Multi-Level Crash Prediction Models Considering Influence of Adjacent Zonal Attributes

This study investigates factors affecting accidents across transport facilities and modes, using micro and macro levels variables simultaneously while accounting for the influence of adjacent zones on the accidents occurrence in a zone. To this end, 15968 accidents in 96 traffic analysis zones of Tehran were analyzed. Adverting to the multi-level structure of accidents data, the present study adopts a multilevel model for its modeling processes. The effects of the adjacent zones on the accidents which have occurred in one zone were assessed using the independent variables obtained from the zones adjacent to that specific zone. A Negative Binomial (NB) model was also developed, and results show that the multilevel model that considers the effect of adjacent zones shows a better performance compared to the multilevel model that does not consider the adjacent zones’ effect and NB model. Moreover, the final models show that at intersections and road segments, the significant independent variables are different for each mode of transport. Adopting a comprehensive approach to incorporate a multi-level, multi-resolution (micro/macro) model accounting for adjacent zones’ influence on multi-mode, multi-segment accidents is the contribution of this paper to accident studies

Predicting the competitive position of extended gates: the case of inland customs zones

The extended gate concept aims to reduce the pressure on international ports by postponing administrative processes from these border gates to inland terminals. At present, this approach is used mainly in the container transport industry in European and Asian ports. In this paper we study an extended gate concept, where inland customs services are made available from all entry points of a country. Our aim is to predict the portion of the current flow through border gates that is diverted to these inland customs zones. We propose a time-series gravity models to predict these changes and estimate the parameters of this model using publicly available data for different cargo groups. The focus of our application is Iran, a nation with a large and emerging economy, where goods currently enter through 26 main border gates. In addition to this flow diversion model we explain how flow matrices can be synthesized from the available transport statistics. Our calculations indicate that transportation cost, travel time and customs tariff discounts are the most important for the choice of customs zone. The attractiveness of extended gates increases as the direct cost of transportation between the border gate and destination province rises. Extended customs zones in Iran would have an average share of import flows in 2025 of around 13% and attract a volume of 8.4 million metric tons of goods

Chronic treatment with the nitric oxide synthase inhibitor, L-NAME, attenuates estradiol-mediated improvement of learning and memory in ovariectomized rats

INTRODUCTION: The role of ovarian hormones and nitric oxide in learning and memory has been widely investigated. OBJECTIVE: The present study was carried out to evaluate the effect of the nitric oxide synthase (NOS) inhibitor, N (G)-nitro-L-arginine methyl ester (L-NAME), on the ability of estradiol to improve learning in OVX rats using the Morris water maze. METHODS: Forty rats were divided into five groups: (1) ovariectomized (OVX), (2) ovariectomized-estradiol (OVX-Est), (3) ovariectomized-L-NAME 10 (OVX-LN 10), (4) ovariectomized-L-NAME 50 (OVX-LN 50) and (5) ovariectomized-estradiol-L-NAME 50 (OVX-Est-LN 50). The animals in the OVX-Est group were treated with a weekly injection of estradiol valerate (2 mg/kg; i.m.). The OVX-LN 10 and OVX-LN 50 groups were treated with daily injections of 10 and 50 mg/kg L-NAME (i.p.), respectively. The animals in the OVX-Est-LN 50 group received a weekly injection of estradiol valerate and a daily injection of 50 mg/kg L-NAME. After 8 weeks, all animals were tested in the Morris water maze. RESULTS: The animals in the OVX-Est group had a significantly lower latency in the maze than the OVX group (p<0.001). There was no significant difference in latency between the OVX-LN 10 and OVX-LN 50 groups in comparison with the OVX group. The latency in the OVX-Est-LN 50 group was significantly higher than that in the OVX-Est group (p<0.001). CONCLUSION: These results show that L-NAME treatment attenuated estradiol-mediated enhancement of spatial learning and memory in OVX rats, but it had no significant effect in OVX rats without estrogen, suggesting an interaction of nitric oxide and estradiol in these specific brain functions

Capacity drop estimation based on stochastic approach applied to Tehran-Karaj freeway

