Benefiting from opportunities offered by connected and autonomous vehicles (CAVs), a concept called Combined Alternate-Direction Lane Assignment and Reservation-based Intersection Control (CADLARIC) was proposed recently for management of directionally unrestricted traffic flows in urban environments. In CADLARIC, resolution of vehicular conflicts is distributed between links and intersections to prevent intersections from turning into traffic bottlenecks. Although CADLARIC has shown promising results, it has been observed that, once traffic volume on a certain lane reaches “physical capacity,” adding more traffic on that lane degrades performance of the entire system, as each lane is exclusively dedicated to a particular movement. To overcome this problem, Combined Flexible Lane Assignment and Reservation-based Intersection Control (CFLARIC) is proposed, which offers more flexible lane assignment possibilities. While CFLARIC allows left- and right-turning lanes to be shared with through traffic, it is unclear how much through traffic should be assigned to turning lanes. Thus, this study investigates which strategy is the most beneficial when reassigning extra through traffic to the turning lanes. This goal is divided into two objectives: 1. Identify which lanes should be shared, and 2. Find a close-to-optimal amount of through traffic that should be assigned to the identified shared lane. The proposed CFLARIC strategies are compared with Fixed-Time Control (FTC), Full Reservation-based Intersection Control (FRIC), and CADLARIC for multiple demand scenarios. The results show that the best performing CFLARIC strategies outperform FTC, FRIC, and CADLARIC for delay and number of stops, and reduce the number of conflicting situations compared with FRIC and CADLARIC.
Work zones are prevalent in the United States as the infrastructure is increasingly in need of maintenance. Lack of reliable data is one of the main obstacles in work zone research. Reliability suffers because of underreporting of crashes and inclusion in the analysis of irrelevant activities that are not attributable to work zones. In addition, the work zone environment is very dynamic, resulting in differing reasons for crashes. These are barriers to gaining an accurate understanding of safety in work zones. The objective of this paper is to design, develop, and deploy a mobile application (app) for real-time work zone data collection to address these issues. The development process consisted of the following steps. First, a user interface was designed to enable users to collect various work zone activity information. Second, taking advantage of recent advances in cloud computing, a real-time database was designed for efficient storage and instantaneous communication of work zone activity data. Field tests were then conducted at 13 work zone sites in Columbia, Missouri. Finally, the performance of the app was evaluated based on scalability, precision, and user friendliness. The app was able to respond to queries at real-time speeds even as the size of the database and the number of users increased. The precision of sensors was within appreciable accuracy for the geolocation. The app’s user friendliness was acknowledged by the users. The successful deployment of this mobile app would lead to accurate work zone data which is very useful for work zone management, traveler information, contract monitoring, safety analysis, and project coordination.
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