Infrastructure-to-Vehicle (I2V) commun...

Public transit is a critical component of transportation planning. One important task is to optimize the public transit service for people by improving current service or having new investm...

This study models and evaluates the accessibility to public transit and public transit equity by integrating the general transit feed specification (GTFS) data. A transit gap index (TGI) an...

Recurrent bottlenecks in the urban rail transit (URT) system during rush hours have become a significant concern for both passengers and URT operators. In order to alleviate the resulting p...

Cycling is a healthier and greener travel mode that city planners and policymakers have encouraged for short-distance trips. Because cycling provides an efficient way to improve public heal...

Route choice behavior of a rail transit passenger is not directly observable and it may be affected by the route travel time to a large extent. Compared to the on-train time, travel times a...

With the increases in both the urban rail transit (URT) network scale and complexity, a route choice model that was previously developed may not function properly anymore and therefore must...

This study investigates factors that significantly contribute to the severity of driver injuries resulting from single-vehicle run-off-road (SV ROR) crashes. A mixed logit model approach is employed to explore the potential unobserved heterogeneous effects associated with each age group: young (ages 16-24), middle-aged (ages 25-65), and older drivers (ages over 65). Likelihood ratio tests indicated that the development of separate injury severity models for each age group is statistically superior to estimating a single model using all data. Based on the crash data collected from 2009 to 2013 in North Carolina, a series of driver, vehicle, roadway, and environmental characteristics are examined. Both parameter estimates and their elasticities are developed and used to interpret the models. The estimation results show that contributing factors which significantly affect the injury severity of an SV ROR crash differ across three age groups. Use of restraint device and horizontal curves are found to affect crash injuries and fatalities in all age groups. Reckless driving, speeding, distraction, inexperience, drug or alcohol involvement, presence of passengers, and driving an SUV or a van are found to have a more pronounced influence in young and middle-aged drivers than older drivers. Compared to the passenger cars, older drivers are less likely to experience possible injuries in a large-size vehicle (e.g., truck or bus). The average annual daily traffic volume and lighting conditions are also found to influence the resulting injury severity of an SV ROR crash specific to young drivers.