Ahmed Elbery

An Intersection Game-Theory-Based Traffic Control Algorithm in a Connected Vehicle Environment

Urban traffic congestion is a growing problem that we experience every day. Intersections are one of the major bottlenecks that contribute to urban traffic congestion. Traditional traffic control methods, such as traffic signal and stop sign control are not optimal for all demand levels as demonstrated in the literature. Recently, numerous research efforts proposed Intelligent Transportation System (ITS) applications to enhance intersection capacity and hence reduce congestion. In this paper we propose a game-theory-based algorithm for controlling autonomous vehicle movements equipped with Cooperative Adaptive Cruise Control (CACC) systems at uncontrolled intersections. The goal of this research effort is to develop an algorithm capable of using the future autonomous/automated vehicle capabilities to replace the usual state-of-the-practice control systems at intersections (e.g. stop signs, traffic signals, etc.). The proposed algorithm is chicken-game inspired and is efficient for application in real-time. It assumes vehicles can communicate with a central agent at the intersection to provide their instantaneous speeds and locations. The proposed algorithm assumes that vehicles obey the Nash equilibrium solution of the game. The simulation results demonstrated reductions in vehicle travel time and delay relative to an all-way stop sign control in the range of 49 and 89 percent on average respectively.

A carpooling recommendation system based on social VANET and geo-social data

Geo-social information can be utilized for user benefits in many applications. Social interaction in vehicular ad hoc networks (VANETs) is an important source for this type of information. In this paper, we first propose and describe a general architecture of the social VANET system (S-VANET) that supports social interaction through vehicular networks. Then, we present a new carpooling recommendation system that works as S-VANET application. The main objective is to recommend individuals to join their friends during trips or travels. The proposed recommendation system uses check-in history and home location to model users, and utilizes Fast Fourier transform to represent user check-ins and find the similarity between users. The system uses hierarchical clustering with weighted center of mass method to estimate the user home location.

Large-scale Agent-based Multi-modal Modeling of Transportation Networks - System Model and Preliminary Results.

The performance of urban transportation systems can be improved if travelers make better-informed decisions using advanced modeling techniques. However, modeling city-level transportation systems is challenging not only because of the network scale but also because they encompass multiple transportation modes. This paper introduces a novel simulation framework that efficiently supports large-scale agent-based multi-modal transportation system modeling. The proposed framework utilizes both microscopic and mesoscopic modeling techniques to take advantage of the strengths of each modeling approach. In order to increase the model scalability, decrease the complexity and achieve a reasonable simulation speed, the proposed framework utilizes parallel simulation through two partitioning techniques: spatial partitioning by separating the network geographically and vertical partitioning by separating the network by transportation mode for modes that interact minimally. The proposed framework creates multi-modal plans for each trip and tracks the travelers trips on a second-by-second basis across the different modes. We instantiate this framework in a system model of Los Angeles (LA) supporting our study of the impact on transportation decisions over a 5 hour period of the morning commute (7am-12pm). The results show that by modifying travel choices of only 10% of the trips a significant reduction in traffic congestion is achievable that results in better traffic flow and lower travel times.

Proactive and reactive carpooling recommendation system based on spatiotemporal and geosocial data

In this paper, we present a new carpooling recommendation system whose main objective is to find the best carpool matchings and recommend individuals to join their friends during trips or travels. The proposed recommendation system utilizes users mobility history and user social network information to find carpool matchings. The proposed system employs a probabilistic model based on continuous time Markov chain to model users mobility and to predict user future movements. Moreover, it uses two similarity measures (interest based similarity and friendship based similarity) to find the similarities between users. The interest based similarity uses a weighted bipartite graph between users and places, where the edges are weighted by the term frequency-inverse document frequency. The friendship based similarity uses the common friends as a similarity measure. The proposed system is evaluated using the number of carpool matchings that can be found, this number gives an indication of the reduction that can be made in vehicular traffic congestion, pollutant emissions and energy consumption.

An Integrated Architecture for Simulation and Modeling of Small- and Medium-Sized Transportation and Communication Networks

The emergence of Vehicular Ad-hoc Networks (VANETs) in the past decade has added a level of complexity to the modelling of Intelligent Transportation System (ITS) applications. In this paper, the Vehicular Network Integrated Simulator (VNetIntSim) is introduced as a new transportation network and VANET simulation tool by integrating transportation and VANET modelling. Specifically, it integrates the OPNET software, a communication network simulator, and the INTEGRATION software, a microscopic traffic simulation software. The INTEGRATION software simulates the movement of travellers and vehicles, while the OPNET software models the data exchange through the communication system. Information is exchanged between the two simulators as needed. The paper describes the implementation and the operation details of the VNetIntSim as well as the features it supports such as multiclass support and vehicle reuse. Subsequently, VNetIntSim is used to quantify the impact of mobility parameters (vehicular traffic stream speed and density) on the communication system performance considering Transmission Control Protocol (TCP) and User Datagram Protocol (UDP) applications. Specifically, the routing performance (packet drops and route discovery time), IP processing delay in case of a file transfer protocol (FTP) application, and jitter in case of a Voice over Internet Protocol (VoIP) application and evaluated.

Eco-Routing Using V2I Communication: System Evaluation

Eco-routing is a technique proposed to optimize the fuel consumption in transportation networks. User feedback is used to compute the routes fuel consumption level for other vehicles to build their minimum path routes. When a vehicle traverses a road link, it reports its fuel consumption on this link to a Traffic Management Center (TMC), which updates the vehicles routing information and then vehicles are assigned routes based on this updated information. The vehicular network is responsible for transferring this information from vehicles to the TMC, where packets are subjected to delays and drops. To the best of our knowledge, none of the previous research efforts on eco-routing studied the effect of the data network and communication parameters on the performance of eco-routing algorithms. This paper, firstly, introduces a realistic simulation framework for eco-routing that can capture all the details of both the transportation and the communication networks. Secondly, it studies the effect of communication parameters on the eco-routing performance. The results show that the errors due to data packet drops and delay are not significant. Consequently, the algorithm is robust against drops and delay. However, the number and locations of the roadside units (RSUs) are important factors that affect the network-wide fuel consumption level.

VNetIntSim - An Integrated Simulation Platform to Model Transportation and Communication Networks

The paper introduces a Vehicular Network Integrated Simulator (VNetIntSim) that integrates transportation modelling with Vehicular Ad Hoc Network (VANET) modelling. Specifically, VNetIntSim integrates the OPNET software, a communication network simulator, and the INTEGRATION software, a microscopic traffic simulation software. The INTEGRATION software simulates the movement of travellers and vehicles, while the OPNET software models the data exchange through the communication system. Information is exchanged between the two simulators as needed. As a proof of concept, the VNetIntSim is used to quantify the impact of mobility parameters (traffic stream speed and density) on the communication system performance, and more specifically on the data routing (packet drops and route discovery time).