Deo Chimba

Effect of bus size and operation to crash occurrences

This paper evaluates roadway and operational factors considered to influence crashes involving buses. Factors evaluated included those related to bus sizes and operation services. Negative binomial (NB) and multinomial logit (MNL) models were used in linearizing and quantifying these factors with respect to crash frequency and injury severities, respectively. The results showed that position of the bus travel lane, presence or absence of on-street shoulder parking, posted speed limit, lane width, median width, number of lanes per direction and number of vehicles per lane has a higher influence on bus crashes compared to other roadway and traffic factors. Wider lanes and medians were found to reduce probability of bus crashes while more lanes and higher volume per lane were found to increase the likelihood of occurrences of bus-related crashes. Roadways with higher posted speed limits excluding freeways were found to have high probability of crashes compared to low speed limit roadways. Buses traveling on the inner lanes and making left turns were found to have higher probability of crashes compared to those traveling on the right most lanes. The same factors were found to influence injury severity though with varying magnitudes compared to crash frequency.

Exploring Factors Contributing to Injury Severity at Freeway Merging and Diverging Locations in Ohio

Identifying factors that affect crash injury severity and understanding how these factors affect injury severity is critical in planning and implementing highway safety improvement programs. Factors such as driver-related, traffic-related, environment-related and geometric design-related were considered when developing statistical models to predict the effects of these factors on the severity of injuries sustained from motor vehicle crashes at merging and diverging locations. Police-reported crash data at selected freeway merging and diverging areas in the state of Ohio were used for the development of the models. A generalized ordinal logit model also known as partial proportional odds model was applied to identify significant factors increasing the likelihood of one of the five KABCO scale of injury severity: no injuries, possible/invisible injuries, non-incapacitating injuries, incapacitating injuries, or fatal injuries. The results of this study show that semi-truck related crashes, higher number of lanes on freeways, higher number of lanes on ramps, speeding related crashes, and alcohol related crashes tend to increase the likelihood of sustaining severe injuries at freeway merging locations. In addition, females and older persons are more likely to sustain severe injuries especially at freeway merge locations. Alcohol related crashes, speeding related crashes, angle-type collisions, and lane-ramp configuration type D significantly increase the likelihood of severe injury crashes at diverging areas. Poor lighting condition tends to increase non-incapacitating injuries at diverging areas only. Moreover, adverse weather condition increases the likelihood of no-injury and fatal injuries at merging areas only and adverse road conditions tend to increase a range of injury severity levels from possible/invisible injuries to incapacitating injuries at merging areas only.

Inconsistencies of Ordered and Unordered Probability Models for Pedestrian Injury Severity

Data on crashes between a single vehicle and a pedestrian recorded in Florida from 2004 to 2008 were used to identify the factors affecting the level of pedestrian injury severity, given that an accident had occurred and to assess the consistency of the ordered (ordered probit) and the unordered (multinomial logit) models. Both models were applied to the same data set. For the impact of individual variables on the levels of pedestrian injury severity to be discerned for the ordered probit and the multinomial logit models, the marginal effects were calculated. The results of a comparison of the two models indicated that the two models were consistent when they suggested the impact of individual factors on the lowest and the highest levels of injury severity (no injury or a possible injury and fatal injury, respectively) but suggested opposing impacts for some factors on intermediate levels of injury severity (nonincapacitating and incapacitating injuries). Such an inconsistency has implications for pedestrian safety measures and policies that are based on the models. Therefore, cautious selection of ordered and unordered probability models should be exercised with the use of a trade-off between recognition of the ordered pedestrian injury outcomes and loss of the flexibility in specification offered by unordered probability models. However, because the models are consistent for determination of the impact of variables on the lowest and the highest outcomes, pedestrian safety measures and policies should be derived on the basis of these outcomes.

