Familiar Drivers Research Articles

The correlation between drivers’ road familiarity and glance behavior using real vehicle experimental data and mathematical models

Objective Road familiarity is an important factor affecting drivers’ visual features. Analyzing the quantitative correlation between drivers’ road familiarity and visual features in complex environment is of great help to improve driving safety. However, there are few relevant studies. This paper takes urban plane intersection as the environmental object to explore the correlation between drivers’ glance behavior and road familiarity, and conducts research on the quantitative evaluation model of road familiarity based on this correlation. Method First, a real vehicle experiment was carried out to record the eye movement data of 24 drivers with different road familiarity. The driver’s visual field plane was divided into 10 areas of interest (AOIs) based on the driver’s perspective. Three measures, including average glance duration, number of glances, and fixation transition probabilities between AOIs at urban plane intersections, were extracted. Finally, based on the experimental results, the driver road familiarity evaluation model was constructed using the factor analysis method. Results There are significant differences between unfamiliar and familiar drivers regarding the average glance duration toward the forward (FW) area, the left window (LW) area, the left rearview mirror (LVM) area and the left forward (LF) area, the number of glances toward the other (OT) area, and the fixation transition probabilities of LW→RF (right forward), LF→LF, LF→FW, FW→LW, FW→FW, FW→RVM (right rearview mirror). The comprehensive evaluation results show that the accuracy rate of the driver road familiarity evaluation model reached 83%. Conclusions This paper revealed that there is a strong correlation between drivers’ road familiarity and drivers’ glance behavior. Based on this correlation, we can include road familiarity as a part of drivers’ working status and establish a high accuracy evaluation model of driver road familiarity. The conclusion of this paper can provide some reference for the humanized design and improvement of advanced driving assistance system, which is of great significance for reducing the driving workload of drivers and improving the driving safety.

The enduring necessity of fitness centres in times of global uncertainty

ABSTRACT Rationale/purpose This study investigated how COVID-19 lockdowns and restrictions impacted member perception of the necessity of their fitness centre membership with a focus on drivers of this perception pre, during and post-COVID-19 lockdowns. Design/methodology/approach Three survey-based data collections were assessed (before COVID-19 lockdowns, in early-stage reopening, and in a “COVID-19 normal” environment). A correlation analysis and multiple regression analysis (OLS) explored the drivers of perceived necessity of fitness centre membership. Findings Results support a consistent perception of the necessity of fitness centre membership, despite drivers varying over the course of the study. Early-stage reopening saw determinants diverge from familiar drivers (such as member characteristics and exercise frequency) to include uncertainty regarding COVID-19. Findings support the enduring necessity of fitness centre membership and articulate a deviation and subsequent return to familiar drivers of member attitudes and perceptions. Practical implications Practically, understanding the drivers of perceived membership necessity can assist fitness centre managers to construct and deliver member communications, as well as services and support. Research contribution Theoretically, the findings add to the limited research that focuses on the impact of COVID-19 on individual leisure activity engagement and assists in assessing how drivers of engagement evolve under differing pandemic circumstances.

A surrogate safety analysis at sharp gore areas of diverging freeway ramps using micro simulation under congested traffic conditions

Safety at the gore areas near diverging ramps is very crucial during planning and implementation of highway safety improvement programs. Limited research has been conducted on safety at the gore areas on arterial roads. This study aims at investigating the impact of improving a sharp gore area in Lincoln, Nebraska by performing a micro simulation before-and-after study with respect to its underlying state of safety and congestion. Data on travel times and traffic volumes for peak hours are incorporated after successful calibration to find out how a geometric intervention can decrease mobility issues as well as the likelihood of crash involvement. This study has utilized VISSIM software package to run the simulation however, to perform safety analysis, Surrogate Safety Assessment Model (SSAM) is used which is developed by the Federal Highway Administration (FHWA). During the model calibration, custom driving behaviors are created to represent driving tendencies of familiar drivers. The simulation results indicated that by adding an auxiliary lane near the gore area, the mobility issues such as bottle necks, lane changing dilemmas and queue lengths are substantially decreased. However, geometric interventions such as provision of a separate lane, increasing ramp spacing, nose spacing, deceleration area and queue storage area considerably reduced the likelihood of rear-end and lane changing crashes. Surrogate safety assessment in diverging ramps, particularly for sharp gores, has not previously been studied, and this study can serve as a primary footmark for future research on ramp-gores safety.

