Urban roadside monitoring and prediction of CO,NO2 and SO2 dispersion from on-road vehicles in megacity Delhi

The study inspects the traffic-induced gaseous emission dispersion characteristics from the urban roadside sites in Delhi, India. The concentration of pollutants viz. CO, NO₂ and SO₂ along with traffic and ambient atmospheric conditions at five selected local urban road sites were simultaneously measured. A developed General Finite Line Source Model (GFLSM) was used to predict the local roadside CO, NO₂ and SO₂ concentrations. A comparison of the observed and predicted values emission parameters using GFLS model has shown that the predicted values for SO₂, CO and NO₂ at all the selected local urban roadside locations are found to lie within the error bands of 5%, 6%, and 7% respectively. A high level of agreement was found between the monitored and estimated CO, NO₂ and SO₂ concentration data. From the study, it has also been established that the developed model exhibits the capability of reasonably predicting the characteristics of gaseous pollutants dispersion from on-road vehicles for the urban city air quality.     

Evaluating the assumption of independent turning probabilities

Several urban traffic models make the convenient assumption that turning probabilities are independent, meaning that the probability of turning right (or left or going straight through) at the downstream intersection is the same for all travelers on that roadway, regardless of their origin or destination. In reality most travelers make turns according to planned routes from origins to destinations. The research reported here identifies and quantifies the deviations that result from this assumption of independent turning probabilities.An analysis of this type requires a set of reasonably realistic “original” route flows, which were obtained by a static user-equilibrium traffic assignment and an entropy maximization condition for most likely route flows. These flows are compared with those route flows resulting from the Assumption of Independent Turning Probabilities (ITP). A small subnetwork of 3 km by 5 km in Tucson, Arizona, was chosen as a case study. An overall “typical ratio” of 2.2 between original route flows and ITP route flows was obtained. Aggregating route flows to origin–destination flows led to an overall “typical ratio” of 1.7. Such deviations are particularly high for routes that go back-and-forth, reaching a ratio of more than 3 in certain time periods. Substantial deviations for origins and destinations that are on the same border of the subnetwork are also observed in the analyses. In addition, under the ITP assumption, morning rush hour traffic peaking is the same in all directions, while in the original flows some directions do not exhibit a peak in the morning rush hour period. Overall, the conclusion of the paper is that the assumption of independent turning probabilities leads to substantial deviations both at the route level and at the origin–destination level, even for such a small network of the case study. These deviations are particularly detrimental when a network is being modeled and studied for route-based measures of effectiveness such as the number and types of routes passing a point – for monitoring specified vehicles and/or managing detouring strategies.     

Average duration and performance of actuated signal phases

This paper describes an approach for evaluating alternative traffic detection designs for a signalized intersection. The models described in this paper can be used to determine the average phase duration and frequency of phase “max-out” as a function of the detector loop layout, detector unit timing, traffic demand, and approach speed. Layout and timing are described by the number of detectors on each approach served by the phase, detector location on each approach, detector length, and detector unit and controller time settings. The authors have used the concept of maximum allowable headway (MAH) to combine the many possible combinations of layout and timing variables into one representative quantity, which greatly simplifies the modelling process. The performance models were used to examine the sensitivity of intersection performance to a range of design values. In general, both phase duration and cycle length increase with higher demands or larger MAHs. Multiloop (i.e. two or more detection zones per lane) detector designs typically have larger MAHs than designs with one detector loop per lane. Phase duration and cycle length also increase for very low demand levels. In terms of performance, the maximum green duration was found to have a contrary effect at higher flow conditions. Larger maximum greens were found to reduce delays to the phase in service by reducing the probability of max-out but they increased delays to drivers waiting for service.     

