• Transport Research

Several state transportation agencies have recently started highway safety corridor (HSC) programs to reduce crashes, injuries, and deaths on roads with a high rate and frequency of crashes. HSC programs use a coordinated campaign of education, enforcement, and low-cost engineering measures to address safety issues. Fines for moving violations are increased in these HSCs as a way to strengthen the potential impact of enforcement. While several states have implemented these programs, little information is available on how these programs have affected safety. In 2003, Virginia passed legislation establishing a state HSC program that increased fines for moving violations within an HSC. This paper documents the initial evaluation of the HSC program on two Interstate HSCs. Travel speeds before and after the HSC designation are examined at one site, while crash data are presented at both Interstate locations. Public opinions on the HSC program are also discussed. The results of the analysis indicate that little improvement in speed compliance and safety was observed at the congested, urban Interstate site. Significant reductions in crash frequency were observed at the more rural Interstate location, with a reduction in crash frequency of almost 30% being estimated in the most recent year. While results have been mixed for the two corridors, they show promise. More consistent effects may be possible if more dedicated resources are invested in the program.

In this article the analysis of existing schemes of periodization of the main stages of evolution of logistics and transportation systems. Analyzes the concept of "logistics revolution", the "waves" of changes in transport infrastructure and others. Revealed and substantiated the necessity of developing a holistic concept of development of transport and logistics systems in accordance with the main stages of development of the world economy. On the basis of this study we propose an original multi-parameter classification scheme of the main stages of the development of international and regional transport systems and complexes

Rapid development of metropolitan cities into smart cities and daily increased in number of vehicles on the roads causes increase in traffic maintenance challenges such as traffic congestion, accidents, dispatching of emergency vehicle and pollution. It will suffers people travel time, delay in response time of emergency vehicle such as ambulance, fire brigade, police etc., causes heavy loss or effects society in terms of wealth, emotions and security. The research work done in the area of Intelligent Transportation Systems and Traffic Management primarily focuses on determining effectively green light duration along with dispatching of emergency vehicle. In this research paper, the authors propose an algorithm which not only determines green light duration dynamically but also handles the emergency vehicle management efficiently. The objectives of the proposed algorithm are minimizing average waiting time. It always analysis the traffic situation at traffic intersection, along with continuous monitoring of emergency vehicle arrival at different lanes causes to optimize the waiting time of vehicle in lanes. It also deals with the deadlock and starvation condition, due to arrival of emergency vehicle in repeated interval of time in traffic intersection. The security level of emergency vehicle is in consideration during dispatching that assigned and verified by authorities to preserve security measures and society values. Here, the source of input on dynamic traffic condition is collected through Wireless Sensor Networks technology.

Wheel tracking tests have seen a vast increase in usage among various state department of transportations for measuring rutting resistance of mixtures that already meet volumetric property requirements. With the increase in using recycled materials and warm mix additives, it is clear that using volumetric properties alone to approve asphalt mixture designs is a risky approach. Wheel tracking tests are among the most widely used methods for evaluating rutting resistance, and the AASHTO T324 (Hamburg Wheel-Tracking [HWT]) is the most widely accepted and followed procedure used today in the U.S. However, there are challenges using the HWT, among which the most difficult are the poor repeatability, time required to complete the test, and the sample preparation details. This study reports on an alternative wheel tracking method called the Rotary Asphalt Wheel Tester (RWT) that can successfully address the challenges currently faced with using the HWT. The method requires no cutting of the gyratory samples, significantly reduces time to complete a sample, and appears to offer acceptable repeatability of the results. The method has existed for more than 15 years, available commercially, but used only in a few labs, and one acceptance criterion is already developed by one agency. The study includes evaluating an expanded set of mixtures tested at two temperatures, and two air voids. The results of the RWT are compared with the results of the HWT for numerous mixtures and they show that similar qualitative ranking can be achieved.

Vehicle detection and classification information is invaluable in many transportation issues. Vehicle feature extraction and detection are the preprocesses required for vehicle classification. Current automatic vehicle classification systems have deficiencies: low accuracy, special requirements, fixed orientation of the camera, or additional hardware and devices. This paper discusses a vehicle detection and classification system using model-based and fuzzy logic approaches. The system was tested with the use of a variety of images captured by the highway traffic control center of the Utah Department of Transportation. In comparison with existing systems, major advantages of the proposed system are ( a) no special orientation of the camera is required, ( b) no additional devices are needed, and ( c) high classification accuracy is provided. Experimental results show that the performance of the proposed system exceeds that of the existing video-based vehicle classification systems.

