Carlo Giacomo Prato

Applying Branch-and-Bound Technique to Route Choice Set Generation

An algorithm to solve explicitly the path enumeration problem is proposed. This algorithm is based on the branch-and-bound technique and belongs to the class of deterministic methods along with existing approaches that combine heuristic or randomization procedures with shortest-path search. The branch-and-bound algorithm is formulated, and a methodology is designed for the application of deterministic approaches to a real case study. Path sets generated with different methods are compared for behavioral consistency, namely, the ability to reproduce actual routes chosen by individuals driving habitually from home to work. Choice set compositions for modeling purposes are determined for the consistency of the path generation process with the observed behavior. Further, model estimates and performance for different route choice specifications are examined for both path set compositions. Results suggest that the proposed branch-and-bound algorithm generates realistic and heterogeneous routes, reproduces better the observed behavior of the interviewed drivers, and produces a good choice set for route choice model estimation and performance comparison.

Modeling the behavior of novice young drivers during the first year after licensure

Novice young drivers suffer from increased crash risk that translates into over-representation in road injuries. In order to effectively confront this problem, a better understanding of the driving behavior of novice young drivers and of its determinants is needed. This study analyzes the behavior of novice young drivers within a Graduated Driver Licensing (GDL) program. Data on driving behavior of 62 novice drivers and their parents, who voluntarily participated in this experiment, were collected using in-vehicle data recorders that calculate compound risk indices as measures of the risk taking behavior of drivers. Data were used to estimate a negative binomial model to identify major determinants that affect the driving behavior of young drivers during the first year after licensure. Estimation results suggest that the risk taking behavior of young drivers is influenced by gender, sensation seeking tendency, driving behavior of their parents, amount of supervised driving and level of parental monitoring.

Risk factors associated with bus accident severity in the United States: A generalized ordered logit model

INTRODUCTION Recent years have witnessed a growing interest in improving bus safety operations worldwide. While in the United States buses are considered relatively safe, the number of bus accidents is far from being negligible, triggering the introduction of the Motor-coach Enhanced Safety Act of 2011. METHOD The current study investigates the underlying risk factors of bus accident severity in the United States by estimating a generalized ordered logit model. Data for the analysis are retrieved from the General Estimates System (GES) database for the years 2005-2009. RESULTS Results show that accident severity increases: (i) for young bus drivers under the age of 25; (ii) for drivers beyond the age of 55, and most prominently for drivers over 65 years old; (iii) for female drivers; (iv) for very high (over 65 mph) and very low (under 20 mph) speed limits; (v) at intersections; (vi) because of inattentive and risky driving.

The Factor of Revisited Path Size: Alternative Derivation

The concept of path size attempts to capture correlations among routes in route choice modeling by including a correction term in the multinomial logit formulation. Several correction terms were proposed in the literature, yet no satisfactory derivation based on theoretical arguments is presented, raising doubts about the correct specification of the correction terms. This paper proposes the detailed and systematic derivation of a new formulation of the measure of path size and explicitly defines the assumptions involved in its derivation. The path size correction (PSC) factor results from the notion of aggregate alternative as well from the simplification of nested logit models. The new measure of path size offers a more natural interpretation of the correlation due to spatial overlap of alternative routes. Estimation of PSC-logit models in two real-world networks and calculation of predicted choice probabilities in synthetic networks allow comparison of the new path size measure with respect to the classic one. Estimates show similar performances between the models, and predictions illustrate better performances of the new version of the path size factor.

Aggravating and mitigating factors associated with cyclist injury severity in Denmark

INTRODUCTION Denmark is one of the leading cycling nations, where cycling trips constitute a large share of the total trips, and cycling safety assumes a top priority position in the agenda of policy makers. The current study sheds light on the aggravating and mitigating factors associated with cyclist injury severity on Danish roads by examining a comprehensive set of accidents involving a cyclist and a collision partner between 2007 and 2011. METHOD This study estimates a generalized ordered logit model of the severity of cyclist injuries because of its ability to accommodate the ordered-response nature of severity while relaxing the proportional odds assumption. RESULTS Model estimates show that cyclist fragility (children under 10 years old and elderly cyclists over 60 years of age) and cyclist intoxication are aggravating individual factors, while helmet use is a mitigating factor. Speed limits above 70-80 km/h, slippery road surface, and location of the crash on road sections are aggravating infrastructure factors, while the availability of cycling paths and dense urban development are mitigating factors. Heavy vehicle involvement and conflicts between cyclists going straight or turning left and other vehicles going straight are aggravating vehicle involvement factors. Practical applications: The results are discussed in the context of applied policies, engineering, and traffic management solutions for bicycle safety in Denmark.