Identification of vehicle sensor locations for link-based network traffic applications

Information on link flows in a vehicular traffic network is critical for developing long-term planning and/or short-term operational management strategies. In the literature, most studies to develop such strategies typically assume the availability of measured link traffic information on all network links, either through manual survey or advanced traffic sensor technologies. In practical applications, the assumption of installed sensors on all links is generally unrealistic due to budgetary constraints. It motivates the need to estimate flows on all links of a traffic network based on the measurement of link flows on a subset of links with suitably equipped sensors. This study, addressed from a budgetary planning perspective, seeks to identify the smallest subset of links in a network on which to locate sensors that enables the accurate estimation of traffic flows on all links of the network under steady-state conditions. Here, steady-state implies that the path flows are static. A “basis link” method is proposed to determine the locations of vehicle sensors, by using the link-path incidence matrix to express the network structure and then identifying its “basis” in a matrix algebra context. The theoretical background and mathematical properties of the proposed method are elaborated. The approach is useful for deploying long-term planning and link-based applications in traffic networks.     

Dynamic location: an iconic model to synchronize temporal and spatial transportation data

This paper describes a model to synchronize the management and query of temporal and spatially referenced transportation data in geographic information systems (GIS). The model employs a method referred to as dynamic location, which facilitates spatial intersect queries from geographic shapes without the use of topological relationships. This is the inverse of how dynamic segmentation works in GIS. In contrast to dynamic segmentation, dynamic location stores geometry as an object within a single database field. This is an efficient, precise iconic model superseding the need for data decomposition into a complex set of tables. As an object model, the dynamic location process lends itself to high performance in an Internet, data-intensive, enterprise environment. Linear events are stored as {x, y} features, and not referenced to any route system. Route systems are built from {x, y, m} values (m for measure) and serve as number lines for mathematical operations. Any {x, y} object can then be referenced to either the Cartesian grid or any selected number line. This method offers the benefits of linear referencing, while making full use of a stable geodetic datum. Combinations of any {x, y} events may be placed over any {x, y, m} number line (route) and an intersect determined by looking through stacked {x, y, m} vertices of the coincident shapes. Since both geometry and shape reside in the same record, the use of “begin” and “end” dates facilitates full spatial and temporal version control. From a business process perspective, this creates a spatially enabled database, pulling GIS business functions back into the information technology mainstream.     

Spatiotemporal evolution of China’s railway network in the 20th century: An accessibility approach

The interrelatedness of transportation development and economic growth has been a constant theme of geographic inquiries, particularly in economic and transportation geography. This paper analyzes the expansion of China’s railway network, the evolution of its spatial accessibility, and the impacts on economic growth and urban systems over a time span of about one century (1906–2000). First, major historical events and policies and their effects on railway development in China are reviewed and grouped into four major eras: preliminary construction, network skeleton, corridor building, and deep intensification. All four eras followed a path of “inland expansion.” Second, spatial distribution of accessibility and its evolution are analyzed. The spatial structure of China’s railway network is characterized by “concentric rings” with its major axis in North China and the most accessible city gradually migrating from Tianjin to Zhengzhou. Finally, the study indicates that railway network expansion has significantly improved economic development and heavily influenced the formation of urban systems in China.     

Effects of countdown timers on queue discharge characteristics of through movement at a signalized intersection

This study investigates how countdown timers installed at a signalized intersection affect the queue discharge characteristics of through movement during the green phase. Since the countdown timers display the time remaining (in seconds) until the onset of the green phase, drivers waiting in the queue at the intersection are aware of the upcoming phase change, and are likely to respond quicker. Thus, the countdown timers could reduce the start-up lost time, decrease the saturation headway, and increase the saturation flow rate. This study observed vehicle flow at an intersection in Bangkok for 24 h when the countdown timers were operating, and for another 24 h when the countdown timers were switched off. The signal plans and timings remained unchanged in both cases. Standard statistical t-tests were used to compare the difference in traffic characteristics between the “with timer” and “without timer” cases. It was found that the countdown timers had a significant impact on the start-up lost time, reducing it by 1.00–1.92 s per cycle, or a 17–32% time saving. However, the effects on saturation headway were found to be trivial, which implies that the countdown timers do not have much impact on the saturation flow rate of signalized intersections, especially during the off-peak day period and the late night period. The savings in the start-up lost time from the countdown timers was estimated to be equivalent to an 8–24 vehicles/h increase for each through movement lane at the intersection being studied.     