Impact of Abandoned and Disabled Vehicles on Freeway Incident Duration

In most cases, abandoned and disabled vehicles are left within the roadway right of ways. It is common to find a vehicle left on the shoulder, median, gore area or on the travel lane for certain period of time. Experience from the state of Tennessee has shown that 78% of the freeway traffic related incidents are due to disabled and abandoned vehicles. It is hypothesized that the longer the vehicle is left unattended within the right of way, the higher the probability of new incidents and secondary crashes. This paper utilized 2004 to 2010 freeway incident data in Tennessee to evaluate the impact of the length of incident durations caused by disabled and abandoned vehicles. Analysis evaluated the impact of these incidents with respect to roadway location, queue lengths, weather conditions, towing times, lane closure, and the source of incident notification. Temporal factors, including the spectra of the time of the day, the day of the week, and the seasons of the year were evaluated with respect to the number of incidents and incident durations. It was found that vehicles left on the left and right shoulders generated more incidents compared to other locations followed by gore areas and the ramps. Parametric hazard based log-logistic survival model was applied to determine the factors affecting the abandoned and disabled vehicles incident duration. Number of closed lanes, length of the queue formed, construction zones, trucks and towing involvement were found to be significantly associated with longer incident duration.

Effects of Rain on Traffic Operations on Florida Freeways

Although the correlation between traffic variables and weather appears to be intuitive, quantifying the effects that weather, especially rain, has on driver response in travel speeds and traffic demands is needed to evaluate practical aspects of traffic operations. Previous studies have researched driver responses to inclement weather on freeways located in northern regions of the United States and Canada. However, driver familiarity with local weather conditions is a factor that should be considered in determining inclement weather effects on traffic variables. The focus of this research was to examine driver response to rain precipitation on freeways located in the southeastern regions of the United States to determine whether results from previous studies were general indicators or location specific in nature. To study the impacts of rain precipitation on hourly mean speeds and traffic volumes, hourly weather data and traffic sensor data were collected for two freeway segments in Jacksonville, Florida. The study investigated conditions such as wet versus dry (rain or no rain) and dry versus rain intensity (no rain or light, moderate, or heavy rain) for each segment. The results indicated that mean travel speeds decreased during rainfall events and speed reductions increased with increasing rain intensity. Reductions found for light rainfall events were within the range of previous studies; however, speed reductions during moderate to heavy rains varied widely. The results also indicated that the hour of the day was a factor in the degree of motorists’ speed reduction. Traffic volumes also declined during rainy conditions, with significant reductions during peak hours.

Scanning secondary derived crashes from disabled and abandoned vehicle incidents on uninterrupted flow highways

INTRODUCTION Extent of secondary crashes derived from primary incidents involving abandoned and disabled vehicles are presented in this paper. METHOD Using years 2004 to 2010 incident and crash data on selected Tennessee freeways, the study identified secondary crashes that resulted from disabled and abandoned vehicle primary incidents. The relationship between time and distance gaps before the secondary crash with respect to individual incident characteristics were evaluated through descriptive statistics and linear regression. RESULTS The time and distance gap analysis indicated that a large portion of secondary crashes occurred within 20 min after the primary incidents and within a distance of 0.5 miles upstream. While 76% of incidents involved shoulder, most secondary crashes were related to the closing of right lanes. Overall, 58% of the secondary crashes occurred within 30 min after the occurrence of the primary incidents. Most of the vehicles in the incidents that involved towing and caused secondary crashes were towed or removed out of the travel way within 60 min from the time of occurrence. The study found that most (95%) secondary crashes were property damage only (PDO), while 49% were rear-end crashes. The negative binomial model was used to evaluate the impact of roadway geometry and traffic factors associated with frequency of these secondary crashes. It was found that the posted speed limit, congested segments, segments with high percentages of trucks, and peak hour volumes increased the likelihood of secondary crash occurrence. Roadway segments with wider medians, shoulders, and multilanes decrease the likelihood of secondary crashes caused by abandoned and disabled vehicles as the primary incidents. Practical applications The paper recommends that wider shoulders be provided on any section of freeway to accommodate abandoned or disabled vehicles to avoid blocking of travel lane(s).

