Jakarta, the economic hub of Indonesia, faces significant air pollution challenges exacerbated by meteorological factors. This study proposes applying Fuzzy Geographically Weighted Clustering (FGWC) combined with Coot Bird Optimization (CBO) to evaluate the vulnerability of air quality in...

Ride-hailing applications create new challenges for governments providing transit services, but also create new opportunities to raise tax revenue. To shed light on the effect of taxing or subsidizing ride-hailing applications, we extend a pseudo-monocentric city model to include multiple...

Time scarcity is one of the strongest correlates of fast food consumption. To estimate the causal effect of time lost on food choice, we match daily store-specific foot traffic data traced via smartphones to plausibly exogenous shocks in highway traffic data in Los Angeles. We find that on days...

This paper proposes a game-theoretic model to analyze the strategic behavior of inc-dec gaming in market-based congestion management (redispatch). We extend existing models by considering incomplete information about competitors’ costs and a finite set of providers. We find that inc-dec gaming...

Traffic congestion in urban centers not only hampers mobility but also significantly impacts economic activities and environmental sustainability. This study leverages advanced machine learning techniques to analyze and predict traffic jams, utilizing a detailed dataset of 9847 recorded accident...

Traffic congestion (TC) disrupts everyday life, elevating stress levels, extending commute durations, diminishing productivity, hampering air quality, and reducing the overall quality of life. Congestion exacerbates already-existing problems in densely populated cities and makes efficient urban...

The urban transportation system is vital for efficient daily travel. Understanding how urban road network density and width influence traffic performance is crucial for informed decision-making in urban planning. In this study, we designed three homogeneous square road networks with varying...

We implement Pigovian transport pricing in a field experiment in urban agglomerations of Switzerland over the course of 8 weeks. Our pricing considers the external costs from climate damages, health outcomes from pollution, accidents and physical activity, and congestion. It varies across time,...

Although there is ample empirical evidence that congestion charges can effectively reduce traffic congestion and its detrimental effects, this instrument has only been implemented in a handful European cities. On the basis of a randomized information experiment that was embedded in a survey...

In September 2021, the city of Bogota' introduced a major market-based reform to its odd-even driving restriction, known as Pico y Placa. Since then, drivers have had the option to pay a daily congestion fee to be exempt from the restriction. We find t hat while the reform increased traffic, it...

We study how preference heterogeneity affects travel behavior and congestion pricing in a dynamic flow congestion model. We formulate and solve a multi-point optimal control problem using a Hamiltonian-based method to derive the social optimum. The properties of the travel equilibrium are...

Purpose This paper seeks to evaluate the factors that contribute to congestion at port entrances, propose a comprehensive approach to managing port gates that addresses the factors causing traffic jams and assess the outcomes of resolving the issue through an optimal model for incoming container...

Background: Container terminals (CTs) have constantly administered truck appointment systems (TASs) to effectively accomplish the planning and scheduling of drayage operations. However, since the operations in the gate and yard area of a CT are stochastic, there is a need to incorporate...

We implement Pigovian transport pricing in a field experiment in urban agglomerations of Switzerland over the course of 8 weeks. The pricing considers external costs from climate damages, health outcomes and congestion and varies across time, space and mode of transport. The treatment reduces...

This paper explores how the interaction between human-driven vehicles (HVs) cruising for parking and autonomous vehicles (AVs) traveling back and forth affects travel behavior and congestion. To capture the spatial distribution of parking, we develop a continuous spatial optimization model, with...

Analyzing the flow of vehicles within a metropolitan area is essential to understand traffic congestion better and evaluate urban mobility for more environmentally and sustainable targets. This study uses real-time big data to conduct a spatiotemporal analysis of traffic congestion patterns in...

Background: This paper introduces an enhanced multi-period p-mobile hub location model that accounts for critical factors such as service time, flow processing delays, and congestion impacts at capacity-constrained hubs. As (urban) transportation networks evolve, mobile hubs play an increasingly...

Predicting freeway traffic states is, so far, based on predicting speeds or traffic volumes with various methodological approaches ranging from statistical modeling to deep learning. Traffic on freeways, however, follows specific patterns in space-time, such as stop-and-go waves or mega jams....