Pedestrian-injury severity analysis in pedestrian-vehicle crashes with familiar and unfamiliar drivers

Pedestrian injury in pedestrian-vehicle crash is significantly related to the driver, pedestrian, vehicle, crash and environment characteristics. Driver’s route familiarity has been found greatly associated with driving behaviours. Two-year pedestrian-vehicle crash data in Yunnan Province were studied to investigate the factors that affect pedestrian-injury severities in crashes with familiar and unfamiliar drivers by employing mixed logit models. Eight variables were found significant only in the familiar driver model. And six variables were found significant only in the unfamiliar driver model. Estimation findings indicate that the factors of early morning and sunny weather condition will be better modelled as random parameters in the model for familiar drivers and the same with the factors of rainy weather condition and afternoon peak in the model for unfamiliar drivers. Some more effective and targeted countermeasures are put forward for familiar drivers, unfamiliar drivers and transportation managers to reduce pedestrians’ injury severities.

The Real-World Effects of Route Familiarity on Drivers' Eye Fixations at Urban Intersections in Changsha, China.

A crucial factor, route familiarity, can affect traffic safety. Nevertheless, focus on the influence of route familiarity on drivers’ eye fixations at urban intersections has received less attention. Identifying the real-world effect of route familiarity on drivers’ eye fixations at urban intersections in Changsha, China, was the objective of this study. Their visual fixation indicators were recorded while unfamiliar drivers and familiar drivers drove a 9 km-long route with nine intersections in an urban environment, but their effectiveness was indicated by the data collected 150 m before the lane stop and 50 m after the lane stop at these intersections. From the analysis of the extracted data, the results indicated that route familiarity could influence drivers’ processing times in the left window (LW) and other areas (OT). Compared with familiar drivers, unfamiliar drivers had longer processing times and higher mental workloads for the right front (RF). For the vehicle’s front (RF, FL, FR), the sampling rates and mental workloads of unfamiliar drivers were higher than those of familiar drivers, but it was the opposite for the driver’s sides (LW, RW) and rear (LM, RM, ReM). It was also indicated that the phenomenon said to increase familiarity with the route and make drivers more likely to be distracted in urban intersections had not been found. From the present findings, the effect of route familiarity on drivers’ eye fixations at urban intersections was confirmed. The high accident risk of familiar drivers could be partly explained by the decrement in drivers’ eye fixation strategies. However, the strategies could not account for the phenomenon that more familiar drivers are involved in rear-end accidents. Therefore, the reason can be investigated based on drivers’ visual scanning strategies, their physiological signals and driving behavior in the future.

Routing Optimization with Generalized Consistency Requirements

The consistent vehicle routing problem (ConVRP) aims to design synchronized routes on multiple days to serve a group of customers while minimizing the total travel cost. It stipulates that customers should be visited at roughly the same time (time consistency) by several familiar drivers (driver consistency). This paper generalizes the ConVRP for any level of driver consistency and additionally addresses route consistency, which means that each driver can traverse at most a certain proportion of different arcs of routes on planning days, which guarantees route familiarity. To solve this problem, we develop two set partitioning-based formulations, one based on routes and the other based on schedules. We investigate valid lower bounds on the linear relaxations of both of the formulations that are used to derive a subset of columns (routes and schedules); within the subset are columns of an optimal solution for each formulation. We then solve the reduced problem of either one of the formulations to achieve an optimal solution. Numerical results show that our exact method can effectively solve most of the medium-sized ConVRP instances in the literature and can also solve some newly generated instances involving up to 50 customers. Our exact solutions explore some managerial findings with respect to the adoption of consistency measures in practice. First, maintaining reasonably high levels of consistency requirements does not necessarily always lead to a substantial increase in cost. Second, a high level of time consistency can potentially be guaranteed by adopting a high level of driver consistency. Third, maintaining high levels of time consistency and driver consistency may lead to lower levels of route consistency.

