Online Calibration of Microscopic Road Traffic Simulator

Microscopic road traffic simulator is a powerful tool to analyze and evaluate various transportation systems due to its efficiency and risk-free operation. It is, therefore, widely used in traffic engineering field along with the gradual implementation of novel intelligent transportation systems. A reliable microscopic traffic simulator is able to accurately represent the real-world traffic situation when it is effectively calibrated with the combination of field data and proper simulation settings. Based on the existing theoretical calibration framework for the microscopic traffic simulator, this paper proposes an online calibration procedure using genetic algorithm as well as a specific implementation method to provide real-time performance measures that adequately mimic the field traffic situation. The proposed method was tested based on loop detector data demonstrating that real-time traffic modeling can be run in parallel with the real-world traffic process

An agent-based approach to assess drivers’ interaction with pre-trip information systems.

This article reports on the practical use of a multi-agent microsimulation framework to address the issue of assessing drivers’ responses to pretrip information systems. The population of drivers is represented as a community of autonomous agents, and travel demand results from the decision-making deliberation performed by each individual of the population as regards route and departure time. A simple simulation scenario was devised, where pretrip information was made available to users on an individual basis so that its effects at the aggregate level could be observed. The simulation results show that the overall performance of the system is very likely affected by exogenous information, and these results are ascribed to demand formation and network topology. The expressiveness offered by cognitive approaches based on predicate logics, such as the one used in this research, appears to be a promising approximation to fostering more complex behavior modelling, allowing us to represent many of the mental aspects involved in the deliberation process

Assessment of traffic impact on future cooperative driving systems: challenges and considerations

Connect & Drive is a start-up project to develop a cooperative driving system and improve the traffic performance on Dutch highways. It consists of two interactive subsystems: cooperative adaptive cruise control (CACC) and connected cruise control (CCC). To assess the traffic performance, a traffic simulation model will be established for large-scale evaluation and providing feedbacks to system designs. This paper studies the factors determining the traffic performance and discusses challenges and difficulties to establish such a traffic simulation model