Robert B. Noland

TRAVEL TIME VARIABILITY: A REVIEW OF THEORETICAL AND EMPIRICAL ISSUES.

Over the past several years a number of research projects have attempted to empirically measure behavioural responses to changes in travel time variability. These have generally been built on theoretical models of scheduling choice that account for changes in departure time in response to the expected costs associated with variability. This paper reviews both the theory and empirical results of several projects that estimated coefficients on various measures of variability using stated preference techniques. Gaps in the understanding of these issues are identified and discussed.

AN ANALYSIS OF MOTORCYCLE INJURY AND VEHICLE DAMAGE SEVERITY USING ORDERED PROBIT MODELS

PROBLEM Motorcycles constitute about 19% of all motorized vehicles in Singapore and are generally overrepresented in traffic accidents, accounting for 40% of total fatalities. METHOD In this paper, an ordered probit model is used to examine factors that affect the injury severity of motorcycle accidents and the severity of damage to the vehicle for those crashes. Nine years of motorcycle accident data were obtained for Singapore through police reports. These data included categorical assessments of the severity of accidents based on three levels. Damage severity to the vehicle was also assessed and categorized into four levels. Categorical data of this type are best analyzed using ordered probit models because they require no assumptions regarding the ordinality of the dependent variable, which in this case is the severity score. Various models are examined to determine what factors are related to increased injury and damage severity of motorcycle accidents. RESULTS Factors found to lead to increases in the probability of severe injuries include the motorcyclist having non-Singaporean nationality, increased engine capacity, headlight not turned on during daytime, collisions with pedestrians and stationary objects, driving during early morning hours, having a pillion passenger, and when the motorcyclist is determined to be at fault for the accident. Factors leading to increased probability of vehicle damage include some similar factors but also show some differences, such as less damage associated with pedestrian collisions and with female drivers. In addition, it was also found that both injury severity and vehicle damage severity levels are decreasing over time.

THE EFFECT OF INFRASTRUCTURE AND DEMOGRAPHIC CHANGE ON TRAFFIC-RELATED FATALITIES AND CRASHES: A CASE STUDY OF ILLINOIS COUNTY-LEVEL DATA

This paper presents analyses of data from the Highway Safety Information System (HSIS) for the State of Illinois. Our analyses focuses on whether various changes in road network infrastructure and geometric design can be associated with changes in road fatalities and reported accidents. We also evaluate models that control for demographic changes. County-level time-series data is used and fixed effect negative binomial models are estimated. Results cannot confirm the hypothesis that changes in road infrastructure and geometric design have been beneficial for safety. Increases in the number of lanes appears to be associated with both increased traffic-related accidents and fatalities. Increased lane widths appears to be associated with increased fatalities. Increases in outside shoulder width appear to be associated with a decrease in accidents. Inclusion of demographic results does not significantly change these results but does capture much of the residual time trend in the models. Potentially mis-leading results are found when the time trend is not included. In this case a negative association between vertical curvature and both accidents and fatalities. No statistical association with changes in safety is found for median widths, inside shoulder widths, and horizontal and vertical curvature.

RELATIONSHIPS BETWEEN HIGHWAY CAPACITY AND INDUCED VEHICLE TRAVEL

The theory of induced travel demand asserts that increases in highway capacity will induce additional growth in traffic. This can occur through a variety of behavioral mechanisms including mode shifts, route shifts, redistribution of trips, generation of new trips, and long run land use changes that create new trips and longer trips. The objective of this paper is to statistically test whether this effect exists and to empirically derive elasticity relationships between lane miles of road capacity and vehicle miles of travel (VMT). An analysis of US data on lane mileage and VMT by state is conducted. The data are disaggregated by road type (interstates, arterials, and collectors) as well as by urban and rural classifications. Various econometric specifications are tested using a fixed effect cross-sectional time series model and a set of equations by road type (using Zellners seemingly unrelated regression). Lane miles are found to generally have a statistically significant relationship with VMT of about 0.3-0.6 in the short run and between 0.7 and 1.0 in the long run. Elasticities are larger for models with more specific road types. A distributed lag model suggests a reasonable long-term lag structure. About 25% of VMT growth is estimated to be due to lane mile additions assuming historical rates of growth in road capacity. The results strongly support the hypothesis that added lane mileage can induce significant additional travel.

TRAFFIC FATALITIES AND INJURIES: THE EFFECT OF CHANGES IN INFRASTRUCTURE AND OTHER TRENDS

An analysis of how various road infrastructure improvements affect traffic-related fatalities and injuries is conducted while controlling for other factors known to affect overall safety. The road infrastructure elements analysed include total lane miles, the fraction of lane miles in different road categories (interstates, arterial, and collector roads), the average number of lanes for each road category, and lane widths for arterials and collector roads. Other variables that are controlled for in the study include total population, population age cohorts, per capita income, per capita alcohol consumption, seat-belt legislation (and seat-belt usage), and a proxy variable that represents underlying changes in medical technology. The data used is a cross-sectional time-series database of US states and is analysed using a fixed effects negative binomial regression that accounts for heterogeneity in the data. Data from all 50 states over 14 years is used. Results strongly refute the hypothesis that infrastructure improvements have been effective at reducing total fatalities and injuries. While controlling for other effects, it is found that demographic changes in age cohorts, increased seat-belt use, reduced alcohol consumption and increases in medical technology have accounted for a large share of overall reductions in fatalities.

