A heuristic methodology to tackle the Braess Paradox detecting problem tailored for real road networks

Adding a new road to help traffic flow in a congested urban network may at first appear to be a good idea. The Braess Paradox (BP) says, adding new capacity may actually worsen traffic flow. BP does not only call for extra vigilance in expanding a network, it also highlights a question: Does BP exist in existing networks? Literature reveals that BP is rife in real world. This study proposes a methodology to find a set of roads in a real network, whose closure improve traffic flow. It is called the Braess Paradox Detection (BPD) problem. Literature proves that the BPD problem is highly intractable especially in real networks and no efficient method has been introduced. We developed a heuristic methodology based on a Genetic Algorithm to tackle BPD problem. First, a set of likely Braess-tainted roads is identified by simply testing their closure (one-by-one). Secondly, a seraph algorithm is devised to run over the Braess-tainted roads to find a combination whose closure improves traffic flow. In our methodology, the extent of road closure is limited to some certain level to preserve connectivity of the network. The efficiency and applicability of the methodology are demonstrated using the benchmark Hagstrom–Abrams network, and on a network of city of Winnipeg in Canada

Dynamic Traffic Network Model and Time-Dependent Braess’ Paradox

We propose a dynamic traffic network model and give the equilibrium condition and the equivalent variational inequality of the network. In this model, instead of the influence of inflow rate and output rate on the link congestion, the influence of the adjacent links at the same paths is considered; in this case, the equivalence between the equilibrium condition and the variational inequality is proved. Then we take an example about the paradox using the variational inequality and find that the probability and the severity that Braess’ paradox occurs change with the influence of other links changing. Subsequently, we discuss the influence of other links on whether the adding link works under the dynamic system optimal. At last, we give the relationship between the total congestion under dynamic user equilibrium and that under dynamic system optimal. The results imply that we should take some methods and adjust the interaction between links rationally with the dynamic change of traffic situations

ANALYSING THE CAPACITY OF A TRANSPORTATION NETWORK. A GENERAL THEORETICAL APPROACH

Estimation of transportation network capacity is important in analysing network performance. In the existing literature, the capacity of a network is defined in conditional terms as a theoretical construct called “reserve capacity”. This may be limited because, when considering local land-use development, the hypothetical uniform increase in O-D flows is not always realistic. This paper, introducing the concept of “capacity function”, proposes a generalized concept of road network capacity which does not require information on either current O-D demand or the corresponding growth trend. Attention focuses on deterministic and stationary situations in which only one path is available for each O-D pair. Some examples regarding simple study cases demonstrate the capacity of this approach to solve problems and, consequently, to contribute to the analysis of network performance

Bridging the user equilibrium and the system optimum in static traffic assignment: a review

Solving the road congestion problem is one of the most pressing issues in modern cities since it causes time wasting, pollution, higher industrial costs and huge road maintenance costs. Advances in ITS technologies and the advent of autonomous vehicles are changing mobility dramatically. They enable the implementation of a coordination mechanism, called coordinated traffic assignment, among the sat-nav devices aiming at assigning paths to drivers to eliminate congestion and to reduce the total travel time in traffic networks. Among possible congestion avoidance methods, coordinated traffic assignment is a valuable choice since it does not involve huge investments to expand the road network. Traffic assignments are traditionally devoted to two main perspectives on which the well-known Wardropian principles are inspired: the user equilibrium and the system optimum. User equilibrium is a user-driven traffic assignment in which each user chooses the most convenient path selfishly. It guarantees that fairness among users is respected since, when the equilibrium is reached, all users sharing the same origin and destination will experience the same travel time. The main drawback in a user equilibrium is that the system total travel time is not minimized and, hence, the so-called Price of Anarchy is paid. On the other hand, the system optimum is an efficient system-wide traffic assignment in which drivers are routed on the network in such a way the total travel time is minimized, but users might experience travel times that are higher than the other users travelling from the same origin to the same destination, affecting the compliance. Thus, drawbacks in implementing one of the two assignments can be overcome by hybridizing the two approaches, aiming at bridging users’ fairness to system-wide efficiency. In the last decades, a significant number of attempts have been done to bridge fairness among users and system efficiency in traffic assignments. The survey reviews the state-of-the-art of these trade-off approaches

Compound Impact on Private and Public Transport Network Performance on Integration of New Forms of Mobility

Continued evolutions in autonomous drive technologies and pandemic leading to a boom in micro-mobility usage make these new forms of mobility an integral part of investigative research to assess their impacts on transportation networks. This research thesis examines their impacts in terms of: quantification of the penetration rate of autonomous vehicles (AVs), the influence of physical characteristics of the urban road network on macroscopic fundamental parameters in heterogeneous traffic stream, inequities in travel costs equilibrium, assessment of public transport (PuT) network vulnerability against random service disruptions and importance of topography for accurate provision of micro-mobility services. Some benefits for 25-35% inclusion of AVs include enhanced network capacity, improvement in travel time, decrement in travel equilibrium costs. Whereas, the integrated micro-mobility modes reduce the commuter’s dis-utility and perceived journey times by 7.14% in case of disruptions. However, the spill-over effects are to watch out for

System optimal traffic assignment with departure time choice

This thesis investigates analytical dynamic system optimal assignment with departure time choice in a rigorous and original way. Dynamic system optimal assignment is formulated here as a state-dependent optimal control problem. A fixed volume of traffic is assigned to departure times and routes such that the total system travel cost is minimized. Although the system optimal assignment is not a realistic representation of traffic, it provides a bound on performance and shows how the transport planner or engineer can make the best use of the road system, and as such it is a useful benchmark for evaluating various transport policy measures. The analysis shows that to operate the transport system optimally, each traveller in the system should consider the dynamic externality that he or she imposes on the system from the time of his or her entry. To capture this dynamic externality, we develop a novel sensitivity analysis of travel cost. Solution algorithms are developed to calculate the dynamic externality and traffic assignments based on the analyses. We also investigate alternative solution strategies and the effect of time discretization on the quality of calculated assignments. Numerical examples are given and the characteristics of the results are discussed. Calculating dynamic system optimal assignment and the associated optimal toll could be too difficult for practical implementation. We therefore consider some practical tolling strategies for dynamic management of network traffic. The tolling strategies considered in this thesis include both uniform and congestion-based tolling strategies, which are compared with the dynamic system optimal toll so that their performance can be evaluated. In deriving the tolling strategies, it is assumed that we have an exact model for the underlying traffic behaviour. In reality, we do not have such information so that the robustness of a toll calculation method is an important issue to be investigated in practice. It is found that the tolls calculated by using divided linear traffic models can perform well over a wide range of scenarios. The divided linear travel time models thus should receive more attention in the future research on robust dynamic traffic control strategies design. In conclusion, this thesis contributes to the literature on dynamic traffic modelling and management, and to support further analysis and model development in this area