Perceived risk of using shared mobility services during the COVID-19 pandemic.

The COVID-19 pandemic has caused our daily routines to change quickly. The pandemic provokes public fear, resulting in changes in what modes of transport people use to perform their daily activities. It is imperative for transportation authorities to properly identify the different degrees of behavioral change among various social groups. A major factor that can substantially explain individuals' behavioral changes is the personal risk perceptions toward using shared mobility solutions. Thus, this study explores the risk that individuals perceive while using public transit and ridesharing services (as the most widespread forms of shared mobility) during the COVID-19 pandemic. To do so, we designed and implemented a multidimensional travel-behavior survey in the Chicago metropolitan area that comprises socio-demographic information and retrospective questions related to attitudes and travel behavior before and during the pandemic. Utilizing a bivariate ordered probit modeling approach to better account for the potential correlation between unobserved factors, we simultaneously modeled the perceived risk of exposure to the novel coronavirus in case of riding transit and using ridesharing services. A wide range of factors is found to be influential on the perceived risk of using shared mobility services, including the socio-demographic attributes, built environment settings, and the virus spread. Further, our results indicate that the mitigation strategies to increase the ridership of shared mobility services should be adaptive considering the spatial variations.

How is COVID-19 reshaping activity-travel behavior? Evidence from a comprehensive survey in Chicago.

The novel COVID-19 pandemic has caused upheaval around the world and has led to drastic changes in our daily routines. Long-established routines such as commuting to workplace and in-store shopping are being replaced by telecommuting and online shopping. Many of these shifts were already underway for a long time, but the pandemic has accelerated them remarkably. This research is an effort to investigate how and to what extent people's mobility-styles and habitual travel behaviors have changed during the COVID-19 pandemic and to explore whether these changes will persist afterward or will bounce back to the pre-pandemic situation. To do so, a stated preference-revealed preference (SP-RP) survey is designed and implemented in the Chicago metropolitan area. The survey incorporates a comprehensive set of questions associated with individuals' travel behaviors, habits, and perceptions before and during the pandemic, as well as their expectations about the future. Analysis of the collected data reveals significant changes in various aspects of people's travel behavior. We also provide several insights for policymakers to be able to proactively plan for more equitable, sustainable, and resilient cities.

Wrong-way driving crashes: A random-parameters ordered probit analysis of injury severity.

In the context of traffic safety, whenever a motorized road user moves against the proper flow of vehicle movement on physically divided highways or access ramps, this is referred to as wrong-way driving (WWD). WWD is notorious for its severity rather than frequency. Based on data from the U.S. National Highway Traffic Safety Administration, an average of 355 deaths occur in the U.S. each year due to WWD. This total translates to 1.34 fatalities per fatal WWD crashes, whereas the same rate for other crash types is 1.10. Given these sobering statistics, WWD crashes, and specifically their severity, must be meticulously analyzed using the appropriate tools to develop sound and effective countermeasures. The objectives of this study were to use a random-parameters ordered probit model to determine the features that best describe WWD crashes and to evaluate the severity of injuries in WWD crashes. This approach takes into account unobserved effects that may be associated with roadway, environmental, vehicle, crash, and driver characteristics. To that end and given the rareness of WWD events, 15 years of crash data from the states of Alabama and Illinois were obtained and compiled. Based on this data, a series of contributing factors including responsible driver characteristics, temporal variables, vehicle characteristics, and crash variables are determined, and their impacts on the severity of injuries are explored. An elasticity analysis was also performed to accurately quantify the effect of significant variables on injury severity outcomes. According to the obtained results, factors such as driver age, driver condition, roadway surface conditions, and lighting conditions significantly contribute to the injury severity of WWD crashes.