Advanced Driver Assistance Systems (ADAS) offer the possibility of helping drivers to fulfill their driving tasks. Automated vehicles are capable of communicating with surrounding vehicles (V2V) and infrastructure (V2I) in order to collect and provide essential information about driving environment. Studies have proved that automated vehicles have a potential to decrease traffic congestion on road networks by reducing the time headway, enhancing the traffic capacity and improving the safety margins in car following. Furthermore, vehicle movement and driver’s behavior of conventional vehicles will be affected by the presence of automated vehicles in traffic networks. Despite different encouraging factors, automated driving raises some concerns such as possible loss of situation awareness, overreliance on automation and degrading driving skills in absence of practice. Moreover, coping with complex scenarios, such as merging at ramps and overtaking, in terms of interaction between automated vehicles and conventional vehicles need more research. This thesis work aims to investigate the effects of automated vehicles on driver’s behavior and traffic performance. A broad literature review in the area of driving simulators and psychological studies was performed to examine the automated vehicle effects on driver’s behavior. Findings from the literature survey, which has been served as setup values in the simulation study of the current work, reveal that the conventional vehicles, which are driving close to the platoon of automated vehicles with short time headway, tend to reduce their time headway and spend more time under their critical time headway. Additionally, driving highly automated vehicles is tedious in a long run, reduce situation awareness and can intensify driver drowsiness, exclusively in light traffic. In order to investigate the influences of automated vehicles on traffic performance, a microscopic simulation case study consisting of different penetration rates of automated vehicles (0, 50 and 100 percentages) was conducted in VISSIM software. The scenario network is a three-lane autobahn segment of 2.9 kilometers including an off-ramp, on-ramp and a roundabout with some surrounding urban roads. Outputs of the microscopic simulation in this study reveal that the positive effects of automated vehicles on roads are especially highlighted when the network is crowded (e.g. peak hours). This can definitely count as a constructive point for the future of road networks with higher demands. In details, average density of autobahn segment remarkably decreased by 8.09% during p.m. peak hours in scenario with automated vehicles. Besides, Smoother traffic flow with less queue in the weaving segment was observed. Result of the scenario with 50% share of automated vehicles moreover shows a feasible interaction between conventional vehicles and automated vehicles. Meaningful outputs of this case study, based on the input data from literature review, demonstrate the capability of VISSIM software to simulate the presence of automated vehicles in great extent, not only as an automated vehicle scenario but also a share of them, in traffic network. The validity of the output values nonetheless needs future research work on urban and rural roads with different traffic conditions.

There are many different types of automatic data collection technologies that have been used in transportation system applications such as pneumatic tubes, radar, video cameras, inductive loops detectors, wireless toll tags, and global positioning systems (GPS). Nevertheless, there are still multiple examples of important and helpful transportation system data that still require manual data collection. In this research, the automatic transportation system data collection capabilities are expanded by enhancements in the use of wireless communications technology. In recent years, smartphones and electronic peripherals with wireless communication capabilities have become very popular. Many of these electronic devices include a Bluetooth or Wi-Fi wireless radio, whose presence in a vehicle can be used as a vehicle identifier. With wireless on-board devices available now and in the future, this research explores how roadside data collection units (DCUs) communicating with on-board devices can be used for the automated data collection of important road system data such as intersection performance data. To this end, two approaches for wirelessly collecting vehicle movement over a short road segment were explored. One approach utilized the collection and triangulation of wireless signal strength data, and demonstrated the capabilities and limitations of this approach. The second approach focused on developing methods for utilizing wireless signal strength data for vehicle point detection and identification. The vehicle point detection methods developed were applied to collect travel time data over signalized arterial roads, and to collect intersection delay data for a three way stop controlled intersection. The results from these case studies indicate a significant advantage in the proposed data collection system over the existing data collection approaches presented in the literature. / Graduation date: 2013

Traffic signals are very cost effective tools for urban traffic management in urban areas. The number of intersections in Sweden controlled by traffic signals has increased since the seventies, but efforts to study the traffic performance of the employed strategies are still lacking. The LHOVRA technique is the predominant isolated traffic signal control strategy in Sweden. Past-end green was originally incorporated as part of LHOVRA (the “O” function) and was intended to reduce the number of vehicles in the dilemma zone. Coordinated signal control in Sweden is often fixed-time with local vehicle actuated signal timing adjustments and bus priority. This research study was undertaken to increase the knowledge of the traffic performance impacts of these strategies. The aim was to evaluate the following control strategies using Stockholm as a case study: 1. The LHOVRA technique with a focus on the “O” function; 2. Fixed time coordination (FTC); 3. Fixed time coordination with local signal timing adjustment (FTC-LTA); 4. FTC-LTA as above + active bus priority (PRIBUSS); 5. Self-optimizing control (SPOT). Field measurements were used for study of driver behavior and traffic impacts as well as for collecting input data needs for simulation. The results from low speed approaches showed a higher proportion of stopped vehicles after receiving green extension. Moving the detectors closer to the stop line, and/or making the detectors speed dependent were suggested as measures to solve these problems. The VISSIM simulation model calibrated and validated with empirical data was used to study traffic performance and safety impacts of the LHOVRA technique as well as to test the suggested improvements. The simulation experiment results from these design changes were shown to reduce accident risk with little or no loss of traffic performance. TRANSYT was used to produce optimized fixed signal timings for coordinated intersections. HUTSIM simulations showed that local signal timing adjustment by means of past-end green was beneficial when applied to coordinated traffic signal control in the study area. Both delays and stops were reduced, although not for the main, critical intersection which operated close to capacity. To study the impacts of strategies for coordinated signal control with bus priority, extensive field data collection was undertaken during separate time periods with these strategies in the same area using mobile and stationary techniques. A method to calculate the approach delay was developed based on the observed number of queuing vehicles at the start and end of green. Compared to FTC-LTA, the study showed that PRIBUSS reduced bus travel time. SPOT reduced both bus and vehicle travel time. Future research efforts for the development of signal control strategies and their implementation in Sweden should be focused on strategies with self-optimization functionality. / QC 20100408

