Intersection Signal Control and Design for Improved Person Mobility and Air Quality in Urban Multimodal Transportation Systems

Alternative geometric designs (e.g. roundabouts) and multi-objective signal control strategies are promising measures to improve sustainability of traffic networks. However, roundabouts are mostly used because of their safety and operational advantages. There has been less attention to the environmental performance of roundabouts. Also, the existing studies have been mostly used through field measurements and current simulation models, which need high calibration efforts and they are not inclusive in terms of considering all influencing factors on vehicular emissions at roundabouts. Furthermore, the existing real-time signal control strategies do not account for the emission rates of different vehicle types (e.g. cars and buses). In addition, the real-time multi-objective signal control systems does not consider environmental objectives. This dissertation develops a real-time bi-objective signal control system for isolated intersections, which operate at undersaturated traffic conditions that minimizes a weighted combination of vehicle delay (or person delay) and emissions of auto and transit vehicles. Pareto Frontiers of the optimal solutions are presented to help decision makers select the most appropriate combinations of objectives to achieve desirable levels of delay and emissions. Additionally, a simple simulation tool based on Cellular Automata (CA) model of traffic simulation is developed to estimate delay and reproduce vehicle trajectories for emission estimation. The models are used to compare the operational and environmental performance of roundabouts and signalized intersections and perform sensitivity analysis with respect to total traffic demand, left turn ratio, and pedestrian volume. Evaluation tests show that replacing a signalized intersection with a roundabout results in improved delay and emissions at undersaturated traffic conditions and any pedestrian volume. It also shows that roundabouts’ performance is less affected by high left turning demand compared to signalized intersections. On the contrary, roundabouts’ performance is sensitive to frequent pedestrian crossings while the performance of signalized intersections is not affected by pedestrian crossings

Improving Traffic Safety and Efficiency by Adaptive Signal Control Systems Based on Deep Reinforcement Learning

As one of the most important Active Traffic Management strategies, Adaptive Traffic Signal Control (ATSC) helps improve traffic operation of signalized arterials and urban roads by adjusting the signal timing to accommodate real-time traffic conditions. Recently, with the rapid development of artificial intelligence, many researchers have employed deep reinforcement learning (DRL) algorithms to develop ATSCs. However, most of them are not practice-ready. The reasons are two-fold: first, they are not developed based on real-world traffic dynamics and most of them require the complete information of the entire traffic system. Second, their impact on traffic safety is always a concern by researchers and practitioners but remains unclear. Aiming at making the DRL-based ATSC more implementable, existing traffic detection systems on arterials were reviewed and investigated to provide high-quality data feeds to ATSCs. Specifically, a machine-learning frameworks were developed to improve the quality of and pedestrian and bicyclist\u27s count data. Then, to evaluate the effectiveness of DRL-based ATSC on the real-world traffic dynamics, a decentralized network-level ATSC using multi-agent DRL was developed and evaluated in a simulated real-world network. The evaluation results confirmed that the proposed ATSC outperforms the actuated traffic signals in the field in terms of travel time reduction. To address the potential safety issue of DRL based ATSC, an ATSC algorithm optimizing simultaneously both traffic efficiency and safety was proposed based on multi-objective DRL. The developed ATSC was tested in a simulated real-world intersection and it successfully improved traffic safety without deteriorating efficiency. In conclusion, the proposed ATSCs are capable of effectively controlling real-world traffic and benefiting both traffic efficiency and safety

Engineering Countermeasures for Left Turns at Signalized Intersections: A Review

Left turn crashes can impact the safety of the drivers due to the speed and angle at which they occur. Left turns are specifically reported to affect older drivers more than the other types of crashes. This paper provides a review of the existing engineering countermeasures that have been evaluated to improve driver safety at left turns. Twenty- eight studies on left turn signal displays (protected left turns, flashing yellow arrow, and digital countdown timers), intersection geometry (offset left turn lanes, diverging diamond interchange, roundabouts, exit lanes for left turn, left turn bay extension, and contraflow left turn lanes), and driver warning systems (infrastructure warning systems, and in-vehicle warning systems) are reviewed. Eighteen studies were evaluated in the field, nine in laboratory environments, and one online. All countermeasures demonstrated varying levels of effectiveness. We found protected left turns, roundabouts, and warning systems to be the most effective engineering countermeasures. Advantages and disadvantages of each countermeasure and research shortcomings of the evaluation studies are discussed. Review findings may help practitioners and researchers guide more effective countermeasures for left turns for older drivers

