caused problems such as traffic congestion and air pollution leading to lower quality of life in metropolises. In such circumstances, using traditional systems such as cycling can be of high value. Previous international studies about cycling have shown that maximum acceptable time for cycling has received little attention. Considering this research gap, this paper aims to investigate impacts of different factors such as individual characteristic, land-use and built environment, on maximum acceptable time for cycling. Based on a field survey of 473 Tehran citizens conducted in one of the twenty-two Tehran municipality districts, mixed logit models were calibrated, validated and interpreted. Results indicate that people traveling through mixed land-use tend to use bicycle for thirty minute-trips more than the other land-use types. Also access to bicycle lane causes more tendency for thirty minute-trips by bicycle. Results also indicate that access to secure parking in destination and increasing number of intersection on the origin-destination routes increase travelers tendency for cycling about fifty-minute.
Keywords: cycling, maximum acceptable time, environmental impacts, mixed logit
 J. Ortuzar, A. Iacobelli, and C. Valeze, Estimating demand
for a cycle-way network, Transportation Research Part A,
vol. 34, no. 5, pp. 353-373, 2000.
 D.A. Rodriguez, and J. Joo, The relationship between nonmotorized mode choice and the local physical environment, Transportation Research Part D, vol. 9, no. 2, pp. 151-173, 2004.
 J. D. Hunt, and J.E. Abraham, Influences on bicycle use, Transportation Research, vol. 34, pp. 453-470, 2007.
 J. Parkin, M. Wardman, and M. Page, Estimation of the determinants of bicycle mode share for the journey to work using census data, Transportation Research, vol. 35, no. 1, pp. 93-109, 2008.
 I.N. Sener, N. Eluru, and C.R. Bhat. An analysis of bicycle route choice preferences in Texas, US, Transportation Research, vol. 36, vol. 5, pp. 511-539, 2009.
 H. Jain, and G. Tiwari. Discrete route choice model for bicyclists in Pune, India, Urban Transportation journal, vol. 9, no. 2, pp.1-12, 2010.
 M. Winters, G. Davidson, D. Kao, and K. Teschke. Motivators and deterrents of bicycling, comparing influences on decisions to ride, Transportation Research Part A, vol. 38, pp. 153-168, 2011.
 R. Buehler, and J. Pucher. Cycling to work in 90 large American cities, new evidence on the role of bike paths and lanes, Transportation Research, vol. 39, pp. 409-432, 2012.
 E. Heinen, M. Kees, and B.V. Wee, The effect of workrelated factors on the bicycle commute mode choice in the Netherlands, Transportation Research, vol. 40, pp. 23-43, 2013.
 K.E. Train, Discrete choice methods with simulation, United States of America: Cambridge University Press, 2009.
 C.R. Bhat, Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model, Transportation Research Part B, vol. 35, no. 7, pp. 677-695, 2000.
 K.E. Train, Halton sequences for mixed logits, Department of economics. University of California: Berkeley, 1999.
 V. Amini, A model for bicycle travel demand: case study of Tehran, MS thesis, Department of Transportation Planning, Faculty of Civil & Environmental Engineering. Tarbiat Modares University, Tehran, Iran, 2013.
The growth in magnitude and various impacts of traffic noise has created an increasing attention on the prediction and control of noise levels. This study aims at developing a noise level prediction model under the local conditions of Amman, the capital of Jordan. Thirty four sites, representing different characteristics, were selected for use in model development. The resulting prediction model incorporated variables describing traffic and site conditions including traffic volume, composition and speed, gradient, and distance from the source as affecting factors, the trial model expresses noise level by the index L10 (1hr). The developed model was validated by comparing its predicted noise levels with those measured. Further evaluation of the model was carried out by comparing its predictions with those obtained using the British Calculation of Road Traffic Noise (CRTN) model. The developed model was found to produce more accurate results, under Jordanian traffic conditions, than the CRTN model with an average error of only 3.2%.
Keywords: traffic noise, prediction, CRTN, modeling, Jordan
 Banihani, Q. Jadaan, K.S. Assessment of Road Traffic Noise, Pollution at Selected Sites in Amman, Jordan: Magnitude,
Control and Impact on the Community. Jordan Journal of Civil
Engineering. 2012; 6: 267-278.
 Banerjee D. Research on road traffic noise and human health in India: Review of literature from 1991 to current. Noise Health 2012;14:113-8.