Eye-Tracking Evaluation of Exit Advance Guide Signs in Highway Tunnels in Familiar and Unfamiliar Drivers.

As a component of the traffic control plan, traffic signs on highways offer drivers necessary information. Unfortunately, many signs are unfamiliar to or misunderstood by drivers, especially when lacking a setting method; this includes exit advance guide signs in tunnels. These are generally set in roadbed sections, but space limitations in tunnels dictate that they must be set differently. To evaluate the effect of the setting method, an experiment was designed and conducted, during which the eye movements of 44 drivers with different familiarity levels were tracked. Twenty-two of the drivers had not previously participated in any experiment involving exit advance guide signs in highway tunnels, while 22 of them had. Time period data were analyzed, including data from before the sign appeared, when it appeared, and when it disappeared. Based on area division and Markov theory, attributes related to gaze transition were obtained, including one- and two-step gaze transition probabilities and area gaze probabilities. The results showed that gaze transition was confirmed to be significantly different between the three periods and between the drivers. Features extracted from eye movement characteristics, gaze transition paths, and gaze areas demonstrated that visual attention is more dispersed in familiar drivers during the lane-change intention period. Therefore, signs should be placed on the left wall of the highway tunnel.

Injury severity analysis of familiar drivers and unfamiliar drivers in single-vehicle crashes on the mountainous highways

Mountainous highways suffer from high crash rates and fatality rates in many countries, and single-vehicle crashes are overrepresented along mountainous highways. Route familiarity has been found greatly associated with driver behaviour and traffic safety. This study aimed to investigate and compare the contributory factors that significantly influence the injury severities of the familiar drivers and unfamiliar drivers involved in mountainous highway single-vehicle crashes. Based on 3037 cases of mountainous highway single-vehicle crashes from 2015 to 2017, the characteristics related to crash, environment, vehicle and driver are included. Random-effects generalized ordered probit (REGOP) models were applied to model injury severities of familiar drivers and unfamiliar drivers that are involved in the single-vehicle crashes on the mountainous highways, given that the single-vehicle crashes had occurred. The results of REGOP models showed that 8 of the studied factors are found to be significantly associated with the injury severities of the familiar drivers, and 10 of the studied factors are found to significantly influence the injury severities of unfamiliar drivers. These research results suggest that there is a large difference of significant factors contributing to the injury severities between familiar drivers and unfamiliar drivers. The results shed light on both the similar and different causes of high injury severities for familiar and unfamiliar drivers involved in mountainous highway single-vehicle crashes. These research results can help develop effective countermeasures and proper policies for familiar drivers and unfamiliar drivers targetedly on the mountainous highways and alleviate injury severities of mountainous highway single-vehicle crashes to some extent. Based on the results of this study, some potential countermeasures can be proposed to minimize the risk of single-vehicle crashes on different mountainous highways, including tourism highways with a large number of unfamiliar drivers and other normal mountainous highways with more familiar drivers.

Influence of Road Geometric Design Consistency on Familiar and Unfamiliar Drivers’ Performances: Crash-Based Analysis

Drivers’ road familiarity is a safety-related factor. Familiar drivers may be prone to inattention and more dangerous behavior, whereas unfamiliar drivers may be affected by demanding and unexpected road environments. Previous research adequately described the role of familiarity in driving behavior and road safety performances. However, the relationships between drivers’ unfamiliarity and safety issues of road design elements are still largely unexplored and there is a lack of dedicated experimental studies. In this work, a database including run-off-road single-vehicle accidents at Norwegian rural two-lane road curves was investigated. Information about familiarity was derived from the distance from the residence of drivers involved in crashes. Road geometric variables were collected on the segment before the accident site, to provide indicators of design consistency of the previous road section. Thereafter, logistic regression was used to find relationships between predictor variables related to the geometric road design consistency and familiarity (the dependent variable). As a result of the analysis, familiarity was confirmed as a factor associated to possible dangerous behavior such as speeding in demanding road environments. However, crashes involving unfamiliar drivers are associated to unexpected curve parameters (radius and length) and the combination of horizontal and vertical curvature. Thus, as well as familiarity, drivers’ unfamiliarity may be considered as an accident factor. Moreover, some possibly useful consequences for road design are suggested for practitioners. They specifically concern provisions about radii of subsequent curves and coordination between radii of horizontal and vertical curves.

