Intersection Types Research Articles

Determinants of bicycle crashes at urban signalized intersections

Problem: Bicycle volumes are increasing in many regions worldwide leading to higher relevance of an in-depth understanding of bicyclist safety mechanisms. Detailed studies on bicyclist safety that consider exposure and distinguish by intersection category and crash types are missing for urban signalized intersections, which are of particular relevance for bicyclist safety. Method: Based on a comprehensive dataset of motorist and bicyclist volumes and infrastructure characteristics for a sample of 269 signalized intersections in two German cities, we utilize a top-down approach to analyze firstly, bicycle crashes of all types and secondly, bicycle crashes by type including turning, right-of-way and loss-of-control. A combination of descriptive statistics and Accident Prediction Models (APM) are applied as analysis methods. Results: Bicycle volumes are relevant for all types of intersections and crashes, whereas the effect of motor vehicle volumes differ between these different applications. The separation of bicyclists from motor vehicles in time and space increases their safety but also leads to behavioral adaption and risk compensation. The likelihood of right-of-way crashes even increases with more separation in the signaling scheme. The main predictor for loss-of-control crashes in terms of infrastructure are tram tracks. Summary: This study provides insights on relevant determinants of bicycle crashes at urban signalized intersections at several levels of detail. Exposure variables as well as the physical separation of bicyclists from motor vehicles show consistent effects on bicycle crash numbers whereas the effects of signaling differ between crash types. Practical Applications: The different types of intersections and crashes follow each specific mechanism of bicyclist safety. The separation of bicyclists and motorists in time and space are paramount at intersections with high bicycle volumes. Risk compensation such as red light running becomes more important as intersections get smaller and motor vehicle volumes decrease.

Impact of Roundabout Metering on the Operational Performance of Roundabout: A Case Study of Jawalakhel, Nepal

Roundabout is a type of intersection which improves efficiency and safety performance compared to other types of intersection. Jawalakhel roundabout serves to minimize the resulting conflict between the vehicles; however, due to increasing vehicular movements it is facing challenges like delay, poor level of service and traffic congestion. Classified traffic volume study through videographic survey is carried out and the volume is converted to passenger car unit at morning and evening peak period. SIDRA intersection V 8.0 was used for simulation and analysis of intersection’s performance. The performance is accessed in terms of delay, degree of saturation, level of service & 95% of queue vehicles were calculated for existing condition. As the operational performance was found unsatisfactory with level of service F; alternatives were considered. Among alternatives, roundabout metering on two approaches was adopted and their respective impact on the operational performance was analyzed. The overall roundabout improvement was not observed on two alternates of roundabout metering.

RISKY BEHAVIOURS AMONG DELIVERY RIDERS AT SIGNALIZED INTERSECTIONS IN MALAYSIA

The increasing number of food delivery riders, known as P-hailing riders, has increased the number of traffic crashes involving this group. The high demand for online orders and delivery time constraints causes the delivery riders to engage in risky riding behaviours during delivery. Thus, there is a need to study this alarming problem before it becomes more serious. This study aims to determine factors influencing risky behaviours among delivery riders at signalized intersections. A roadside observation was conducted in the month of October 2022 at Subang Jaya, Selangor. A total of 19,803 delivery riders were observed for four days observations at two signalized T- and two cross-signalized intersections. A bivariate analysis (logistic regression) was applied to determine the relationship between seven risky behaviours (unfastened helmet, not wearing shoes, incomplete set of side mirrors, red light running, mobile phone use, stopping after stop lines, and abrupt lane change) with five explanatory variables including the day of the week, time of the day, weather condition, type of intersection and approach road. The result shows that red light running, and mobile phone use is more likely to occur during the weekend. Clear weather increases risky behaviours such as red light running, using a mobile phone, and abrupt lane changes. The findings of this study are useful as input to the related authorities in developing programs to decrease the number of crashes involving food delivery riders.

Typing Records, Maps, and Structs

Records are finite functions from keys to values. In this work we focus on two main distinct usages of records: structs and maps. The former associate different keys to values of different types, they are accessed by providing nominal keys, and trying to access a non-existent key yields an error. The latter associate all keys to values of the same type, they are accessed by providing expressions that compute a key, and trying to access a non-existent key usually yields some default value such as Null or nil. Here, we propose a type theory that covers both kinds of usage, where record types may associate to different types either single keys (as for structs) or sets of keys (as for maps) and where the same record expression can be accessed and used both in the struct-like style and in the map-like style we just described. Since we target dynamically-typed languages our type theory includes union and intersection types, characterized by a subtyping relation. We define the subtyping relation for our record types via a semantic interpretation and derive the decomposition rules to decide it, define a backtracking-free subtyping algorithm that we prove to be correct, and provide a canonical representation for record types that is used to define various type operators needed to type record operations such as selection, concatenation, and field deletion.