Homogeneous optimal fleet

The structure of chains in the optimal chain decomposition of a periodic schedule S is investigated. A finite oriented graph termed the Linis Graph (LG) is defined which serves as the key for this investigation. The edges of the LG are trip-types of S and the vertices of the LG represent terminals. It is proved that there is an Euler cycle for a connected LG satisfying natural precedence relations between arrival and departure times. Expansion of this cycle in a real time gives a “master-chain” of trips which, being repeated periodically, gives an infinite periodic chain. Time-shifted periodic replication of this chain allows obtaining a group of twin-type periodic chains forming an optimal fleet over S. It is proved that if the LG has m connected components then there is an optimal fleet consisting of m groups of similar periodic chains. It is shown that if the graph of terminals is connected and the LG is disconnected then it is possible to obtain a twin-type fleet over S by adding to S “dummy” trip-types. A general approach to constructing a twin-type fleet of minimal size for this case is described. The relation of the theory developed to the so-called center problem is discussed.     

How wide should be the adjacent area to an urban motorway to prevent potential health impacts from traffic emissions?

In recent years, several studies show that people who live, work or attend school near the main roadways have an increased incidence and severity of health problems that may be related with traffic emissions of air pollutants. The concentrations of near-road atmospheric pollutants vary depending on traffic patterns, environmental conditions, topography and the presence of roadside structures. In this study, the vertical and horizontal variation of nitrogen dioxide (NO₂) and benzene (C₆H₆) concentration along a major city ring motorway were analysed. The main goal of this study is to try to establish a distance from this urban motorway considered “safe” concerning the air pollutants human heath limit values and to study the influence of the different forcing factors of the near road air pollutants transport and dispersion. Statistic significant differences (p = 0.001, Kruskal–Wallis test) were observed between sub-domains for NO₂ representing different conditions of traffic emission and pollutants dispersion, but not for C₆H₆ (p = 0.335). Results also suggest significant lower concentrations recorded at 100 m away from roadway than at the roadside for all campaigns (p < 0.016 (NO₂) and p < 0.036 (C₆H₆), Mann–Whitney test). In order to have a “safe” life in homes located near motorways, the outdoor concentrations of NO₂ must not exceed 44–60.0 μg m⁻³ and C₆H₆ must not exceed 1.4–3.3 μg m⁻³. However, at 100 m away from roadway, 81.8% of NO₂ receptors exceed the annual limit value of human health protection (40 μg m⁻³) and at the roadside this value goes up to 95.5%. These findings suggest that the safe distance to an urban motorway roadside should be more at least 100 m. This distance should be further studied before being used as a reference to develop articulated urban mobility and planning policies.     

Influence of coordinated traffic lights parameters on roadside pollutant concentrations

The paper examines the effects of coordinated traffic lights on CO and C₆H₆ roadside concentrations in an urban area of Palermo in Southern Italy. Traffic loop detectors and one pollution-monitoring are used to collect data for use in DRACULA traffic microsimulator software. CO and C₆H₆ roadside concentrations associated with varying cycle and offset times of the coordinated traffic lights are estimated using a neural network. Two functions were set up describing the relations of pollutant concentrations in term of cycle and offset time.     

Development of an emissions inventory model for mobile sources

Traffic represents one of the largest sources of primary air pollutants in urban areas. As a consequence, numerous abatement strategies are being pursued to decrease the ambient concentrations of a wide range of pollutants. A mutual characteristic of most of these strategies is a requirement for accurate data on both the quantity and spatial distribution of emissions to air in the form of an atmospheric emissions inventory database. In the case of traffic pollution, such an inventory must be compiled using activity statistics and emission factors for a wide range of vehicle types. The majority of inventories are compiled using ‘passive’ data from either surveys or transportation models and by their very nature tend to be out-of-date by the time they are compiled. Current trends are towards integrating urban traffic control systems and assessments of the environmental effects of motor vehicles. In this paper, a methodology for estimating emissions from mobile sources using real-time data is described. This methodology is used to calculate emissions of sulphur dioxide (SO₂), oxides of nitrogen (NO_x), carbon monoxide (CO), volatile organic compounds (VOC), particulate matter less than 10 μm aerodynamic diameter (PM₁₀), 1,3-butadiene (C₄H₆) and benzene (C₆H₆) at a test junction in Dublin. Traffic data, which are required on a street-by-street basis, is obtained from induction loops and closed circuit televisions (CCTV) as well as statistical data. The observed traffic data are compared to simulated data from a travel demand model. As a test case, an emissions inventory is compiled for a heavily trafficked signalized junction in an urban environment using the measured data. In order that the model may be validated, the predicted emissions are employed in a dispersion model along with local meteorological conditions and site geometry. The resultant pollutant concentrations are compared to average ambient kerbside conditions measured simultaneously with on-line air quality monitoring equipment.     