Familiar versus Unfamiliar Drivers on Curves: Naturalistic Data Study

Human factors studies have shown that route familiarity affects driver behavior in various ways. Specifically, when drivers become more familiar with a roadway, they pay less attention to signs, adopt higher speeds, cut curves more noticeably, and exhibit slower reaction times to stimuli in their peripheral vision. Numerous curve speed models have been developed for purposes such as predicting driver behavior, evaluating roadway design consistency, and setting curve advisory speeds. These models are typically calibrated using field data, which gives information about driver behavior in relation to speed and sometimes lane placement, but does not provide insights into the drivers themselves. The objective of this paper is to examine the differences between the speeds of familiar and unfamiliar drivers as they traverse curves. The authors identified four two-lane rural highway sections in the State of Indiana which include multiple horizontal curves, and queried the Second Strategic Highway Research Program (SHRP2) database to obtain roadway inventory and naturalistic driving data for traversals through these curves. The authors applied a curve speed prediction model from the literature to predict the speed at the curve midpoints and compared the predicted speeds with observed speeds. The results of the analysis confirm earlier findings that familiar drivers choose higher speeds through curves. The successful use of the SHRP2 database for this analysis of route familiarity shows that the database can facilitate similar efforts for a wider range of driver behavior and human factors issues.

Influence of spatial visual conditions in tunnel on driver behavior: Considering the route familiarity of drivers

The objective of this study was to investigate how route familiarity affected drivers’ eye movement features (fixation and saccade) and driving speed when driving in the entrance zone of highway tunnels with different spatial visual conditions. On-road tests were conducted on the drivers’ visual characteristics and the speed were recorded in real time using an eye tracker and onboard diagnostic system. The variations in the eye movement features and speed in the entrance zone of the tunnels were analyzed. Then, statistical methods were conducted to examine the influence of the route familiarity and spatial visual conditions of tunnels on the driver behavior. The results demonstrated that the variations in the drivers’ eye movements and speed were much more significant in the entrance zone of a tunnel without spatial intervisibility than in a tunnel with spatial intervisibility. The impact of this environmental transition on unfamiliar drivers was greater than that on familiar drivers. Road familiarity reduced the drivers’ period of adaptation to the tunnel entrance environment and increased the driving speed.

Exploring the relationships between drivers’ familiarity and two-lane rural road accidents. A multi-level study

Previous research has suggested that drivers’ route familiarity/unfamiliarity (using different definitions of familiarity), and the interactions between familiar and unfamiliar drivers, may affect both the driving performances and the likelihood of road crashes. The purpose of this study is to provide a contribution in the search for relationships between familiarity and crashes by: 1) introducing a measure of familiarity based on the distance from residence; 2) analyzing a traffic and accident dataset referred to rural two-lane sections of the Norwegian highways E6 and E39; 3) using a multi-level approach, based on different perspectives, from a macro analysis to more detailed levels.In the macro analyses, the accident rates computed for different seasons and for different summer traffic variation rates (used as indicators of the share of familiar drivers in the flow) were performed. At the second level, a logistic regression model was used to explain the familiarity/unfamiliarity of drivers (based on their distance from residence), through variables retrieved from the database. In the last step, an in-depth analysis considering also accident types and dynamics was conducted.In the macro analysis, no differences were found between accident rates in the different conditions. Whereas, as emerged from the detailed analyses, the factors: high traffic volume, low summer traffic variation, autumn/winter, minor intersections/driveways, speed limits <80 km/h, travel purposes (commuting/not working) are associated to higher odds of having familiar drivers involved in crashes; while the factors: high traffic volume, high summer traffic variation, summer, head on/rear end-angle crashes, heavy vehicles involved, travel purposes (not commuting), young drivers involved are associated to higher odds of finding unfamiliar drivers involved. To a minor extent, some indications arise from the in-depth analyses about crash types and dynamics, especially for familiar drivers.With regard to the definitions used in this article, the familiarity was confirmed as an influential factor on the accident risk, possibly due to distraction and dangerous behaviors, while the influence of being unfamiliar on the accident proneness has some unclarified aspects. However, crashes to unfamiliar drivers may cluster at sites showing high summer traffic variation and in summer months.