Synchro Software-Based Alternatives for Improving Traffic Operations at Signalized Intersections

Traffic congestion is a considerable problem in urban arterials, especially at signalized intersections. Signalized intersections are critical elements of the highway system, thus improving their performance would significantly influence the overall operating performance of the system in terms of delay and level of service (LOS). The aim of this study is to assess the capacity performance of two signalized intersections in Duhok city, namely, Zari land intersection and Salahaddin Mosque intersection using the procedure in the Highway Capacity Manual and Synchro software. Total intersection delay, LOS, and volume to capacity ratio (v/c) were the measures of effectiveness used for comparison purposes. Different optimization alternatives have been tested to improve current and future performance. The results have shown that the Zari land intersection is currently operating at LOS F with an average delay of 590 s/veh and high values of v/c at specific movements. Results of optimization show that the scenario of creating an overpass with a change in cycle length and adding one additional lane in each direction is the best alternative to improve its performance to the LOS D with the maximum v/c ratio of 0.86. For Salahaddin Mosque intersection, the delay can be reduced from 544 s/veh (LOS F) with high values of v/c at the major street through movement to an average delay of 70 s/veh (LOS E) and maximum v/c ratio of 1, when cycle length and geometrics are changed, and approaching traffic from the minor street is prohibited

Fuzzy logic traffic signal controller enhancement based on aggressive driver behavior classification

The rise in population worldwide and especially in Egypt, together with the increase in the number of vehicles present serious complications regarding traffic congestion and road safety. The elementary solution towards improving congestion is to expand road capacities by building new lanes. This, however, requires time and effort and therefore new methodologies are being implemented. Intelligent transportation systems (ITS) try to approach traffic congestion through the application of computational and engineering techniques. Traffic signal control is a branch of intelligent transportation systems which focuses on improving traffic signal conditions. A traffic signal controllers’ main objective is to improve this assignment in a way which reduces delays. This research proposes a new approach to enhancing traffic signal control and reducing delays of a single intersection, through the integration of an aggressive driving behavior classifier. Previous approaches dealt with traffic control and driver behavior separately, and therefore their successful integration is a new challenging area in the field. Multiple experiment sets were conducted to provide an indication to the effectiveness of our approach. Firstly, an aggressive driver behavior classifier using feed-forward neural network was successfully built utilizing Virginia Tech 100-car naturalistic driving study data. Its performance was compared against long short-term memory recurrent neural networks and support vector machines, and it resulted in better performance as shown by the area under the curve. To the best of our knowledge, this classifier is the first of its kind to be built on this 100-car study data. Secondly, a representation of aggressive driving behavior was constructed in the simulated environment, based on real life data and statistics. Finally, Mamdani’s fuzzy logic controller was modified to accommodate for the integration of the aggressive behavior classifier. The integration results were encouraging and yielded significant improvements at higher traffic flow volumes when compared against the built Mamdani’s controller. The results are promising and provide an initial step towards the integration of driver behavior classification and traffic signal control

Efficiency of Roundabouts as Compared to Traffic Light Controlled Intersections in Urban Road Networks

Evaluating the performance of a multi-lane intersection is important to identify the best scheme as congestion is becoming a worldwide serious problem. A Multi-stream Minimum Acceptable Space (MMAS) Cellular Automata (CA) model is used for the simulation of vehicular traffic at double-lane roundabouts and cross intersection. Comparison is made between roundabouts with traffic light and without traffic light and signalized intersections on the basis of their performance to simplify traffic congestion. Computer simulations are used to propose critical arrival rates to separate between the three mentioned modes to decrease congestion at intersection points.Keywords: Traffic flow, Roundabout, Throughput, Multi-stream Minimum Acceptable Space, Cellular Automat