The Impacts of Congestion on Commercial Vehicle Tours Characteristics and Costs

Congestion is a common phenomenon in all major cities of the world. Increased travel time and uncertainty brought about by congestion impacts the efficiency of logistics operations. Recent studies indicate that a significant proportion of commercial vehicle kilometers traveled (VKT) and vehicle hours traveled (VHT) are generated by trip-chains or multi-stop tours. This paper presents research demonstrating the impact of congestion on multi-stop tours in urban areas. An analytical model, numerical experiments, and real-world tour data are used to understand the impact of congestion on tour characteristics, carriers? costs, VKT, and VHT. This research shows that travel time/distance between customer and depot is a crucial factor that exacerbates the negative impacts of congestion. Travel time variability is not as significant when the travel time between the depot and the customers is small in relation to the maximum tour duration and when the routes are not highly constrained. As congestion increases, the number of vehicles needed to complete the tour also increases. This is accompanied by an increase in the percentage of total driving time and the average distance travelled per customer. Congestion impacts on carriers? costs are also considerable since congestion not only increases carriers? operating costs but also affects carriers? cost structure. As congestion worsens the relative weight of labor costs ? wages and overtime ? escalates. This paper categorizes tours into three classes based on tour efficiency and the relative weight of time and distance related costs. These are intuitive and valuable tools to monitor congestion, represent real-world tour data, and classify tours in regards to their sensitivity to congestion

Modeling the Impact of Technological Changes on Urban Commercial Trips by Commercial Activity Routing Type

An array of noteworthy developments in logistics practice has taken place without an equivalent and comprehensive development in urban freight transportation modeling. Part of the problem is the lack of deep understanding of the workings of distribution processes in relation to the generation of truck traffic. In this paper it is emphasized the role and importance that distribution network size, and information and communication technology have on the truck traffic flows that materializes as the supply chain that flows over the public infrastructure. This paper develops the concept of commercial activity routing types that characterize the interplay between transportation demand requests and routing characteristics. This research contributes to the field proposing a novel and detailed characterization of truck flows in a supply chain context. Using well-known yet simple models and formulas from vehicle routing, operations research, and management science literature, we derive behavioral insights about distributors and carriers’ routing and order sizing decisions, as routing constraints and second order effects are important drivers of truck flows. The main contribution is to bring a new commercial activity-routing perspective and deeper level of operational decision-making analysis to cope with the intricacies of freight transportation modeling

Oregon Freight Data Mart

Increasing freight volumes are adding pressure to the Oregon transportation system. Monitoring the performance of the transportation system and freight movements is essential to guarantee the economic development of the region, the efficient allocation of resources, and the quality of life of all Oregonians. Freight data is expensive to collect and maintain. Confidentiality issues, the size of the datasets, and the complexity of freight movements are barriers that preclude the easy access and analysis of freight data. Data accessibility and integration is essential to ensure successful freight planning and consistency across regional partner agencies and planning organizations. In relation to Internet-based mapping technology in freight data collection and planning, the main objectives of this project are: (a) address implementation issues associated with data integration, (b) present a system architecture to leverage existing publically-available interfaces and web applications to accelerate product development and reduce costs, (c) describe an existing web-based mapping prototype and its capabilities, (d) state lessons learned and present suggestions to streamline the integration and visualization of freight data, and (e) discuss load-time and display quality issues associated with the visualization of transportation data on internet-based mapping applications. The strategies and methodologies described in this report are equally applicable to the display of areas such as states or counties as well as linear data such linear data such as highways, waterways, and railways. Despite data integration challenges, Internet-based mapping provides a cost effective and appealing tool to store, access, and communicate freight data as well as enhance our understanding of freight issues. Institutional barriers, not technology, are the most demanding hurdles to widely implementing a freight data web-based mapping application in the near future

Evaluation of the Performance of the Sydney Coordinated Adaptive Traffic System (SCATS) on Powell Boulevard in Portland, OR