Comparative Analysis of Toll Plaza Safety Features in Puerto Rico and Massachusetts with a Driving Simulator

Driving simulators have been widely used in transportation research and have potential applications for toll plaza safety research. The University of Puerto Rico at Mayagüez (UPRM) and the University of Massachusetts, Amherst (UMass-Amherst) performed a collaborative investigation using driving simulators to evaluate drivers’ behavior in two toll plazas with different signage and lane configurations that operate under the U.S. jurisdiction. The studied toll roads were the Caguas South Toll Plaza in Puerto Rico and the West Springfield Toll Plaza in Massachusetts. The major safety issues identified in both toll roads were unexpected lane changes, sudden vehicle stops, and variable speed patterns. The purpose of this study was to exchange research scenarios between UPRM and UMass-Amherst to test drivers who were unfamiliar with the areas of the study and enlarge the scope. Assuming that the patterns of behavior were similar, the results would suggest that drivers’ behaviors from different regions depend largely on the geometry of the toll plaza and not on the driving culture particular to a region. This study will greatly add to the utility of driving simulator studies because the results reported from one region and one toll plaza arrangement should generalize to other regions around the country and to territories. Results show that familiar drivers had a better driving performance, with respect to variability of lane position, when compared with unfamiliar drivers. However, the proposed treatments for each toll plaza improved road safety for both familiar and unfamiliar drivers.

Enhancing Driver Performance: A Closed Track Experiment

Abstract Signalized intersection operations are important for urban mobility, safety, travel times and environmental issues. Saturation flow rate and start-up lost time are two of the most important parameters when it comes to calculating signalized intersection capacity. Consequently, it is not surprising that countless studies have aimed towards estimating saturation flow rates and start up lost times at signalized intersections. Reports on saturation flow rates reveal large variations between different cities and countries. Values of 1800-2000 veh/h are common, but ranges from 1500-2500 veh/h have been observed. Driver performance is often regarded to be a result of the prevailing conditions, such as intersection geometry, grade, vehicle attributes, percentage of heavy vehicles and weather. Population characteristics, degree of familiar drivers (commuters) and traffic pressure are other factors that are reported to affect flow rates and lost times. As a result, most traffic management strategies are not aimed towards enhancing driver performance. This paper takes a different approach: How can we enhance driver performance, and more specifically; to what extent can behavior change increase signalized intersection capacity? The potential efficiency gains are studied by conducting a field trial on a closed track. Unlike other studies, this paper examines individual driver performance as well as overall traffic flow.

Book Review: Knowledge Workers in Contemporary China: Reform and Resistance in the Publishing Industry by Jianhua Yao