 Jadaan, k., Gammoh, H., Okasha, A., Breizat, E., and Hadidi, T. Evolution of Traffic Noise Impacts In Amman, Jordan, International Journal of Automotive Engineering and Technologies, 2015; 4 (1): 7-11
 Al-Dakhlallah, A., and Jadaan, K, Attitudes of Jordanian Population Towards Traffic Noise Int. J. of Appl. Sci. Eng. 2005, 3 ( 2 ):145-150.
 Goussous, J., Al-Dakhlallah, A. Jadaan, K., and Al-zioud, M. Road Traffic Noise in Amman, Jordan: Magnitude and Cost investigation. Journal of Traffic and Logistics Engineering, 2014; 2: 104- 107.
 Jadaan, K., Al-Dakhlallah, A., Goussous, J., and Gammoh, H. Evaluation and Mitigation of Road Traffic Noise in Amman, Jordan. Journal of Traffic and Logistics Engineering 2013; 1: 51- 53.
 Jamrah, A., Al-Omari, A. and Sharabi, R.. Evaluation of Traffic Noise Pollution in Amman, Jordan, Environmental Monitoring and Assessment. 2006, 120: 499- 525.
 Calculation of Road Traffic Noise.1988. Department of Environment and welsh Office Joint Publication, HMSO, London, United Kingdom.
 Francis C, Giovanni L. Environmental modeling for traffic noise in urban area. Am J Environ Sci 2012;8:345-35.
 Agarwal S, Swami BL, Gupta AB. Development of a noise prediction model under interrupted traffic flow conditions. Noise Health 2009;11:189-93.
 da Paz EC, Urban Zannin PH. 2010. Daytime traffic noise prediction models. Environ Monit Assess. 2010. 163:515-29.
 Sharma A, Vijay R, Sardar VK, Sohony RA, Gupta A. Development of noise simulation model for stationary and mobile sources: A GIS approach. Environ Model Assess.2010;51:189-97.
 Sharma A, Bodhe GL , Schimak G . Development of a traffic noise prediction model for an urban environment. Noise Health 2014. 15:63-67.
 Steele C. A critical review of some traffic noise prediction models. Appl Acoust 2001;62:271-87.
 Shukla AK, Jain SS, Parida M, Srivastava JB. Performance of FHWA model for predicting T.N. Transport 2009;24:234-40.
The evaluation of the traffic flow parameters and relating the parameters to the level of services in Daura to Kongolom Niger Republic Border road is presented in this paper. The study was carried out by using moving car observer method. Data was collected for seven consecutive days; a distance of 14 km was considered for 12 runs which make a total coverage of 336 km/day. The result shows that the traffic volume was 220 veh/h (two ways) in which the proportions of trucks, buses, cars and cycles were respectively 30 %, 30 %, 23 % and 19 %. The percent time spent following was 29.42 % and the average travel speed was 72 km/h. This corresponding to level of service “C’ this showed that the flows falls under a zone of stable flow.
Keywords: Traffic volume, Average travel speed, Percent time spent following and Level of services
 David Levinson (2015) Highway Capacity and level and Level of Service retrieved from http://nexus.umn.edu/ Courses/ce3201/CE3201-L2-04.pdf on December 8, 2015
 Md. Mizanur R. and Fumihiko N. (2005) A Study on Passing - Overtaking Characteristics and Level of Service of Heterogeneous Traffic Flow Journal of the Eastern Asia Society for Transportation Studies, Vol. 6, pp. 1471 - 1483
 Ian Clark (2008) Level of Service F: Is It Really as Bad as it Gets? IPENZ Transportation Group Conference New Plymouth retrieved on December 14, 2015 from http://www.flownz.com/ Portals/104/PDF/FlowTransportationSpecialists20IC2008.pdf
 Nicholas J. Gaber and Lester A. Hoel, (2009) Traffic and Highway Engineering, fourth Edition, Vol. 1, pp. 387-443. Cengage Learning, USA
 Kutub U. C., Md. Ashraful I.and Shahjalal M. (2014), Determination of Level of Service of Agrabad to CEPZ Road at Chittagong in Bangladesh, International Journal of Social, Behavioral, Educational, Economic, Business and Industrial Engineering Vol:8, No:6, World Academy of Science, Engineering and Technology
 Highway Capacity Manual (1985), Special Report 209, TRB, National Research Council, Washington D.C., 1985
 City population (2015) Daura Local Government Area retrieved on December 11, 2015 from http://www.citypopulation. de/php/nigeriaadmin.php?adm2id=NGA021010
 Wikipedia (2014) Daura Emirate, retrieved on December 11, 2015 from https://en.wikipedia.org/wiki/Daura
 Haiyuan Li, Zong T. and Yue Z. Capacity Models and Level-of-Service Analysis in Road Diet retrieved on December 14, 2015 fromhttp://www.westernite.org/annualmeetings/alaska11/ Compendium/PapersNotPresented/HaiyuanLi.pdf
 Anjaneyulu M.V.L.R. and Nagaraj B.N. (2009) Modelling Congestion on Urban Roads Using Speed Profile Data, Journal of the Indian Roads Congress.
