Project Appraisal in Transportation - Assignment Example

SECTION-1: Introduction to Transport Analysis & Modeling Question-1: 1(a) Why do the conventional transport models deal only with mechanized trips, and when do you think walk trips should be considered? Ans: Conventional transportation planning, design, modeling and funding practices are predominantly inclined towards automobile transportation and mechanized trips (VTPI-2005) undervaluing alternative non-motorized modes like walk-trips, cycling, etc. These types of models were originally devised for analysis of such transport modes whose trip distance from origin to destination is fairly higher than the distance possible to be covered by walking. In such a model, transport analysis is based on flows between specified zones or regions rather than individual trips or shipments and the model oversimplifies travel behavior. This type of modeling involves 04-steps- trip generation, trip distribution, mode choice and trip assignment. The ‘mode choice’ step of such models do not include slow & non-motorized modes like walking. End walks for taking a motorized mode (like bus) and again for physically reaching the destination (office, home, etc.) are not considered as part of traveling in this type of model. Thus, walking, perhaps the most eco-friendly, least expansive and also the oldest and the most conventional form of human movement or traveling finds no place in the conventional transport model. Another view is that this modeling system was developed for evaluating large scale infrastructure projects and not for more subtle and complex policies involving management and control of existing infrastructure or introduction of policies which directly influence travel behavior (TDM Encyclopedia, 2005). Conventional modeling tends to assume that transport progress is linear, with newer, faster modes replacing older, slower modes (UCI-ITS-AS-WP-005). This series model assumes that the older modes are unimportant, and so, for example, there is no harm if walking conditions and transit service decline, provided that automobile ownership and vehicle traffic speeds increase. From this perspective, such models always find it undesirable to give walking priority over automobile travel. However, it is time that such drawbacks of conventional models are addressed and recently there have been a lot of developments in this direction. The conventional models are being functionally upgraded and their ability for considering slow modes like walking, bicycling, etc. can now be ensured by integrating such models with various sub-models. The conventional modeling approach is getting transformed to the more sophisticated and reliable integrated transport models where in walk-trips and walk-ability are very important considerations. The motivation for such integrated modeling approach comes from the realization that under today’s concentrated and centralized form of urban developments, walking is a significant mode of transportation which cannot be kept out from the planning and development frameworks. The concept of walk-able cities is catching up fast and following this walk-trips and walk-ability have now become unavoidable parameters for planning and development. (b) It was found in a recent survey of the Mong Kok District that there has been a rising trend in road accidents involving pedestrians. The air quality there is also getting worse as a result of increasing traffic. You are required to carry out a transport planning study for the District to look into alternatives solution to these problems. Briefly outline the objectives, evaluation criteria for the improvement options and constraints that you would establish/identify for the study. Ans: Mongkok is one of Hong Kong's most densely populated districts and it has emerged as one of the leading shopping areas in Hong Kong. Along with the local population this area also attracts overseas tourists and people from Mainland China and this exodus of so many people into this area aggravates the congestion and other planning problems affecting Mongkok. The main roads dissect the districts into several discrete sub-areas. The pedestrian environment is also not comfortable as pavements are often congested and adversely affected by fumes and noise from vehicular traffic close by. The findings of a recent survey of the Mong Kok District also confirm the existence of aforesaid problems. The survey also indicates that there has been a rising trend in road accidents involving pedestrians and deterioration of air quality in the Mong Kok district. The deteriorating air quality in Mong Kok is mainly due to street level automobile emissions and the situation is becoming more severe day-by-day