Vehicle sorting for platoon formation: Impacts on highway entry and throughput

Automated highway systems (AHS) are intended to increase the throughput and safety of roadways through computer control, communication and sensing. In the “platoon” concept for AHS, vehicles travel on highways in closely spaced groups. To maximize benefits, it is desirable to form platoons that are reasonably large (five or more vehicles), and it is also desirable to ensure that platoons remain intact for considerable distances. This paper develops and evaluates strategies for organizing vehicles into platoons at highway entrances, with the objective of maximizing the distance that platoons stay intact, so that they do not need to be regrouped into new platoons on the highway itself. Fundamentally, this entails grouping vehicles according to their destination. We evaluate various strategies in which vehicles are sorted on entrance ramps, with respect to platoon sizes, throughput and platoon formation time.     

Consistent link flow estimation from counts

Partly because of counting errors and partly because counts may be carried out on different days, traffic counts on links of a network are unlikely to satisfy the flow conservation constraint “flow IN = flow out” at every node of the network. Van Zuylen and Willumsen (1980) have described a method of eliminating inconsistencies in traffic counts when a single count is available for each link in the network. In this paper, the method is extended to the case when more than one count is available on some links of the network. In addition, an algorithm is described for application of the method.     

The cost of convenience; Air pollution and noise on freeway and arterial light rail station platforms in Los Angeles

Light rail transit (LRT) systems constitute one of the most sustainable public transportation modes and transit agencies have increasingly constructed LRT lines along the median of roadways to reduce land acquisition costs and traffic conflicts. Despite these conveniences, few studies have examined the air pollution and noise exposures for passengers on LRT station platforms within freeway or arterial medians. In response, we monitored particle number count (PNC) concentrations and noise levels on 17 station platforms in the Los Angeles metro system in summer 2012 and assessed differences between freeway and arterial platforms. We visited each station on average 7 times for approximately 19 min with two teams carrying a full set of instruments. As expected, impacts were higher on green line platforms in the center of a grade-separated freeway compared to blue line platforms in the center of an arterial due to being in close proximity to greater traffic volumes. Overall, freeway-arterial platform differences were 35,100 versus 20,000 particles/cm³ for PNC and 83 versus 62 dBA for noise. This average noise intensity on green line platforms was four times that on blue line stations. We also found that PNC concentrations were significantly higher at open air monitoring platform positions compared to standing under a shade canopy (about 2000 particles/cm³ higher), but that noise levels were significantly lower at open air positions compared to under canopy positions (about 3.2 dBA lower). Results identify important factors for transport planners to consider when locating and designing in-roadway LRT platforms.     

A system based approach to develop hybrid model predicting extreme urban NOx and PM2.5 concentrations

One of the major drawbacks of conventional air quality models is their inability in accurately predicting extreme air pollutant concentrations. Hybrid modelling is one of the techniques that estimates/predicts the ‘entire range’ of the distribution of pollutant concentrations by combining the deterministic based models (capable in predicting average range) with suitable statistical (probability) distribution models (capable in predicting extreme range). This research paper describes system based approach in developing hybrid model to predict hourly averages as well as extreme percentile ranges of NO_x and PM_2.5 concentrations at two urban locations having complex traffic heterogeneity, highly variable tropical meteorology and different geographical characteristics. At one of the selected locations i.e. Delhi megacity, during winters, hybridization of AERMOD and Lognormal predicts NO_x and PM_2.5 concentrations satisfactorily with index of agreement ‘d’ values of 0.98–0.99, respectively; however, during summers, AERMOD-Log-logistic and AERMOD-Lognormal are best predicting NO_x and PM_2.5 concentrations with d values of 0.98–0.96, respectively. In another, i.e., Chennai, a coastal megacity, AERMOD-Lognormal predicts PM_2.5 concentrations satisfactorily with d values of 0.98 and 0.99 during winter and summer seasons, respectively. Further, hybrid model has also been used to evaluate regulatory compliance.     

