GPS-Based Highway Performance Monitoring Performance Monitoring Using GPS: Characterization of Travel Speeds on any Roadway Segment

Presented is a characterization of travel speed on any roadway segment based on probe vehicle position data. Most of the characterization is based position data obtained from GPS receivers because of their high precision and their increasing availability. Comparison is also made to Qualcomm’s Automatic Satellite Position Reporting (QASPR) system because of its long history (10+ years) of extensive use by the long-haul trucking industry. Described is the use of these data in conjunction with digital map representations of roadways with particular reference to ALK’s digital map database of North America. Two examples of the use of probe vehicle based GPS data to ascertain and monitor speed on roadway segments are presented. One is a demonstration of the monitoring of the speed performance of the various road segments that make up the Québec-Windsor corridor. Extensive GPS data from the first half of 2008 characterize the speed performance of the corridor by day-of-week and time-of-day. The second example also uses GPS probe vehicle data to assign a median speed , by direction, to all 31 million arcs of ALK’s digital map database of North America. Examples of that assignment are displayed in geographic bandwidth charts and a generic example of a fastest route computed based on the assigned median speeds is presented

Arroyo, S.

In transportation networks, it is more useful to think of costs on links as travel times as opposed to distances. Furthermore, while distances are usually constant, deterministic values, between nodes, travel times often vary substantially, as a result of incidents, road conditions, weather, traffic volume and drivers ' preferences, among others. Recent research has developed a variety of algorithms for routing in these non-deterministic networks, but less has been done in identifying the proper functional forms to describe these travel times distributions. Moreover, most of the routing algorithms rely on the assumption that travel time distributions are independent random variables between links. In this paper, recently available data obtained from drivers using in-vehicle route guidance systems is used to empirically analyze the behavior of travel times on the US road network. Normal, lognormal, gamma and Weibull distributions are fitted to these travel times and it is concluded that the lognormal model provides the better fit. The data is then used to test the assumption of independence between arcs. A road segment comprised of eight links is selected and the correlation between travel times on the links is obtained. The correlations for consecutive links are compared, as well as for links separated by one or more links. The issue of convoluting travel time distributions when these times are not independent is analyzed. For this purpose, Reciprocal Gamma distributions are used, which have been proven to represent the infinite sum of correlated lognormal distributions

The Effect of Augmented Driver Behavior on Freeway Traffic Flow

This paper investigates the possible virtue of the modification of longitudinal and lane-change behaviors of drivers by intelligent cruise control systems that augment individual driver behavior by enforcing minimum separation between vehicles. Such systems would not only reduce collisions but may also improve traffic flow by reducing the frequency of bottlenecks on freeways. This hypothesis is tested using a modified microsimulation of a length of freeway in Los Angeles County. A transit-oriented minimum time headway controller is compared to a traditional minimum separation intelligent cruise controller. The results show that using a fixed distance policy to control the separation tends to keep the flow more stable during peak periods and reduces travel times

Analysis, Characterization, and Visualization of Freeway Traffic Data in Los Angeles

Presented is an analysis of a large volume of readily available loop detector based traffic data for the Los Angeles and Ventura Counties. The data suggests that the daily temporal variation of congestion along any directional road segment can be characterized quite well by a 10-parameter function. The function is shown to be suitable for use in the classification of road segments, such as having morning but no afternoon or evening congestion, as well as for the purpose of improving real-time forecasts of congestion ahead for use in generating dynamic real-time minimum estimated time-of-arrival turn-by- turn navigation instructions. Automation of the process allows for the characterization of all of the Los Angeles and Ventura Counties and can be applied to any metropolitan area having similar data. Several interactive and dynamic visualization tools using Google Earth are also developed and presented

Getting the Goods Delivered in Dense Urban AreasA Snapshot of the Last Link of the Supply Chain

Data were analyzed from 74 Freight Mobility Interviews - surveys conducted with key transportation executives whose products and services are shipped into New York City\u27s central business district (CBD). Quantitative data collected included company profiles, defined by product category; kind of transportation service; type of distribution channel; characteristics of dispatched truck trip; and time and cost for last leg of trip. Major barriers to freight mobility identified by logistics/distribution/ transportation managers were widespread congestion, theft/vandalism, inadequate docking space, and insufficient curbside parking for commercial vehicles. Recommendations to increase productivity in the CBD included off-peak and extended delivery hours, additional truck parking zones, and incentives to upgrade docking areas. Barriers to freight mobility were consistent across industry sectors. Initiatives that have the potential to increase the efficiency of urban goods movement include improved law enforcement to deter theft/vandalism, information-based improvements such as accurate signage, the use of ITS technology and management systems to actively manage curbside commercial parking zones, and improved road maintenance. The nontraditional methodology developed for collecting urban freight mobility data provides process-oriented data that reflect changing supply chain strategies of private-sector shippers and carriers

Getting the Goods Delivered in Dense Urban Areas: a Snapshot of the Last Link of the Supply Chain

Data were analyzed from 74 Freight Mobility Interviews - surveys conducted with key transportation executives whose products and services are shipped into New York City\u27s central business district (CBD). Quantitative data collected included company profiles, defined by product category; kind of transportation service; type of distribution channel; characteristics of dispatched truck trip; and time and cost for last leg of trip. Major barriers to freight mobility identified by logistics/distribution/ transportation managers were widespread congestion, theft/vandalism, inadequate docking space, and insufficient curbside parking for commercial vehicles. Recommendations to increase productivity in the CBD included off-peak and extended delivery hours, additional truck parking zones, and incentives to upgrade docking areas. Barriers to freight mobility were consistent across industry sectors. Initiatives that have the potential to increase the efficiency of urban goods movement include improved law enforcement to deter theft/vandalism, information-based improvements such as accurate signage, the use of ITS technology and management systems to actively manage curbside commercial parking zones, and improved road maintenance. The nontraditional methodology developed for collecting urban freight mobility data provides process-oriented data that reflect changing supply chain strategies of private-sector shippers and carriers