Mixed-Effects Zero-Inflated Negative Binomial Crash Predictive Models for Unsignalized Intersections along Two-Lane Highways with Minor Roads Operating with Very Low Traffic Volumes

Current and past investigations into road accidents have mainly focused on high-volume roads which have experienced a significant number of collisions. However, low-volume roads also record crash data which merit analysis to understand the causes of accidents and find potential countermeasures. This study focuses on unsignalized intersections linking major highways and minor stop-controlled local roads that operate with very low traffic volumes. In this scenario, an over-abundance of zero observations has to be accounted for. To address this issue, zero-inflated Poisson and negative binomial regression models have been calibrated and analyzed to find the geometric and operational factors which contribute most to the crash rate. Random effects have also been considered to account for unobserved heterogeneity inherent in the grouping of intersections within the database. The results indicate that the mixed-effect negative binomial model had the best prediction performance. Developing models for subgroups of crashes, for example, failure-to-yield and other types of crash, resulted in better prediction performance. The major road’s average annual daily traffic and the surface type (i.e., paved or unpaved) of minor road approaches had a significant effect on the frequency of all crash types. The type of intersection (three- or four-legs), the skew angle of intersection, deviation angle of near curves, and operating speed differences also had statistically significant effects on the frequency of crashes that do not include the failure-to-yield.

Impacts of Red-Light Enforcement Cameras on Start-Up Lost Time at Urban Signalized Intersections

Red-light cameras (RLCs) are used extensively in numerous countries as a tool to regulate traffic and enhance safety at signalized urban intersections. In this regard, a case study conducted in the Dammam metropolitan area has uncovered a potential unintended consequence of RLC usage. The presence of RLCs can lead to an increase in first-vehicle reaction time (FVRT), resulting in a higher start-up lost time (SLT) at these intersections. To investigate this phenomenon, data were collected from two distinct types of locations wherein three intersections were equipped with RLCs and three were without RLCs. A total of 311 observations or cycles were recorded, with 72 belonging to the first type and 239 belonging to the second type. The analysis revealed that the average FVRT for the intersections with RLCs was 4.27 s. For those without RLCs, it was slightly lower, at 3.68 s. Similarly, the average SLT for the RLC-equipped intersections was 3.63 s, while it measured 2.73 s at the non-RLC intersections. These findings highlighted a noticeable disparity in SLT between the two types of intersections. Further statistical analysis confirmed the existence of significant differences in the means of SLT and FVRT for the two categories of intersections. Specifically, for every 1-second delay in FVRT per location, the total SLT at intersections with RLCs increased by 7.5 s. These results underscored the potential impact of RLCs on traffic efficiency and supported the recommendation for implementing a red-light countdown system at intersections with RLCs. Such a system has the potential to reduce the FVRT and enhance traffic flow. These findings emphasize a careful consideration of the implications of RLC implementation and provide valuable insights for traffic management authorities.

