A Genetic Algorithm Approach for Optimizing Traffic Control Signals Considering Routing

Abstract:   It is well known that coordinated, area-wide traffic signal control provides great potential for improvements in delays, safety, and environmental measures. However, an aspect of this problem that is commonly neglected in practice is the potentially confounding effect of drivers re-routing in response to changes in travel times on competing routes, brought about by the changes to the signal timings. This article considers the problem of optimizing signal green and cycle timings over an urban network, in such a way that the optimization anticipates the impact on traffic routing patterns. This is achieved by including a network equilibrium model as a constraint to the optimization. A Genetic Algorithm (GA) is devised for solving the resulting problem, using total travel time across the network as an illustrative fitness function, and with a widely used traffic simulation-assignment model providing the equilibrium flows. The procedure is applied to a case study of the city of Chester in the UK, and the performance of the algorithms is analyzed with respect to the parameters of the GA method. The results show a better performance of the signal timing as optimized by the GA method as compared to a method that does not consider rerouting. This improvement is found to be more significant with a more congested network whereas under a relatively mild congestion situation the improvement is not very clear.     

Design of Sustainable Cordon Toll Pricing Schemes in a Monocentric City

This paper addresses the design issue of sustainable cordon toll pricing schemes in a monocentric city. An analytical model that maximizes the total social welfare of urban system is first proposed for simultaneous optimization of the cordon toll location and charge level. The solution properties of the model with/without considering traffic congestion and/or environmental effects are explored and compared analytically. The proposed model is then extended to explicitly incorporate the effects of subsidizing the retrofit of old vehicles on reduction in average vehicle emissions. The optimal subsidy scheme for maximizing the social welfare of the system is also determined. Finally, a numerical example is given to illustrate the model applications. Insightful findings are reported on the interrelationships among cordon toll scheme, traffic congestion and environmental effects, urban population distribution, and subsidy scheme as well as their implications in practice.     

The use of natural rubber latex as a renewable and sustainable modifier of asphalt binder

Natural rubber (NR) powder as a bio-modifier of asphalt binder has been shown to have some beneficial effects. However, there is limited research into the use of the liquid form of NR, i.e. concentrated NR latex, as an asphalt binder modifier. Compared to NR powder, NR latex is cheaper and more accessible in some countries, and potentially creates viscosity-reducing foams in the modified binder during mixture production. In this research, asphalt binders modified with different amount of NR latex were systematically studied, including the rotational viscosities, rutting resistance, fatigue resistance, low-temperature behaviour and temperature sensitivity. The dispersion of the NR latex in the modified binders was examined using fluorescence microscope and atomic force microscope. Test results indicate that the addition of NR latex increases the viscosity and elastic recovery of the modified binders and potentially enhances asphalt pavements’ resistance to rutting, thermal cracking and fatigue damage. The NR latex also reduces the temperature sensitivity of the modified binders. The optimum NR latex content was found to be 7% of the total mass of the modified binder. A network of extensive microstructures mixed with bubbles was identified in the modified binders under heat. As a renewable and sustainable material, NR latex has the potential to be used as an effective asphalt modifier.     

A Genetic Algorithm Based Approach to Optimal Toll Level and Location Problems

The derivative based approach to solve the optimal toll problem is demonstrated in this paper for a medium scale network. It is shown that although the method works for most small problems with only a few links tolled, it fails to converge for larger scale problems. This failure led to the development of an alternative genetic algorithm (GA) based approach for finding optimal toll levels for a given set of chargeable links. A variation on the GA based approach is used to identify the best toll locations making use of location indices suggested by Verhoef (2002).     

Finding Reliable Shortest Paths in Road Networks Under Uncertainty

The aim of this study is to investigate the solution algorithm for solving the problem of determining reliable shortest paths in road networks with stochastic travel times. The availability of reliable shortest paths enables travelers, in the face of travel time uncertainty, to plan their trips with a pre-specified on-time arrival probability. In this study, the reliable shortest path between origin and destination nodes is determined using a multiple-criteria shortest path approach when link travel times follow normal distributions. The dominance conditions involved in such problems are established, thereby reducing the number of generated non-dominated paths during the search processes. Two solution algorithms, multi-criteria label-setting and A* algorithms, are proposed and their complexities analyzed. Computational results using large scale networks are presented. Numerical examples using data from a real-world advanced traveller information system is also given to illustrate the applicability of the solution algorithms in practice.     

Optimal Road User Charging Cordon Design: A Heuristic Optimization Approach

Abstract:   This article addresses the optimal design problem of selecting a charging cordon in a general traffic network. A charging cordon is a set of tolled links surrounding a designated area so that all travelers entering or passing through this area will be tolled. Travelers in the network are assumed to respond to the tolls imposed by adjusting their behaviors to achieve a new equilibrium following Wardrop's equilibrium condition. The necessity of this equilibrium condition is imposed as one of the constraints in the optimal charging cordon design problem. This problem can be categorized as a Mathematical Program with Equilibrium Constraints (MPEC). This article presents an innovative Genetic Algorithm (GA) based method to tackle the problem. A new framework, called branch–tree framework, is developed to represent a closed charging cordon so that the method of GA can be used. The method is tested with a network of Edinburgh. Although the proposed algorithm is a heuristic-based method, the optimization result in the test is very promising. The optimal closed charging cordon as found by the algorithm produces a significantly higher benefit than that of judgmental cordons .     

A Study on Network Design Problems for Multi-modal Networks by Probit-based Stochastic User Equilibrium

This paper develops a multi-modal transport network model considering various travel modes including railway, bus, auto, and walking. Travellers are assumed to choose their multi-modal routes so as to minimise their perceived disutilities of travel following the Probit Stochastic User Equilibrium (SUE) condition. Factors influencing the disutility of a multi-modal route include actual travel times, discomfort on transit systems, expected waiting times, fares, and constants specific to transport modes. The paper then deals with the multi-modal network design problem (NDP). The paper employs the method of sensitivity analysis to define linear approximation functions between the Probit SUE link flows and the design parameters, which are then used as constraints in the sub-problem of the NDP instead of the original SUE condition. Based on this reformulated NDP, an efficient algorithm for solving the problem is proposed in the paper. Two instances of this general NDP formulation are then presented in the paper: the optimal frequency design problem for public transport services (FDP), and the anti-freezing admixture dispersion problem (AADP).     

Network Capacity Reliability Analysis Considering Traffic Regulation after a Major Disaster

The focuses of this paper are optimal traffic regulation after a major disaster and evaluation of capacity reliability of a network. The paper firstly discusses the context of traffic regulation and its importance after a major disaster. Then, this problem is formulated as an optimisation program in which the traffic regulator attempts to regulate the amount of traffic movements or access to some areas so as to maximise the traffic volumes in the network while (a) link flows must be less than link capacities and (b) re-routing effect due to changes of traffic condition in the network is allowed. The re-routing behaviour is assumed to follow Probit Stochastic User's Equilibrium (SUE). The paper explains an optimisation algorithm based on an implicit programming approach for solving this problem with the SUE condition. With this optimisation problem, the randomness of the link capacities (to represent random effects of the disaster) is introduced and the paper describes an approach to approximate the capacity reliability of the network using Monte-Carlo simulation. The paper then adopts this approach to evaluate the performances of different traffic regulation policies with a small network and a test network of Kobe city in Japan.