Impact of ITS services on the safety and efficiency of road traffic

This paper describes the project entitled: “Impact of the use of Intelligent Transport Systems on the level of road safety” (agreement no. DZP/RID-I-41/7/NCBR/2016), implemented as part of the Road Innovations Development (RID) programme, funded by the National Centre for Research and Development and the General Directorate for National Roads and Motorways (GDDKiA). The project is run by a consortium comprising the Motor Transport Institute, University of Gdańsk, Warsaw University of Technology, Military University of Technology and Research Institute of Roads and Bridges. The impact of ITS services and accompanying modules on road safety may be considered in functional, logical or physical terms. The aim of the project is to understand how ITS services change road safety

Microsimulating Cross-Border Truck Movements between Ontario and the United States: An Application using Connected Vehicle Technology

The land-border crossings between Canada and the United States facilitate over half of the goods transported between the two countries. Since trucks are the primary mode of transportation for the movement of these goods, studying the traffic flows and the characteristics of border crossings is of paramount importance for decision makers, planners and researchers. The province of Ontario is home to the busiest border crossings in Canada including the Ambassador Bridge in Windsor, Ontario and the Blue Water Bridge in Sarnia, Ontario. GPS data collected from a large sample of trucks shows the route choice characteristics for these border crossings. The same dataset also shows the destination locations for these trucks. This thesis utilizes VISSIM, a microscopic traffic simulator, and its dynamic traffic assignment, an imbedded route choice model, to replicate these route choice conditions. Once the model is validated with the shares of flows from the observed (i.e., reference) datasets, the route choice behavior is analyzed under different delay conditions. The research also analyzed the effects of connected vehicle technology, at different penetration rates, on the efficiency of border crossing operations. As the connected vehicles increased in the traffic stream, it was observed that traffic was more streamlined and would switch to use the Blue Water Bridge during the simulation of an incident on Highway 401. The penetration rate was increased in 20% increments and with 100% penetration, 7% of total truck traffic had switched to Blue Water Bridge to travel to their U.S. destination

Automation-ready framework for urban transport planning

The mission of the H2020 CoEXist project is to enable mobility stakeholders to get “Automation-ready” – which CoEXist currently defines as conducting transport and infrastructure planning for connected and automated vehicles (CAVs) in the same comprehensive manner as for existing modes such as conventional vehicles, public transport, pedestrians, and cyclists, while ensuring continued support for existing modes on the same network. This definition will be fine-tuned through stakeholder engagement processes. The H2020 CoEXist project started in May 2017 and will run until April 2020. This paper introduces this project and covers its progress until January 2018, with a focus on the methodology of the “Automation-ready framework” that provides a planning framework for urban road authorities to prepare for the introduction of CAVs on the road network. The framework includes elements about strategic urban mobility planning for CAVs and a clear guide for urban transport planners with a list of concrete actions that cities can do now to plan for CAVs on their road network

The impact of autonomous vehicles on highway tunnel work zones

In the transition step to the near future where autonomous vehicles fill the highways, the autonomous vehicles’ successful implementation counts on knowledge about their interaction with conventional vehicles. Due to the lack of numbers of the autonomous vehicles on roadways, many transportation professionals depend on simulations in order to examine the coexistence of both vehicle types and their interaction in the circumstance of higher market penetration rates of the autonomous vehicles. In this study, VISSIM microscopic simulator is used for inspecting the autonomous vehicles interactions and assessing their impacts on traffic stream. A case study that evaluates the effects on vehicles throughput, delay, queue length, and safety at the highway work zone merging area is investigated. The simulation was generated the proximity of the Louis-Hippolyte La Fontaine tunnel, which connects Boucherville and Montréal island. To simulate coexist periods, the autonomous vehicles were put into the simulation with different penetration rates starting at 20% and increasing 20% for each scenario until reaching 80% of the rates of the autonomous vehicles. Furthermore, the safety impact of the autonomous vehicles in the matter of conflicts was studied using the Surrogate Safety Assessment Model (SSAM). The simulation results showed that the tunnel work zone’s capacity per lane was increased when CAVs were added to the simulation. The average vehicle delay did not improve a low CAV penetration rates. However, as CAVs account for more than 40% of the total passenger vehicles, the vehicle delay improved. The simulated model also showed that the average queue length increased with the increase of CAV in the traffic stream. Nonetheless, the conflict analysis results proved that CAVs can improve overall traffic safety at the work zone