Kinematic cues in driver-pedestrian communication to support safe road crossing

ObjectiveRight-of-way negotiation between drivers and pedestrians often relies on explicit (e.g., waving) and implicit (e.g., kinematic) cues that signal intent. Since effective driver-pedestrian communication is important for reducing safety-relevant conflicts, this study uses information theory to identify vehicle kinematic behaviors that provide the greatest information gain and serve as cues for pedestrians to cross safely. Data SourcesA driver-pedestrian dataset with 348 interactions was extracted from a large naturalistic driving data collection effort. It includes 325 instances of a pedestrian crossing the vehicle’s path and 23 instances in which the vehicle did not yield to a pedestrian. Kinematic data were collected from the vehicle’s CAN. Pedestrian behaviors, driver cues, and contextual information were manually annotated from a forward-facing video. MethodsWe used kernel density estimation to quantify the probabilities of vehicle acceleration, speed, and standard deviation of speed, for a given vehicle position and pedestrian behavior. Mutual information was then calculated between the estimated distributions given a pedestrian behavior (crossing/not crossing; walking/pausing) across intersection types (protected, e.g., stop signs; designated, e.g., crosswalks; and undesignated, e.g., jaywalking). ResultsThe patterns mutual information conveyed by vehicle kinematics differed across measures (acceleration, speed, and standard deviation of speed) reaching peak values (in bits of information) at different distances from the pedestrian path. The mutual information conveyed by vehicle acceleration and pedestrian crossing behaviors peaked the farthest from the pedestrian path in the designated crossings, about 18 m away from the pedestrian path, with a difference in median deceleration of 1.01 m/s2 (p < 0.001) between pedestrian pausing and walking epochs. For protected crossings, the peak in mutual information occurred closer (10 m) to the pedestrian path, where median vehicle deceleration was significantly lower (0.55 m/s2; p < 0.05) in pausing epochs compared to walking epochs. For undesignated crossings, the peak in mutual information was the closest to the pedestrian crossing path, around 5 m, and was associated with a stronger deceleration behavior in pedestrian crossing epochs (-0.33 m/s2; p < 0.1). Vehicle speed demonstrated a similar sensitivity to distance from the pedestrian path across intersection types. Lastly, looking at the outcome of pedestrian behavior (i.e., crossing/not crossing), we find that the mutual information conveyed by acceleration, speed, and standard deviation of speed, peaked when the vehicle was at 30 m (stronger braking −0.37 m/s2; p < 0.1) and 10 m away, with greater acceleration (0.81 m/s2; p < 0.001) and faster speeds (2.41 m/s; p < 0.001) in pedestrian crossing epochs. Significance of resultsThis study examined driver-pedestrian information exchange using vehicle kinematic behavioral cues. We find that the differences in mutual information are shaped by multiple factors including the intersection type. In general, there was less mutual information gain in protected crossings which may be explained by unambiguous right-of-way rules guiding driver and pedestrian behavior, reducing the need for negotiation. Driver-pedestrian interactions in designated crossings seem to take place over a larger distance range compared to undesignated or protected crossings. These findings may support the design of automated driving and pedestrian safety systems that are able to consider the type, strength, and timing of kinematic cues to optimize driver-pedestrian negotiation. Eventually, such systems may enhance safe, efficient, and social interactions with pedestrians.

Sociolinguistics and linguistic intersection: the case of some Kwa languages of Côte d'Ivoire for didactics of related languages.

This article addresses the issue of lexical similarities between some Kwa languages of Côte d'Ivoire. These languages often use the same item or an item whose pronunciation differs only by one phoneme or one syllable to designate the same reality. We analyze this phenomenon using the notion of linguistic intersection. The aim is to facilitate the choice and teaching of these languages. . To achieve our objectives, this study falls within the general framework of sociolinguistics and language teaching, using comparative linguistics. Through a few items from the six Kwa languages of our work, we proceeded to a lexico-semantic crossing to arrive at the following results: our research revealed two types of (linguistic) lexico-semantic intersection: nominal items having the same meaning are phonetically either totally or partially identical. Keywords : linguistic intersection, language didactics

Deposition order and physicochemical process visualization of ink intersections using X‐ray photoelectron spectroscopy imaging for forensic analysis

The physicochemical events at ink intersections are largely understudied. Chemical imaging techniques and multivariate analyses applied to this problem thus far lack the performance characteristics to make confident conclusions about these processes. This deficiency leads to subjective and controversial deposition order determinations in forensic investigations. In this comprehensive report, 44 unique crossings involving laser toners and stamps, as well as felt‐tip, rollerball, gel, and ballpoint pen inks, were imaged with X‐ray photoelectron spectroscopy (XPS), using a 50‐μm X‐ray spot size and 100‐μm steps. The specificity and surface sensitivity of XPS enabled the objective visualization of the inks' chemistry upon deposition via spatial elemental distribution in‐situ. Signal intensity and atomic concentration were mapped for each element detected. Discrimination was possible in 100% of written and printed inks analyzed, and the relationship between the elemental concentration profile in each intersection was compared with the known sequence. Formation of ink layers, mixing, and separation of ink components by way of electrostatic forces were observed. Insights into the known complexity of ink intersection processes were revealed and highlight the need for understanding the chosen analytical technique's information depth and for complementary analyses to increase sequencing confidence. We also provide evidence that these processes invalidate the utility of principal component analysis for analyzing ink intersections. However, sequencing accuracy was 84% for all samples analyzed, and its success was highly dependent on the presence of physical features (i.e., thick coatings and embossed regions). In some intersection types, especially toners, the features exposed with XPS imaging enabled a sequencing accuracy of 100%.