Distributing demand in a transportation network is based on route choice behavior models. Generally, it is assumed that drivers use routes with minimum time. In real world, drivers may consider many factors other than travel times in congested networks especially in metropolitan or two way congested transportation networks. Travel safety is a factor that one may consider in his/her trip route choice. The main objective of this paper was to investigate influence of safety factors such as crash delays on drivers’ route choice behaviors. Parameters that can cause to crash occurrences were specified and their impacts were modeled at macroscopic level using a simple statistical model. Then, an equilibrium based mathematical programming model for two way networks with symmetric link interactions was proposed. The model was tested for a simple network and results showed that how crash delays can impact on route choice behaviors.
Keywords: route choice, crash delay, two way networks
 Sheffi, Y. “Urban Transportation Networks: Equilibrium
Analysis with Mathematical Programming Methods. Prentice-
Hall, Incorporated, Englewood Cliffs, NJ, 1985.
 Daganzo, C. F., Sheffi, Y. On Stochastic Models of Traffic Assignment. Transportation Science, vol. 11(3), pp. 253-274, 1977.
 Soltani-Sobh, A., Heaslip, K., El Khoury, J. Estimation of road network reliability on resiliency: An uncertain based model. International Journal of Disaster Risk Reduction, vol. 14, pp. 536- 544, 2015.
 Soltani-Sobh, A., Heaslip, K., Stevanovic, A., El Khoury, J., Song, Z. Evaluation of transportation network reliability during unexpected events with multiple uncertainties. International Journal of Disaster Risk Reduction, In Press.
 Abdel-Aty, M., Kitamura, R., Jovanis, P. Exploring route choice behavior using geographical information system-based alternative routes and hypothetical travel time information input, Transportation Research Record 1493, pp. 74-80, 1995.
 Bell, M. G. H., Cassir, C. Risk-averse user equilibrium traffic assignment: an application of game theory, Transportation Research Part B, vol. 36 (8), pp. 671-681, 2002.
 Lo, H. K., Luo, X. W., Siu, B. W. Y. Degradable transport network: travel time budget of travelers with heterogeneous risk aversion. Transportation Research Part B, vol. 40 (9), pp. 792- 806, 2006.
 Mirchandani, P., Soroush, H. Generalized traffic equilibrium with probabilistic travel times and perceptions. Transportation Science, vol. 21 (3), pp. 133-152, 1987.
 Siu, B. W. Y., Lo, H. K. Doubly uncertain transport network: degradable link capacity and perception variations in traffic conditions. Transportation Research Record 1964, pp. 59-69, 2006.
 Aashtiani, H.Z., Iravani, H. Use of intersection delay functions to improve reliability of traffic assignment model. Presented at the 14th Annual International EMME/2 Conference, Chicago, Illinois, 1999.
 Zolghadri, N., Halling, M., Barr, P. Comparison of Wireless and Wired Structural System Identification. Structures Congress 2014, pp. 2839-2852, 2014. doi: 10.1061/9780784413357.248
 Zolghadri, N., Halling, M., Barr, P. Effects of Temperature Variations on Structural Vibration Properties. Geotechnical and Structural Engineering Congress 2016, pp. 1032-1043, 2016. doi: 10.1061/9780784479742.087
 Khalilikhah, M., Heaslip, K. Important environmental factors contributing to the temporary obstruction of the sign messages. Transportation Research Board 95th Annual Meeting, Washington, D.C., 2016.
 Khalilikhah, M., Heaslip, K. GIS-based study of the impacts of air pollutants on traffic sign deterioration. Transportation Research Board 95th Annual Meeting, Washington, D.C., 2016.
 Baratian, F., Zhou, H. Effects of photo enforcement cameras on intersection delays and driver behavior. Transportation Research Board 95th Annual Meeting, Washington, D.C., 2016.
