Modelling shared space users via rule-based social force model

The promotion of space sharing in order to raise the quality of community living and safety of street surroundings is increasingly accepted feature of modern urban design. In this context, the development of a shared space simulation tool is essential in helping determine whether particular shared space schemes are suitable alternatives to traditional street layouts. A simulation tool that enables urban designers to visualise pedestrians and cars trajectories, extract flow and density relation in a new shared space design and achieve solutions for optimal design features before implementation. This paper presents a three-layered microscopic mathematical model which is capable of representing the behaviour of pedestrians and vehicles in shared space layouts and it is implemented in a traffic simulation tool. The top layer calculates route maps based on static obstacles in the environment. It plans the shortest path towards agents' respective destinations by generating one or more intermediate targets. In the second layer, the Social Force Model (SFM) is modified and extended for mixed traffic to produce feasible trajectories. Since vehicle movements are not as flexible as pedestrian movements, velocity angle constraints are included for vehicles. The conflicts described in the third layer are resolved by rule-based constraints for shared space users. An optimisation algorithm is applied to determine the interaction parameters of the force-based model for shared space users using empirical data. This new three-layer microscopic model can be used to simulate shared space environments and assess, for example, new street designs

Modelling unsignalised traffic flow with reference to urban and interurban networks

A new variant of cellular automata (CA) models is proposed, based on Minimum Acceptable Space (MAP) rules, to study unsignalised traffic flow at two-way stop-controlled (TWSC) intersections and roundabouts in urban and interurban networks. Categorisation of different driver behaviour is possible, based on different space requirements (MAPs), which allow a variety of conditions to be considered. Driver behaviour may be randomly categorised as rational, (when optimum conditions of entry are realised), conservative, urgent and radical, with specified probabilities at each time step. The model can successfully simulate both heterogeneous and inconsistent driver behaviour and interactions at the different road features. The impact of driver behaviour on the overall performance of intersections and roundabouts can be quantified and conditions for gridlock determined. Theorems on roundabout size and throughput are given. The relationship between these measures is clearly non-monotonic. Whereas previous models consider these road features in terms of T-intersections, our approach is new in that each is a unified system. Hence, the relationship between arrival rates on entrance roads can be studied and critical arrival rates can be identified under varied traffic and geometric conditions. The potential for extending the model to entire urban and interurban networks is discussed

Optimised Traffic Flow at a Single Intersection: Traffic Responsive signalisation

We propose a stochastic model for the intersection of two urban streets. The vehicular traffic at the intersection is controlled by a set of traffic lights which can be operated subject to fix-time as well as traffic adaptive schemes. Vehicular dynamics is simulated within the framework of the probabilistic cellular automata and the delay experienced by the traffic at each individual street is evaluated for specified time intervals. Minimising the total delay of both streets gives rise to the optimum signalisation of traffic lights. We propose some traffic responsive signalisation algorithms which are based on the concept of cut-off queue length and cut-off density.Comment: 10 pages, 11 eps figs, to appear in J. Phys.

Investigation of pedestrian evacuation scenarios through congestion level and crowd dang

In this paper, we present two quantities aimed at numerically describing the level of congestion and the intrinsic risk of pedestrian crowds. The congestion level allows to assess the smoothness of pedestrian streams and recognize regions where self-organization is difficult or not possible. This measure differs from previous attempts to quantify congestion in pedestrian crowds by employing velocities as vector entities (thus not only focusing on the absolute value). The crowd danger contains elements related to congestion, but also includes the effect of density, consequently allowing to asses the risks intrinsically created by the dynamics of crowds. Details on the computational methods related to both quantities are described in the paper and their properties are discussed. As a practical application, both measures are used to investigate supervised experiments where evacuation (or similar conditions) are considered. Results for small room sizes and limited number of pedestrians show that the crowd danger distribution over the space in front of the exit door has similar patterns to typical quantities used in the frame of pedestrian dynamics (density and flow) and symmetrical shapes are obtained. However, when larger scenarios are considered, then congestion map and crowd danger become unrelated from density and/or flow, showing that both quantities express different aspects of pedestrian motion

Development and evaluation of low cost 2-d lidar based traffic data collection methods