From semantics to types: The case of the imperative λ-calculus

We study the logical semantics of an untyped λ-calculus equipped with operators representing read and write operations from and to a global store. Such a logic consists of an intersection type assignment system, which we derive from the denotational semantics of the calculus, based on the monadic approach to model computational λ-calculi.The system is obtained by constructing a filter model in the category of ω-algebraic lattices, such that the typing rules can be recovered out of the term interpretation. By construction, the so-obtained type system satisfies the “type-semantics” property and completeness.

Optimal intersection design and signal setting in a transportation network with mixed HVs and CAVs

It is widely recognized that human-driven vehicles (HVs) and connected and autonomous vehicles (CAVs) are expected to coexist and share the urban traffic infrastructure in the transportation network for a long time. To fully utilizes CAVs’ potential to reduce congestion in the transitional period, this study proposes and addresses the intersection design and signal setting problem in the transportation network with mixed HVs and CAVs. Due to the difference in terms of communication technology and autonomous driving technology for HVs and CAVs, three types of intersections have been proposed to amplify the efficiency-improvement benefit from CAVs by separating CAVs from HVs in a temporal or local-spatial dimension: the conventional signalized intersection, the novel signalized intersection with a dedicated CAV phase and dedicated CAV approaches, and the intelligent signal-free intersection. The problem is to determine the spatial layout of different types of intersections in the transportation network, the cycle time, and green time duration for each phase of signalized intersections that minimize the total travel cost, in which the route choice behavior of heterogeneous travelers has been respected based on the user equilibrium principle. A mixed-integer nonlinear programming model is developed to formulate the proposed intersection design and signal setting problem based on the link-node modeling method, in which the path enumeration is avoided. Then, by employing various linearization techniques (e.g., disjunctive constraints, logarithmic transformation, piecewise linearization with logarithmic-sized binary variables and constraints, outer-approximation technique), the proposed model can be further transformed into a relaxed sub-problem in the form of mixed-integer linear programming. A globally optimal solution algorithm embedding with solving a sequence of relaxed sub-problems and nonlinear mixed complementarity problems is proposed to converge to a global optimum. The results of numerical experiments illustrate that the proposed methodology can significantly improve the performance of the whole network. Moreover, it consistently outperforms the optimization model considering only conventional signalized intersections under various CAV market penetration rates.

Comprehensive Investigation of Commercial Motor Vehicle Crashes at Signalized and Unsignalized Intersections in Kentucky

This study develops safety performance functions (SPFs) for “fatal and injury” (FI) commercial motor vehicle (CMV) crashes (here, a CMV is defined as a large truck or a bus) at both signalized and unsignalized intersections in Kentucky. Five count-response regression models—negative binomial, Conway–Maxwell–Poisson, heterogeneous Conway–Maxwell–Poisson, zero-inflated Conway–Maxwell–Poisson, and zero-inflated heterogeneous Conway–Maxwell–Poisson (ZI-HTCMP)—were developed and compared at each of the selected signalized and unsignalized intersections. FI CMV intersection-related crash data in Kentucky over a period of five years (2015 to 2019) were used. Information on road-specific characteristics, for example, shoulder width, median width and type, International Roughness Index (IRI) value, and traffic volume (including annual average daily traffic [AADT] and heavy vehicle percentage [HVP]) was collected. Additionally, information on intersection-specific characteristics, for example, number of through lanes and presence of exclusive left- and right-turn lanes on major and minor roads, was collected using Google Maps’ street view time slider back to the crash year. For both signalized and unsignalized intersections, the ZI-HTCMP model (with a varying dispersion parameter) outperformed the other comparative models. With regard to signalized intersections, a speed limit of greater than 45 mph on the major road, a speed limit greater than 45 mph on the minor road, and a median on the major road wider than 3 ft were significantly associated with increased FI CMV crashes. As far as unsignalized intersections were concerned, higher major road AADT, 4-legged configuration, a speed limit greater than 45 mph on the major road, and an IRI value of greater than 100 for the major road were significantly associated with increased FI CMV crashes. The SPF results (for each of the signalized and unsignalized intersections) were then used to identify the top 10 hazardous locations for each intersection type.