An Emulation Framework for Evaluating V2X Communications in C-ITS Applications

C-ITS enhances transportation systems with advanced communication tech, enabling vehicle-to-vehicle and vehicle-to-infrastructure data exchange for real-time decision-making. The thesis explores C-ITS concepts, DSRC, and C-V2X tech, and proposes a versatile C-ITS framework for app prototyping and communication evaluation. Real-world tests and simulations validate its potential to improve road safety and efficiency, suggesting integration opportunities for stakeholders and promoting a smarter, sustainable transportation ecosystem

ESTIMATING THE IMPACT OF INTERSECTION TRAFFIC ON AIR QUALITY EMISSIONS AT CAMDEN COOPER MEDICAL HEALTH INTERSECTION THROUGH THE INTEGRATION OF VISSIM/MOVES MODELS

Traffic emissions near intersections can increase significantly due to idling as well as stop-and-go traffic conditions. Increased emissions of pollutants like particulate matter (PM), nitrogen oxides (NOx), carbon monoxide (CO), and polycyclic aromatic hydrocarbons (PAHs) found in traffic exhaust deteriorate the health of the population that is exposed to them. Since general traffic emissions are increased by the stop-and-go conditions produced at intersections, PAH traffic emissions should also increase from intersection driving conditions. The intersection of Dr. Martin Luther King Jr. Blvd and Haddon Ave in Camden, NJ was identified as an ideal site to study PAH traffic emissions. To identify intersection effect on PAH emissions, the traffic modeler VISSIM was used to generate individual vehicle data for intersection driving conditions and hypothetical uncontrolled “Free-Flow” driving conditions based on traffic data obtained from Go Pro videos of the intersection. Output data from VISSIM was converted into input data for the emissions modeler MOVES3 using, VISSIM-MOVES Integration, an Excel-based tool developed for this study. The MOVES results were limited to the PM and PAH emissions to compare with collected air samples. The model showed that particle-bound PAH emissions were 2.4 to 3.4 times higher at intersections and gaseous PAH and PM emissions were twice as high

D.1.4 Mapping & Impact Assessment Report

Definitions of Lighthouse and Follower cities, and pertinent characteristics of replication use cases are presented in this deliverable, together with various earlier European efforts for smart and clean mobility and impact assessment, including Tide, Flow, Trilater and SHOW impact assessment approaches. The CIVITAS initiative has provided a fundamental framework for the RECIPROCITY project, and it has been adopted as the source of the guiding principles for impact assessment. The report presents a summary of the preliminary work on simulation-based assessment of the environmental impact and passenger transport effectiveness performed on two mobility use-cases: ‘’32. Intelligent BRT’’ (Istanbul, TR) and ‘’6. SOftly MObile Tourism Mobility’’ (Alpine Pearls/Werfenweng, AT). The PTV Vissim tool1 was used for simulation. Specifically, CO2 emission and passenger experience parameters of two lines (Avcılar – Zincirlikuyu, Zincirlikuyu – Söğütlüçeşme) of the Istanbul Metropolitan BRT system and three lines of the Werfenweng W3 Shuttle (Werfenweng-Pfarrwerfen-Bischofshofen, Werfenweng-Pfarrwerfen-Werfen and Tenneck-Werfen) were evaluated under various scenarios. For the Intelligent BRT use-case, it is shown that autonomous platooning significantly enhances transport effectiveness, decreasing passenger delays while reducing fuel consumption and CO2 emissions by up to 21%. For the SOftly Mobile Tourism Mobility use case, it is shown that e-cars and e-bikes improve passenger experience, in terms of reduced waiting times, while also significantly reducing local emissions. An important issue, however, is that indirect emissions from e-vehicles, that is greenhouse gases generated in energy production plants, can reach significant levels, even though not local

Evaluating the Impacts of Accelerated Incident Clearance Tools and Strategies by Harnessing the Power of Microscopic Traffic Simulation

