Implementation of CAVENET and its usage for performance evaluation of AODV, OLSR and DYMO protocols in vehicular networks

Vehicle Ad-hoc Network (VANET) is a kind of Mobile Ad-hoc Network (MANET) that establishes wireless connection between cars. In VANETs and MANETs, the topology of the network changes very often, therefore implementation of efficient routing protocols is very important problem. In MANETs, the Random Waypoint (RW) model is used as a simulation model for generating node mobility pattern. On the other hand, in VANETs, the mobility patterns of nodes is restricted along the roads, and is affected by the movement of neighbour nodes. In this paper, we present a simulation system for VANET called CAVENET (Cellular Automaton based VEhicular NETwork). In CAVENET, the mobility patterns of nodes are generated by an 1-dimensional cellular automata. We improved CAVENET and implemented some routing protocols. We investigated the performance of the implemented routing protocols by CAVENET. The simulation results have shown that DYMO protocol has better performance than AODV and OLSR protocols.Peer ReviewedPostprint (published version

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

Integrated Traffic and Communication Performance Evaluation of an Intelligent Vehicle Infrastructure Integration (VII) System for Online Travel Time Prediction

This paper presents a framework for online highway travel time prediction using traffic measurements that are likely to be available from Vehicle Infrastructure Integration (VII) systems, in which vehicle and infrastructure devices communicate to improve mobility and safety. In the proposed intelligent VII system, two artificial intelligence (AI) paradigms, namely Artificial Neural Networks (ANN) and Support Vector Regression (SVR), are used to determine future travel time based on such information as current travel time, VII-enabled vehicles’ flow and density. The development and performance evaluation of the VII-ANN and VII-SVR frameworks, in both of the traffic and communications domains, were conducted, using an integrated simulation platform, for a highway network in Greenville, South Carolina. Specifically, the simulation platform allows for implementing traffic surveillance and management methods in the traffic simulator PARAMICS, and for evaluating different communication protocols and network parameters in the communication network simulator, ns-2. The study’s findings reveal that the designed communications system was capable of supporting the travel time prediction functionality. They also demonstrate that the travel time prediction accuracy of the VII-AI framework was superior to a baseline instantaneous travel time prediction algorithm, with the VII-SVR model slightly outperforming the VII-ANN model. Moreover, the VII-AI framework was shown to be capable of performing reasonably well during non-recurrent congestion scenarios, which traditionally have challenged traffic sensor-based highway travel time prediction methods

An Investigation into the Performance Evaluation of Connected Vehicle Applications: From Real-World Experiment to Parallel Simulation Paradigm

A novel system was developed that provides drivers lane merge advisories, using vehicle trajectories obtained through Dedicated Short Range Communication (DSRC). It was successfully tested on a freeway using three vehicles, then targeted for further testing, via simulation. The failure of contemporary simulators to effectively model large, complex urban transportation networks then motivated further research into distributed and parallel traffic simulation. An architecture for a closed-loop, parallel simulator was devised, using a new algorithm that accounts for boundary nodes, traffic signals, intersections, road lengths, traffic density, and counts of lanes; it partitions a sample, Tennessee road network more efficiently than tools like METIS, which increase interprocess communications (IPC) overhead by partitioning more transportation corridors. The simulator uses logarithmic accumulation to synchronize parallel simulations, further reducing IPC. Analyses suggest this eliminates up to one-third of IPC overhead incurred by a linear accumulation model

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

Analyzing Benefits of Connected Vehicle Technologies During Incidents on Freeways and Diversion Strategies Implementation: A Microsimulation-Based Case Study of Florida\u27s Turnpike

The full utilization of connected vehicles (CVs) is highly anticipated to become a reality soon. As CVs become increasingly prevalent in our roadway network, connected technologies have enormous potential to improve safety. This study conducted a microscopic simulation to quantify the benefits of CVs in improving freeway safety along a 7.8-mile section on Florida’s Turnpike (SR-91) system. The simulation incorporated driver compliance behavior in a CV environment. The simulation was implemented via an existing VISSIM network model partially developed by the Florida Department of Transportation (FDOT). In addition, the study analyzed how CVs would assist in detour operations as a strategy for congestion management during traffic incidents on freeways. The Surrogate Safety Assessment Model (SSAM) software was used to evaluate the benefits of CVs based on time-to-collision (TTC) as the performance measure. The TTC was evaluated at various CV market penetration rates (MPRs) of 0%, 25%, 50%, 75%, and 100%. The results showed a decreasing trend of conflicts for morning and evening peak hours, especially from 25% to 100% CV MPRs. The benefits were statistically significant at a 95% confidence level for high CV MPR (above 25%). Upon an incident on the freeway, at higher CV MPRs simulations, the detour strategy seemed to reduce travel time on the freeway. Besides, the detour strategy was more helpful when the incident clearance duration lasted more than 30 minutes. Findings from this study may help the incident management process prepare for detour strategies based on the severity of the incident at hand and could explain the importance of CVs in supporting warning and management strategies for drivers to improve safety on freeways. Keywords: Conflicts, Connected Vehicles, Driver Compliance Rate, Detour, Incident Modeling, Safety Surrogate Measure

Change in Microscopic Traffic Simulation Practice with Respect to the Emerging Automated Driving Technology

It is believed that autonomous vehicles will replace conventional human drive vehicles in the next decades due to the emerging autonomous driving technology, which will definitely bring a massive transformation in the road transport sector. Due to the high complexity of traffic systems, efficient traffic simulation models for the assessment of this disruptive change are critical. The objective of this paper is to justify that the common practice of microscopic traffic simulation needs thorough revision and modification when it is applied with the presence of autonomous vehicles in order to get realistic results. Two high-fidelity traffic simulators (SUMO and VISSIM) were applied to show the sensitivity of microscopic simulation to automated vehicle’s behavior. Two traffic evaluation indicators (average travel time and average speed) were selected to quantitatively evaluate the macro-traffic performance of changes in driving behavior parameters (gap acceptance) caused by emerging autonomous driving technologies under different traffic demand conditions