ABSTRACT: Existence of capacity drop phenomenon, as the difference between pre-queue and queue discharge flow rates, has been one of the controversial concepts of traffic engineering. Several researches have focused on capacity drop existence and also its estimation issues. This paper aims to estimate capacity drop based not only on a comparison between breakdown and queue discharge flow rates, but also on the estimation of the capacity distribution function before and after breakdown. In the empirical case, speed and flow rate data are collected in a section of Iran’s most crowded freeway for four months, based on which the threshold speed as the boundary between congested and non-congested flow is determined, and breakdown flow rates and their subsequent queue discharge flows are detected. Paired t-test between pre-queue and queue discharge flow rates is conducted to find the mean difference. Also, the distribution function of capacity under non-congested and congested flow is estimated using maximum likelihood and product limit methods. Based on the 11,600-record data set, it was observed that end results of both methods are consistent, revealing roughly five percent drop in capacity for the section under investigation

An Assessment of the Impact of Pedestrian Refuge Islands on Vehicle Speed Changes and Pedestrian Safety: Case Study in Tehran

Abstract: Pedestrians are among the most vulnerable road users. Speed of vehicles is considered as one of the major causes of danger for pedestrians crossing the street. Therefore, it is of utmost importance to devise suitable solutions to reduce speed of vehicles. One of these solutions is installation of Pedestrian Refuge Islands (PRI) in very wide midblocks. With regard to fluctuations in pedestrian and vehicle traffic volume in traffic hours, there are different variations in collisions between vehicle and pedestrian. In this article the effect of constructed PRI in Tehran on speed of vehicles and consequently their effects on probability fluctuations of fatal accidents are determined. Speed of vehicles in two phases of before and after arriving to the PRI is assessed. Additionally, speed of vehicles in non-observed volumes of vehicle and pedestrian are calculated using Aimsun.v6 simulation software. Paired T-test is applied to compare average speed of vehicles before and after the PRI. The results revealed that except for traffic volumes of 3000-4000 veh/h and 400-600 ped/h in other volumes reduction of average speed of vehicles as a result of PRI is significant. Also, the results show that in all volumes, these equipment reduce the probability of fatal accidents to under 10%. According to the results, it is recommended that PRI should be installed in mid blocks where traffic volume of vehicles in each lane is less than 750 veh/h

The effect of chronic administration of l-arginine on the learning and memory of estradiol-treated ovariectomized rats tested in the morris water maze

OBJECTIVE: The present study was carried out to evaluate the effect of L-arginine on the learning and memory of estradiol-treated ovariectomized (OVX) rats. METHODS: Forty-eight rats were divided into six groups: (1) sham, (2) OVX, (3) sham-Est, (4) OVX-Est, (5) sham-Est-LA, and (6) OVX-Est-LA. The animals of the sham-Est and OVX-Est groups were treated by weekly injection of estradiol valerate (2mg/kg). The sham-Est-LA and OVX-Est-LA groups were treated in the same manner but with an additional daily injection of L-arginine (200mg/kg). After eight weeks, animals of all groups were tested in the Morris water maze. The escape latency and path traveled to reach the platform were compared between groups. RESULTS: Time latency and path length in the OVX group were significantly higher than in the sham group (P<0.05). The OVX-Est group had a significantly shorter traveled path length and time latency compared to the OVX group (P<0.001). Time latency and path length in the sham-Est group was significantly higher than in the sham group (P<0.001). Time latency and path length in the OVX-Est-LA group were significantly higher than in the OVX-Est group. CONCLUSIONS: These results allow us to propose that chronic treatment with estradiol enhances the spatial learning and memory of OVX rats, and that long term L-arginine treatment attenuates the effects of improvement produced by estradiol in OVX rats

Development of safety improvement method in city zones based on road network characteristics