Knowledge Workers in Contemporary China: Reform and Resistance in the Publishing Industry. Jianhua Yao. Lanham, MD: Lexington Books, 2014. 192 pp. $90.00 hbk.If I had a time machine, I would like to take back about four decades and tell my anticommunist father what has become of China. First, Dad, we live in a world, in 2016, in which China, still nominally run by its Communist Party, now engages in capitalist boom-and-bust cycles not unlike those the United States experienced during its Gilded Age, more than a century ago, with more than 10 times as many people. Moves in the Shanghai stock (my Dad might ask: China has a stock market?) have become a very strong tail that sometimes wags the world capitalist dog, with markets undulating on speculations of Chinese growth rates. No, Dad, this isn't my father's world-Vietnam has a stock named after its former communist leader Ho Chi Minh, leading one to wonder, perhaps, who won that war.Chinese publishing, like the rest of its fascinating and swiftly changing society, sometimes does not fit the boxes prescribed for by Communist Party organization charts that subordinate editors to government agencies. The number of publishing enterprises exploded by a factor of 10 between 1978 and 2008, with many that serve the familiar drivers of media in capitalist countries (perceptions of audience desires and profit). The government maintains its own publishing enterprises as well. All of these are subject to censorship of varying forms and intensity. The Communist hierarchy resembles nothing so much as a rider of a gigantic, restless horse doing its best to cope with swiftly changing realities, hoping will not be bucked off with the same force that terminated the Soviet Union. A nation of 1.4 billion has conflicts; does not conduct its affairs in an air of seamless tranquility.Author Jianhua Yao has his finger on the pulse of this rapidly evolving industry, and of its publishers, editors, and writers, who have been re-defining their relationships with state power. His is a study, in Yao's words, about the reconfiguration of class power during China's market reform, about which he writes becomes impossible to fully understand the characteristics of China's socioeconomic changes without clarifying China's social classes, or conceptualizing China's class relations (p. 3). In this context, writes Yao, have become important figures. Thus, insomuch as China remains socialist, the computer keyboard joins the hammer and sickle as important symbols for the society as a whole.Yao's focus concerns how knowledge workers (mainly editors) in China's publishing industry are responding to the pressure brought about by media reform and social (p. 6). These pressures include the transformation from state agencies to private enterprises as technology develops to incorporate electronic publishing with older methods, as Chinese publishing also has become increasingly integrated into the world economy.The author uses archival studies, surveys, interviews, and case studies, concentrating on two large Chinese publishing houses: The Shanghai Science and Technology Publishing House (which issues about 1,000 titles a year, as well as magazines and academic journals), and the Shanghai Education Publishing House (with about 2,000 kinds of books, newspapers, and magazines).Yao describes a system that has evolved after economic reform began in 1978 that presents Chinese editors with a dual challenge of dealing with a state elite as described by the propaganda model, as well as dealing with the commodification process led by the economic elite that has profited from it (p. …

Route familiarity breeds inattention: A driving simulator study

Inattention is a major cause of traffic accidents. Here, we show that, contrary to common-sense expectation, familiarity with a route is itself a source of driving impairment. This effect may be attributed to increased mind-wandering along familiar routes. In the present work, participants followed a vehicle along a route with which they were either familiar or unfamiliar. During the experimental session, the lead-vehicle braked at random locations, forcing participants to brake to avoid a collision. Participants were also required to respond with a button press when they noticed pedestrians heading toward the road from a sidewalk. In Experiment 1 we found that familiar drivers follow the lead vehicle more closely and are slower to notice approaching pedestrians. In Experiment 2, with following distance held constant, reaction times to central and peripheral events were longer for familiar drivers. Consistent with the mind-wandering hypothesis, all these effects were eliminated in Experiment 3 when drivers were made to focus on the driving task.

Traffic Composition during the Morning Peak Period

Using registration plate analysis, this paper investigates 1) the proportions of ‘unique’ vehicles, 2) the proportions of vehicles re-appearing from day-to-day and their individual arrival variances and 3) the numbers of locally registered vehicles among those seen during the morning commute period on three roads in Southampton. During incidents, a traffic controller would hope to divert the more familiar drivers onto less congested parts of the network using VMS and other media. Knowing the proportions of regular and unique drivers which make up the peak commuting periods would help in the timely dissemination of this traffic information. The proportions of unique vehicles varied significantly with road and time. Vehicles appearing on more than one day formed 80% of the traffic before 08:15 but only 60% between the 08:45 and 09:00 peak period during the 1996 Bassett Avenue survey. Although the proportions of vehicles re-appearing from day to day varied significantly with road, their arrival variances were found to be very similar. On average, 65% of the returning vehicles re-appeared within +/- 5 minutes of their previous day’s time implying that this frequency of arrival could be part of an habitual behaviour pattern. The results suggest that for occasions where congestion can be anticipated in advance, such as prior to emergency roadworks or special events, warning messages would be most effective before 08:30 a.m. when the largest proportion of regular vehicles would be using the roads. If regular users are more familiar with the local road network than one-off ‘unique’ vehicles, and would be more likely to divert on receiving incident information relevant to their route, then later in the morning, the proportion of knowledgeable local drivers falls substantially. (Some mathematical expressions are not shown, please refer to the paper)