The Sydney Coordinated Adaptive Traffic System (SCATS) is used to mitigate traffic congestion along urban arterial corridors. Although there has been research on SCATS\u27 performance, this report combines three different areas of research about SCATS that are not known to be represented in any research literature. These include: (a) the relationship between SCATS, traffic volumes, and Transit Signal Priority (TSP); (b) between TSP and traffic conditions; and (c) the correlation between signal timing and air quality; in particular, human exposure to the air pollutant PM2.5 at intersections. In addition, this research looked at the key factors affecting transit user exposure to traffic-related pollutants at bus shelters. All areas of study present the results of statistical tests and regressions to determine SCATS or traffic variables impacts. SCATS did show statistically significant improvements regarding traffic speeds at one minor intersection, even when traffic volumes showed a statistically significant improvement. At a major intersection, results were mixed and not conclusive. Overall, it was determined that the improvements available through SCATS vary depending on the time of day and the direction of travel. TSP was not negatively affected by SCATS. In controlling for both priority and traffic conditions, each were shown to have a distinguished and significant impact on bus travel time. Non-priority signals had a much greater impact on travel time than priority signals (11.0 and 0.6 seconds for the corridor model, respectively). In controlling for both priority and traffic conditions, each were shown to have a distinguished and significant impact on travel time. Utilizing a regression model, results in an intuitive ranking of the intersections’ delay was produced; major intersections with high traffic volumes on crossing streets are likely to not experience TSP benefits. To a high degree, this research has shown that pedestrian exposure can be considered as an outcome of traffic-signal timing decisions made by cities and counties. The statistical results have shown the high impact that signal timing and queuing have on pedestrian level exposure. Heavy vehicle volume was a significant variable as well as the presence of buses. The reduction of bus idling time through more efficient operations and transit-signal priority is likely to reduce pedestrian and transit users\u27 pollution exposure levels. Longer green times along the main corridor are able to significantly reduce particulate matter for transit users and pedestrians waiting at the sidewalk of the intersection, whereas time allocated to cross the street increases queuing and exposure along the main corridor. The impact of heavy-duty diesel engines is also clear. The reduction of bus idling time through more efficient operations and transit-signal priority is likely to reduce pedestrian and transit users\u27 pollution exposure levels. Transit agencies can also reduce pollution significantly by improving the efficiency and cleanliness of their engines. TriMet (the local transit agency) initiatives to improve fuel efficiency by installing EMP engine-cooling devices not only improve fuel efficiency, but also air quality. Finally, significant reductions in transit users’ exposure to traffic-related pollution can be made at bus stops by properly orienting the shelter and by reducing bus idling

Modeling and Analyzing the Impact of Advanced Technologies on Transit Performance Measures in Arterial Corridors

Transportation and transit agencies have implemented advanced technologies like transit signal priority (TSP) and Sydney Coordinated Adaptive Traffic System (SCATS) to reduce travel times and improve reliability. However, due to the lack of detailed empirical data, the joint impact of these factors and improvement strategies on bus travel time has not been studied at the stop-to-stop segment level. With the aim of assessing the performance of an existing TSP/SCATS system, this study had access to a unique set of high-resolution bus and traffic signal data. Novel algorithms and performance measures to measure TSP performance are proposed. Results indicate that a timely and effective TSP system requires a high degree of sophistication, monitoring and maintenance. Empirical data suggest that most TSP phase adjustments were granted in time (i.e., within a cycle) to buses that requested priority, but that only a small proportion resulted in reduced delay. In this study, many green extension phases were granted late, making them less effective than early green signal phases. Despite this, the TSP system did not increase delays for passengers and vehicles when side-street traffic is also considered

Empirical Analysis of Bus Bunching Characteristics Based on Bus AVL/APC Data

Bus bunching takes place when headways between buses are irregular. Bus bunching is associated with longer waiting times for riders, overcrowding in some buses, and an overall decrease on the level of service and capacity. Understanding the temporal and spatial characteristics and the causes and effects of bus bunching incidents from archived bus data can greatly aid transit agencies to develop efficient mitigation strategies. This paper presents methods to identify and visualize specific time periods and segments where bus bunching incidents occur based on automatic vehicle location (AVL) and automatic passenger count (APC) data. The paper also proposes methods that help analyze the causes and effects of bus bunching based on AVL/APC data. Temporal and spatial distributions of bus bunching events indicate high concentration during high frequency service hours and segments, and increasing concentration toward downstream. Time point bus stops can help reduce bus headway variability but with limited capability. Results indicate that irregular departure headway at the initial stop is the key cause of bus bunching rather than downstream traffic conditions and passenger demand uncertainty. A bus departure headway control at the initial stop of high frequency service zone is highly recommended, and a switch from schedule-based control to headway-based control strategy at time point stops in high frequency service zone is suggested

