Ramakrishna R Tadi

Using GPS Technology to Relate Macroscopic and Microscopic Traffic Parameters

Traffic congestion on todays freeways is a serious problem, causing significant delays for both passengers and goods. Freeway traffic congestion also results in increased vehicle emissions; however, this increase has not been quantified using current vehicle emission models. Current models use emission factors based on driving cycles that do not properly represent freeway driving characteristics. This paper presents a new methodology for relating the macroscopic speed, flow, and density parameters measured by traffic sensors with statistics of microscopic driving traces under different levels of congestion. This approach can be used to better estimate freeway emissions when combined with an appropriate modal emissions model. Preliminary experimentation has been carried out with a vehicle equipped with global positioning system (GPS) instrumentation, allowing for precise localization in both space and time. With the GPS, second-by-second velocity traces are acquired and matched with simultaneously measured freeway traffic data obtained by embedded traffic sensors. Statistical measures of velocity variation are derived from the velocity traces and are functionally related to the macroscopic traffic parameters of speed, flow, and density. Given a known distribution of vehicle types, models, and model years, vehicle emissions can be related to these statistical measures of velocity variation using a modal emission model, and, thus given speed-flow-density measures of freeway traffic, localized emissions estimates can be made.

Emissions Comparison Between Truck and Rail: Case Study of California I-40

A comprehensive goods movement study of the California Interstate 40 corridor (from Barstow to Needles) has recently been completed. This study attempted to characterize goods movement in the region, perform a corridor emissions analysis, and make recommendations in terms of capacity and improvements, as well as economic feasibility of using rail in conjunction with trucks for goods movement. The emissions analysis of goods movement along the I-40 corridor is examined, specifically emissions of carbon monoxide, hydrocarbons, nitrogen oxides (NOx), and particulate matter associated with both truck and rail traffic. Heavy-duty diesel truck emissions are estimated using truck activity data recorded along the corridor. A unique methodology is used to calculate these truck emissions, incorporating road grade factors and determining engine load on a link-by-link basis. These emissions are then compared with the emissions associated with freight trains that travel along this I-40 corridor. On the basis of curren...

Emissions Analysis of Southern California Metrolink Commuter Rail

The Southern California Regional Rail Authority began constructing a new commuter rail system called Metrolink in October 1992. When complete, the Metrolink system will form the nations sixth largest commuter rail system and is expected to alleviate congestion and help obtain better air quality. To estimate the air quality impact, emissions of CO, HC, NOx, and PM associated with an automobile-only—based commute and a Metrolink-based commute from Riverside to Los Angeles are compared. Analysis of the Metrolink-based commuting scenario includes the emissions from the home-to-station automobile trip and the Metrolink diesel locomotive emissions. Essential data for the automobile emissions modeling process were obtained through a survey of Metrolink passengers and through remote emissions sensing of Metrolink passenger vehicles. Train emissions were estimated using emission rate data provided by recent diesel locomotive studies. Results indicated that at current ridership levels there is a reduction in total...

Different Types of High-Occupancy Vehicle Access Control: Comparative Analysis of Empirical Capacities

High-occupancy vehicle (HOV) facilities have been widely implemented in the United States as a way to improve mobility, trip time reliability, and air quality of freeway systems. In California there are two types of HOV facilities, namely, limited access and continuous access with part-time or full-time operation. This paper presents a framework for comparing the mobility performance of the types of HOV facilities on the basis of regression analyses using a California data set as a case study. Parametric regression models were developed to explain empirical freeway capacity as a function of a set of explanatory variables including the type of HOV access. Modeling results consistently indicated that freeway segments with limited-access HOV lanes would have had higher overall capacities than those of continuous-access HOV facilities, everything else being equal. In addition, the proposed framework can be applied well to the analyses on other types of managed lanes.