The aim of this thesis is to investigate the traffic patterns in the mobile data networks. In this work, a simple Cellular Digital Packet Data (CDPD) network was modeled in order to be used in simulations. For the purpose of using in the CDPD model, a synthetic bursty traffic model was produced and using different traffic patterns some performance investigations were made in CDPD network. During the whole work, OPNET simulation tool was used. The CDPD network modeled by OPNET simulation tool was compared with a CDPD model described in the literature and the differences were shown. The new model has some new features: 1) Burst transmission of MAC blocks. 2) Exponential backoff. 3) New packet structures. 4) Frame segmentation and encapsulation into MAC layer frames. Using OPNET, a traffic having higher level of burstiness was produced and applied to the CDPD network model. Under the bursty traffic, some CDPD performance parameters were collected and according to the collected results some suggestions were given.

Road network of a region is of a paramount importance in the overall development. Management of road traffic is a key factor for the city authority and reducing the road traffic congestion is a significant challenge in this perspective. In this thesis, a Wireless Sensor Network (WSN) based road-traffic monitoring scheme with dynamic mathematical traffic model is presented that will not necessarily include all adjacent intersections of a block; rather the important major intersections of a city. The objective of this scheme is to reduce the congestion by re-routing the vehicles to better performing road-segments by informing the down-stream drivers through broadcasting the congestion information in a dedicated radio channel. The dynamic model can provide with the instantaneous status of the traffic of the road-network. The scheme is a WSN based multi-hop relay network with hierarchical architecture and composed of ordinary nodes, Cluster-Head nodes, Base Stations, Gateway nodes and Monitoring and Control Centers (MCC) etc. Through collecting the traffic information, MCC will check the congestion status and in defining the congestion, threshold factors have been used in this model. For the congested situation of a road-segment, a cost function has been defined as a performance indicator and estimated using the weight factors (importance) of these selected intersections. This thesis considered a traffic network with twelve major intersections of a city with four major directions. Traffic arrivals in these intersections are assumed to follow Poisson distribution. Model was simulated in Matlab with traffic generated through Poisson Random Number Generator and cost function was estimated for the congestion status of the road-segments over a simulation period of 1440 minutes starting from midnight. For optimization purpose we adopted two different approaches; in the first approach, performance of the scheme was evaluated for all threshold factor values iteratively one at a time, applying a threshold factor value to define threshold capacities of all the road segments; traffic was generated and relative cost has been estimated following the model specifications with the purpose of congestion avoidance. In the second approach, different values of threshold factor have been used for different road segments for determining the optimum set-up, and exhaustive search technique has been applied with a smaller configuration in order to keep computations reachable. Simulation results show the capacity of this scheme to improve the traffic performance by reducing the congestion level with low congestion costs.

Road network of a region is of a paramount importance in the overall development. Management of road traffic is a key factor for the city authority and reducing the road traffic congestion is a significant challenge in this perspective. In this thesis, a Wireless Sensor Network (WSN) based road-traffic monitoring scheme with dynamic mathematical traffic model is presented that will not necessarily include all adjacent intersections of a block; rather the important major intersections of a city. The objective of this scheme is to reduce the congestion by re-routing the vehicles to better performing road-segments by informing the down-stream drivers through broadcasting the congestion information in a dedicated radio channel. The dynamic model can provide with the instantaneous status of the traffic of the road-network. The scheme is a WSN based multi-hop relay network with hierarchical architecture and composed of ordinary nodes, Cluster-Head nodes, Base Stations, Gateway nodes and Monitoring and Control Centers (MCC) etc. Through collecting the traffic information, MCC will check the congestion status and in defining the congestion, threshold factors have been used in this model. For the congested situation of a road-segment, a cost function has been defined as a performance indicator and estimated using the weight factors (importance) of these selected intersections. This thesis considered a traffic network with twelve major intersections of a city with four major directions. Traffic arrivals in these intersections are assumed to follow Poisson distribution. Model was simulated in Matlab with traffic generated through Poisson Random Number Generator and cost function was estimated for the congestion status of the road-segments over a simulation period of 1440 minutes starting from midnight. For optimization purpose we adopted two different approaches; in the first approach, performance of the scheme was evaluated for all threshold factor values iteratively one at a time, applying a threshold factor value to define threshold capacities of all the road segments; traffic was generated and relative cost has been estimated following the model specifications with the purpose of congestion avoidance. In the second approach, different values of threshold factor have been used for different road segments for determining the optimum set-up, and exhaustive search technique has been applied with a smaller configuration in order to keep computations reachable. Simulation results show the capacity of this scheme to improve the traffic performance by reducing the congestion level with low congestion costs.