Multimodal Intelligent Traffic Signal System Simulation Model Development and Assessment

Abstract

The study demonstrated the multimodal intelligent traffic signal system (MMITSS) simulation tool to assess the potential effects of a broader MMITSS deployment that would ultimately facilitate the site-independent analysis of MMITSS applications. The study also identified the most beneficial operational conditions for each MMITSS operational scenario by considering a combination of simulation variables and traffic demand levels. The MMITSS simulation platform consists of the Vissim microscopic traffic simulation software, the basic safety message distributor program, an Econolite ASC/3 traffic controller emulator that runs on a Windows platform, and a roadside equipment module that runs on a Linux platform. The study demonstrated that the intelligent traffic signal system reduced vehicle delay by up to 35% and increased average traffic stream speed by up to 27%. In addition, transit signal priority (TSP) reduced travel time for both transit and passenger vehicles on the corridor by up to 29% and 28%, respectively. However, TSP can increase systemwide delay because it reduces green times on the side streets. Freight signal priority (FSP) can be used effectively along major freight routes. Although FSP significantly reduced truck delay, networkwide delay was increased substantially, especially in the scenario with a large percentage of trucks in the traffic composition. The TSP and FSP bundle simulation study demonstrated that the bundle operation successfully executed a hierarchical level of priority and provided higher priority for trucks. MMITSS applications effectively improve vehicle travel time and delay for equipped and potentially nonequipped vehicles, depending on the scenarios considered. Typically, systemwide disbenefits are observed when TSP, FSP, or both are applied.

Autonomous and Semi-Autonomous Intersection Management: A Survey

“…A recent study conducted by Chen et al [74] illustrated that the computational complexity should be factored in when it comes to algorithm design for intersection management. Even though the I-SIG system [75] in the study is robust in theory, it is subject to exploitation in practice when only a simplified version of the algorithm can be used due to computational limitation of the RSU. Therefore, security research should also extend to the design of an AIM algorithm.…”

Transit Priority Signal Control Scheme Considering the Coordinated Phase for Single-Ring Sequential Phasing Under Connected Vehicle Environment

“…L †(k) denotes the critical queue length of compression phase for the k th historical cycle. In summary, the maximum compression time of the phase is calculated by (6).…”

“…After more than 40 years of research, TSP has developed from the initial The associate editor coordinating the review of this manuscript and approving it for publication was Yuanguo Bi. manual priority to passive priority, active priority and realtime priority, and several valuable research results have been achieved [6].…”

Deployment and Testing of Optimized Autonomous and Connected Vehicle Trajectories at a Closed-Course Signalized Intersection

“…This creates many opportunities for improving the efficiency and safety of surface transportation. For example, the U.S. Department of Transportation Multimodal Intelligent Traffic Signal Systems (MMITSS) initiative aims to provide a comprehensive traffic information framework to service all modes of transportation in a connected vehicle environment ( 1 , 2 ).…”