Abstract The paper presents a case study of applying crowdsourcing to library deliveries. The trial was conducted in the city of Jyvaskyla in Finland as part of the Resource Wise Communities program funded by The Finnish Innovation Fund Sitra. The city has a population of 120 000 inhabitants and is facing the shut-down of half of the public libraries in order to adapt its economy to lowered revenues and compulsory cost savings. The assumption was that the level of service for customers not able to settle for e-books would be lowered and/or customers would have to travel longer distances. However, a research pilot was carried out where –instead of lowering the level of service in the area– books and other library media were delivered to customers' homes by utilizing a novel crowdsourced delivery service called PiggyBaggy. Crowdsourced delivery means that citizens deliver goods to each other along their way. Ideally, the deliveries would be made with minimal detour, along the way, thus maximizing the reduction in natural resource use and related environmental impacts from the transport. However, the transport fuel forms only one part of the overall footprint and in practice rebound effects such as drivers traveling longer distances motivated by monetary compensation, can reduce the targeted environmental improvement. The objective of our study was to investigate whether an existing consumer service, in this case the library public service, can adopt crowdsourced deliveries quickly from scratch, and to whether consumers participate in the deliveries in a way that has real sustainability benefits. Despite prevailing regulative challenges, the study found that existing library deliveries can be successfully crowdsourced. Each crowdsourced delivery reduced an average of 1.6 km driven by car, despite 80 per cent of the deliveries being made within less than a 5-km distance. Mobility related footprint reduction potential for Finland is also estimated.

This research investigates the differences in AERMOD-predicted pollutant concentrations across input source types (AREAPOLY, VOLUME, LINE, RLINE, and RLINEXT without barriers). AERMOD (version 19191) microscale dispersion modeling is performed for the Atlanta I-75/I-575 Northwest Corridor (NWC) subarea in the U.S., including freeway corridors, managed lanes, connecting arterials, and intersections serving the NWC system. Modeling is performed for all link-receptor pairs, for each hour of the year, using the approved AERMET meteorological files (24 h × 365 days in 2019) from Georgia Environmental Protection Division (GA EPD), and emissions rates are estimated using MOVES-Matrix, based on predicted speed and volume by hour (output from ARC’s ABM2020 travel demand model). The AERMOD comparative analyses are performed for the same receptor sets, link-level volumes and speeds, and fleet compositions, across the five source types to generate comparative model results by input source type for the subarea. Results indicate concentrations from RLINEXT and RLINE were similar, with differences smaller than 0.05%, and their results were significantly higher than other source types. The results from AREAPOLY were similar to those from LINE (both smaller than RLINE and RLINEXT results). It is indicated that the results from VOLUME are systematically different from AREAPOLY and LINE for both downwind (much lower than AREAPOLY and LINE) and upwind (much higher than AREAPOLY and LINE) of the sources, and the sensitivity analysis indicates these predictions occur when wind speeds are low (less than approximately 2.5 m/s), which is because the enhanced wind meander approach employed with VOLUME is different from other source types.

In this paper, we present a quantization method to evaluate congestion from traffic flow information based on fuzzy logic. Level of congestion is considered as a continuous variable in the fuzzy inference system to estimate the congestion. As a result, we summarized a serial rules to generate congestion level with basic traffic parameters.

Existing literature does not draw conclusions as to which speedometer type is better for truck driving. A digital speedometer would be more beneficial when obtaining absolute and relative readings, while an analogue speedometer would be more efficient and less distracting when detecting dynamic speed changes. Redundant speedometers, which simultaneously present digital and analogue speedometers, appear increasingly in vehicles, but no information is available on their ergonomic qualities. This study compared three speedometers: digital speedometers, analogue speedometers, and redundant speedometers. This study compared the efficiency, usability and visual distraction measures for all three types of speedometers in a simulated truck driving setting. The task-dependant results were confirmed for the digital and analogue speedometer. The redundant speedometer combined the benefits of each type presented separately, which highlights interesting theoretical and applied implications.

The main purpose of this study is to demonstrate the applicability of the genetic algorithm (GA) to solve nonlinear optimization problems encountered in asphalt pavement design. The fundamentals of the GA are briefly discussed, and three case studies are presented. The first case study is an example showing the backcalculation of layer moduli with deflection data from a falling weight deflectometer and a layered-elastic program. The second case study demonstrates how to construct the master curve, either from a mix flexural frequency sweep test or from a binder rheometer test, and how to apply the master curve in pavement design. The last case shows how to apply the GA to characterize the binder discrete relaxation spectrum with a generalized Maxwell solid model. The results indicate that the GA is successful in resolving the nonlinear optimization problem. The GA presents some difficulty in terms of computing efficiency; however, several techniques have been developed to alleviate this problem.