with the exponential increase in vehicle population leading to increasing congestions. Excess entry of vehicles in the inner city areas, pedestrian unfriendly road infrastructures and ineffective traffic management are the dominant reasons causing road accidents. Thus, as revealed by the survey, Mong Kok is reeling under severe transport related problems which demand immediate interventions. To tackle and minimize the problems, it is proposed to carry out a transport planning study for Mong Kok aiming to look at alternative solutions to these problems. A brief outline of the study objectives, evaluation criteria and constraints or limitations is given below. Study Objectives The assignment here is to carry out a transportation planning study for the Monk Kok District with the principal aim of tackling the problems of road accidents and deteriorating air quality. In order to accomplish this aim, the following objectives have been identified for this study. Assess the baseline situation of traffic congestion and air pollution caused by the existing transportation arrangement in the Mong Kok District, Identify and analyze the deficiency of transportation system in the urban areas, Evaluate selective alternative strategies for alleviation of traffic congestion and consequent air pollution in the city; and Finally, conceive a transport plan which can help alleviate the problems of road accidents and deteriorating air quality in Mong Kok. Also, as required, the overall plan shall objectively adhere to the visions and sustainable development needs as prescribed by the Hong Kong Government through various planning and strategy documents like the CTS-3, HK-2030, etc. Improvement Options & Evaluation Criteria The main problems in Mong Kok are road-side vehicle emissions and road accidents. It is first required to identify the problems along with the factors causing such problems. The factors contributing to deteriorating air quality in Mong Kok appears to be: (a) Very high vehicle density and the average road utilization rate is about four to five times higher than in normal conditions. (b) Lack of natural ventilation as vehicle emissions are often trapped by high-rise buildings and hilly surroundings. (c) Very high proportion of diesel vehicles and they account for about 70% of the total on-road travel distance. (d) Traffic congestion also increases emissions. (e) Idling vehicles in waiting or carrying out loading/unloading activities without switching off the engines also cause significant air pollution. Similarly, the factors causing the road accidents are: (a) Unrestricted entry of all vehicles in the inner city areas. (b) No priority and facilities for pedestrians. (c) Insufficient road space catering to both vehicles and pedestrians. (d) Grade separation and traffic management measures are inefficient. (e) Proper right of way and infrastructures for non-motorized transports like cycling, walking, etc. are not given high priority. Considering all the above mentioned problems and the factors contributing to the problems, a transport plan may be devised which will: Prioritize safe movement of pedestrians and non-motorized transports in lieu of motorized transports in the inner city areas of Mong Kok. Implement footpath widening, traffic calming and vehicle speed reduction measures. Discourage non-essential traffic in the areas to reduce the traffic flow as well as to reduce the pressure on roads in the surrounding area. Cancellation of on-street parking spaces and provision of improved by-lanes. Rationalization of GMB/taxi routes/stands and reduction of waiting/idling vehicles through no-stopping restrictions. Better use of transits and mass railways and HOVs. Introduction of financial measures like tolls, high parking fees, etc. for discouraging private vehicles. This plan when implemented successfully is expected to bring in a lot of benefits for the Mong Kok District. Some of the performance criteria that can be used to evaluate the success of this plan are: Increased choices for mobility. Increased transit ridership. Reduction in use of autos and private vehicles. Better retail development and business scenario. Improvement in air quality and ambiance of the city. Decreased congestion and better accessibility. Direct reduction in trends of road accidents and Better health and wellbeing. Limitations However, there will also be some limitations and constraints in course of implementation of this plan. Some of the constraints and challenges expected are: This plan is based on the principles of integrated transport development and there may be initial problems in integrating transport, land-use and other functions. Restricting and discouraging vehicle movements and imposing