The Application of Smart Phone, Weight-Mile Truck Data to Support Freight-Modeling, Performance Measures and Planning

Oregon is one of the few states that currently charge a commercial truck weight-mile tax (WMT). The Oregon Department of Transportation (ODOT) has developed a data-collection system – Truck Road Use Electronics (TRUE) – to simplify WMT collection. The TRUE system includes a smart phone application that collects and records Global Positioning System (GPS) data. The TRUE data has enormous advantages over GPS data used in previous research due to its level of geographic detail and the potential to also integrate trip origin and destination, vehicle class, and commodity-type data. This research evaluates the accuracy of the TRUE data and demonstrates its use for significant ODOT ancillary applications. Specifically, ancillary applications that address ODOT freight modeling, performance measures, and planning needs are explored. The use of the data for highly accurate trip-generation rates and mobility performance measures is demonstrated. In addition, it is shown that the TRUE data has strong potential to be used for safety, accessibility and connectivity, system condition and environmental stewardship performance measures. The potential use of the TRUE data for emissions estimates that take into account truck-type details, truck weight and detailed speed profiles is considered. Results indicate that TRUE data, integrated with ODOT weigh-in-motion (WIM) data, will greatly improve the accuracy of emission estimates at the project and regional level. This research confirms the potential use of the TRUE data for significant ancillary applications and demonstrates the regional value of the TRUE data to enhance existing freight modeling, performance measures and planning

Value of Travel Time Reliability Part II: A Study of Tradeoffs Between Travel Reliability, Congestion Mitigation Strategies and Emissions

Capacity, demand, and vehicle based emissions reduction strategies are compared for several pollutants employing aggregate US congestion and vehicle fleet condition data. We find that congestion mitigation does not inevitably lead to reduced emissions; the net effect of mitigation depends on the balance of induced travel demand and increased vehicle efficiency that in turn depend on the pollutant, congestion level, and fleet composition. In the long run, capacity-based congestion improvements within certain speed intervals can reasonably be expected to increase emissions of CO2e, CO, and NOx through increased vehicle travel volume. Better opportunities for emissions reductions exist for HC and PM2.5 emissions, and on more heavily congested arterials. Advanced-efficiency vehicles with emissions rates that are less sensitive to congestion than conventional vehicles generate less emissions co-benefits from congestion mitigation

Commercial vehicle tour data collection using passive GPS technology: Issues and potential applications

In mid-2006 a GPS survey of commercial vehicles was piloted in Melbourne, Australia to support a major update of freight data and modelling capabilities in the metropolitan region. This survey marked the first of its kind in Australia, and to the best of the authors’ knowledge, one of the first world-wide. This paper presents the issues surrounding the collection and use of GPS data as a method to provide information on commercial vehicle tours within an urban setting. The paper focuses on passive GPS methods where the truck driver’s involvement in the data collection effort is minimal. We address (a) implementation issues with the data collection, (b) the algorithms used to process the raw GPS data into meaningful trip tour information, (c) pilot survey data tour results, and (d) potential uses and limitations of passive GPS technology in urban freight modelling and planning. Despite processing challenges, GPS provides an appealing method to enrich commercial vehicle data collection and enhance our understanding of on-road behaviour. As increasing numbers of commercial vehicles become equipped with GPS receivers, we argue only privacy concerns remain as a major barrier to gathering and using such data on a wide-spread basis in the future

Practical Approximations to Quantify the Impact of Time Windows and Delivery Sizes on Freight VMT in Urban Areas

This paper studies approximations to the average length of Vehicle Routing Problems (VRP). The approximations are valuable for strategic and planning analysis of transportation and logistics problems. The research focus is on VRP with varying number of customers, demands, and locations. This modeling environment can be used in transport and logistics models that deal with a distribution center serving an area with daily variations in the demand. The routes are calculated daily based on what freight is available. New approximations and experimental settings are introduced. Average distance travelled is estimated as a function of the number of customers served and the number of routes needed. Approximations are tested in instances with different customer spatial distributions, demand levels, number of customers, and time windows, Regression results indicate that the proposed approximations can reasonably predict the average length of VRP problems in randomly generated problems and real urban networks