Drivers' familiarity with urban route network layout in Amman, Jordan

Abstract Advanced traveler information systems (ATISs) have attracted a considerable amount of attention in recent years. By providing drivers with traffic information, these information systems are likely to help in reducing travel time, traffic-related congestion and consequently lead to reduced levels of vehicle emissions. With the presence of in-car navigation and communication systems, the ATIS can benefit commuters as well as unfamiliar drivers. However, in the absence of in-car navigation systems – the case in most developing countries, familiar drivers are likely to use these information systems more effectively and hence are likely to make well-informed route-diversion and other travel-oriented decisions. This paper is devoted to developing driver familiarity models to identify the factors that influence drivers' familiarity with the urban route network layout. A number of non-linear familiarity models are developed and coefficients are estimated. Estimation results indicate that travel characteristics such as familiarity with one alternative route, residence leaving times, travel time to job location and the presence of young children have a profound impact on the driver's level of familiarity. Separate familiarity models for male and female drivers are also specified and estimated. When subjected to the same set of predictors, the familiarity of male drivers turned out to be more responsive than the familiarity of female drivers. This result could reflect, among other things, the fact that male drivers have more frequent and diverse activity stops that expose them to different sections of the transportation network layout.

Modeling default behavior in the presence of information and its application to the route choice problem

A new approach for modeling default behavior is presented and applied to route choice behavior in the presence of information. It is based on the assumption that drivers follow their usual behavior pattern and modify it only if the information received differs substantially from their existing perceptions and knowledge. Default behavior is linked to the interactions between existing knowledge and new information. These interactions are modeled through measures of compatibility, and several measures are suggested and analyzed. The approximate-reasoning model, which was earlier suggested for modeling discrete choices made in the presence of information, is adapted to handle default behavior. The model is briefly presented and its implementation and calibration are discussed. Default behavior is implemented by discounting existing knowledge when it does not agree with the new information, and by discounting the new information when it does not significantly differ from existing knowledge. A small case study is conducted using a driver simulator to collect data from two types of drivers: familiar and unfamiliar. The results obtained provide interesting insights on the choice behavior of the sample population, and support a default type of behavior among the familiar drivers.

Validating the results of a route choice simulator

This paper describes the validation of a route choice simulator known as VLADIMIR (Variable Legend Assessment Device for Interactive Measurement of Individual Route choice). VLADIMIR is an interactive computer-based tool designed to study drivers’ route choice behaviour. It has been extensively used to obtain data on route choice in the presence of information sources such as Variable Message Signs or In-Car Navigation devices. The simulator uses a sequence of digitized photographs to portray a real network with junctions, links, landmarks and road signs. Subject drivers are invited to make journeys between specified origins and destinations under a range of travel scenarios, during which the simulator automatically records their route choices. This paper describes validation experiments carried out during the period Summer 1994 to Autumn 1995 and reports on the results obtained. Each experiment involved a comparison of routes selected in real life with those driven under simulated conditions in VLADIMIR. The analysis included investigation of the subjects’ own assessment of the realism of the VLADIMIR routes they had chosen, a comparison of models based on the real life routes with models based on VLADIMIR routes, and a statistical comparison of the two sets of routes. After an extensive series of data collection exercises and analyses, we have concluded that a well designed simulator is able to replicate real life route choices with a very high degree of detail and accuracy. Not only was VLADIMIR able to precisely replicate the route choices of drivers who were familiar with the network but it also appears capable of representing the kind of errors made and route choice strategies adopted by less familiar drivers. Furthermore, evidence is presented to suggest that it can accurately replicate route choice responses to roadside VMS information.