higher parking fees sometimes become very unpopular with the common public. This re requires synergy among many different uses and functions, but this synergy is extremely difficult to achieve. The whole plan requires the common public to shift from their present habits and adopt and get used to new system. This may result in delay of actual implementation and compliance to the requirements of the plan. It requires different entities and sectors working in the same table and this multiplicity of agencies may give rise to management problems. However, there exist enough benefits in implementing this plan outweighing the associated problems and as such there should not be many problems in convincing the policy makers to adopt it as a policy option. Question-2: 2 (a) Estimation of trip generation…… The number of households (HH) and the total trips made in a day are given categorized by household size and car ownership levels (Table-a) along with the forecast of households (Table-b) after 5 years. Table-(a): 0 car 1 car 2+ cars HH Size HH Trips HH Trips HH Trips 1 1400 1810 2060 6080 300 750 2 2300 3450 3050 9870 850 2500 3 1650 2530 4500 21010 5400 29700 4+ 1200 2580 5820 27600 6430 37700 Table-(b): HH Size 0 Car 1 Car 2+ Cars 1 1950 2890 390 2 3950 5190 1440 3 2740 7010 8900 4+ 1360 6730 7434 Here the individual households have been classified to the common parameters of household size and auto-ownership levels and also the forecast number of households are available here. Here a cross-classification trip analysis model can be used. The total trip generated can be arrived at by estimating the total number of trips generated in the urban area (per type of trip) by multiplying the forecast number of households with the average trip rate. Average trip rate can be computed from table-(a) from the number of households and the total trips. Tables-(c) & (d) show the results of the estimation. Table-(C) Trip Rates HH Size 0 Car 1 Car 2+ Cars 1 1.29 2.95 2.5 2 1.5 3.23 2.94 3 1.53 4.67 5.5 4+ 2.15 4.74 5.86 Table-(d): HH Size Auto Ownership Total 0 Car 1 Car 2+ Cars 1 2516 8526 975 12017 2 5925 16764 4234 26923 3 4192 32737 48950 85879 4+ 2924 31900 43563 78387 2 (b) Estimation of future zonal movements by doubly-constrained….. Ans: Given here is the small-scale survey results (Table-a) for the base year and the estimated total trip ends for the same area for the next five-year period (Table-b). The trip matrix provided consists of four zones. Table-a: Zone 1 2 3 4 ∑j 1 30 70 310 650 1060 2 60 20 470 480 1030 3 130 70 10 50 260 4 230 280 90 70 670 ∑i 450 440 880 1250 3020 Table-b: Zone 1 2 3 4 Generations 1560 1430 450 1040 Attractions 620 680 1220 1960 A doubly-constrained distribution model can be used here as both the departures (Oi) and arrivals (Dj) boundaries are given. Along with the present trip matrix (Table-a), we also have more information about the future number of trips (Table-b) that will be produced in the zones of origin, and about the number of future trips attracted by the zones of destination. The future trip matrix which represents future zonal movements has been generated in line with the Fratar or Furnessing approach for trip distribution. The general form for a doubly-constrained distribution model is: Tij = ai*bj*Oi*Dj*f(Gij) Where: Tij is the number of trips from zone i to zone j, Oi is the total number of trips originating in zone i and Dj is the total number of trips ending in zone j Tij depends on the travel disutility or cost via the deterrence function as f(Gij), Which in most models is a logit function exp(-λdist Gijcomp)/{∑kexp(-λdist Gikcomp), Where Gijcomp is a composite cost calculated across the available modes and time periods, ai and bj are balancing factors or doubly constrained to ensure that ∑j Tij = Oi (ie there are Oi trips originating in zone i), and ∑i Tij = Dj (ie there are Dj trips ending in zone j), and are calculated at each iteration of the constraining routine as ai = 1/∑j Bj Dj f(Gij) or bj = 1/∑i aI OI f(Gij). In the above equation, Tij is proportional to Oi, the total number of trips originating in zone i,Tij is also proportional to Dj, the total number of trips ending in zone j. This doubly constrained model then has been balanced with the aim that the ∑j & ∑I of the forecast trip matrix are with in the limits of the forecast Oi & Dj (future generations & attractions as given in Table-b). The resulting new trip matrix is given below (Table-C). Table-C: Zone 1 2 3 4 ∑j Predicted (Oi) 1 41.3 100.2 400.5 1018.0 1560.0 1560.0 2 82.7 30.9 620.0 696.0 1429.6 1430.0 3 179.1 108.2 25.0 138.0 450.3 450.0 4 316.9 440.0 175.0 108.0 1039.9 1040.0 ∑i 620.0 679.3 1220.5 1960.0 4479.7 Predicted(Dj) 620.0 680.0 1220.0 1960.0 4480.0 