Structure and topology of a brittle-ductile fault swarm at Crawford Knob, Franz Josef, New Zealand

ABSTRACT We present surface and structural models of a swarm of dm-scale subparallel faults exposed in a ∼2000 m2 glaciated outcrop near Franz Josef Glacier, in the Southern Alps of New Zealand. These structures are inferred to have slipped at ∼20 km depth in the hanging-wall Alpine Schist of the Alpine Fault under conditions that were variably brittle to ductile as the Pacific Plate was tilted and uplifted. Using field mapping, real-time kinematic GPS and digital images from a remotely piloted aircraft system, we have created a digital surface model of the outcrop and orthophotographs at a ground resolution of ∼1 cm to map compositional layering in the metasediments and the array of brittle-ductile faults displacing them. In order of decreasing relative age (and average thickness), displaced markers in the schist include primary psammite and pelite beds, quartz veins, and a deformational foliation. The surface models have been used to create 2-D transects and a 3-D model where faults are projected down-dip, to determine the connectivity, topology and intersection types of the fault swarm. Lithological variations, particularly the interface between pelitic and psammitic schist, were a primary control on the topology of the fault network and the spacing between faults.

Towards a Temporal Probabilistic Argumentation Framework

In recent years, the notion of time has been studied in different ways in Dung-style Argumentation Frameworks. For example, time intervals of availability have been added to arguments and relations. As a result, the output of Dung semantics varies over time. In this paper, we consider the situation in which arguments hold with a certain probability distribution during a given interval. To model the uncertain character of events, we propose different notions of temporal conflict between arguments according to the type of availabilities intersection (partial, inclusive, or total). Then, we refine these notions of conflict by a defeat relation, using criterion functions that evaluate an attack’s significance according to the probability over time.

Comprehensive Review on Capacity Analysis of Rotary Intersection

Rotary intersection, which is a special type of at-grade intersection, where all converging vehicles are forced to move round a central island in clock-wise direction. Increasing trends of traffic in urban area is a major concern in all the cities in India. The heterogeneous traffic are more diverse in nature due to lane changing and lack of lane discipline characteristics of driver’s in India. The rotary intersections are of the most vital components of urban roadway network. Intersection is one when either three or more road meets or intersects each other. It has been observed that the entry capacity of vehicles become comparatively lower at intersection than that of the straight portion of the road due to reduction in speed. The traffic flow characteristics at rotary intersections are study to observe the performance of intersection. The capacity of the roadway rotary depends on the flow at different legs approaching the rotary. The present traffic scenario is usually used to characterize the present traffic condition to access the different parameters at different types of intersection. The crossing of vehicles is avoided by allowing all vehicles to merge into the streams around the rotary and then to diverge out to the desired radiating road. Thus the crossing conflict is eliminated and converted into weaving maneuver or a merging operation from the right and diverging operation to the left. In this paper, an comprehensive review is presented on capacity analysis of rotary intersection.

The Effect of Vehicle Automation Styles on Drivers’ Emotional State

Self-driving vehicles promise many safety, mobility, and environmental benefits. However, users’ lack of trust and acceptance may threaten the success and potential of this technology. Monitoring the driver’s emotional state is one way to address this challenge. Empathetic automation can respond to the driver’s state and improve the experience and acceptance of self-driving vehicle drivers. In this study, 24 participants rode in a self-driving vehicle simulator and experienced three automation styles (aggressive, moderate, conservative) and four intersection types (with and without a stop sign, and with and without traffic.) We identified the observed drivers’ emotions from the video data and labeled the video frames using the dimensional and discrete emotion models to examine how automation behavior affects the driver’s emotional state. We used multilevel Bayesian linear regression and multilevel Dirichlet regression to model the continuous and discrete emotions, respectively. The automation driving style effect varied for each participant. The same conditions provoked positive responses for some participants, and negative for others. Furthermore, the results showed that intersection type, the position within the intersection, and their interaction affected the driver’s emotional state. This indicates that personalized driver state monitoring systems might enhance drivers’ experience in self-driving vehicles.

