Traffic congestion | EPFL Graph Search

Traffic congestion is a condition in transport that is characterized by slower speeds, longer trip times, and increased vehicular queueing. Traffic congestion on urban road networks has increased substantially since the 1950s. When traffic demand is great enough that the interaction between vehicles slows the traffic stream, this results in congestion. While congestion is a possibility for any mode of transportation, this article will focus on automobile congestion on public roads. As demand approaches the capacity of a road (or of the intersections along the road), extreme traffic congestion sets in. When vehicles are fully stopped for periods of time, this is known as a traffic jam or (informally) a traffic snarl-up or a tailback. Drivers can become frustrated and engage in road rage. Drivers and driver-focused road planning departments commonly propose to alleviate congestion by adding another lane to the road. This is ineffective: increasing road capacity induces more dem

Spatial and Temporal Analysis of Congestion in Urban Transportation Networks

Yuxuan Ji

Research on congestion and propagation in large urban city networks has been mainly based on microsimulations of link-level traffic dynamics. However, both the unpredictability of travel behaviors and high complexity of accurate physical modeling remain challenging and simulation results may be far time consuming and not realistic. It has been recently shown that amacroscopic fundamental diagram (MFD) linking space-mean network flow, density and speed exists in the urban transportation networks under some conditions. An MFD is further well defined if the network is homogeneous with links of similar properties. This collective behavior concept can also be utilized to introduce simple control strategies to improve mobility in homogeneous city centers without the need for details in individual links. However many real urban transportation networks are heterogeneous with different levels of congestion. In order to study the existence of MFD and the feasibility of simple control strategies to improve network performance in heterogeneously congested networks, this thesis mainly focuses on three issues: (1) static partitioning of traffic networks, (2) congestion propagation and dynamic partitioning, and (3) the effect of network structure on congestion propagation. Firstly, we study the static partitioning of transportation networks based on the spatial features of congestion during a specific time period. A partitioning mechanism which consists of three consecutive algorithms, is designed to minimize the variance of link densities while maintaining the spatial compactness of the clusters. Secondly we explore the dynamics of traffic conditions and thus the corresponding dynamic partitioning scheme. We reveal the hidden information during the process of congestion formation by exploring empirical data from large-scale urban networks. Specifically, we aim at studying the spatiotemporal relation of congested links, observing congestion propagation from an macroscopic perspective, and finally identifying critical congestion regimes to aid the design of peripheral control strategies. Finally, we study the formation of traffic congestion by simulation in large scale cities with different network structures. A parsimonious model of congestion propagation is developed and validated by real data in San Francisco in US and Shenzhen in China (20000 taxis with 30 million logs per day). The effect of network structure on congestion propagation is investigated by simulations conducted in a variety of network structures.

EPFL2014

City size, network structure and traffic congestion

Nikolaos Geroliminis

This paper presents an alternative approach for analyzing the relationship between land use and traffic congestion by employing the Macroscopic Fundamental Diagram (MFD). The MFD is an empirically observed relationship between traffic flow and traffic density at the level of an urban region, including hypercongestion, where flow decreases as density increases. This approach is consistent with the physics of traffic and allows the parsimonious modeling of intra-day traffic dynamics and their connection with city size, land use and network characteristics. The MFD can accurately measure the inefficiency of land and network resource allocation due to hypercongestion, in contrast with existing models of congestion. The findings reinforce the 'compact city' hypothesis, by favoring a larger mixed-use core area with greater zone width, block density and number of lanes, compared to the peripheral area. They also suggest a new set of policies, including the optimization of perimeter controls and the fraction of land for transport, which constitute robust second-best optimal strategies that can further reduce congestion externalities. (C) 2013 Elsevier Inc. All rights reserved.

Elsevier2013

Modeling and Optimization of Dedicated Bus Lane network design under dynamic traffic congestion

Nikolaos Geroliminis, Anastasios Kouvelas, Dimitrios Tsitsokas

Collective transport has been seen for long as a proper solution to fight congestion. While collectivity has been successful with respect to subways, it is not the norm in road traffic. Dedicated Bus Lanes (DBL) have been proposed as a measure to reduce the impact of traffic congestion in the travel time and accuracy of buses, by providing them with exclusive road space. However, DBL presence decreases road capacity, which may induce local congestion. Balancing this inherent trade-off of a DBL network, by carefully selecting the location of DBLs while considering the dynamics of congestion propagation is challenging. This work aims at finding a reliable modeling and optimization methodology to address this problem. An adjusted version of Store-and-Forward queuing model and microscopic simulation are used to simulate the traffic dynamics in presence of DBLs and assess the global network performance, while a local search algorithm is used to improve some state-of-practice solutions.

2019

Spatial and Temporal Analysis of Congestion in Urban Transportation Networks

Yuxuan Ji

EPFL2014