Traffic data collection is one of the essential components of a transportation planning exercise. Granular traffic data such as volume count, vehicle classification, speed measurement, and occupancy, allows managing transportation systems more effectively. For effective traffic operation and management, authorities require deploying many sensors across the network. Moreover, the ascending efforts to achieve smart transportation aspects put immense pressure on planning authorities to deploy more sensors to cover an extensive network. This research focuses on the development and evaluation of inexpensive data collection methodology by using two-dimensional (2-D) Light Detection and Ranging (LiDAR) technology. LiDAR is adopted since it is economical and easily accessible technology. Moreover, its 360-degree visibility and accurate distance information make it more reliable. To collect traffic count data, the proposed method integrates a Continuous Wavelet Transform (CWT), and Support Vector Machine (SVM) into a single framework. Proof-of-Concept (POC) test is conducted in three different places in Newark, New Jersey to examine the performance of the proposed method. The POC test results demonstrate that the proposed method achieves acceptable performances, resulting in 83% ~ 94% accuracy. It is discovered that the proposed method\u27s accuracy is affected by the color of the exterior surface of a vehicle since some colored surfaces do not produce enough reflective rays. It is noticed that the blue and black colors are less reflective, while white-colored surfaces produce high reflective rays. A methodology is proposed that comprises K-means clustering, inverse sensor model, and Kalman filter to obtain trajectories of the vehicles at the intersections. The primary purpose of vehicle detection and tracking is to obtain the turning movement counts at an intersection. A K-means clustering is an unsupervised machine learning technique that clusters the data into different groups by analyzing the smallest mean of a data point from the centroid. The ultimate objective of applying K-mean clustering is to identify the difference between pedestrians and vehicles. An inverse sensor model is a state model of occupancy grid mapping that localizes the detected vehicles on the grid map. A constant velocity model based Kalman filter is defined to track the trajectory of the vehicles. The data are collected from two intersections located in Newark, New Jersey, to study the accuracy of the proposed method. The results show that the proposed method has an average accuracy of 83.75%. Furthermore, the obtained R-squared value for localization of the vehicles on the grid map is ranging between 0.87 to 0.89. Furthermore, a primary cost comparison is made to study the cost efficiency of the developed methodology. The cost comparison shows that the proposed methodology based on 2-D LiDAR technology can achieve acceptable accuracy at a low price and be considered a smart city concept to conduct extensive scale data collection

The MATSim Network Flow Model for Traffic Simulation Adapted to Large-Scale Emergency Egress and an Application to the Evacuation of the Indonesian City of Padang in Case of a Tsunami Warning

The evacuation of whole cities or even regions is an important problem, as demonstrated by recent events such as evacuation of Houston in the case of Hurricane Rita or the evacuation of coastal cities in the case of Tsunamis. This paper describes a complex evacuation simulation framework for the city of Pandang, with approximately 1,000,000 inhabitants. Padang faces a high risk of being inundated by a tsunami wave. The evacuation simulation is based on the MATSim framework for large-scale transport simulations. Different optimization parameters like evacuation distance, evacuation time, or the variation of the advance warning time are investigated. The results are given as overall evacuation times, evacuation curves, an detailed GIS analysis of the evacuation directions. All these results are discussed with regard to their usability for evacuation recommendations.BMBF, 03G0666E, Verbundprojekt FW: Last-mile Evacuation; Vorhaben: Evakuierungsanalyse und Verkehrsoptimierung, Evakuierungsplan einer Stadt - Sonderprogramm GEOTECHNOLOGIENBMBF, 03NAPAI4, Transport und Verkehr: Verbundprojekt ADVEST: Adaptive Verkehrssteuerung; Teilprojekt Verkehrsplanung und Verkehrssteuerung in Megacitie

Development of a hardware-in-the-loop analysis framework for advanced ITS applications

As Intelligent Transportation Systems (ITS) become more prevalent, there is a need for a system capable of the rigorous evaluation of new ITS strategies for a wide variety of applications. Pre-deployment testing and fine-tuning of the system, performance evaluation, and alternatives analysis are all potential benefits that could be gained through the evaluation of ITS. Simulation, an increasingly popular tool for transportation analysis, would seem an ideal solution to this problem as it allows for the consideration of many scenarios that may be improbable or impossible to observe in the field. Also, simulation provides a framework that allows for the application of rigorous analysis techniques to the output data, providing an accurate and statistically significant conclusion. The difficulty is that many ITS strategies are difficult or impossible to implement in a simulated environment. The rapid nature of technology development and the complicated nature of many ITS solutions are difficult to emulate in simulation models. Furthermore, the emulation of a particular ITS solution is not guaranteed to provide the same result that the physical system would, were it subject to the same inputs. This study seeks to establish a framework for the analysis of advanced ITS applications through the use of Hardware-in-the-Loop Simulation (HILS), which provides a procedure for interfacing simulation models with real-world hardware to conduct analysis. This solution provides the benefits of both advanced ITS evaluation and simulation for powerful and accurate analysis. A framework is established that includes all the steps of the modeling process including construction, validation, calibration, and output analysis. This ensures that the process surrounding the HILS implementation is valid so that the results of the evaluation are accurate and defendable. Finally, a case study of the application of the developed framework to the evaluation, a real-world implementation of an advanced ITS application (SCATS in this case) is considered. The effectiveness of the framework in creating and evaluating a corridor using a simulation model wed to real-world hardware is shown. The results of the analysis show the power of this method when correctly applied and demonstrate where further analysis could expand upon the proposed procedure.M.S.Committee Chair: Dr. Michael Hunter; Committee Member: Dr. Jiawen Yang; Committee Member: Dr. Jorge Laval; Committee Member: Dr. Michael Rodger