Exploration of the acceptability of different behaviors of an autonomous vehicle in so-called conflict situations

The acceptability of autonomous vehicles is an important issue for car manufacturers. The subject of this work attempts to address this issue in the context of conflict situations in urban environments. We present the results of a preliminary study that was conducted to investigate the effects of the driving mode and context on the acceptability of the behavior of an autonomous vehicle. We thus measured acceptability on 30 drivers confronted with three driving modes (defensive, aggressive, and transgressive) as well as different situations constituted by the most common urban intersections in France. We then formulated hypotheses on the effects that the driving mode, the context, or the socio-demographic characteristics of the passengers may have on their acceptability of the autonomous vehicle behavior. In the context of our study, the driving mode of the vehicle was the most influential parameter on the level of acceptability assessed by the participants. The type of intersection used did not result in a significant difference, nor did the socio-demographic characteristics studied. The results of these works allow an interesting first approach and lead us to guide our future works on the study of the parameters involved in the driving modes of autonomous vehicles.

Highly Efficient Traffic Planning for Autonomous Vehicles to Cross Intersections Without a Stop

Waiting in a long queue at traffic lights not only wastes valuable time but also pollutes the environment. With the advances in autonomous vehicles and 5G networks, the previous jamming scenarios at intersections may be turned into non-stop weaving traffic flows. Toward this vision, we propose a highly efficient traffic planning system, namely DASHX, which enables connected autonomous vehicles to cross multi-way intersections without a stop. Specifically, DASHX has a comprehensive model to represent intersections and vehicle status. It can constantly process large volumes of vehicle information, resolve scheduling conflicts, and generate optimal travel plans for all vehicles coming toward the intersection in real time. Unlike existing works that are limited to certain types of intersections and lack considerations of practicability, DASHX is universal for any type of 3D intersection and yields the near-maximum throughput while still ensuring riding comfort. To better evaluate the effectiveness of traffic scheduling systems in real-world scenarios, we developed a sophisticated open source 3D traffic simulation platform (DASHX-SIM) that can handle complicated 3D road layouts and simulate vehicles’ networking and decision-making processes. We have conducted extensive experiments, and the experimental results demonstrate the practicality, effectiveness, and efficiency of the DASHX system and the simulator.

The Factors Influencing the Prediction of Crash Frequency, Severity and Type: the Case of California Intersections

Traffic crashes are one of the most severe problems that affect communities worldwide. According to the World Health Organization, the annual number of global fatalities due to traffic crashes is about 1.35 million. Many factors affect the likelihood and the severity of a crash. In this paper, different factors are studied to evaluate their impact on the frequency, the severity, and the type of crashes at intersections, in order to boost road safety. California crash data have been obtained from the Highway Safety and Information System (HSIS) database and have been analyzed statistically. The analysis has included several factors such as severity, type of intersection, and the characteristics of the driver, roadway, environment, and vehicle. A negative binomial regression has been conducted by using the Statistical Analysis System (SAS®) Software for building three models. As a result, different parameters have been considered significant factors in each model. From all the models, the type of intersection and collision, the area of the crash, the type of surface type and its condition, the number of lanes, the age, and the gender have been considered significant factors for crashes at intersections. The result of this study could help reduce the likelihood and severity of crashes.

Impact of Driver's Age and Gender, Built Environment, and Road Conditions on Crash Severity: A Logit Modeling Approach.

The purpose of this research is (1) to investigate the relationship between crash severity and the age and gender of the at-fault driver, the socio-economic characteristics of the surrounding environment, and road conditions, and (2) to explain the probability of a bodily injury crash, including fatality, with the alternative being a property damage only crash. In contrast to earlier research that has focused on young and old drivers, age is considered here on its lifetime continuum. A logit model is adopted and the gender and age of the at-fault drivers are part of the independent explanatory variables. The unit of analysis is the individual crash. Since age is a continuous variable, this analysis shows more precisely how age impacts accident severity and identifies when age has little effect. According to the results, the type of vehicle, timing of the crash, type of road and intersection, road condition, regional and locational factors, and socio-economic characteristic have a significant impact on crashes. Regarding the effect of age, when an accident occurs the probability of bodily injury or fatality is 0.703 for female drivers, and 0.718 for male drivers at 15 years of age. These probabilities decline very slightly to 0.696 and 0.711, respectively, around 33 years of age, then very slightly increase to 0.697 and 0.712, respectively, around 47.5 years of age. The results show that age affects crash severity following a polynomial curve. While the overall pattern is one of a downward trend with age, this trend is weak until the senior years. The policy implications of the results are discussed.