Calibration and validation of a shared space model: case study

Shared space is an innovative streetscape design that seeks minimum separation between vehicle traffic and pedestrians. Urban design is moving toward space sharing as a means of increasing the community texture of street surroundings. Its unique features aim to balance priorities and allow cars and pedestrians to coexist harmoniously without the need to dictate behavior. There is, however, a need for a simulation tool to model future shared space schemes and to help judge whether they might represent suitable alternatives to traditional street layouts. This paper builds on the authors’ previously published work in which a shared space microscopic mixed traffic model based on the social force model (SFM) was presented, calibrated, and evaluated with data from the shared space link typology of New Road in Brighton, United Kingdom. Here, the goal is to explore the transferability of the authors’ model to a similar shared space typology and investigate the effect of flow and ratio of traffic modes. Data recorded from the shared space scheme of Exhibition Road, London, were collected and analyzed. The flow and speed of cars and segregation between pedestrians and cars are greater on Exhibition Road than on New Road. The rule-based SFM for shared space modeling is calibrated and validated with the real data. On the basis of the results, it can be concluded that shared space schemes are context dependent and that factors such as the infrastructural design of the environment and the flow and speed of pedestrians and vehicles affect the willingness to share space

Spatial econometrics models for congestion prediction with in-vehicle route guidance

This study explores the congestion dependence relationship among links using microsimulation, based on data from a real road network. The work is motivated by recent innovations to improve the reliability of Dynamic Route Guidance (DRG) systems. The reliability of DRG systems can be significantly enhanced by adding a function to predict the congestion in the road network. This paper also talks about the application of spatial econometrics modelling to congestion prediction, by using historical Traffic Message Channel (TMC) data stored in the vehicle navigation unit. The nature of TMC data is in the form of a time series of geo-referenced congestion warning messages which is generally collected from various traffic sources. The prediction of future congestion could be based on the previous year of TMC data. Synthetic TMC data generated by microscopic traffic simulation for the network of Coventry are used in this study. The feasibility of using spatial econometrics modelling techniques to predict congestion is explored. Results are presented at the end

ICNavS: A tool for reliable dynamic route guidance

The aim of this paper is to devise a new reliable dynamic route guidance approach by integrating the A* algorithm, the concept of reliability and an existing route guidance method into a single package. A new purpose-developed software tool, the Imperial College Navigation Software (ICNavS), is presented, so as to implement and demonstrate the new approach on a real road network, using simulated data. A summary of the background of the program is given, followed by a procedure developed in order to model the features of real road networks, as well as missing data. Then, a imulation experiment on a part of West London’s road network is carried out and the results are presented

Testing a reliable in-vehicle navigation algorithm in the field

The results of a field experiment carried out to assess the accuracy and efficiency of a new in-vehicle navigation algorithm, whose aim is to incorporate and consider travel time reliability and route the guided vehicle along uncongested roads, in the absence of real-time traffic information are presented. Using historical travel time profiles deduced from floating vehicle data, the algorithm is implemented in a purpose-developed software tool and tested in the London Congestion Charging Zone. The experiment consists of driving a vehicle along routes computed by the algorithm and comparing the outcome with that of a conventional navigation system installed in a second vehicle. The results indicate that the new algorithm outperforms the conventional system in most cases, thus suggesting that it is a step forward towards a more intelligent navigation system

The Physics of Star Cluster Formation and Evolution

© 2020 Springer-Verlag. The final publication is available at Springer via https://doi.org/10.1007/s11214-020-00689-4.Star clusters form in dense, hierarchically collapsing gas clouds. Bulk kinetic energy is transformed to turbulence with stars forming from cores fed by filaments. In the most compact regions, stellar feedback is least effective in removing the gas and stars may form very efficiently. These are also the regions where, in high-mass clusters, ejecta from some kind of high-mass stars are effectively captured during the formation phase of some of the low mass stars and effectively channeled into the latter to form multiple populations. Star formation epochs in star clusters are generally set by gas flows that determine the abundance of gas in the cluster. We argue that there is likely only one star formation epoch after which clusters remain essentially clear of gas by cluster winds. Collisional dynamics is important in this phase leading to core collapse, expansion and eventual dispersion of every cluster. We review recent developments in the field with a focus on theoretical work.Peer reviewe

Traffic signal timing optimisation based on genetic algorithm approach, including drivers' routing

The genetic algorithm approach to solve traffic signal control and traffic assignment problem is used to tackle the optimisation of signal timings with stochastic user equilibrium link flows. Signal timing is defined by the common network cycle time, the green time for each signal stage, and the offsets between the junctions. The system performance index is defined as the sum of a weighted linear combination of delay and number of stops per unit time for all traffic streams, which is evaluated by the traffic model of TRANSYT [User guide to TRANSYT, version 8, TRRL Report LR888, Transport and Road Research Laboratory, Crowthorne, 1980]. Stochastic user equilibrium assignment is formulated as an equivalent minimisation problem and solved by way of the Path Flow Estimator (PFE). The objective function adopted is the network performance index (PI) and its use for the Genetic Algorithm (GA) is the inversion of the network PI, called the fitness function. By integrating the genetic algorithms, traffic assignment and traffic control, the GATRANSPFE (Genetic Algorithm, TRANSYT and the PFE), solves the equilibrium network design problem. The performance of the GATRANSPFE is illustrated and compared with mutually consistent (MC) solution using numerical example. The computation results show that the GA approach is efficient and much simpler than previous heuristic algorithm. Furthermore, results from the test road network have shown that the values of the performance index were significantly improved relative to the MC. © 2003 Elsevier Ltd. All right reserved

Sensitivity analysis on stochastic equilibrium transportation networks using genetic algorithm

This study deals with the sensitivity analysis of an equilibrium transportation networks using genetic algorithm approach and uses the bi-level iterative sensitivity algorithm. Therefore, integrated Genetic Algorithm-TRANSYT and Path Flow Estimator (GATPFE) is developed for signalized road networks for various level of perceived travel time in order to test the sensitivity of perceived travel time error in an urban stochastic road networks. Level of information provided to drivers correspondingly affects the signal timing parameters and hence the Stochastic User Equilibrium (SUE) link flows. When the information on road system is increased, the road users try to avoid conflicting links. Therefore, the stochastic equilibrium assignment concept tends to be user equilibrium. The GATPFE is used to solve the bi-level problem, where the Area Traffic Control (ATC) is the upper-level and the SUE assignment is the lower-level. The GATPFE is tested for six-junction network taken from literature. The results show that the integrated GATPFE can be applied to carry out sensitivity analysis at the equilibrium network design problems for various level of information and it simultaneously optimize the signal timings (i.e. network common cycle time, signal stage and offsets between junctions)

A reliability-based dynamic re-routing algorithm for in-vehicle navigation

This paper presents a new algorithm for a car navigation system, whose purpose is to offer a reliable re-route to the driver in case he/she deviates from the route he/she has been following, or if a traffic incident is reported en route. A reliable route is defined as one that has a low probability of being congested. The new method makes use of the A* route finding algorithm and introduces a link penalizing procedure to avoid unreliable (i.e. potentially congested) and incident-affected links in order to re-route the driver from his/her current position to his/her destination, while constraints are imposed on the route output by the algorithm so as to ensure driver acceptability. The new algorithm, called RDIN-R, is first described and then tested through a simulation experiment on the road network of Munich, Germany