Background and Objective: Extensive studies have so far been carried out on developing safety models. Despite the extensive efforts made in identifying independent variables and methods for developing models, little research has been carried out in providing amendatory solutions for enhancing the level of safety. Thus, the present study first developed separate accident frequency prediction models by transportation modes, and then in the second phase, a development of safety improvement method (DSIM) was proposed. Materials and Methods: To this end, the data related to 14,903 accidents in 96 traffic analysis zones in Tehran, Iran, were collected. To evaluate the effect of intra-zone correlation, a multilevel model and a negative binomial (NB) model were developed based on both micro- and macro-level independent variables. Next, the DSIM was provided, aiming at causing the least change in the area under study and with attention to the defined constraints and ideal gas molecular movement algorithm. Results: Based on a comparison of the goodness-of-fit measures for the multilevel model with those of the NB model, the multilevel models showed a better performance in explaining the factors affecting accidents. This is due to considering the multilevel structure of the data in such models. The final results were obtained after 200 iterations of the optimization algorithm. Thus, to decrease accidents by 30 and cause the least change in the area under study, the independent variable of vehicle kilometer traveled per road segment underwent a considerable change, while little change was observed for the other variables. Conclusions: The final results of the DSIM showed that the ultimate solutions derived from this method can be different from the final solutions derived from the analysis of the results from the safety models. Hence, it is necessary to develop new methods to propose solutions for increasing safety

Hazard Detection Prediction Model for Rural Roads Based on Hazard and Environment Properties

A driver’s reaction time encountering hazards on roads involves different sections, and each section must occur at the right time to prevent a crash. An appropriate reaction starts with hazard detection. A hazard can be detected on time if it is completely visible to the driver. It is assumed in this paper that hazard properties such as size and color, the contrast between the environment and a hazard, whether the hazard is moving or fixed, and the presence of a warning are effective in improving driver hazard detection. A driving simulator and different scenarios on a two-lane rural road are used for assessing novice and experienced drivers’ hazard detection, and a Sugeno fuzzy model is used to analyze the data. The results show that the hazard detection ability of novice and experienced drivers decreases by 35% and 64%, respectively, during nighttime compared to daytime. Also, moving hazards increase hazard detection ability by 9% and 180% for experienced and novice drivers, respectively, compared to fixed hazards. Moreover, increasing size, contrast, and color difference affect hazard detection under nonlinear functions. The results could be helpful in safety improvement solution prioritization and in preventing vehicle-pedestrian, vehicle-animal, and vehicle-object crashes, especially for novice drivers

Comparison of Speed-Density Models in the Age of Connected and Automated Vehicles

peer reviewedFundamental diagrams (FDs) present the relationship between flow, speed, and density, and give some valuable information about traffic features such as capacity, congested and uncongested situations, and so forth. On the other hand, high accuracy speed-density models can produce more efficient FDs. Although numerous speed-density models are presented in the literature, there are very few models for connected and autonomous vehicles (CAVs). One of the recent spend-density models that takes into account the penetration rate of CAVs is provided by Lu et al. However, the estimation power of this model has not been tested against other speed-density models, and it has not been applied to high-speed networks such as freeways. Thus, this paper made a comparison between the Lu speed-density model and a well-known speed-density model (Papageorgiou) in freeway and grid networks. Different CAV behaviors (aggressive, normal, and conservative) are evaluated in this comparison. The comparison has been made between two speed-density models using the mean absolute percentage error (MAPE) and a t-test. The MAPE and t-test results show that differences between the two speed-density models are not significant in two case studies and that Lu is a powerful speed-density model to estimate speed compared with a well-known speed-density model. For the sake of comparing the above-mentioned models, this paper investigates the impact of CAVs on capacity based on FDs. The results suggest that the magnitude of the impacts of CAVs on road capacity (capacity increment percentage) which are obtained from two speed-density models are very close to each other. Also, the extent to which CAVs affect road capacity is highly dependent on their behavior

Investigating on the Effects of Congestion Pricing on Increasing Public Transit Share Investigating on the Effects of Congestion Pricing on Increasing Public Transit Share

Abstract cars. Therefore, applying demand management policies which decrease the utility of personal cars and increase the regarding the use of pricing economic and trip characteristics of the respondents. Based on the pricing scenarios, three choices including &quot;personal car&quot;, &quot;public transit&quot;, and &quot;other modes&quot; were included