A practical concern about the relevance of alternative-specific constants for new alternatives in simple logit models

When a “new” alternative is introduced, post-estimation, into a logit model, analysis initially exclude an ASC or occasionally assume a correspondence with an existing alternative. Using a recent data set for mode and route choice, the paper highlights the forecasting implications of ignoring the ASC in the utility expression of a “new” alternative, and how sensitive the market shares are to the inclusion/ exclusion of the ASC.     

A combined land use-transportation model when zonal travel demand is endogenously determined

A combined transportation-land use model is proposed in this paper. Unlike other existing urban land use and transportation planning models in which a “fixed demand” for services is assumed to be known at the zonal level of an urban area, zonal travel demand is endogenously determined together with link congestion costs, optimal amounts of production and resulting efficient densities of land uses, once the transportation network is given. Some characteristics of alternative solutions are demonstrated. The proposed model represents progress over previous efforts in combining land use-transportation problems since the travel choice as to origin, destination and routes as well as amounts of goods to be produced at the optimal density of land uses are integrated into a consistent mathematical programming framework.     

A real-time traffic signal control system: architecture, algorithms, and analysis

The paper discusses a real-time traffic-adaptive signal control system referred to as RHODES. The system takes as input detector data for real-time measurement of traffic flow, and “optimally” controls the flow through the network. The system utilizes a control architecture that (1) decomposes the traffic control problem into several subproblems that are interconnected in an hierarchical fashion, (2) predicts traffic flows at appropriate resolution levels (individual vehicles and platoons) to enable pro-active control, (3) allows various optimization modules for solving the hierarchical subproblems, and (4) utilizes a data structure and computer/communication approaches that allow for fast solution of the subproblems, so that each decision can be downloaded in the field appropriately within the given rolling time horizon of the corresponding subproblem. The RHODES architecture, algorithms, and its analysis are presented. Laboratory test results, based on implementation of RHODES on simulation models of actual scenarios, illustrate the effectiveness of the system.     

Analyzing spatiotemporal traffic line source emissions based on massive didi online car-hailing service data

Nowadays, the massive car-hailing data has become a popular source for analyzing traffic operation and road congestion status, which unfortunately has seldom been extended to capture detailed on-road traffic emissions. This study aims to investigate the relationship between road traffic emissions and the related built environment factors, as well as land uses. The Computer Program to Calculate Emissions from Road Transport (COPERT) model from European Environment Agency (EEA) was introduced to estimate the 24-h NOx emission pattern of road segments with the parameters extracted from Didi massive trajectory data. Then, the temporal Fuzzy C-Means (FCM) Clustering was used to classify road segments based on the 24-h emission rates, while Geographical Detector and MORAN’s I were introduced to verify the impact of built environment on line source emissions and the similarity of emissions generated from the nearby road segments. As a result, the spatial autoregressive moving average (SARMA) regression model was incorporated to assess the impact of selected built environment factors on the road segment emission rate based on the probabilistic results from FCM. It was found that short road length, being close to city center, high density of bus stations, more ramps nearby and high proportion of residential or commercial land would substantially increase the emission rate. Finally, the 24-h atmospheric NO₂ concentrations were obtained from the environmental monitor stations, to calculate the time variational trend by comparing with the line source traffic emissions, which to some extent explains the contribution of on-road traffic to the overall atmospheric pollution. Result of this study could guide urban planning, so as to avoid transportation related built environment attributes which may contribute to serious atmospheric environment pollutions.