Road pricing is advocated as an effective travel demand management strategy to alleviate
traffic congestion and improve environmental conditions. This paper analyzes the impacts of …

基于第260 期“双清论坛”, 本文分析了大数据和人工智能时代政策信息学与政策智能发展的国家
重大需求, 围绕着政策决策建模与效果评估, 总结了“复杂政策决策场景建模 …

Abstract Spatial Data Intelligence (SDI) encompasses acquiring, storing, analyzing, mining,
and visualizing spatial data to gain insights into the physical world and uncover valuable …

Simulation plays a crucial role in transportation studies. However, most simulation tools are
individually developed to tackle specific transportation problems, making it challenging to …

Understanding the holistic city-wide impact of planned transportation solutions and
interventions is critical for decision making, but challenged by the complexity of the urban …

Road network pricing and congestion charging continue to be debated as efficient
instruments to address traffic congestion and emissions. For cities where the schemes have …

Abstract The classic Dial-A-Ride Problem (DARP) aims at designing the minimum-cost
routing that accommodates a set of user requests under constraints at an operations …

Agent-based models have been an emerging approach in epidemiological modelling,
specifically in investigating the COVID-19 virus. However, there are challenges to its …

Transportation Network Companies (TNC), like Uber, Lyft, and VIA, started their activities a
decade ago with a far-reaching hope that Mobility-On-Demand (MOD) transportation …

The purpose of this review is to present the different facets of multi-agent systems (MAS) with
an accent on their two main areas: MAS for developing decentralized systems and MAS for …