Factors affecting median cable barrier crash frequency: new insights

This study evaluated the impact of roadway cross-sectional and geometric features, traffic characteristics, and median cable barrier placement to the frequency of median-related crashes through statistical modeling using multiyear data. A unique aspect of the model specification was the inclusion of median cable barrier placement data, horizontal curve data, and differential elevation of opposite travel lanes. Negative binomial model was used in linearizing and quantifying these factors with respect to median crossover crash frequency. The variables that were found to significantly influence the frequency of median crashes include the number of lanes, differential elevation, and cable barrier offset from the inside shoulder. Increasing traffic volume was found to increase the frequency of median barrier crashes as well as the presence of curves on a median barrier section was found to increase the frequency of crashes. Higher differential elevation between opposite travel lanes was also found to increase the frequency of median barrier crashes. Increasing the median barrier offset from the inside shoulder of the travel way decreases median barrier injury and fatal crash frequency. Segments with a higher number of lanes and a wider median width were associated with low crash frequencies.

Development of Safety Performance Functions: Incorporating Unobserved Heterogeneity and Functional Form Analysis

To improve transportation safety, this study applies Highway Safety Manual (HSM) procedures to roadways while accounting for unobserved heterogeneity and exploring alternative functional forms for Safety Performance Functions (SPFs). Specifically, several functional forms are considered in Poisson and Poisson-gamma modeling frameworks. Using 5 years (2011–2015) of crash, traffic, and road inventory data for two-way, two-lane roads in Tennessee, fixed- and random-parameter count data models are calibrated. The models account for important methodological concerns of unobserved heterogeneity and omitted variable bias. With a validation dataset, the calibrated and uncalibrated HSM SPFs and eight new Tennessee-specific SPFs are compared for prediction accuracy. The results show that the statewide calibration factor is 2.48, suggesting rural two-lane, two-way road segment crashes are at least 1.48 times greater than what HSM SPF predicts. Significant variation in four different regions in Tennessee is observed with calibration factors ranging between 2.02 and 2.77. Among all the SPFs considered, fully specified Tennessee-specific random parameter Poisson SPF outperformed all competing SPFs in predicting out-of-sample crashes on these road segments. The best-fit random parameter SPF specification for crash frequency includes the following variables: annual average daily traffic, segment length, shoulder width, lane width, speed limit, and the presence of passing lanes. Significant heterogeneity is observed in the effects of traffic exposure-related variables on crash frequency. The study shows how heterogeneity-based models can be specified and used by practitioners for obtaining accurate crash predictions.

Capacity-constrained traffic forecasting model

Projecting future traffic is an important stage in any traffic and transportation planning study. Accurate traffic forecasting is vital for transportation planning, highway safety evaluation, traffic operations analysis, and geometric and pavement design among others. In view of its importance, this paper introduces a regression-based traffic forecasting methodology for a one dimensional capacity-constrained highway. Five different prediction functions are tested; the best was selected according to the accuracy of projections against historical traffic data. The three-parameter logistic function produced more accurate projections compared to other functions tested when highway capacity constraints were taken into consideration. The R 2 values at various test locations ranged from 88% to 98%, indicating good prediction capability. Using the Fishers information matrix approach, the t-statistic test showed all parameters in the logistic function were highly statistically significant. To evaluate reliability of projections, predictive intervals were calculated at a 95% level of confidence. Predictions using the logistic function were also compared to those predicted using the compound growth rate and linear regression methods. The results show that the proposed methodology generates much more reasonable projections than current practices.

Modeling Dynamics of Vehicle-Based Performance Measures of High-Occupancy Vehicle and General-Purpose Traffic Systems

AbstractThis study aimed at modeling dynamics of traffic systems with integrated and cointegrated stochastic processes using multiple time series of traffic flows generated by general purpose (GP) ...