Question-3: 3(a) Estimation of split of trips……. Diversion curve relates modal split to the travel time ratio, the travel cost ratio, and the travel service ratio by two modes. Similar curves for other trip purposes can also be calibrated. The independent variables used in diversion curve model include the ratio of transit to auto travel time (TTR), the ratio of transit to auto costs (CR), the ratio of transit to auto service (L), which is defined as the time spent outside the vehicle, and the traveler's income category (EC). The application of this model is simple. The number of trips by transit is the number obtained from the trip distribution phase multiplied by the appropriate ratios. Estimation of Modal Split Modal split for those travelers who have a car available is likely to be substantially different from the overall split across all travelers. Here we have the generalized costs given for both the private and the public modes. The notional modal split is calculated as: PPT = exp(-λmodeGPT)/{exp(-λmodeGPT) + exp(-λmodeGcar)}; Where PPT is the proportion of travellers choosing public transport, GPT and Gcar are the generalised costs of travel by public transport and car respectively, and λmode is the mode choice sensitivity parameter, (which can be given a value of say 0.04), unless there is local knowledge of the prevailing value. 3 (b) Discuss how you would choose, in the case of Hong Kong, between a binary and a multi-nominal logit models in determining the split of trips between various modes, and explain why?.. Ans: The traditional sequential transportation modeling is not just unquestioned; it has been an unchallenged tool in the field of transportation analysis and forecasting. However, the significance which it used to enjoy in the early years are diminishing fast, and at present there is increased activities in exploring other better alternatives, especially for predicting travel choices or modal splits. The modal split assignment is actually the 3rd stage of the traditional model and this is where logit models are employed for predicting and estimating choice of modes. The binary and the multi-nominal models are required at this stage. With the evolution of transportation systems, the complexities in this field increased along the years and this situation demands better functionality and capability of the models to account for the changes and complexities. Predominance of congestion, deterioration air quality, road accidents, etc. are some of the complexities which are very much common today. Hong Kong appears to be a good example where all such complexities are dominant and importantly, it also has one of the best public transportation systems in the world and also a very good framework for countering such problems or complexities. Thus, the modeling needs of Hong Kong are entirely different today than the early periods. The traditional model consists of the four stages as shown in the above figure. Curiously, in the early travel forecasting literature, there is little discussion of the underlying, more general problem of travel demand, or choice, and its relation to congested road travel times. The four-step procedure now appears to be a rather crude solution procedure, or heuristic, proposed in an attempt to solve the unstated, underlying problem of the relationship of origin-destination, mode, and route choices to network costs. Considering the traditional models and the current dynamics of the transportation system in Hong Kong, some concerns are surfacing about the appropriateness of such model, especially for the mode choice analysis part. It is usually difficult to estimate the changes in travel demand by using the classical Urban Transportation Modeling System. Many binary mode-choice modeling techniques developed during the 1960s have proved to be ineffective in computing the changes in travel demand. These techniques were primarily designed for System-level transportation and land-use studies and could not easily split the travel demand among the several competing transit and automobile mode choices usually present in a large metropolitan area like Hong Kong. Since these models cannot adequately simulate the equilibrium flows along competing transit routes, changes in travel demand due to minor changes in level of service cannot be accurately estimated. Mult-inomial loglt models enable analysis of multiple transit and highway options simultaneously. In addition, the incremental form of a multinomial logit model is especially suited for analyzing the shifts in market shares of competing modes. Considering all these, multi-nominal model appears to be the best choice for Hong Kong’s trip analysis, ----------------------------------- Read More