Estimate freeway travel time reliability under recurring and nonrecurring congestion

Travel time and its reliability are considered as intuitive measure of service quality by transportation agencies. Moreover, highly reliable travel times allow for arriving at work or other destinations on time in the context of personal travel and facilitate just-in-time logistics services in freight operations. Travel times are the result of the traffic congestion. By considering different impact factors and shortcoming of the sensing technologies, this dissertation proposed methods for travel time and its reliability estimation. First of all, this dissertation presented a method to estimate corridor-level travel times based on data collected from roadside radar sensors, considering spatially correlated traffic conditions. Link-level and corridor-level travel time distributions are estimated using these travel time estimates and compared with the ones estimated based on probe vehicle data. The maximum likelihood estimation is used to estimate the parameters of Weibull, gamma, normal, and lognormal distributions. According to the log likelihood values, lognormal distribution is the best fit among all the tested distributions. Corridor-level travel time reliability measures are extracted from the travel time distributions. The proposed travel time estimation model can well capture the temporal pattern of travel time and its distribution. Second, a travel time reliability measure estimation method is proposed by incorporating standstill distance and time headway distributions in car-following models. The method is based on simplified two-component travel time distribution. By using Monte Carlo simulation, the speed-density region under congested condition and the travel time reliability measures can be generated. The results shows that the speed-density region derived from the steady-state Pipes model encloses most of the field data. Moreover, the proposed method estimate travel time reliability measures more precisely and faster, compared with using VISSIM simulation. Finally, a work zone travel time estimation approach is proposed in this dissertation. First, the impact of work zone on capacity is investigated. For the work zone capacity prediction framework, the predicted upper bound of capacity is close to the maximum 15-min flow rate. Moreover, based on the predicted capacity, density at capacity and free flow speed, work zone travel times are estimated by using the modified segment speed estimation model from the study of Newman. The estimated travel times roughly followed the pattern of the INRIX travel times. Moreover, the travel time reliability indices are estimated directly from the estimated travel times. The result shows that the travel time reliability indices based on estimated travel times are close to the indices based on INRIX travel times

Exploration of the characteristics and trends of electric vehicle crashes: a case study in Norway

With the rapid growth of electric vehicles (EVs) in the past decade, many new traffic safety challenges are also emerging. With the crash data of Norway from 2011 to 2018, this study gives an overview of the status quo of EV crashes. In the survey period, the proportion of EV crashes in total traffic crashes had risen from zero to 3.11% in Norway. However, in terms of severity, EV crashes do not show statistically significant differences from the Internal Combustion Engine Vehicle (ICEV) crashes. Compared to ICEV crashes, the occurrence of EV crashes features on weekday peak hours, urban areas, roadway junctions, low-speed roadways, and good visibility scenarios, which can be attributed to the fact that EVs are mainly used for urban local commuting travels in Norway. Besides, EVs are confirmed to be much more likely to collide with cyclists and pedestrians, probably due to their low-noise engines. Then, the separate logistic regression models are built to identify important factors influencing the severity of ICEV and EV crashes, respectively. Many factors show very different effects on ICEV and EV crashes, which implies the necessity of reevaluating many current traffic safety strategies in the face of the EV era. Although the Norway data is analyzed here, the findings are expected to provide new insights to other countries also in the process of the complete automotive electrification

Gamma-Ray Burst Optical Afterglows with Two-Component Jets: Polarization Evolution Revisited

Gamma-ray bursts (GRBs) have been widely argued to originate from binary compact object mergers or core collapses of massive stars. Jets from these systems may have two components, an inner, narrow sub-jet and an outer, wider sub-jet. Such a jet subsequently interacts with its ambient gas, leading to a reverse shock (RS) and a forward shock (FS). The magnetic field in the narrow sub-jet is very likely to be mixed by an ordered component and a random component during the afterglow phase. In this paper, we calculate light curves and polarization evolution of optical afterglows with this mixed magnetic field in the RS region of the narrow sub-jet in a two-component jet model. The resultant light curve has two peaks: an early peak arises from the narrow sub-jet and a late-time rebrightening is due to the wider sub-jet. We find the polarization degree (PD) evolution under such a mixed magnetic field confined in the shock plane is very similar to that under the purely ordered magnetic field condition. The two-dimensional `mixed' magnetic fields confined in the shock plane are essentially the ordered magnetic fields only with different configurations. The position angle (PA) of the two-component jet can change gradually or abruptly by $90^\circ$. In particular, an abrupt $90^\circ$ change of the PA occurs when the PD changes from its decline phase to rise phase.Comment: 21 pages, 6 figures, accepted by Ap

Lifecycle Cost Optimization for Electric Bus Systems With Different Charging Methods: Collaborative Optimization of Infrastructure Procurement and Fleet Scheduling

