Risk of Automated Driving: Implications on Safety and Productivity

Automated driving has been predicted to be transformational in improving safety and productivity on roads. However, there are several unknowns with regards to how drivers’ will interact with automated vehicles, especially at moments requiring manual resumption of vehicle control. This is a situation involving risk, and understanding the relationship of drivers’ attitudes and perception toContinue reading “Risk of Automated Driving: Implications on Safety and Productivity”

Integrating HTS and Social Media Data to Improve the Quality of OD Matrix

Collecting effective data is a fundamental step in developing transport networks and related research. Social media have become an emerging source of data for traffic analyses. In this study, we demonstrate that the function of a city influences the utility of social media data in travel demand models by generating models for eight US citiesContinue reading “Integrating HTS and Social Media Data to Improve the Quality of OD Matrix”

Investigating vehicle utilization patterns of carsharing users

Facing the growing demand for carsharing services, it is critical for operators to accurately predict users’ preferences on different vehicle types and their vehicle usage. This vehicle choice behavior involves choosing multiple vehicle types simultaneously and allocating continuous amounts of budget to the chosen vehicles. The recent developed multiple discrete-continuous extreme value (MDCEV) modeling frameworkContinue reading “Investigating vehicle utilization patterns of carsharing users”

Understanding vehicle selection behavior of carsharing users

To determine the most efficient allocation of resources within a carsharing program, it is critical to understand what factors affect the users’ behavior when selecting vehicles. This study attempts to investigate the importance of users’ attributes and fleet characteristics on choice set formation behavior in selecting vehicles using a Spatial Hazard Based Model (SHBM).  “HowContinue reading “Understanding vehicle selection behavior of carsharing users”

A Clustering Algorithm for Bi-Criteria Stop Location Design with Elastic Demand

The design of transit networks is a challenging task for transportation planners that span numerous often counter-intuitive considerations. Broadly, the Network Design Problem (NDP) can be approached through cost-benefit models that are capable of representing multiple aspects of system-wide behavior, such as travel demand, transit route location, traffic congestion, or service frequency.  In this study,Continue reading “A Clustering Algorithm for Bi-Criteria Stop Location Design with Elastic Demand”

Quantifying day-to-day evolution of travel choices in public transit systems

The day-to-day evolution of travel choices (e.g., departure time choice and mode choice) are impacted by various factors. Reliability of transport services is one of these factors, which significantly affects their attractiveness and further influences the travel demand. This study develops day-to-day models to explore how unreliability of public transit service affects the day-to-day evolutionContinue reading “Quantifying day-to-day evolution of travel choices in public transit systems”

On integrating carsharing and parking sharing services

Parking is one of the main concerns for carsharing users, since a user must park the car somewhere after each trip. If users are allowed to park the cars at paid parking spaces, there would be a parking fee incurred between the current and the next carsharing user. It is unfair to let either theContinue reading “On integrating carsharing and parking sharing services”