A study of the environmental impacts of intelligent automated vehicle control at intersections via V2V and V2I communications

This article presents a novel intersection traffic management system for automated vehicles and quantifies its impact on fuel consumption and greenhouse gas emissions of CO₂ relative to traditional traffic signal and roundabout intersection control. The developed intelligent traffic management (ITM) techniques, which are based on a spatiotemporal reservation scheme, ensure that vehicles proceed through the intersection without colliding with other vehicles while at the same time reducing the intersection delay and environmental impacts. Specifically, the spatiotemporal reservation scheme provides each vehicle a collision-free path that is decomposed into a speed profile along with navigational instructions. The integration of the developed microscopic traffic simulator with instantaneous emission model, provides improved assessments of the environmental impact of traffic control strategies at intersections. The simulator architecture integrates several ITM algorithms, vehicle sensors, V2V/V2I communications, and emission and fuel consumption models. Each vehicle is modeled by an agent and each agent provides information depending on the specific vehicle sensors. The ITM system is supported by V2V and V2I communications, allowing the exchange of information among vehicles and infrastructure. The data include the estimated vehicle position and speed. Compared with traditional traffic management techniques, the simulation results prove that the proposed ITM system reduces CO₂ emissions significantly. The research also shows that these reductions are more significant when the traffic flow increases.     

A field evaluation case study of the environmental and energy impacts of traffic calming

This study quantifies the energy and environmental impact of a selection of traffic calming measures using a combination of second-by-second floating-car global positioning system data and microscopic energy and emission models. It finds that traffic calming may result in negative impacts on vehicle fuel consumption and emission rates if drivers exert aggressive acceleration levels to speed up to their journeys. Consequently by eliminating sharp acceleration maneuvers significant savings in vehicle fuel consumption and emission rates are achievable through driver education. The study also demonstrates that high emitting vehicles produce CO emissions that are up to 25 times higher than normal vehicle emission levels while low emitting vehicles produce emissions that are 15–35% of normal vehicles. The relative increases in vehicle fuel consumption and emission levels associated with the sample traffic calming measures are consistent and similar for normal, low, and high emitting vehicles.     

A discrete optimization approach for locating Automatic Vehicle Identification readers for the provision of roadway travel times

This paper develops an algorithm for optimally locating Automatic Vehicle Identification tag readers by maximizing the benefit that would accrue from measuring travel times on a transportation network. The problem is formulated as a quadratic 0–1 optimization problem where the objective function parameters represent benefit factors that capture the relevance of measuring travel times as reflected by the demand and travel time variability along specified trips. An optimization approach based on the Reformulation–Linearization Technique coupled with semidefinite programming concepts is designed to solve the formulated reader location problem. To illustrate the proposed methodology, we consider a transportation network that is comprised of freeway segments that might include merge, diverge, weaving, and bottleneck sections. In order to derive benefit factors for the various origin–destination pairs on this network, we employ a simulation package (INTEGRATION) in combination with a composite function, which estimates the travel time variability along a trip that is comprised of links that include any of the four identified sections. The simulation results are actually recorded as generic look-up tables that can be used for any such section for the purpose of computing the associated benefit factor coefficients. Computational results are presented using data pertaining to a freeway section in San Antonio, Texas, as well as synthetic test cases, to demonstrate the effectiveness of the proposed approach, and to study the sensitivity of the quality of the solution to variations in the number of available readers.     

Development of 19-plex Y STR system and polymorphism studies in Pakistani population

For the development of 19-plex Y STR system and polymorphism studies in locl ethnic populations sixteen markers of non-recombining regions (NRY) of Y chromosome, which show high power of discrimination among individuals, were selected in this study. Blood samples (600) were e.ollected from the males of three most common castes of Pakistani population (Arnin, Awan and Rajput) with different parent lineages. Three markers (DYS385a/b, DYS389Ⅰ/Ⅱ and YCAⅡa/b) among 16 Y STRs are double-targeted regions of the Y chromosome and thus provide two polymorphie peaks for each respective primer set. These 16 Y-STRs were developed into Megaplex system for simultaneous amplification of all markers within the population. The overall power of discrimination observed in focused populations was 60.5%, 66.5% and 55% in Rajput, Awan and Arain casts respectively. This discrimination power will be helpful in haman identification for forensic casework studies including sexual assaults and paternity testing.