Current literature does not adequately discuss India's quickly changing transportation scenario, especially road traffic crash (RTC) concerns. The objectives of this work were to (a) present the national RTC framework and a case study of Andhra Pradesh (AP); (b) analyze and identify risk types; (c) discuss trends and data deficiencies; and (d) recommend prevention strategies. During the period 1970-2009, the nation's road length increased at a compounded annual growth rate (CAGR) of 3.2%, whereas the number of registered vehicles, RTCs, and fatalities grew at 12%, 3.8%, and 5.7% CAGR respectively. Exposure risk dropped from 103 to 11 fatalities per 10 000 vehicles but increased from 2.7 to 10.8 fatalities per 100 000 people. In 2001, AP had 7.5% of the nation's population but 10.4% fatalities. In 2009, the share of urban:rural RTCs was 40%:60%, while 4%, 7%, 4.3%, and 7.1% of fatal crashes occurred near schools, bus stops, gas stations, and pedestrian crossings respectively. In 2009, 22% of fatal crashes were due to heavy vehicles, while motorized two-wheeler fatalities more than tripled during the 2001-2009 period. Vehicles under four years old were involved in 43% of the fatal crashes while 11% to 14% of the fatal crashes were due to 'overturning' and 'head-on' collisions; more than 75% of crashes were due to driver error. 42% of RTCs occurred at 'uncontrolled' intersections, while the crash risk at police-regulated locations was 40% less than at traffic signals. Recommended prevention strategies include: developing a road accident recording system and an access management policy; integrating safety into corridor design and road construction; undertaking capacitybuilding efforts; and expanding emergency response services.

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Mathematical formulations linking road traffic fatalities to vehicle ownership, regional population, and economic growth continue to be developed against the backdrop of Smeed and Andreassen models. Though a few attempts were made, Smeed's law has not been fully tested in India. Using the 1991-2009 panel data from all states, this work (a) developed the generalized Smeed and Andreassen models; (b) evaluated if traffic fatalities were impacted by structural changes; and (c) examined if -in relation to the generalized model -the individual (time and regional) models are more relevant for application. Seven models (Smeed: original, generalized, time-variant, state-variant; and Andreassen: generalized, time-variant, state-variant) were developed and tested for fit with the actual data. Results showed that the per vehicle fatality rate closely resembled Smeed's formulation. Chow-test yielded a significant F-stat, suggesting that the models for four pre-defined time-blocks are structurally different from the 19-year generalized model. The counterclockwise rotation of the log-linear form also suggested lower fatality rates. While the new government policies, reduced vehicle operating speeds, better healthcare, and improved vehicle technology could be the factors, further research is required to understand the reasons for fatality rate reductions. The intercept and gradients of the time-series models showed high stability and varied only slightly in comparison to the 19-year generalized models, thus suggesting that the latter are pragmatic for application. Regional formulations, however, indicate that they may be more relevant for studying trends and tendencies. This research illustrates the robustness of Smeed's law, and provides evidence for timeinvariance but state-specificity.

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