This study aimed to evaluate the performance of asphalt mixes utilized Reclaimed Asphalt Pavement (RAP). In addition, the study will assess the environmental and cost impact of utilizing RAP in asphalt mix. The study included collection and evaluation of milled materials from three roads from the northern, central and southern parts of Jordan, then evaluation of inclusion of different percentages of the RAP (0%, 5%, 10% and 15%) on the mechanical properties of HMA mixes. Evaluation tests included dynamic creep at 25Cand 40C. For RAPs collected from the central and southern parts of Jordan, dynamic creep strain was found to be decreased as the percentage of RAP in the mix was increased. However, for the RAP, 10% of RAP was found to be the optimal replacement percentage. This is due to marginal properties of this RAP. The environmental impacts of producing asphalt mixtures with different percentages of RAP were assessed The results indicated that the utilizing RAP in asphalt pavements is very advantageous from different perspectives. Some of the advantages of utilizing RAP include saving of energy, reducing emissions, conservation of asphalt and aggregate resources, reduction in asphalt concrete mixes life-cycle cost, reduce landscape Disfigurement, disruption to Natural Vegetation, soil erosion and sedimentation. A case study was performed to analyze the impacts of producing asphalt mixes with 20% amount of RAP on construction cost asphalt mixtures. The results of the analysis indicated that using 20 % RAP will save 7.85 $/ton (17.7%), which is equivalent to 0.0.88 $/sq.m of HMA layer with 5 cm layer thickness.
Keywords: Asphalt Mixture, Performance, Cost Impact, Environmental
 Abo-Qudais, S. A. and Al-Shweily, H. (2004) Effect of Aggregate Properties on Asphalt Mixtures Stripping and
 Abo-Qudais et al. Creep Behavior. Construction and Buildings Materials Journal, Vol. 21 (9), pp. 1886-1898.
 Abo-Qudais, S. A. and Al-Shweily, H. (2007) “Effect of Antistripping Additives on Environmental Damage of Bituminous Mixtures. Building and Environment Journal, Vol. 42 (8), pp. 2929-2938.
 Al-Rousan, T., Asi, I., Al-Hattamle, O. and Al-Qablan, H. (2008) “Performance of Asphalt Mixes Containing RAP, Jordan Journal of Civil Engineering, Vol. 2, No. 3, pp. 218-227.
 American Association of State Highway and Transportation Officials. “AASHTO M 323: Standard Specification for Superpave Volumetric Mix Design, Standard Specifications for Transportation Materials and Methods for Sampling and Testing, 30th Edition, AASHTO, Washington, DC; 2012.
 Federal Highway Administration (FHWA). (2011). "Asphalt Pavement Recycling with Reclaimed Asphalt Pavement (RAP)" Web page on FHWA website. http://www.fhwa.dot.gov/ pavement/recycling/rap/index.cfm; (Sep., 2011).
 Brown E. (1984). Evaluation of properties of recycled asphalt concrete hot mix. U.S. army engineer waterways experiment station, final report # CL-84-2.
 Kandahal P., Brown E., Cross S. (1989). Guide-lines for hot mix recycling in Georgia. Georgia DOT Project No. 8807, Final Report.
 Little D., Homgreen R., Epps J. (1981). "Effect of recycling agents on the structural performance of recycled asphalt concrete materials." AAPT, (50) pp. 32-63.
 Meyers F., Tessier G., Hass R., Kennedy T. (1983). Study of hot mix recycling of asphalt pavements. Road and Transportation Association of Canada, Report # TP2964E.
 Little D., Epps J. (1980). "Evaluation of certain structural characteristics of recycled pavement materials." AAPT, (49) pp. 219-251.
 Oliveira1, J., Silva1, H., Jesus, C., Abreu, L. and Fernandes, S. (2013) “Pushing the Asphalt Recycling Technology to the Limit, International Journal of Pavement Research and Technology, Vol. 6 (2), pp. 109-116.
 PIARC - World Road Association. (2003). "Pavement recycling guidelines for in-place recycling with cement, in-place recycling with emulsion or foamed bitumen and hot mix recycling in plant. PIARC Committee C7/8 - "Road Pavements", 78.02.E.
 Yang, R., Ozer, H., Kang, S., Al-Qadi, I. L. (2014), "Environmental Impacts of Producing Asphalt Mixtures with Varying Degrees of Recycled Asphalt Materials," International Symposium on Pavement LCA.
 Mohammad, L. N., Negulescu, I. I., Wu, Z., Daranga, C., Daly, W. H., and Abadie, C., (2003) “Investigation of the Use of Recycled Polymer Modified Asphalt Binder in Asphalt Concrete Pavements, Journal of the Association of Asphalt Paving Technologists, Vol. 72, pp. 551-594.
 Aurangzeb, Q., Al-Qadi, I. L., Ozer, H., and Yang, R., (2013). “Hybrid life cycle assessment for asphalt mixtures with high RAP content. Resources, Journal of Resources, Conservation of Recycling, Vol. 83, pp 77-86.