Traffic incidents cause Americans delay, waste fuel, cause injuries, and create toxic emissions. Transportation professionals have implemented a variety of tools to manage these impacts and researchers have studied their effectiveness, illustrating a wide range between different tools and locations. To improve this state of knowledge, this dissertation sought to 1) identify prominent and effective incident management strategies, 2) model six selected incident management strategies within five highway corridors in South Carolina, and 3) apply benefit-cost analysis to evaluate the impact of various combinations of these strategies. To meet these objectives, the author evaluated published literature of the selected strategies, administered a nationwide survey of these strategies, conducted traffic simulation, and performed benefit-cost analysis. The literature review guided the author to fill gaps in knowledge regarding the effectiveness and expense of identified strategies. The nationwide survey identified effective incident management tools, the extent of their adoption, and their common problems. The author then applied PARAMICS traffic simulation software to evaluate the impact of six tools at five sites on metropolitan interstates throughout South Carolina. Finally, benefit-cost analysis was used to evaluate the benefits against costs at each study site. The survey provided many insights into both the effectiveness and collaboration within and among traffic incident management agencies and guided the author in selecting tools for evaluation. While the simulation study found that as the severity and duration of incident increases, so does the potential benefit of incident management tools, the frequency of incidents also produces significant impact on annual benefits. The benefit-cost analysis indicated that while all the incident management tools evaluated provided more benefits than costs, freeway service patrols and traffic cameras produced the highest return for incidents of varying severity. It was also found more advantageous to select one expensive but efficient incident management technology, rather than engage in the incremental deployment of various systems that might provide redundant benefits. Departments of transportation across the United States see the need to manage incidents more efficiently, consequently this dissertation developed data and analysis to compare benefits with costs to aid decision makers in selecting tools and strategies for future incident management endeavors

Development of mathematical models to improve road freight movements for tunnel infrastructure using connected and autonomous vehicles

Road freight transportation is considered the backbone of country’s socio-economic framework and thus its vital to ensure it is working optimally. The research detailed in this thesis is focused on improving the movement of road freight, especially for hazardous goods vehicles via a road tunnel, with the help of Connected and Autonomous Freight Vehicles (CAV-F). The study analyses real-world Dartford Crossing tunnel data to identify the impact of existing check and allow procedures for Dangerous Goods Vehicles (DGVs) and Abnormal Load Vehicles (ALVs) at a tunnel. A near realistic traffic simulation model is developed as part of analysis and is validated against an independent Highways England’s Motorway Incident Detection and Automatic Signalling (MIDAS) data. The effectiveness of CAV-F in improving road traffic conditions is measured using different simulation scenarios involving mixed traffic (i.e. CAV-F and conventional vehicles alongside) and different real-world tunnel closure conditions. Once the effective performance of CAV-F is established, this research develops a novel mathematical model aimed at automating the check and allow procedures for DGVs at the tunnel. The mathematical model calculates the geo-reference locations for the placement of cooperative communications between the vehicles and road infrastructure to generate dynamic vehicular gaps. This will allow desired safety gaps between the platoon of DGVs and its preceding and following vehicles enabling isolated travel via the road tunnel to ensure safe and secure passage. The mathematical model is verified for different road layouts determined based on geo-referenced locations, approaching a road tunnel. Using traffic simulation, the results determine if the modulation of vehicles’ speeds at identified geo-referenced locations are suitable for desired gap generation. Finally, to conclude the research questions, the second mathematical model is developed to help uninterrupted traffic merging at the junctions, as was observed after the successful gap generation. This model could also be generalised to optimise the traffic merge sequence at a motorway junction. The approach is inspired by the noise cancellation technique which utilises destructive wave interference patterns, where vehicular flow on two merging roads is considered as traffic waves. By analysing the merge sequence of vehicles at the junction from fixed equidistant positions on separate roads, the dynamic phase shifting is applied by modulating the speeds of the identified vehicles which would otherwise approach at the junction simultaneously, leading to queue formation (or collision). The performance of the approach is then measured using a traffic simulation model and are determined against existing real-world traffic flow on motorways for improvements in travel time, and traffic throughput and reduction in congestion, with increasing traffic density