Battery electric buses (BEBs) have been regarded as effective options for sustainable mobility while their promotion is highly affected by the total cost associated with their entire life cycle from the perspective of urban transit agencies. In this research, we develop a collaborative optimization model for the lifecycle cost of BEB system, considering both overnight and opportunity charging methods. This model aims to jointly optimize the initial capital cost and use-phase operating cost by synchronously planning the infrastructure procurement and fleet scheduling. In particular, several practical factors, such as charging pattern effect, battery downsizing benefits, and time-of-use dynamic electricity price, are considered to improve the applicability of the model. A hybrid heuristic based on the tabu search and immune genetic algorithm is customized to effectively solve the model that is reformulated as the bi-level optimization problem. A numerical case study is presented to demonstrate the model and solution method. The results indicate that the proposed optimization model can help to reduce the lifecycle cost by 7.77% and 6.64% for overnight and opportunity charging systems, respectively, compared to the conventional management strategy. Additionally, a series of simulations for sensitivity analysis are conducted to further evaluate the key parameters and compare their respective life cycle performance. The policy implications for BEB promotion are also discussed

Incorporating the standstill distance and time headway distributions into freeway car-following models and an application to estimating freeway travel time reliability

Standstill distances and following time headways are two important microsimulation model parameters associated with driver aggression. This paper investigates the distributions of standstill distances and time headways and incorporates these distributions into car-following models to estimate travel time reliability. By incorporating standstill distance and following headway into car-following models as stochastic parameters, a speed-density region can be generated, based on which various travel-time-reliability measures can be calculated. Key findings of this study are as follows: (1) Both standstill distances and time headways follow fairly dispersed distributions. Therefore, it is suggested that microsimulation models should include the option of allowing standstill distances and time headways to follow distributions as well as to be specified separately for different vehicle classes. (2) By incorporating stochastic standstill distance and time headway parameters in car-following models, travel-time-reliability measures can be estimated more precisely and faster compared with using VISSIM

VISSIM Calibration for Urban Freeways

In urban areas, interchange spacing and the adequacy of design for weaving, merge, and diverge areas can significantly influence available capacity. Traffic microsimulation tools allow detailed analyses of these critical areas in complex locations that often yield results that differ from the generalized approach of the Highway Capacity Manual. In order to obtain valid results, various inputs should be calibrated to local conditions. This project investigated basic calibration factors for the simulation of traffic conditions within an urban freeway merge/diverge environment. By collecting and analyzing urban freeway traffic data from multiple sources, specific Iowa-based calibration factors for use in VISSIM were developed. In particular, a repeatable methodology for collecting standstill distance and headway/time gap data on urban freeways was applied to locations throughout the state of Iowa. This collection process relies on the manual processing of video for standstill distances and individual vehicle data from radar detectors to measure the headways/time gaps. By comparing the data collected from different locations, it was found that standstill distances vary by location and lead-follow vehicle types. Headways and time gaps were found to be consistent within the same driver population and across different driver populations when the conditions were similar. Both standstill distance and headway/time gap were found to follow fairly dispersed and skewed distributions. Therefore, it is recommended that microsimulation models be modified to include the option for standstill distance and headway/time gap to follow distributions as well as be set separately for different vehicle classes. In addition, for the driving behavior parameters that cannot be easily collected, a sensitivity analysis was conducted to examine the impact of these parameters on the capacity of the facility. The sensitivity analysis results can be used as a reference to manually adjust parameters to match the simulation results to the observed traffic conditions. A well-calibrated microsimulation model can enable a higher level of fidelity in modeling traffic behavior and serve to improve decision making in balancing need with investment

A longitudinal analysis of the effectiveness of California’s ban on cellphone use while driving

Cellphone use while driving is an increasingly serious threat for traffic safety and is prohibited in many jurisdictions. In California, the use of handheld cellphones while driving has been prohibited since July 1, 2008. Using interrupted time series analysis, this study explores the effectiveness of the ban by specifically analyzing the crashes caused by cellphone usage in California from 2002 to 2014. These crashes were thought to be able to reflect the role of the ban more accurately than total crashes. The ban was found effective in reducing the cellphone usage-caused crashes in terms of both crash frequency and crash proportion. The study also confirms that crashes caused by cellphone use produce more severe outcomes than other crashes. These findings show that the ban on handheld cellphone use while driving plays an important role for improving traffic safety in California. In addition, it is found that the ban motivates drivers to switch from handheld cellphones to hands-free cellphones, but in terms of crash severity, hands-free cellphone usage and handheld cellphone usage do not show significant differences. These findings support a complete ban on cellphone use while driving--not just a prohibition of handheld cellphone use. The study results are expected to provide new insights for future policy-making related to cellphone use while driving

Effectiveness evaluation of advisory speed limit at horizontal curve at two-way two-lane rural highway in Texas

This research paper has evaluated the effectiveness of the advisory speed limit at a two-way two-lane rural highway. Advisory speed limits are usually used on roads with some complex conditions, such as on horizontal curve. Even though driving over advisory speed limit is not a violation, over advisory speed limit would easily cause accidents or uncomfortable. In this research, the vehicle speeds at horizontal curve of different time duration are analyzed. The data collection sites are located on rural highway 77 and 665, and the speed limits of them are 70 mph. The results in the research indicate that there are more vehicles that follow the advisory speed limit at day time non-peak hour and night time than day time peak hour. Moreover, there are more vehicles that follow the advisory speed limit at the horizontal curve which the advisory is 65 mph than the curve which the advisory is 55 mph. As a result, at day time non-peak hour and night time, when the advisory speed limit is 65 mph, the advisory speed limit is higher than the drivers’ expectation. However, when the advisory speed limit is 55 mph, the advisory speed limit is lower than the drivers’ expectation