Intrafamilial Transmission of Driving Behavior: Evidence from In-Vehicle Data Recorders

This study analyzes intrafamilial transmission of driving behavior by examining driving patterns of newly licensed young drivers and their family members as recorded over a period of 9 months using in-vehicle data recorders. Various maneuvers that the drivers undertook were identified in the measurements and used to compute risk indices for each driver during each month. The correlations between risk indices of drivers within the same family were studied. The results show intrafamilial transmission of driving behavior and reveal that this transmission evolves over time, as the behavior of young drivers is initially more closely related to that of their family members but gradually develops into a more differentiated personal driving style. Higher correlations are also found for specific maneuver types, such as braking and accelerating, and to a lesser extent for other maneuvers, such as speeding. The findings of the study indicate a need to carefully consider the role played by parents in the driving education of young adults and advising parents to exert control over their offsprings driving through positive modeling, and not only through well-designed commentary during driving.

Mapping patterns of pedestrian fatal accidents in Israel

This study intends to provide insight into pedestrian accidents by uncovering their patterns in order to design preventive measures and to allocate resources for identified problems. Kohonen neural networks are applied to a database of pedestrian fatal accidents occurred during the four-year period between 2003 and 2006. Results show the existence of five pedestrian accident patterns: (i) elderly pedestrians crossing on crosswalks mostly far from intersections in metropolitan areas; (ii) pedestrians crossing suddenly or from hidden places and colliding with two-wheel vehicles on urban road sections; (iii) male pedestrians crossing at night and being hit by four-wheel vehicles on rural road sections; (iv) young male pedestrians crossing at night wide road sections in both urban and rural areas; (v) children and teenagers crossing road sections in small rural communities. From the perspective of preventive measures, results suggest the necessity of designing education and information campaigns for road users as well as allocating resources for infrastructural interventions and law enforcement in order to address the identified major problems.

Cyclist-Motorist Crash Patterns in Denmark: A Latent Class Clustering Approach

Objective: The current study aimed at uncovering patterns of cyclist–motorist crashes in Denmark and investigating their prevalence and severity. The importance of implementing clustering techniques for providing a holistic overview of vulnerable road users’ crash patterns derives from the need to prioritize safety issues and to devise efficient preventive measures. Method: The current study focused on cyclist–motorist crashes that occurred in Denmark during the period between 2007 and 2011. To uncover crash patterns, the current analysis applied latent class clustering, an unsupervised probabilistic clustering approach that relies on the statistical concept of likelihood and allows partial overlap across clusters. Results: The analysis yielded 13 distinguishable cyclist–motorist latent classes. Specific crash patterns for urban and rural areas were revealed. Prevalent features that allowed differentiating the latent classes were speed limit, infrastructure type, road surface conditions, number of lanes, motorized vehicle precrash maneuvers, the availability of a cycle lane, cyclist intoxication, and helmet wearing behavior. After the latent class clustering, the distribution of cyclists’ injury severity within each cluster was analyzed. Conclusions: The latent class clustering approach provided a comprehensive and clear map of cyclist–motorist crash patterns. The results are useful for prioritizing and resolving safety issues in urban areas, where there is a significant share of cyclists potentially involved in multiple hazardous situations or where extensive bicycle sharing programs are planned.

Influence of the Built Environment on Pedestrian Route Choices of Adolescent Girls

We examined the influence of the built environment on pedestrian route selection among adolescent girls. Portable global positioning system units, accelerometers, and travel diaries were used to identify the origin, destination, and walking routes of girls in San Diego, California, and Minneapolis, Minnesota. We completed an inventory of the built environment on every street segment to measure the characteristics of routes taken and not taken. Route-level variables covering four key conceptual built environment domains (Aesthetics, Destinations, Functionality, and Safety) were used in the analysis of route choice. Shorter distance had the strongest positive association with route choice, whereas the presence of a greenway or trail, higher safety, presence of sidewalks, and availability of destinations along a route were also consistently positively associated with route choice at both sites. The results suggest that it may be possible to encourage pedestrians to walk farther by providing high-quality and stimulating routes.

Understanding traffic crash under-reporting: Linking police and medical records to individual and crash characteristics

ABSTRACT Objective: This study aligns to the body of research dedicated to estimating the underreporting of road crash injuries and adds the perspective of understanding individual and crash factors contributing to the decision to report a crash to the police, the hospital, or both. Method: This study focuses on road crash injuries that occurred in the province of Funen, Denmark, between 2003 and 2007 and were registered in the police, the hospital, or both authorities. Underreporting rates are computed with the capture–recapture method, and the probability for road crash injuries in police records to appear in hospital records (and vice versa) is estimated with joint binary logit models. Results: The capture–recapture analysis shows high underreporting rates of road crash injuries in Denmark and the growth of underreporting not only with the decrease in injury severity but also with the involvement of cyclists (reporting rates of about 14% for serious injuries and 7% for slight injuries) and motorcyclists (reporting rates of about 35% for serious injuries and 10% for slight injuries). Model estimates show that the likelihood of appearing in both data sets is positively related to helmet and seat belt use, number of motor vehicles involved, alcohol involvement, higher speed limit, and females being injured. Conclusions: This study adds significantly to the literature about underreporting by recognizing that understanding the heterogeneity in the reporting rate of road crashes may lead to devising policy measures aimed at increasing the reporting rate by targeting specific road user groups (e.g., males, young road users) or specific situational factors (e.g., slight injuries, arm injuries, leg injuries, weekend).