A review of traffic simulation software

Computer simulation of tra c is a widely used method in research of tra c modelling, planning and development of tra c networks and systems. Vehicular tra c systems are of growing concern and interest globally and modelling arbitrarily complex tra c systems is a hard problem. In this article we review some of the tra c simulation software applications, their features and characteristics as well as the issues these applications face. Additionally, we introduce some algorithmic ideas, underpinning data structural approaches and quanti able metrics that can be applied to simulated model systems

Extending TRANSIMS Technology to an Integrated Multilevel Representation

The TRANSIMS system developed at Los Alamos in the USA over the past decade is a world leader in providing an integrated land-use transportation dynamical model for large areas with a million or more inhabitants. TRANSIMS uses standard survey data to create synthetic micropopulations, including family structure, to simulate trip making and emergent traffic dynamics. We propose to extend TRANSIMS by adapting it to a new multi-level representation, allowing dynamics to be algebraically integrated at the micro-, meso- and macro-levels. The new representation builds a lattice hierarchy in a way that integrates non-partitional hierarchies of links and routes based on the usual hierarchy of geographical zones, e.g. neighbourhoods, districts, cities, counties and countries. Applying the representation to a big city starts by defining sets of zones at different levels. At the first level, N, is the street. This can be subdivided to building plots at level N-1, buildings at level N-2, and even rooms at level N-3. At level N+1 are the neighbourhoods, at level N+2 is the set of district zones (each of them containing the different neighbourhoods in the previous level), and at the top level N+3 (in this case), is just one zone, the city itself. If a larger study area is to be considered, we would have a whole set of N+3 zones defining N+4-level areas, and so on, extending to the level of counties, countries or even continents. This paper will explain the fundamentals of TRANSIMS technology and compare it to other systems. We will show how TRANSIMS and the new multi-level representation can be brought together to give new insights into the macro-dynamics of very large road systems such as London, England and even the whole of Europe

Evolutionary Computation Applied to Urban Traffic Optimization

At the present time, many sings seem to indicate that we live a global energy and environmental crisis. The scientific community argues that the global warming process is, at least in some degree, a consequence of modern societies unsustainable development. A key area in that situation is the citizens mobility. World economies seem to require fast and efficient transportation infrastructures for a significant fraction of the population. The non-stopping overload process that traffic networks are suffering calls for new solutions. In the vast majority of cases it is not viable to extend that infrastructures due to costs, lack of available space, and environmental impacts. Thus, traffic departments all around the world are very interested in optimizing the existing infrastructures to obtain the very best service they can provide. In the last decade many initiatives have been developed to give the traffic network new management facilities for its better exploitation. They are grouped in the so called Intelligent Transportation Systems. Examples of these approaches are the Advanced Traveler Information Systems (ATIS) and Advanced Traffic Management Systems (ATMS). Most of them provide drivers or traffic engineers the current traffic real/simulated situation or traffic forecasts. They may even suggest actions to improve the traffic flow. To do so, researchers have done a lot of work improving traffic simulations, specially through the development of accurate microscopic simulators. In the last decades the application of that family of simulators was restricted to small test cases due to its high computing requirements. Currently, the availability of cheap faster computers has changed this situation. Some famous microsimulators are MITSIM(Yang, Q., 1997), INTEGRATION (Rakha, H., et al., 1998), AIMSUN2 (Barcelo, J., et al., 1996), TRANSIMS (Nagel, K. & Barrett, C., 1997), etc. They will be briefly explained in the following section. Although traffic research is mainly targeted at obtaining accurate simulations there are few groups focused at the optimization or improvement of traffic in an automatic manner â not dependent on traffic engineers experience and âartâ. O pe n A cc es s D at ab as e w w w .ite ch on lin e. co

The Effects of Varying Penetration Rates of L4-L5 Autonomous Vehicles on Fuel Efficiency and Mobility of Traffic Networks

Microscopic traffic simulators that simulate realistic traffic flow are crucial in studying, understanding and evaluating the fuel usage and mobility effects of having a higher number of autonomous vehicles (AVs) in traffic under realistic mixed traffic conditions including both autonomous and non-autonomous vehicles. In this paper, L4-L5 AVs with varying penetration rates in total traffic flow were simulated using the microscopic traffic simulator Vissim on urban, mixed and freeway roadways. The roadways used in these simulations were replicas of real roadways in and around Columbus, Ohio, including an AV shuttle routes in operation. The road-specific information regarding each roadway, such as the number of traffic lights and positions, number of STOP signs and positions, and speed limits, were gathered using OpenStreetMap with SUMO. In simulating L4-L5 AVs, the All-Knowing CoEXist AV and a vehicle with Wiedemann 74 driver were taken to represent AV and non-AV driving, respectively. Then, the driving behaviors, such as headway time and car following, desired acceleration and deceleration profiles of AV, and non-AV car following and lane change models were modified. The effect of having varying penetration rates of L4-L5 AVs were then evaluated using criteria such as average fuel consumption, existence of queues and their average/maximum length, total number of vehicles in the simulation, average delay experience by all vehicles, total number of stops experienced by all vehicles, and total emission of CO, NOx and volatile organic compounds (VOC) from the vehicles in the simulation. The results show that while increasing penetration rates of L4-L5 AVs generally improve overall fuel efficiency and mobility of the traffic network, there were also cases when the opposite trend was observed