A review of the evidence for induced travel and changes in transportation and environmental policy in the US and the UK

Abstract This paper reviews recent research into the demand inducing effects of new transportation capacity. We begin with a discussion of the basic theoretical background and then review recent research both in the UK and the US. Results of this research show strong evidence that new transportation capacity induces increased travel, both due to short run effects and long run changes in land use development patterns. While this topic has long been debated amongst transportation planners, the fundamental hypothesis and theory has long been apparent in studies of transportation economics and planning that evaluated different issues (e.g. travel time budgets and urban economic development effects). We summarize much of this work and relate the theoretical issues to recent empirical research. We then proceed to examine recent changes in transportation and environmental policy in the US and the UK. The role of the new knowledge of induced travel effects would be expected to lead to changes in the conduct of transportation and environmental policy. Changes in policy and implementation of those policies are still occurring and we provide some suggestions on how to move forward in these areas.

A High Accuracy Fuzzy Logic Based Map Matching Algorithm for Road Transport

Recent research on map matching algorithms for land vehicle navigation has been based on either a conventional topological analysis or a probabilistic approach. The input to these algorithms normally comes from the global positioning system (GPS) and digital map data. Although the performance of some of these algorithms is good in relatively sparse road networks, they are not always reliable for complex roundabouts, merging or diverging sections of motorways, and complex urban road networks. In high road density areas where the average distance between roads is less than 100 m, there may be many road patterns matching the trajectory of the vehicle reported by the positioning system at any given moment. Consequently, it may be difficult to precisely identify the road on which the vehicle is travelling. Therefore, techniques for dealing with qualitative terms such as likeliness are essential for map matching algorithms to identify a correct link. Fuzzy logic is one technique that is an effective way to deal with qualitative terms, linguistic vagueness, and human intervention. This article develops a map matching algorithm based on fuzzy logic theory. The inputs to the proposed algorithm are from GPS augmented with data from deduced reckoning sensors to provide continuous navigation. The algorithm is tested on different road networks of varying complexity. The validation of this algorithm is carried out using high precision positioning data obtained from GPS carrier phase observables. The performance of the developed map matching algorithm is evaluated against the performance of several well-accepted existing map matching algorithms. The results show that the fuzzy logic-based map matching algorithm provides a significant improvement over existing map matching algorithms both in terms of identifying correct links and estimating the vehicle position on the links.

AN EXTENDED KALMAN FILTER ALGORITHM FOR INTEGRATING GPS AND LOW COST DEAD RECKONING SYSTEM DATA FOR VEHICLE PERFORMANCE AND EMISSIONS MONITORING

This paper describes the features of an extended Kalman filter algorithm designed to support the navigational function of a real-time vehicle performance and emissions monitoring system currently under development. The Kalman filter is used to process global positioning system (GPS) data enhanced with dead reckoning (DR) in an integrated mode, to provide continuous positioning in built-up areas. The dynamic model and filter algorithms are discussed in detail, followed by the findings based on computer simulations and a limited field trial carried out in the Greater London area. The results demonstrate that use of the extended Kalman filter algorithm enables the integrated system employing GPS and low cost DR devices to meet the required navigation performance of the device under development.

Estimating Trip Generation of Elderly and Disabled People: Analysis of London Data

The aging of populations has implications for trip-making behavior and the demand for special transport services. The London Area Travel Survey 2001 is analyzed to establish the trip-making characteristics of elderly and disabled people. Ordinal probit models are fitted for all trips and for trips by four purposes (work, shopping, personal business, and recreational), with daily trip frequency as the latent variable. A log-linear model is used to analyze trip length. A distinction must be made between young disabled, younger elderly, and older elderly people. Retired people initially tend to make more trips, but as they become older and disabilities intervene, trip making tails off. Household structure, income, car ownership, possession of a drivers license, difficulty walking, and other disabilities are found to affect trip frequency and length to a greater or lesser extent.

Analysis of Metropolitan Highway Capacity and the growth in vehicle miles of travel

A number of recent studies have examined the hypothesis of induced travel in an attempt to quantify the phenomenon (Hansen & Huang 1997; Noland, forthcoming). No study has yet attempted to adjust for potential simultaneity bias in the results. This study addresses this issue by the use of an instrumental variable (two stage least squares) approach. Metropolitan level data compiled by the Texas Transportation Institute for their annual congestion report is used in the analysis and urbanized land area is used as an instrument for lane miles of capacity. While this is not an ideal instrument, results still suggest a strong causal relationship but probably that most previous work has had an upward bias in the coefficient estimates. The effect of lane mile additions on VMT growth is forecast and found to account for about 15% of annual VMT growth with substantial variation between metropolitan areas. This effect appears to be closely correlated with percent growth in lane miles, suggesting that rapidly growing areas can attribute a greater share of their VMT growth to growth in lane miles.